Andrew Huberman (6:56)

Dr. Jay Bhattacharya, welcome.

Jay Bhattacharya (6:58)

Thank you for having me, Andrew.

Andrew Huberman (7:00)

I've been wanting to do this for a very long time. We are colleagues at Stanford, although now you've formally moved to Washington to be the Director of the National Institutes of Health. But you've played such an essential role in shining a light on certain aspects of public health, mostly that happened during the time of the pandemic related to lockdowns, vaccines, et cetera. We'll talk about that. But now you are in the chief position of directing research dollars and the initiatives of what is arguably the most important health organization in the entire world, not just in the United States. So thank you for taking the position. Thank you for being here. And the first question I have is, for those that are not familiar, what is the not just stated mission of the nih, but what is the really essential mission of the National Institutes of Health?

Jay Bhattacharya (7:52)

So let me start with the stated mission. Because the state admission is something entirely worthwhile. Anyone who listens to it should say, yeah, we should do this. It is that to support research that advances the health and longevity of the American people. And of course, the research that we do doesn't just advance American health, it advances the health of the entire world. For a very long time, the nih, the National Institute of Health, has been the premier biomedical organization supporting research that translates into almost every drug that you take. The NIH has had some role in developing almost every, you know, all the fights over what's the right thing to do to get good sleep, what's the right thing to do for your diet. The NIH has played some role. And for American biomedicine, it's the essential institution. It supports the careers of a very large number of biomedical scientists around the world, and specifically me. I mean, I got NIH funding for most of my career. I was a reviewer for the nih, a scientific reviewer for grants. It's an absolutely essential organization.

Andrew Huberman (9:03)

Yeah, I agree. My lab ran on NIH money primarily. So thank you, taxpayers, American taxpayers, and I think for most people, when they hear that word health, and what you just said about the, you know, the mission statement for nih, there is this assumption that most of the work being done at or funded by NIH is human clinical studies or even mouse studies that are testing a particular drug. A dose response curve, you know, what's the lethal dose of this? What's the half life of that? But as you and I both know, much of what NIH does is fund basic research, research for which we don't have any clear idea, maybe even the foggiest of ideas, that there could be a potential upside for human health. Things like what controls the pigmentation patterns of the noses of Doberman pinscher dogs. I bet you we could find that grant. So when we. Maybe not anymore, but when we step back and we look at basic versus applied, AKA clinical research, what percentage of the NIH budget, which we'll talk about in a moment, is directed toward basic research? And what percentage is directed toward clinical studies or the testing of some drug, what we call pre clinical trials testing in mice or non human primates, et cetera.

Jay Bhattacharya (10:24)

So there's big fights over exactly what that demarcation line is. So I'm not going to commit to a single number, but I will say is that a substantial part of the NIH portfolio appropriately focuses on basic science. Basic science meaning fundamental biological facts that can be used in many, many, many drug drug studies, other, other other research where you don't necessarily know specifically in advance when you're doing it what the applications are going to be. The NIH very appropriately funds that work, especially work that's not patentable.

Co-host (11:01)

Right.

Jay Bhattacharya (11:01)

Because no drug company has an incentive to do that work. And yet it's vital. Let me give an example just to put some meat on the bone of it, of something that the NIH didn't fund, but actually is within the mission of the NIH to have funded if it had. Let's just take the research that led to the understanding of the the structure of DNA is a double helix, right? Watson, Crick, Rosalind Franklin, all those folks in England in the 1950s. Well, that work is not patentable. It's hard to imagine someone trying to patent the double helix structure of DNA. So that means that it's not going to be in the interest of any specific company to support those scientists that discovered that. And yet it's vital to almost everything we do in biology, right? The NIH very appropriately funds that kind of work, work that is not in the interest of any particular company to do. It solves a market failure. If you think like an economist, the market failure is there's no incentive of the private sector to do that, that kind of basic work. And yet that basic work really advances human health in ways that are sometimes unpredictable. And so it's correct and right that the NIH continues to fund that kind of basic science work as well as the applied work where you take the advances and say, okay, well here's a drug that might work to treat this disease, right? That kind of work also is appropriate for the NIH to fund. There's an interesting dividing line where the question is like, what should be left to the private sector to do so? The private sector tends to fund large scale clinical trials at sort of the tail end of the development process. Sometimes they'll fund earlier clinical trials, but the private sector has an incentive to fund those kinds of studies because that gives them exclusivity patents things. So why should the taxpayer pay for that when there's already private actors that are willing to pay for that? So this interesting dividing line you Want the NIH work to be translated so that patients can have it. That means the private sector has to be involved to some degree, certainly has to be using the products of the NIH research. But that dividing line is fuzzy and controversial. Same thing with between basic and applied. As I said earlier, there are huge like almost religious horse over where that, where that dividing line is. Are you a basic scientist or are you an applied, applied scientist? So all the numbers like don't make sense to me exactly, given that religious war. But the fundamental thing which is we have to fund basic work that I believe in pretty strongly.

Andrew Huberman (13:50)

Well, as a basic scientist, I'm not a clinician, but I worked on clinically relevant issues in my lab related to restoration of vision, in blinding diseases like glaucoma, things like related to anxiety, et cetera. I also know that we have some beautiful cases, as you pointed out, of basic research leading to important, I will say, cures to serious diseases. And there was no thought at the beginning of that basic research that the outcome would be related to human health. I'll just briefly mention a couple. I want to ask more questions than I want to speak, but my scientific great grandparents, David Hubel and Torrenson Wiesel, did the early work defining the structure and function of the visual system, first in cats, then in monkeys, eventually was clear. The same was true of their findings in human work. And early plasticity changes in the visual system if, say, there was a cataract or a droopy eyelid or divergent eye strabismus or convergent, so what we call cross eyedness and things of that sort, and we know on the basis of that work that children need corrective surgeries early or else the brain is forever blind to the perfectly fine eyeball if the eyes aren't correctly aligned. Okay, in other words, the old practice of, oh, you don't want to put kids under anesthesia, it's too risky, et cetera. The work of Hubert Wiesel saved the vision of millions and millions of children in the US and abroad. People with cataract have those cataracts removed early and on and on. And I would also say as a second example that much of the basic work on cell biology that took place in the second half of the last century, you know, where are the mitochondria? What's in the mitochondria? Electron microscopy, lights. Let's talk about all the folds in the mitochondria. Let's talk about the Golgi. All that basic cellular biology that is the stuff of textbooks. Was, as we say, necessary, perhaps not sufficient, but necessary for the development of essentially every existing cancer treatment. But the cell biologists that did that work weren't thinking about cancer until much later in that work. So those are just two that I would argue NIH had funded a tremendous amount of. And the reason I'm setting it up this way is because I think nowadays part of the reason you're here is that we are potentially looking at a redirecting of a significant amount of the research dollars that taxpayers provide to the NIH and the NIH to labs away from basic research, which understandably has some people concerned. That said, in order to translate things from the lab to the clinic, we also need to think about translational work. So I just put that out as kind of an offering to elaborate, Andrew.

Jay Bhattacharya (16:31)

I have no intention of implementing that, of shifting the balance between, I think, as I said, basic science work and applied work are both tremendously important parts of the NIH portfolio. And the question to me is what's scientifically important and interesting in terms of accomplishing the NIH mission, which is again advancing the health and longevity of the American people. Both basic work and applied work can contribute to that mission. In fact, I think any large scale scientific institution that seeks to support the mission that the NIH has has to have both in it. So I don't have any intention of gutting basic science. I mean, I personally, I do epidemiology, health policies, health economics, statistics. That's very, very applied. But I have great admiration for my colleagues like you who do basic science work. I think it's what advances and fuels the next generation of advances. So it's going to stay part of the NIH mission as long as I'm the director.

Andrew Huberman (17:42)

Thank you. I and many others will be very relieved to hear that answer. I think there is this fear that the new administration is going to eliminate basic research somehow and replace it with only applied research and clinical studies. And that somehow, and this is not my belief that there's going to be some private interest related to that and it's all going to get co opted in some kind of cloudy way. What I'm hearing from you is that is not the direction that NIH is going to.

Jay Bhattacharya (18:07)

Not in fact, I've not heard anyone inside the administration tell me to do that or suggest that as the appropriate path. I just, I mean everyone I've spoken to about my vision has said yes, that makes sense.

Andrew Huberman (18:20)

Great.

Narrator (18:22)

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Andrew Huberman (21:20)

I'd like to talk a little bit about something that most people perhaps are not familiar with in terms of its acronym, but is a very important issue, which is this notion of IDC indirect costs. So my lab ran on NIH grants for many years and my lab and other labs would apply for grants. If we were fortunate enough to get one of those grants funded, we might receive, let's say a typical grant would be a million dollars over the course of four years. So 250 a year for four years. But then in addition to that, my home university, Stanford would get some percentage above that, not a percentage of that million. I would still get the million to spend on mice, antibodies, graduate student salaries, et cetera, but some percentage of that 1 million. And I think at Stanford it's roughly 50x percent. So let's say another 500,000 would be given to the university for so called indirect costs. This is not something that just happens at Stanford. This is typical of every single NIH grant that I'm aware of. And the indirect costs pay in principle for administrative handling of the grant and the, you know, the, the various infrastructure things related to the mouse care, keeping the lights on, having a janitor empty the trash at night, these sorts of things. IDC, as it's called, has become a hot button issue for two reasons. One, as soon as the new administration came in, the Trump administration came in and this just this last year, they cut the IDC rate across the board. Not from say 55% at Stanford. Other places were 75%, some places were as low as 30%. They said, nope, we're not paying this stuff anymore. The National Institutes of Health, in other words, the taxpayers will pay up to. But no more than 15,1 5% above any given grant. I'd like your thoughts on that because this weaves into some bigger issues that relate to a lot of the sentiment that, you know, why should taxpayers be paying for these universities to run, especially when universities, some, not all, have large endowments.

Jay Bhattacharya (23:30)

Right. So actually I just preface my remarks by saying that there was litigation against that 15% which essentially said the government couldn't impose that 15%.

Andrew Huberman (23:41)

So it's been blocked.

Jay Bhattacharya (23:42)

Yes. So right now the, the rates are. Whatever they were, they're not, they're not, they're not 15%. Based on that court order. I can't comment on the litigation and I can't comment as a result of. I'm now a member of the government. I'm not allowed to do that. But I do want to talk about the broader issues related to indirect costs and I want to put it in a broader context. Right. So the context is this. Right. So in the mid-40s, Vannevar Bush, who was like one of the main science administrators in the United States, he made an argument that, that the federal government should partner with universities in organizing the scientific infrastructure of the United States. The universities were tremendously important parts of the scientific infrastructure, and the federal government had an appropriate role in supporting the universities of the country to do scientific research of interest to the American people. So the indirect cost structure came out of that commitment. And frankly, it makes sense to me.

Co-host (24:45)

Right.

Jay Bhattacharya (24:46)

It's appropriate that the federal government have some role in deciding how to support the universities of the country to be organized around research that is in the American interest. The question is how much should it be? How should it be structured, in what way? Those are the key policy issues that we're really talking about. We're not talking about should there be some federal support for the universities? The question is how? Let me just step back and talk about the current structure, the way it works, because it's really non intuitive. So first, you're a brilliant scientist. You apply to the nih. You get a grant that gives you a million dollars a year. I'll just make a clean number. So a million dollars for the next five years, the federal government's going to give you money to run your lab and do all this kind of stuff. You work at Stanford. Stanford has a 55% indirect rate. So that's on top of the million dollars a year. The administrators at Stanford then will get $550,000.

Co-host (25:52)

Right.

Jay Bhattacharya (25:53)

So that's. So for your million dollars of work, the taxpayers will pay one and a half million dollars roughly to Stanford a year.

Co-host (26:00)

Right?

Jay Bhattacharya (26:01)

So that's, now that, as you said correctly, that half a million dollars will go to the fixed cost of doing research, right? The stuff that's like, not specific to the, your, you know, like the, the lab you're running, the people you have to hire to do the work that you propose. But the fixed cost, the building, the maintenance, the, you know, all the, all.

Andrew Huberman (26:23)

The songs, got to take the biohazard stuff away, all that stuff.

Jay Bhattacharya (26:26)

And it's not just you. Like there are other folks who are like using the same material, like radioactive materials. And so it can support many, many research projects, not just one.

Co-host (26:34)

Right?

Jay Bhattacharya (26:34)

So it's, it's funding that kind of work, right? So, and again that's a legitimate use of that money. So right, here's the way that the economics of this work. In order to get fixed cost support, you have to have brilliant scientists like you that can win NIH grants. If you don't win NIH grants, Stanford doesn't get the 550.

Co-host (26:56)

Right.

Jay Bhattacharya (26:57)

But in order to attract brilliant scientists, you have to have the infrastructure where the scientists can do their work. So it's a ratchet, right? So in order to have the money, the infrastructure support, fixed cost support, you have to have scientists. In order to have the scientists, you have to have the infrastructure. It's a ratchet that essentially makes it so that we concentrate the federal support for the money to a select few universities. They're winners and losers. And so the scientific infrastructure of the country is concentrated in a relatively few universities, mainly on the coast. And they're brilliant scientists in other places that are not at those select few universities that have trouble getting NIH grants even though they're brilliant scientists. It draws the federal support away in a structure that essentially says lots and lots of states, lots and lots of institutions are going to have trouble getting the infrastructure support that they need in order to have the scientists come there. So that's the basic economics of, of the, the way indirect costs actually, actually work. And so the question is that the right structure, there's also questions about, you know, like, so for instance, your, your, your, your science involves your basic scientists, your science involves lots and lots of fixed costs, right? Radioactive disposal, all the stuff the research I did, you know, epidemiology, health policy, statistics. It's basically a computer me with a, with a data set and a computer, I can hire some biostatisticians to help me or we call that a carpet lab. Yeah. And so like do the universe. Does the university need the same indirect cost support to support my fixed cost as it does yours. And the answer is obviously no. And yet that's the structure we currently have.

Co-host (28:50)

Right.

Jay Bhattacharya (28:51)

So there are policy questions to be answered about are we. Have we structured the indirect cost support in the right way? Are we inducing the right incentives?

Co-host (29:01)

Right.

Jay Bhattacharya (29:02)

Can the American taxpayer be sure that we're auditing the use of the indirect costs appropriately? Those are the policy questions, I think, that are at issue in the indirect cost fight. Again, I won't get into the litigation. I'm not allowed to actually comment on that. So I wanted to abstract it to a higher level because I think the policy question is not should the federal government support universities to do this kind of research to have sort of the facilities? The question is, how should it be distributed across the country? To what extent should the researchers get it versus the administrators get it? And then on the back of that, there's also other research institutions that have very different indirect cost recovery rates for the same university.

Co-host (29:47)

Right.

Jay Bhattacharya (29:48)

So, like, you know, I think Gates foundation is, I don't know the exact number, like 15% something on that order, whereas the NIH is 50% to the same university. It looks funny. The question is, I mean, sometimes I've heard, well, the Gates foundation puts more of the money into the directs.

Co-host (30:10)

Right.

Jay Bhattacharya (30:11)

So that maybe they'll charge you for the rental cost of the building or something. I don't know exactly, but I'm very.

Andrew Huberman (30:16)

Familiar with foundation versus NIH money, and it differs by foundation. But typically a university, and I've been at 2. I'm tenured at Stanford, but my lab started off at University of California, San Diego, a public university. Typically when foundation money comes in, there's. The university imposes a minimum of about 8% administrative cost just for handling. Like we're just to do the paperwork to pay the admins that do the handling. There's something very important in what you're bringing about. There are actually two issues. I want to backtrack to one issue to make sure that we, that people really understand this, because I realize that some of this might sound a little bit down in the weeds, but it's just so important. The first thing that I really want to draw up from earlier in our conversation is you pointed out that the current model of NIH is that taxpayer dollars pay for the basic research and for the exploration of whether or not the findings from that basic research will benefit disease. If there's any technology, device, drug, whatever, that is brought to the public through the private sector. Put differently, the Taxpayers fund the research and development, but they don't capture any of the upside from the private companies that make money selling you the ssri. Selling you the note, hopefully someday. Novel Alzheimer's treatment. We don't yet have a satisfactory treatment for Alzheimer's as we'll get into. So the general public, who are not basic scientists, in other words, if I take off my hat as a basic scientist and I say, yeah, I'm a taxpayer, I give a significant amount of my income to the state of California and to the federal government. I like science. I certainly would like to live a long, healthy life. And I hope some of that science helps me do that.

Narrator (32:07)

But I'm going to have to buy.

Andrew Huberman (32:08)

Back the results of what I paid for. That's where I think a lot of the general public sit. And I'm not saying they don't like, appreciate and respect science and scientists, but to any rational person, you don't need a degree in economics to say that kind of sucks. I'm paying. And made worse, if I want to read a paper that was published with the work that I provided from my tax dollars, I have to buy that from the journal.

Jay Bhattacharya (32:40)

By the way, that changes in July.

Andrew Huberman (32:42)

Okay.

Jay Bhattacharya (32:42)

Yeah.

Andrew Huberman (32:43)

I mean, this is a huge issue.

Jay Bhattacharya (32:44)

That's one of the decisions I made.

Andrew Huberman (32:45)

$34. Listen, I've been grateful to publish in Nature and Science. You know, these are like super bowl rings for. For scientists. I'm sure it's part of the reason I got tenure at Stanford. And I had great fun doing the work. And I believe in the work. It stood the test of time. But were I not an employee of Stanford that pays for the subscriptions to.

Narrator (33:06)

Those journals, I have to buy the.

Andrew Huberman (33:09)

Work back using my tax dollars that funded the work. This is crazy. This is like me giving you the money for the supplies to build a home. I get to. You get to live in the home. I don't even get to see the home. I have to purchase a ticket to see the home. That's how irrational it is from the perspective of somebody who's just not understanding the pipeline of basic to applied research. So let's just. I want to return to that briefly because this relates, in my opinion, directly to idc. So that's a crazy picture for anyone that doesn't understand how one piece relates to the next relates to the next. And now that I'm in public, I'm in media, I'm public facing. What I've come to learn is that the general public is very smart. Max Dillbrook was Right. You know, assume infinite intelligence and zero knowledge, but it's very hard for people to connect more than two or three dots. They're busy. So we could talk all day about how this leads to. That leads to this, the brick on the wall model. And then there's this treatment and they're like, I'm paying for this stuff and I can't even read the paper about it, let alone glean the positive benefits without paying out the nose.

Jay Bhattacharya (34:16)

Yeah. So. So a couple of things. Let me go backwards because you had two, two major issues you brought up. So first, the journal thing. My predecessor, Monica Bergnoli, who was the NIH director, the National Institute for Health director before me, she made a decision, a really great decision, essentially to say if the NIH supports a scientist's work and then that work leads to a journal publication, that publication ought to be available free to the public immediately upon publication. You're not allowed, as an NIH funded scientist to publish in a journal that doesn't have that as a policy. That policy was due to go into effect in December of this year. I think it's a great policy because I agree with your analysis entirely. If the American taxpayer pays for the research, why shouldn't the American taxpayer be able to read the research for free? Because they already paid for it. Why do they pay a second time on the back end after the research is, you know, is published?

Andrew Huberman (35:14)

It's not like it's free. If you're a university employee, the university has to purchase a very costly subscription to the journal in order to. For a faculty member to read the papers. Now, I'm lucky enough I can access pretty much any paper in the world, but that's because Stanford spends millions and millions of dollars and it's made worse. I forgot the one real stinger in this. When you publish a paper, you use taxpayer dollars to pay the journal.

Jay Bhattacharya (35:39)

That's correct.

Andrew Huberman (35:40)

Thousands of dollars to publish it. Then they sell it back to the general public.

Jay Bhattacharya (35:43)

Nature charges $12,000 for like the major. It's.

Andrew Huberman (35:47)

But okay, so that's a.

Co-host (35:50)

Right.

Jay Bhattacharya (35:51)

Yeah.

Andrew Huberman (35:51)

Sorry, I. I realize I'm talking more than I'm asking questions.

Jay Bhattacharya (35:54)

No, no, this is, I mean, like, I'm agreeing with you. So, like. So I. The. Monica Bertinelli, the previous NIH director in December of this year was the. She made a policy that those papers have to be available to the public for free. I made a decision. One of my first things I did was I said, why wait till December? Let's just do it in July.

Andrew Huberman (36:15)

Great. Thank You.

Jay Bhattacharya (36:16)

And so starting in July, that what you just said will no longer be the case. Americans and everybod have access to the papers that the Americans already paid for if they're NIH funded for free.

Andrew Huberman (36:26)

Thank you. On the behalf of. Literally, this isn't a political statement. On the behalf of myself and every other American citizen, thank you. We've been paying for this research forever and have had to pay to get it back. I mean, it's not like journal editors make that much money, but the journals make a fortune. So Macmillan Press, El savior. I've done my homework on this. We're talking billions of dollars in income.

Jay Bhattacharya (36:48)

And the marginal cost of publishing now is effectively zero. It's just you put it online, right? And there's, there's, I mean, yeah, there's some, some cost for maintaining the web page and all that, but, but, or the, and there's some editorial staff. But like the, the, the, the, the level of investments that the public had been making for the NIH to then be asked to pay 30, 50 hundred dollars for, for the papers itself that are published. I mean, it's just insulting. And actually it impedes the progress of science because it makes it so that there's this barrier where regular people can't get access to the things that scientists are talking about.

Co-host (37:26)

Right.

Jay Bhattacharya (37:27)

There's like this public transparency aspect of it where scientists ought to be engaging with the public about their ideas. The idea is that we are just living in this ivory tower and only we get to decide what's true and false, and then we impose it on the public. During the pandemic, we saw the folly of that model.

Co-host (37:45)

Right.

Jay Bhattacharya (37:46)

So it's, I think, a small step forward, but an important one.

Andrew Huberman (37:49)

I think you're being humble, and I'd like to point out that I think it's a big step forward because it's not just, you know, a token to the public for all their, you know, dollars over the last. How old is the nih?

Jay Bhattacharya (38:02)

One hundred and some years.

Andrew Huberman (38:03)

One hundred and some years. It's really what should have happened a long time ago. So thank you very much, and I, and I guess thank you to Monica as well for initiating this, but thanks for accelerating that. I think when people start to understand how the NIH works a bit and they understand this IDC thing, this indirect cost thing, the question comes to mind, you know, how much of the cost of running science at a university, public or private university, should the public be responsible for? I mean, that's a kind of really interesting question.

Jay Bhattacharya (38:36)

Yeah, I mean, I think so. Let me tie it back. As you said, these are all interlinked topics. Let me tie it back to something else you just said earlier, which is, okay, so the NIH funds your work, your work then results in maybe not necessarily you, but somebody else who uses your work to like create a product that they patent and they make a lot of money off of, they sell to the public, at least indirectly or sometimes directly. Those patents are funded by American taxpayers, right? Well, the NIH also has a big intramural program, but it's like a scientist who work directly for the nih, they make some advances and sometimes those advances result in patents, right? So, and those patents then result in products that are, that are sold that above marginal cost. And so the question is like by, by again by American taxpayers because the patent protects, you know, entry into those markets. So, so the question is, how much should the American taxpayer be funding for this kind of work? Should there be private actors to be allowed to like, have to make, to make money off of this, this, this research the American taxpayer funded? And, and the question as, as an economist, I'll say the question is complicated. And the reason it's complicated is you might say, okay, well, there should not be a patent at all. I think shouldn't be patent at all. There was a law called the Bayh Dole act in the mid-80s, I can't forget the exact date that essentially said that NIH funded work ought to be patentable. And the reason was that it's the last mile problem. You have some fantastic basic science research that has some fantastic biomedical results that there's no way for the patent, right? Then there's no interest to develop into a product that then advances health. The wisdom of the Bayh Dole act was to say, well, look, if you allow there to be patent on the last mile, then now we've created a commercial interest to take the basic science advances and translate them into something that actually benefits people. Now the price is going to be higher, at least while the patent is still in place. But then eventually the patent go away and then the price, the thing will be available to the public at large to accelerate the transition from the basic science investments we make to things that actually benefit the public very directly. In a sense, there's a trade off there, right? So you're trading off the fact that for a while there's products funded by the American taxpayers that are at higher prices than it kind of would be in a purely competitive market for the fact that you get more rapid access to the benefits of that investment. So that's the basics, trade off at play. And that's why I say it's complicated.

Andrew Huberman (41:29)

When I joined UCSD and when I joined Stanford, I signed something saying if I make a discovery here that translates to an important device or drug, that the university is going to capture some of that upside. And Stanford is a place where there's, let's just say, a history of people going into biotech and to neurotech. And because of the influence of the engineering school, there's actually a great joke about Stanford that a former president of Stanford told me, which is there's only two kinds of Stanford faculty, Stanford faculty with companies and Stanford faculty with successful companies. Discussion for another time. But it's commonplace for faculty at Stanford to have companies to split their time between the university and their companies. But most places, like most of the NIH grants that I reviewed when I was on study section reviewing grants, most of the great work I would hear about at meetings came from people at universities who were really focused on, you know, charting the cell types in the retina, understanding the activity patterns in the brain during sleep, and how it relates to neuroplasticity. Very few of them were involved with companies in a serious way, let alone had their own companies. So for the taxpayer who make up the majority of our listenership is giving money to universities and the universities are spending that money making discoveries, I think most of the time that the university and the scientists who do that work are not capturing the upside. The general public isn't capturing the upside. They're actually paying for the upside. So it's a little bit like the journal situation. That's why I brought that up. It's a little bit like the journal situation all over again, where we're as taxpayers funding a lot of this and then have to buy it back over and over again.

Jay Bhattacharya (43:15)

Okay, so there's one other complication about the United States versus the rest of the world. So let's just put that aside for just a second. Let's get back to that. Before I get there, I want to say in response that in fact, when you take medication or when you have some health advice that actually works, often the NIH research was somewhere in the path leading up to that involved, and there are huge returns to that. Right. If you have a drug that treats your disease well, you have congestive heart failure and now you have a drug that allows you to live longer in a way that allows you to live more fully, or if you have diabetes and you slow the progress of the disease. So it doesn't result in your kidneys failing, you're going blind or whatnot. Those are advances that are really worthwhile. And even if the price is higher than marginal cost, it still could be very worthwhile. So you take Metformin, it's a very cheap drug now, but once upon a time it was a patented drug and you prevent the progress of type 2 diabetes. That's a big advance. Right.

Andrew Huberman (44:34)

For patients.

Jay Bhattacharya (44:35)

Right. So the value that you get from the NIH sponsored research then is potentially very, very high in terms of improving your health even more than the marginal price for the drugs that you end up paying or the products or the advice or whatever it is. Right.

Andrew Huberman (44:48)

So you're saying it was a good investment for the taxpayer.

Jay Bhattacharya (44:50)

Yeah, even for the taxpayer.

Co-host (44:51)

Right.

Jay Bhattacharya (44:52)

Now I wanted to put aside the business about international like the US versus the rest of the world. Now I want to bring that to the forefront. It is also true that American taxpayers and Americans pay somewhere between 2 to 10 times more for the same product, the same drug product as people in Europe pay.

Andrew Huberman (45:14)

Why is that?

Jay Bhattacharya (45:17)

There's again, a lot of complicated reasons around to do that. But I mean, just, it's a very, very simple observation. There's something in economics called the law of one price.

Co-host (45:26)

Right.

Jay Bhattacharya (45:26)

When you have one country's charging 10, there's a market in one country where the price is 10 times more than for another country. What you'd expect is somebody to go buy the goods from the other country, from the cheap country, let's pay the cheap price, then go resell it in the country that has a high price. And now what would end up happening is that you'd get an equalization of the price. As long as there's sort of the capacity to move across and essentially close this arbitrage opportunity through competition, you'd see those price differences collapse. And yet for decades, Americans pay two to 10 times more for the same product, often made in the same manufacturing facility, than Europeans do. And it's again a complicated reasons why, but it has to do partly with the way that American health insurers interact with drug companies. Drug companies essentially use Americans as a way to fund their research and development efforts. That's what they say. The higher prices that we pay fund the last mile research that the drug companies do to test the new products.

Andrew Huberman (46:42)

Are you saying the last mile research is the most expensive because it's the stage four clinical?

Jay Bhattacharya (46:47)

Yeah.

Andrew Huberman (46:47)

The straight face Right. Before we go into humans at large.

Jay Bhattacharya (46:51)

Yes.

Andrew Huberman (46:52)

We want to know if anyone's going to drop.

Jay Bhattacharya (46:54)

That's the argument that they make, that the drug companies make, is that, well, yes, the Americans are paying this high price. It's really worth it to do that. And then they go to Europe and Europe says, well, we're not going to pay those high prices. We're going to charge you if you're going to market the drug in France, in Belgium, in Germany or wherever you can do it. But you're going to have to charge us essentially marginal costs.

Andrew Huberman (47:19)

So if I understand correctly, the United States taxpayer is funding the late stage and most expensive research and development that the drug companies do. They sell the drugs to us at a premium and they use the difference between the real cost and the sort of allowed cost abroad to make it very cheap overseas. In other words, we are paying for the insurance, so to speak, that the drugs that are marketed in Europe and elsewhere are safe.

Jay Bhattacharya (47:51)

Yes.

Andrew Huberman (47:52)

So the taxpayers in the United States are funding the basic research and the clinical late stage research.

Jay Bhattacharya (48:00)

Yes.

Andrew Huberman (48:01)

For the entire world?

Jay Bhattacharya (48:03)

Yes, in large part. I mean, like Europe does have some institutions that invest in basic research. So it's not entirely zero. And there are, of course, private foundations that do it. But through the nih, that's the single largest investment in basic science research in the world. And also applied research and also by higher drug prices in the United States relative to the rest of the world. We are funding the phase three trials, all the research and development efforts that happen at the tail end of the research pipeline that the drug companies do. So essentially, American taxpayers are the piggy bank for the world for almost all of this research pipeline.

Andrew Huberman (48:49)

Wow. Okay. What is being done to bring drug prices down in the United States? I heard this recently as a press release from President Trump that drug prices in the United States are soon to come down. Knowing what I know now, based on what you just told us, the immediate question becomes, who's going to pay for that late stage safety research? I mean, it's not expensive because it's fun to do expensive research. It's not expensive because they're still exploring the basic chemistry of these molecules or functioning of the devices. It's expensive because you have to make sure that people aren't going to drop dead or form some other worse pattern of illness through the use of these drugs. And that means a lot of human subjects and many, many measures. It's not just one endpoint, like, did it lower blood sugar? It's like, did it lower blood sugar? And also, did you blow a gasket in here? You know, some capillary in a critical part of your brain. So I mean, this is very expensive work. So who, it still needs to be done is what I'm saying. Who's going to pay for it?

Jay Bhattacharya (49:48)

Okay, so let me just take a couple of cuts at this. So first like that, that phase four surveillance that happens after the drug's been marketed, that's typically the FDA that conducts that work. The NIH can fund some, some of it. But it's mostly, it's mostly the FDA that tracks the safety and efficacy of drug in broader populations after the drug has been approved for use. So again, American taxpayers are paying for that. The phase three studies, the studies of large scale clinical studies to check the effectiveness of a drug, check again like safety profiles from larger populations. That's typically the drug companies paying for that. Right in principle. But then American taxpayers pay for that with higher drug costs. President Trump in the last couple of weeks issued an executive order essentially saying we have to make the other countries of the world pay their fair share of this. So he put an executive order in place with various mechanisms. If you want, we can talk about some of those mechanisms that will reduce the difference in price between what the US pays and what the rest of the world pays. What likely happen is that Europe will pay a slightly higher price for again funding the research and development efforts to do that last mile of research. The US Will pay a lower price and so the world will share that R and D burden more equally than we currently do. Currently it's American taxpayers on whose shoulders that burden of R and D currently falls. What President Trump has said is that that's not a equilibrium that should hold, that there ought to be policies that allow us to equalize those prices. And the kind of mechanisms used include things like including drug price discussions in trade negotiations. So the linking it to the tariff policies he's implemented allowing re importation of drugs. So the idea is that let's say I'm in Europe and I'm charging basically nothing for some drug and you're the United States. Someone can come to me, buy the drugs from Europe or Canada or wherever, bring them in the United States, resell them at a much cheaper price and you know, make a little bit of money. But that then would equalize the price and various other mechanisms to try to bring the United States much more close to where the price of the rest of the world. It's not that the R and D won't happen, it's just that the prices everywhere will be more equal so that the burden of R and D is shared more equally across the developed world.

Andrew Huberman (52:24)

What is to say that these other countries will simply say, no, we're not going to absorb more of the cost? People don't like to see prices go up. They're comfortable with seeing prices go down for obvious reasons. And I can think of one example, maybe not the most critically important example in most people's minds. There's a class of drugs that was released last year or about last year called the Doras. These are drugs that encourage sleep by suppressing the wakefulness mechanism as opposed to promoting the sleepiness mechanism in loose terms. They have much lower abuse potential than a lot of other sleep medications. And given the essential role of sleep in mental and physical health. And I'm a strong believer that behavioral tools, sunlight, et cetera are critical. But some people truly struggle with clinical grade insomnia. And it's extremely detrimental. It's widespread. These drugs are very expensive. $300 a month or more in the United States. Knowing what I know now, just the idea that some of that $300, let's say, let's make up a number, 200 of those dollars is to cover the research costs so that in Northern Europe it can be available for $50 a month. I mean, that borders on upsetting for me.

Jay Bhattacharya (53:40)

Yeah, it is upsetting. And I think I understand why President Trump issued that executive order. It's upsetting for me too. Like it makes no sense that the American taxpayer should bear the burden. This R and D expenditures. When there are lots of rich countries in the world, why shouldn't be more equally distributed? The question is what will happen, how the drug companies respond to the executive order and how our allied nations respond to the executive order is open Still, I don't know what it's going to look like, but what I can say is that the current equilibrium is not sustainable. The American taxpayers, once they understand what's actually been happening, this is for decades long, they're going to say no.

Co-host (54:24)

Right.

Jay Bhattacharya (54:24)

And so the way that it plays itself out, it's hard to project. Exactly. But what I do know is that every effort the government currently is making, every effort to make sure that those prices get more equalized. I think just take it from the perspective of a European citizen, right? Someone French citizen or Spanish or Portuguese or English citizen or citizen Great Britain, for them, raising allowing this prices more equalized in a way that so they share the burden, essentially creates an interest of the drug companies to focus on the kinds of health conditions that they have. Most of the research now, since it's paid for by Americans. The drug companies are focused on problems that Americans have. It aligns the interests of the drug companies to think more broadly about what they should be investing in to include the health problems that Europe has.

Andrew Huberman (55:33)

Is it true that I've heard this before? 90% of the psychoactive drugs like the antidepressants, the SSRIs and related things in the world are prescribed and consumed in the United States.

Jay Bhattacharya (55:47)

Again, I don't know the specific number, but it is a pretty, pretty substantial, I think as far as like drug profits go, I think it's like 2/3 or 3/4 of all drug profits are had in the United States.

Andrew Huberman (55:59)

And are most of those for the sort of Adderall and psychotropic type stuff? No, sorry, I don't know if psychotropic is the correct term. I know I'm going to get beaten up by people if I don't get this right. Let's just say psychoactive. Excuse me, I meant to say psychoactive drugs like SSRIs, which by the way, in my view of the literature, they're not always bad, but we hear that they are bad in some instances or many instances. But for the treatment of clinical grade OCD, the SSRIs have been a tremendous tool. They haven't cured OCD in every case, but they've been a tremendous tool. So I want to make sure not to demonize them.

Jay Bhattacharya (56:33)

So I don't know the specific numbers for psychoactive drugs, but as an industry as a whole, it's the United States that drives drug company profits, that pays for drug company profits. I think it's like 2/3 or 3/4, I forget the exact number.

Andrew Huberman (56:47)

And so what are these American problems? So it's obese. Are they obesity related issues?

Jay Bhattacharya (56:52)

Yes, obesity, depression. I mean those are a lot of the obese. I mean the United States is, I think it's like Mexico is now above us, but like for a long time was the most obese nation in the world. You know, big nation in the world. So like the diseases related to obesity now. Now admittedly the European countries have those problems too, but just to a lesser degree. The drug companies, their research and development efforts naturally go to where they're making the most money. And so what this will end up doing is it'll align the drug company incentives to focus on the problems that Europeans have at slightly higher, at higher levels than the Americans have relative. Now these are all rich countries. So it's not like there are unique diseases that happen in Europe that also happen in the U.S. it's a question of relative levels of investment.

Co-host (57:47)

Right.

Jay Bhattacharya (57:48)

And so, you know, I don't think that's necessarily bad. Like an excessive investment in just the things that Americans have at scale don't necessarily translate to better health for Americans.

Co-host (57:59)

Right.

Jay Bhattacharya (57:59)

So you can see this. Since 2012, there's been no increase in American life expectancy from 2012 to 2019. Literally, it was. Well, not literally almost entirely flat life expectancy. Whereas the European countries had advances in life expectancy during that period. During the pandemic, life expectancy dropped very sharply in the United States, and only just last year did it come back up to 2019 levels. In Sweden, the life expectancy dropped in 2020 and then came right back up by 2021, 2022, to the previous trend of increasing life expectancy. Whatever those investments we're making as a nation in the research are not actually translating into meeting the mission of the nih, which is to advance health and longevity of American people. We've had some tremendous biomedical advances have now allowed us to treat diseases that were previously untreatable, which is great, that's a good thing. But it's not actually as far as the broad health of the American public. Address the chronic disease crisis that we face, or address the crisis in longevity that we face. The next generation of kids, our kids are likely to live shorter, less healthy lives than we have lived as parents, as American parents. And I think that. That, I think, is an indictment on this entire industry. We focused on managing illnesses and treating illnesses and try to hold on, especially chronic diseases. And as a result, and we're failing at it.

Co-host (59:40)

Right.

Jay Bhattacharya (59:40)

Europe, on the other hand, is seeing expanded life expectancy. I think this change of trying to equalize drug prices, aligning our portfolio of NIH investments to meet the health needs of the American people. It's a long needed corrective. You asked if will it succeed? I hope so. That's the reason I took this job.

Narrator (60:01)

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Andrew Huberman (60:24)

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Andrew Huberman (62:56)

Well, I really appreciate that you explained so clearly what's going on with this drug price differential and who's paying for it. I was not aware of that. Perhaps I should have been, but I was not aware of that. And as we talked about a little bit earlier, most of the general public, even the science and engineering, mathematics trained, they can connect two or three dots, but they're also very busy. And the general public, like I said, I believe are smart, but. But it has to be spelled out very clearly the way you did for people to really understand.

Jay Bhattacharya (63:21)

I'm a health economist. Right.

Andrew Huberman (63:23)

Well, I think, and I mentioned that in my introduction, but I think it is very important for people to understand that you look at things through the lens of science and medicine, but also epidemiology and economics. There's a saying in laboratories which is that just adding more money doesn't improve the science, but it certainly allows you to take, take bigger risks in service to health and discovery. And without money, no science gets done. I mean, no money, no science. You can't pay graduate students, postdocs, et cetera. I don't want to spend too much time on the structure of basic laboratories, although that's my leaning. I could spend hours talking to you about what's going to happen with the universities, et cetera. We'll come back to that. But there is one piece that we opened up earlier that I think it's important that we close the hatch on, which is the notion of indirect costs being now. Well, it's pending litigation, but level to a lower number, 15% if the administration has their way back to the variable rates, depending on the university. If this lawsuit has its way, and here's what I hear a lot to just put in the simplest of terms, Stanford, Harvard, ut, Austin, big universities, often the private universities have big endowments. So money that's been given by donors, some might have come in through tuition. It's been invested. They sometimes will spend the interest. But as you and I both know, no university likes to spend the endowment, just like no one really likes to spend their savings. Right? People like to spend the interest they make on their investments from their savings. Nobody likes to spend their savings, universities included. The general public tells me all the time, not just on X, but on all platforms and whenever I interact with the public, why should we pay for research at these universities that have these large endowments, to which I say now it's true. Stanford has a very large endowment, Harvard as well, UT Austin, and other places. But many universities, fine universities, superb universities throughout the United States do not have extremely large endowments. And as you pointed out, there's excellent work, important work, I should say, being done those places. So to cut the IDC to 15% for everybody, I can see where I'd say, well, why don't they just dip into their savings, the endowment. But if you're. I'm not going to name names, but if you're at a smaller public university in, in particular in certain areas of the country, not on the coast, unless you're at like a Washu in St. Louis or UT Southwestern, and they got riches, if I'm honest. They have a lot of money. There isn't a savings account to go into. The buildings don't look the way they do at these other universities. You don't have these impressive of lawns and thousands of gardeners, which we're so blessed to have at places like Stanford and Caltech that have tons of money. So to cut the IDC across the board for everybody isn't just sort of trying to restore order to the, to the rich. I do think it potentially punishes the less wealthy universities and important research. I say that in service to them. And frankly, just being at Stanford, it wouldn't be right for me to be like, oh, yeah, 15% will dip into the savings. It doesn't quite work that way if you're at a public university.

Jay Bhattacharya (66:37)

Well, I think you're hitting on the exact policy question, the right policy question. The question is how should the federal investment in fixed cost of research be distributed? Right now it's distributed in a very unequal way where the top universities have access to that money because they have scientists that can win NIH grants. It's a funny thing because if you think of it as support for the fixed cost of research, you have to have scientists, scientists who are good at getting support for the marginal cost of research in order to get the fixed cost of research. But if they're fixed, why would you do that? Why wouldn't you have the money go more equally spread across.

Co-host (67:19)

Right.

Jay Bhattacharya (67:20)

The endowment money is another, more complicated question. I think that endowment monies often are focused on particular projects. There are restrictions on it. But you're absolutely right, it does make a buffer for some of the bigger universities that allow it to survive the vicissitudes of NIH funding or the economy, more so than for universities that don't have that endowment. But from the federal perspective, the key thing is how should the funds be distributed across universities? There's a program called Ideas Program that the nih, the National Institute of Health, has, and I apologize because I don't remember the acronym, but I'll tell you what it does. It says for research institutions in the 25 states that are in the bottom half of the distribution of NIH funding, it gives them a leg up in being able to get access to this federal funding for the fixed cost of research. I think that's a great program because what it does, it says, look, the federal government shouldn't just be funding the top universities. It doesn't make sense from the point of view of trying to get the, the biggest bang for the buck in scientific knowledge. Just like, just a very narrow. Actually, this isn't a narrow thing. It's like an important thing. I think scientific groupthink happens when scientists are all just on the coast and the only scientists you interact with are scientists already agree with you. Geographic dispersion of scientific support allows more richer conversations about science that allows different scientific ideas to develop. Just simply because it's more geographically dispersed, it combats scientific groupthink. There's other reasons too, as you said, like other excellent scientists in universities that aren't in the, you know, like the Stanfords, Harvard's or whatever, that if you gave them an environment where they could do their work, they would have you make tremendous advances.

Co-host (69:21)

Right?

Jay Bhattacharya (69:21)

So I think for lots of reasons, it makes sense to do that. I don't want to comment on the specific. 15% of them are subject to litigation. I will say that the key policy issue is exactly the thing you said. How should the money be distributed for fixed costs of research across the universities? Like one system you could imagine would be where different universities compete on costs. So a university that's able to more inexpensively provide a square foot of lab space fully supported with radioactive disposal and all other stuff, maybe the NIH ought to be giving money to that university more than a university that has to provide it at much more expensive rates. That's not the current system, but you can imagine a system like that. So I think this fight over this 15%, I think it's a great time now to rethink how the NIH and the federal government supports the research infrastructure of the country. It's for the first time in, I think in 40 years, it's now part of the public consciousness, this thought. And I don't think I've not seen anybody who says that we shouldn't have federal support for universities. The question is how should it be structured and to what extent those Are, I think, legitimate questions for public policy debate.

Andrew Huberman (70:41)

Yeah. Well, before moving on from funding and the relationship between tax dollars and universities, I want to ask one more question. Then we'll, we'll move into issues of public health specifically. But having been on study section, I realize I never explained what study section is. Study section is when a group of scientists convene, it used to be in different cities or virtually, and they review grants. Typically, the people who review the grants are expert or near expert in a given area. Typically three primary reviewers, a bunch of people vote on the grant. And to make a long story short, whether you get money to do research from the federal government, AKA the taxpayers, is voted on by a jury of your peers. This has distinct advantages in my opinion, because real experts or close to experts are evaluating your work and they either have to advocate for it or they actively try and kill it. From the perspective of a Reviewer, you're given 12 grants and you know that only three of those can be funded or so. And so you literally have to advocate for the one or two that you feel most strongly about, and you find ways to legitimately make sure that the other grants are not scored as well, and you evaluate each one on the basis of its merits. But you go into those study sections knowing like, goodness, like this grant, I sure would like to see this one. And this other work is kind of pedestrian. It's kind of like, like all the others. Now this is a great model in principle. However, it you talked about groupthink, it lends itself very well to people who are very good at grant writing, which is important. Grantsmanship is important. Continuing to get money and in particular, new ideas, ideas that are outside the vein of what a researcher has been doing for the last, last five, ten years, from promoting the, of doing new ideas, of chasing new new concepts, new hypotheses. It tends to make science move very slowly and very and very incrementally. And so that's one issue. However, I realize I'm weaving two questions, but there's what you described before, that the, the majority of science that's funded at these universities on the coast has this geographic effect, group think effect. What about the rest of the country and these other places, the study sections? The people who review the grants intentionally include people from throughout the country. It's related, in fact, I think, to the distribution of the electoral bodies and people who lobby in Congress. So in other words, there's no study section on a given topic, say Alzheimer's, where you don't see people from the coast, but where you also don't see somebody from the Midwest, somebody from the desert Southwest. There's always been geographic coverage in the. In the people who decide which grants get funded. So I just. This is a historical component here. But. So the question is a very straightforward one, which is, given that a jury of peers decides what gets funded, that checks off the box of, are they experts? Yes, more or less. But it also means that nothing really that new can get funded.

Jay Bhattacharya (74:02)

Yeah, I mean, I think you've hit on a real problem, which is, I think. Let me contrast it with Silicon Valley, right? So in Silicon Valley, you're an angel investor or VC or something, and venture capitalist, and you invest in a portfolio of 50 projects, and 49 of them fail, and the 50th succeeds, it becomes Google or Apple or something. That's a very successful portfolio. The process of how we at the NIH review grants embeds in it a certain conservatism in a desire to make sure that every grant that's funded succeeds. You can have a portfolio where every grant succeeds, but then the portfolio as a whole is not as productive as it ought to be. Because how do you make every grant succeed? Well, you just fund incremental work that you know will work.

Andrew Huberman (74:58)

We call that turning the crank. There was a professor at the Salk Institute, a very superb institution down in San Diego, said to me, the two kinds of science. There's a kind of science where you really test a really bold hypothesis, and most of the time it will be wrong. But if you hit something, it's apt to be spectacular, maybe even open up an entire field, maybe cure a disease. This has happened before, many times over. Or there's the science that will get you funded. Where you turn the crank, you look at a different protein in a pathway that is marginally interesting but is predictable in terms of its ability to create papers. Students need papers, postdocs need papers. Most of them don't want to go on to be lab heads. So they just kind of need papers and a PhD and you learn something along the way. And, hey, you might stumble on something really interesting, but it's kind of like, stand on one foot, stand on the other, spin around, and without money, there is no science. So you could understand why people would be incentivized to do this kind of more incremental. I'll just call it pedestrian. Kind of like, really, they're showing this again. You go to the meetings. It's like they've been doing this stuff for like 15 years, but they keep their NIH grants. And then at the end, they go, they were. We were funded for 30 years. I've had this. When people brag about having the Same grant for 30 years, I just go, oh, my goodness, that's. You should be embarrassed. You know, how about seven different grants over the course of 30 years?

Jay Bhattacharya (76:21)

Yeah.

Andrew Huberman (76:21)

And tell me that one of them led to something interesting. But don't kid yourself into thinking that having a grant, an R01 that lasted 30 years with five renewals, it's like, I look at a lot of those careers of some of my senior colleagues, and I'm like, you made the interesting discovery in the third year of the first iteration of the grant. The only thing you've proven is that tenure keeps people around too long. This is coming from a tenured professor.

Jay Bhattacharya (76:47)

Yeah, I was formerly a tenured professor until recently.

Andrew Huberman (76:52)

But you gave it up by choice.

Jay Bhattacharya (76:55)

Okay, so before the pandemic in 2020, actually, for a decade before, I'd been working on measuring the innovativeness of scientific portfolios, I had a paper that was published on the eve of the pandemic asking, how innovative is the NIH portfolio in particular? And so let me just describe the methodology because it's easy to understand. So take every single published paper published in biomedicine in 1940. Take all the words and word combinations in it and just list them. Okay? Then you do the same. Then you do the same thing for all the papers published in 1941, and subtract off all the 1940 words and word combinations. What you're left with are the unique words that were introduced into the biomedical literature in 1941. You do this for 42, 43, 44, into 2020. And what you get is a history of biomedicine that comes right out of the words that were actually published. You can do this because computers, Right. So you have an age for every single idea that was introduced in biomedicine that just comes out of this automatic process. You go back to the papers and ask, how new are the newest ideas in the papers when they were published? So just to take a concrete example, polymerase chain reaction in 1982, 83, was a new idea. And so if you were Kerry Mullis publishing a paper with the words polymerase chain reaction in 1982, that's a paper that's relying on new ideas. If the newest idea in your paper in 2020 is a preliminary chain reaction, well, that's an idea that's, you know, almost 40 years old. 40 plus years old.

Co-host (78:42)

Right.

Andrew Huberman (78:43)

And now it's in the method section, barely. Right, right.

Jay Bhattacharya (78:46)

Because, you know, it's just like Xerox, right? You just, you barely mention it.

Co-host (78:49)

Right?

Jay Bhattacharya (78:49)

So now the point is that you can use this method to ask how new are the ideas in every single biomedical paper that's ever been published? We did that, me and my colleague Miko Paklen at University of Waterloo. We asked, and then we asked for NIH funded papers. Has the age of the ideas in the paper shifted over time? And the answer is yes. Papers that were published in the 1980s with NIH support tended to work on ideas that were 1, 2, 3 years old. Papers published in the 2000 teens were working on ideas that were 7, 8 years old at the same time. In the 1980s, the age at which you could win a large Grant at the NIH, they're called RO1s. You know all about that. But like folks. But the reason why these large grants are important is because is they are the ticket first to getting funding so that you can actually test your ideas and do the experiments you want to do. But also they're the ticket to getting tenure at fancy universities.

Andrew Huberman (79:56)

In part, I should say, because RO1s, these large grants carry large amounts of IDC indirect costs. Let me put it differently. If a professor comes to a university and does absolutely groundbreaking work, but does it entirely on foundation money, which carries very little indirect funds to provide to the university, there's a chance they'll get tenure, but very small chance. Professors that have R01s stand a much higher probability of getting permanent employment at that university, so called tenure. There are ways to lose tenure, but in principle, it's academic freedom. Tenure was never really about a job for life. It was really about the freedom to explore ideas.

Jay Bhattacharya (80:44)

Turns out there's some subtleties in that.

Andrew Huberman (80:45)

There's some subtleties in that, but. But I think it's so important for people to understand. So much so that when I heard about this Perhaps reduction in IDC to 15%, my first thought was, whoa, that's a big cut. My second thought was, who will get tenure and who won't get tenure? Now it will have to be based on the merits of the work. Now there is a correlation, right? People who do spectacular work tend to get grants. People who get grants tend to get more money. And then you can explore more, et cetera. And the dirty secret in all the R01 stuff is that everybody knows that the R01s are used to fund the next bout of research. But what you propose in an R01, sorry to break every. It's work that's already completed. This is the inside secret of every scientist.

Jay Bhattacharya (81:29)

Oh, I.

Andrew Huberman (81:30)

Every scientist. Because you want to say, look, I can do this.

Jay Bhattacharya (81:33)

I've had our one support also.

Andrew Huberman (81:34)

I mean, you show them the preliminary data. This is what I did. This is what I'm going to do for the next five years. But the dirty secret is this is what I already did for the past five years. I get the money, I do the next thing. This is the shell game that every scientist learns to play. Because otherwise, as you say, you get it in the neck, which is grant speak for you're done. You fire your. You have to can't take students or postdocs. You got to fire your technicians. You close your lab and you become what's called dead wood. So there's a game that's being played, and it's not a dirty game, but it's this kind of like, how about like, kind of don't ask, don't tell game? Everyone knows that people are doing this. And look, scientists are good people. I want to be very clear. They're just trying to survive. Most scientists, I think most of them, I believe most scientists are trying to get it right. I think that local culture can contaminate things. And this grant, this need to be funded.

Jay Bhattacharya (82:24)

I'll grant you most.

Andrew Huberman (82:25)

Okay.

Jay Bhattacharya (82:26)

Yeah.

Andrew Huberman (82:26)

And you know, I'm here in part as an advocate for the public and in part as an advocate for the science community. I can't split myself. Right. But with lower idc, who will get tenure? I mean, who will get tenure? What's it going to be based on?

Jay Bhattacharya (82:41)

Yes, I mean, that background is really helpful. But, but, but here's a fact. In the 1980s, the age at which scientists won their first large grant, RO1 was mid-30s.

Andrew Huberman (82:52)

Okay, I got mine. Let's see. I started my lab when I was 35. I got mine at my first R01. I got when I was 37. But I started my lab in 2011.

Jay Bhattacharya (83:00)

Right. In 2011-2020. You were young for RO1.

Andrew Huberman (83:06)

I was, yeah.

Co-host (83:06)

Right.

Jay Bhattacharya (83:07)

It's a typical scientist within the mid-40s, before they got their first ROI.

Andrew Huberman (83:11)

I didn't have a family. I worked 90 hours a week.

Co-host (83:13)

Right.

Jay Bhattacharya (83:13)

So the point is that young early career scientists take much longer now to be able to get support, to test their ideas out than they did in the 1980s. This is important for innovation because it turns out that this is another paper that I published before the pandemic. It turns out that it's early career Scientists that are most likely to try out new ideas in their work, in their published work, in fact. This is depressing, but for me, with a man with gray hair, but it's monotonic. The first year after your PhD is when you're most likely to have. Have newer ideas in your papers. And then every year after that, for every single year of chronological age, the age of the ideas you tend to work on tends to increase by about a year.

Andrew Huberman (83:57)

Well, the late Ben Barris, my postdoc advisor and beloved colleague at Stanford, who unfortunately passed away in 2017, he used to say. He used to. Like, he was 60 when he died, roughly. He used to say. He's like, nobody does anything after they get full professor. And I was like, that's crazy. We have Howard Hughes investigators, people that win. Nobody. He goes, all the critical work is done early. I said, what about you, Ben? You're there. He's like, oh, yeah, I'm done. You know, this is before he knew he was dying. You know, I mean, this is the dirty secret, because when you're young, you're hungry, given the space from your previous mentors, you are. You're gonna go for it, because you have to go for it. And I. If nothing else comes of today's discussion, already a lot has come of today's discussion. I want to put in a really strong vote for encouraging. I'm gonna catch so much heat for this. But the older labs talk about funding the next generation of science while taking most of the pie for themselves. I really believe, like, if I could just. I'm not going to beg, but I am going to.

Jay Bhattacharya (84:57)

No, you don't have to beg.

Andrew Huberman (85:00)

We need young labs.

Jay Bhattacharya (85:02)

This is an open door. Thank you. In my Senate testimony, when I became, like, before I became NIH director, this is a major initiative that I want. I mean, I think that that early career. Let me put probably too sharp a point on it, right? So right now, what we do is we take the careers of young scientists and effectively put them at the service of older scientists, more established scientists, so that the early career scientists are essentially doing the work of the older career scientists. So you have to have postdoc 1, postdoc 2, postdoc 3, before you have any chance of getting an assistant professor job where you could test your own ideas out. Essentially, the labor of young scientists is devoted to the ideas of older scientists in the current system. That wasn't always true, and the NIH has played a role in that. And it's part of the reason why we have had essentially this sort of more incremental progress than I would have hoped for when I was I did my PhD and did my MD in the early 90s and then, and then into the mid 90s. I envisioned a career where there'd be huge advances in science that I would spend my entire career thinking about and chasing.

Co-host (86:22)

Right.

Jay Bhattacharya (86:22)

And there have been some huge advances but frankly I have this sense that there have been fewer of them than I would have want expected as the 1990 version of me, especially in the.

Andrew Huberman (86:32)

Biomedical sciences because I think we see the expansion of AI, we see the expansion of of computer science, et cetera. I could not agree more. I actually think some of the programs like the PostBAC programs at NIH. I don't want to destroy this program by saying this, but these are where people finish college and they decide to go two years of research before they decide to go to graduate school. This in my mind delays and kind of drains the initiative of a lot of. Look, there's nothing more beautiful than someone graduating college who's still excited about biomedical science taking that energy. Usually they don't have a lot of other commitments yet. I think we should fund them so they can have a healthy life. They don't need to have a lavish lifestyle, but a healthy life and spend as many hours as is reasonable in the lab making discoveries to get through their PhD. Do like it used to be, a short postdoc start a lab and hit the ground running in their 30s and get major funding to be able to test new ideas. It's not just the Silicon Valley model. It captures everything we know about brain plasticity. Their brains are still plastic, they're full of energy, they're full of dopamine naturally. And I'm not saying that everyone past 60 is like dead wood, old wood. There's some amazing work being done at the but it's very top heavy and of course no one wants to give up their lab. I know people in their 70s and 80s, they don't know what to do if they retire. They think they'll do I don't care, get a hobby, let the next generation in.

Jay Bhattacharya (87:55)

Actually there's a one good result. One result that was made me a little bit comforted was in this paper that I did with Miko Pakalin on age and the trying out of new ideas. That is that teams of young scientists, first author, relatively young, teaming with a mid career or later career scientist as a senior author, that combination is most likely to try out newer ideas in their work. It's like you kind of need the.

Andrew Huberman (88:22)

So keep the old folks around. By the way, I'm turning 50 in September, so I'm nearing these numbers.

Jay Bhattacharya (88:27)

You're still a young man.

Andrew Huberman (88:28)

All right. Well, I have, I'm very passionate about this, in part because some of my former graduate students and postdocs are now professors at universities working extremely hard on extremely interesting questions. But I know they would be pursuing even bolder questions related to immune system function and autism, related to, you know, visual repair to cure. Cure blindness. I mean, these are not trivial issues that they're trying to pursue. They deserve, and their peers deserve the majority of the taxpayer dollars for discovery. Because I think that therein lie the, the discoveries and there is this culture in academia of people kind of pinning awards on each other as you go up the ladder. Some of those awards are nice. A good friend of mine just was. He's a member of the National Academy of Sciences. He called me. I said, congratulations. I was like, this is fantastic. And he said, feels good, but like, you know, it. I want to be in lab, I want to be in clinic. I mean, that's what's important. The titles are, in the end, they're meaningless. I've seen so many colleagues die. Like, their offices get cleaned out. Within a week, they're gone. And so the discoveries that young scientists make with tax dollars, to me, is the most important and beautiful thing that can happen. I mean, we'll soon migrate into a discussion about public health. But I'm so relieved to hear, A, that journals are going to be accessible to the public, and B, that you feel this way about young scientists, because I got nothing against the old. I'm not an ageist. But let's face it, youth is when discovery happens.

Jay Bhattacharya (89:58)

But I think let's bring this back to something you brought up earlier and I haven't yet addressed, which is how we evaluate science at the nih. These study sections, they're inherently, and you alluded to this, they're inherently conservative. So just to put a real fine point on it. So I think in the 2000 and tens, there was a policy that in order to be on as active member of a study section, standing member of these grant review panels, you had to have an active R01, a large grant. Active large grant. Think about that, right? So I am a scientist. I'm really well accomplished my field. I have a large grant. By every measure of scientific success, I'm a success. Success. And now I'm sitting judging young scientists, pitching their ideas, some of which, if they turn out to be true, Maybe undermine my ideas. I mean, it's really hard to like, open your brain and say, oh, okay, I'm going to support a project that might undermine my entire career.

Andrew Huberman (91:02)

I mean, everything we know about cognitive bias supports what you're saying. There's another aspect too, which is, you know, letting go of one's own ideas, especially if you're funding and your ability to pay your people depends on them, is tricky. There's another kind of. This is not just inside ball. If you're on study section, your grants are evaluated differently. A lot of people are on study session because you get what's called a special, where people you know and you know who they are, a small team of people that generally like you and you like them. You even can suggest names for who's going to review your grant. Being on study section helps you get grants. You have to get one first in the open water of grant study section. But I hope what people are starting to understand is that the system isn't corrupt. It's just structured in a way that doesn't favor bold, innovative change. And those words, bold, innovative change, are thrown around a lot. I was part of the National Eye Institute's Audacious Goals initiative. We'd get into a room every year. We'd sit around, how are we going to cure blindness? What are we going to do about pigmentosa macular degeneration? And then everyone, everyone went back to doing the same work they were doing before. And so there, a lot of times these, these phrases get thrown out there, websites get put up and like, nothing changes.

Jay Bhattacharya (92:15)

When I talk to the public about science, like, there's, there's a couple of modes, like now post pandemic, a lot of it is just purely cynical. But like, there's another mode of like, thinking about scientists that are just like sitting around thinking deep thoughts, making big advances. But in fact, what you're saying and I agree with is true, but. And it's not entirely cynical, but like, the fact is that there's a sociology to science, right? So I'm trying. There's a. This is sort of like careerism inside science. And sometimes it can lead to good.

Co-host (92:43)

Right.

Jay Bhattacharya (92:43)

You know, your competition with other scientists to like make the big next big advance. But sometimes. But I think in the current way we structure incentives in biomedicine, very often we discourage that kind of sharp innovation. We encourage essentially incremental advances. So I have a safe scientific career for the rest of my life rather than take a big scientific risk where I might fail. But if I succeed, I cure macular degeneration, I cure type 2 diabetes or whatever.

Co-host (93:19)

Right.

Jay Bhattacharya (93:23)

The structure of this, essentially, if you want to, like, put it down as the key problem, is that in biomedicine, academic biomedicine, we are too intolerant of failure. If you have a big idea that doesn't work, essentially, you're out. That's not true in Silicon Valley. Silicon Valley, a failed startup doesn't mean that you can't get another draw at trying to make a successful startup.

Co-host (93:53)

Right.

Jay Bhattacharya (93:53)

Silicon Valley does not punish failure that sharply, and that is the key to its success. Whereas in biomedicine, in the current version of it we have now, we punish failure way too sharply.

Andrew Huberman (94:05)

Yeah, no, I completely agree. And I should definitely point out I never had trouble getting grants, so I'm not coming to this with any cynicism. I moved on to podcasting and I still teach and closed my lab out of a joy of what I'm currently doing. It wasn't that I couldn't fund myself. I did see excellent grants get killed. I also saw some excellent work progress. I definitely agree with this analysis that you did. Thanks for doing that paper. I'll take a look at it. We'll put a link to it. That work early in one's career tends to be the really innovative stuff. There's just something about the younger brain that is more ambitious. It's higher risk taking. And unfortunately, now there's so much pressure to get funding for IDC reasons and to get tenure that oftentimes young investigators will lean toward the more pedestrian, turn the crank type of science, get tenure, and then think they're going to, they're going to go do something. But typically there's something bigger. I am very relieved to hear that young investigators, young scientists, new ideas are going to be prioritized hopefully through the where it really matters, like brass tacks. Like, I think early career R01s should be bigger than late career R01s. It should be inversely related to the size of a laboratory. I think smaller universities should get a bigger piece of the pie. I do. If the work is up to par. Right. You don't just want to give them money just because. But I imagine if R01s were, I don't know, 50, 75% bigger for new investigators, maybe they weren't four years or five years, maybe they were six years, you could really take a run at something or multiple things. And then maybe older investigators who've had grants for a while, you don't want to turn them out to pasture too fast. You want to pivot them slowly. I'm kind of joking, but maybe there are ones should be smaller and they should be more selective about what they're doing because with a lot of grants top heavy in the older generation, they can kind of just spread it around. Well that postdoc went back overseas and this, that didn't work out. I hear about a lot more kind of quiet exit type failures as opposed to we tried really hard. We thought this, this signaling pathway was going to be the thing. It wasn't. Close that hatch, pivot quickly to the next thing.

Jay Bhattacharya (96:19)

There's a few things we could, I mean like one of the nice things of being the NIH director, there's lots of smart people have given me fantastic suggestions for, especially for this specific problem, which I think is the key, probably the most important thing I'm going to be dealing with that plus the replication crisis, which maybe we'll talk about. And I'm not sure exactly what the exact portfolio of things we do will fix this, but we have to support young scientists, early career scientists, we have to punish failure less and we have to change the incentives around so that people want to test the big thing, the big thing that translates into advances for some of the most intractable health problems we face. And if we don't do that, the nih, we're going to look back and say, well, the NIH portfolio of investments the American taxpayer made have not paid paid off just from a macro scale. I mean you can frankly say this for the last, at least since 2012, we have had no increase in life expectancy in the United States. The NIH portfolio in that sense did not pay off during that period that occurred.

Andrew Huberman (97:21)

And I think it was the former director of NIH in a public forum at the end of last year, it was November of last year, I tuned in for that said that we've developed more treatments to extend the life of older people or at least to limit their suffering somewhat. So cerebrovascular disease, cardiovascular disease, things related to dementia, small differences to keep them alive longer. But the real dearth of meaningful treatments sits around younger populations who are dying deaths of despair or whose health is in really just in dire condition due to obesity, diabetes and and mental health issues. So in other words, young people are getting sicker earlier and staying sicker and older people are getting sick but holding on to some remnants of health longer. And most of the treatments are geared toward the older population. Is that true?

Jay Bhattacharya (98:15)

Yeah, that's true. That's exactly right.

Andrew Huberman (98:17)

That's a terrible situation because it essentially is not preparing for the future.

Co-host (98:20)

Right.

Jay Bhattacharya (98:21)

So what we have is a system as a sick care system. The advances we've made, I've allowed people to stay sick longer. It hasn't translated a longer life.

Co-host (98:31)

Right.

Jay Bhattacharya (98:32)

There was a hope, I think when I first started doing research in 2001 in population aging, there was this idea of a compression of morbidity. That is, you live a long life and the time you spent really sick and disabled was compressed at the very end of your life, rather than spending a long time disabled and sick and you die after having spending like a decade or more or very sick. The idea was that we have advances in our cultures as produced results so that you live a long life and you only spend a few months really sick at the end of your life. That hasn't panned out. In fact, we have very little increase in life expectancy. And for many, many people, unfortunately, a very long period of time in a state where they're. The quality of life is not that high, not that good. Right? Dementia, chronic disease, leading to say, diabetes, leading to all kinds of kidney failure, macular degeneration, you name it, peripheral vascular disease, heart disease. You end up with a situation where all of these amazing biomedical advances that we've had over the last decades have not translated to actually improving the health and well being and longevity of the American people. I think that the biomedical infrastructure, research infrastructure of the country has to translate over for results, for real people, for the American people. Otherwise people can ask us, why are we having these, why are we doing what we're doing? It can't just be that we're doing cool things. I mean, not that we're not doing cool things, a lot of cool things are getting done. But if they don't somehow eventually translate over again. I don't mean to distinguish basic science work. I think basic science work is really important, but eventually it has to translate over or else people will say, why have we made these vast investments? The key thing is if we're not actually improving health as a result of the research we do, then we haven't accomplished our mission.

Co-host (100:38)

Right.

Jay Bhattacharya (100:38)

And the research agenda of the NIH as we've talked about, it's like we talked about, you know, international relations as determining in part what scientists work on, you know, for in drug pricing. We've talked about how politics determines the, the agenda that scientists work on.

Co-host (100:58)

Right.

Jay Bhattacharya (100:58)

So you talked about hiv.

Co-host (100:59)

Right.

Jay Bhattacharya (100:59)

So the political focus on HIV led to the vast investments the NIH has made in HIV with some positive effect, actually a lot of positive effect. And then also the sociology professions, the scientific profession determining these are all complicated things that result in the portfolio. But if the portfolio ultimately doesn't meet the health needs of the American people, then it's not doing what it's supposed to be doing. Part of my job is to make sure that it does meet those health needs. The Make America Healthy Again movement, that's what it's asking for, that the health institutions of this country actually meet the health needs of the people where they are. And in large part, we've not successfully done that in this country for decades. Otherwise we wouldn't have this major chronic disease crisis we're currently facing. And so that's, you know, it's a complicated question. It's not like, you know, it's not just solved by funding one grant or making specific decisions. It's about the incentive. That's the system at large to focus on, to create incentives so that scientists turn their ingenuity toward those health needs rather than, rather than just advancing their careers incrementally.

Andrew Huberman (102:13)

I'd like to take a quick break.

Narrator (102:15)

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Andrew Huberman (103:12)

I love the raspberry.

Narrator (103:13)

I love the citrus flavor. Right now, Element has a limited edition lemonade flavor that is absolutely delicious. I hate to say that I love one more than all the others, but this lemonade flavor is right up there with my favorite other one, which is Raspberry or watermelon. Again, I can't pick just one flavor. I love them all. If you'd like to try Element, you can go to drinkelement.com huberman spelled drinklm n t.com huberman to claim a free Element Sample pack with a purchase of any Element Drink mix. Again, that's drinkelement.com huberman to claim a.

Andrew Huberman (103:44)

Free sample Pack this is a perfect segue for a discussion about the replication crisis. It's a perfect segue because up until now, and still now, the independent investigator model, for those that aren't familiar, is Andrew Huberman gets hired as a assistant professor who might get tenure at a university. And then the so called Huberman Lab. Before it was a podcast, it was also a actual laboratory space. Physical space has to come up with a set of ideas that hopefully pan out. You get funded for, you get tenure and then you can pursue new ideas. But it's an independent kind of startup of its own. My neighbor two doors down in the hallway works on something else. One of the major issues, I believe, that led to the so called replication crisis is that it is very difficult, even with the best of intentions, for two laboratories to do the same work in an identical way. Five minutes longer on a countertop at room temperature might change an antibody. That could lead to a different outcome. I mean, there are so many variable the solution to this is collaboration. Instead of having independent investigators, you have clusters of laboratories, hopefully distributed throughout the country, working on the same problems collaborating. There are grants of this sort. But here's the problem. As you point out, it's a sociological issue. The graduate student in my lab needs a first author paper if they want to eventually get their own lab. The postdoc in another laboratory doesn't want to be a middle author with 20 other authors to continue to flesh out the world of science with scientists. The independent investigator model works. Those independent laboratories are naturally going to come up with different answers, talk about them at meetings, and maybe there'll be some convergence of ideas. But wouldn't it be beautiful if laboratories collaborated to try to solve important problems related to public health? And everyone was incentivized for through perhaps not easier but more plentiful funding to do the research, salaries that these people can live on reasonably while they're graduate students and postdocs, and maybe even laboratories that are more structured around a problem. So it's not called the Huberman Lab. It's called the Laboratory for Curing Blindness. And there's another Laboratory for curing blindness at WashU and another one in university in Illinois. And we all collaborate and we try and cure blindness as opposed to making it all about the principal investigator, the independent investigator. The rock star model of science kind of works and it kind of is part of the problem in my opinion.

Jay Bhattacharya (106:26)

I agree with you about collaboration in the following sense. So science is a collaborative process, but the incentives within science for individual advance can often lead to a sort of a, a structure that, that elevates, elevates careers without necessarily producing truth. So let me, let me, let me, let me flesh this out.

Andrew Huberman (106:52)

Very tactfully put.

Jay Bhattacharya (106:54)

Okay, so there's a, a colleague of ours at, at, at Stanford named John Ioannidis. He wrote a paper in 2005, absolutely brilliant scientist. I think the most highly cited science living scientist in the world.

Co-host (107:03)

Right?

Jay Bhattacharya (107:04)

So, so he, he wrote a paper in 2005 with the title why Most Published Biomedical Papers are False. I mean when you make a title like that for a scientific paper, it better be convincing. And in just a few pages it's an utterly convincing paper. And it's not because scientists commit fraud. That's not the reasoning behind it. Because science is hard. And the hard in exactly the way you just said, Andrew. So you publish a result, you believe it to be true, you have some statistically significant result at some level, you know, we say P equals 0.05. What does that mean? That you know, some percentage of the time, even though you believe the result is true, it's been peer reviewed by your colleagues. The peer review actually doesn't involve, as you know, the peer reviewers taking your data, rerunning your experiments. It doesn't mean any of that. They just read your paper, looked for logical flaws, didn't find any, and then they recommend to the editor it be published. So the peer review is not a guarantee that it's true. You have some statistic significance that say that your data meet. Even with that some percentage of the time the published result is going to be false. Now if you think of science a priori is hard, any result that you publish is most likely going to be a false positive result.

Andrew Huberman (108:28)

So called negative results aren't incentivized. Yes, they're very hard to get a good paper published for showing that something isn't true. It happens. I had a paper published in Science which argued that at least one aspect of a theory was not true. It was a very prominent theory. Turns out other aspects of that theory were true. So sometimes it happens. But no self respecting graduate student or postdoc who values their life is going to say, hey, I want to go in and try and disprove the hypothesis of one of the more famous people in the, in the field. In fact, I didn't set out to do that. It just so happened that's the way it landed. And no one shows up in graduate school and says, you know, I love these papers, let's replicate them.

Jay Bhattacharya (109:08)

Yeah, right. So let's get back to that because that's. You're absolutely right about the incentives and that this is. But this is the. Let's just. Before we get to that and the incentives we analyze that just put a fine point of the nature of the problem. The published biomedical literature, something that I've searched basically every day for the last 30 years. 40 years. Oh my God, 40 years that published biomedical literature. Most of the time that I'm reading papers in that literature, the papers I'm reading, even though they say their result is true, is likely not true. Look, I had a professor in medical school who once told me, as one of my favorite professors, he told me, look, half of what we're teaching you is false.

Andrew Huberman (109:51)

Well, okay, so I'm glad you're pointing this out. I asked a very prominent neurosurgeon, perhaps one of the most prominent neurosurgeons in the world. I said, what percentage? Someone else asked him, but I was right there. What percentage of information in medical school textbooks do you think is false? And he said, half. And then the second question was, what do you think the implication is for people, for human health? And he said, incalculable.

Co-host (110:15)

Right?

Jay Bhattacharya (110:16)

Exactly. And that's true of the biomedical literature as well.

Co-host (110:18)

Well, right.

Jay Bhattacharya (110:19)

So the published peer reviewed biomedical literature is not reliable is the bottom line. So a lot of the things that we think we know, even with some fair degree of certainty, are probably not true. And the question is, like, which half? Well, we don't know the answer to that question.

Andrew Huberman (110:36)

It's probably a mix. Parts of papers are probably true and other parts are not.

Jay Bhattacharya (110:40)

Right.

Andrew Huberman (110:41)

It's not like all the papers from one. Well, there are those labs, but they don't last long.

Jay Bhattacharya (110:44)

And this is done even with pure goodwill and no fraud at all.

Co-host (110:49)

Right.

Jay Bhattacharya (110:49)

And the reason is a combination of the fact that science is hard and the incentives we created for publication.

Co-host (110:57)

Right.

Jay Bhattacharya (110:58)

Those two together mean that the scientific literature is. The biomedical scientific literature is not reliable. I've talked with drug developers who tell me that before they make make vast investments in a phase three randomized trial or even phase one or phase two trials studies. They conduct independent replication efforts of the basic biomedical literature to see if it actually is true. Now those are private replication efforts so that the drug developers know which parts of the literature are true and false, but the scientific community at large doesn't know. We've set up a system, a publication that guarantees that much of what we think is true is not true. That's a major problem for science. And it's linked to this idea that you have to publish or you're out. It's linked to this idea that if you fail, if you publish failure, you're out. It's linked to this sort of reward that we give to scientific volume, like the number of papers we publish and scientific influence. That's what citation counts are. There's a number. I'm sure you know this, Andrew. I'm explaining it to the folks who are listening. Something called an H index, right? So if you go to a site called Google Scholar, every scientist listening to this, I'm sure, has gone and looked at their Google Scholar page. They have a little card at the top, right, that essentially looks like a baseball card to me. And it has a few statistics. And if you're not a scientist, you won't necessarily know what the statistics are, but what they are. Things like an H index is. Okay, so if you have an H index of 10, that means you have at least 10 papers published in the peer reviewed journals that have 10 citations each. But you don't have 11 papers with 11 citations each. So in order to get a high H index, you have to have both a lot of papers and a lot of citations to those papers. It's a funny number because like you can imagine, just to bring back Watson and Crick, imagine Watson and Crick, the only paper they ever published was the structure of DNA. Good paper, let's say it has a million citations.

Andrew Huberman (113:14)

Not peer reviewed, but good paper. That's a fantastic paper and was never peer reviewed.

Jay Bhattacharya (113:17)

Right. But a million citations. And imagine it was their only paper. Well, they have one paper with at least one citation, but they don't have two papers with two citations, so their H index is one. Or you could have a million papers in the Journal of Irreproducible Results, each with one citation each, and you have one paper, at least one paper with one, one citation. So you have, but you don't have two papers with two citations, so your index is one.

Andrew Huberman (113:42)

Or you could write a lot of reviews because reviews get cited like crazy.

Jay Bhattacharya (113:46)

Yes. Okay, so now what you have then is a, is a, is a incentive for scientists embedded in Google Scholar that says, look, you have to publish a lot of papers, you have to have a lot of influence because that's what a citation is. It's a measure of influence. You go to scientific meetings in order to sort of shop your ideas around.

Co-host (114:06)

Right.

Jay Bhattacharya (114:09)

And so we reward scientists for the influence that they have, and we reward scientists for the volume of papers they publish. What we don't reward scientists for is, is honesty about their failures. We don't reward scientists for pro social behavior like the sort you suggested, where you collaborate, you share your data openly and honestly. In fact, we punish scientists for that.

Co-host (114:33)

Right.

Jay Bhattacharya (114:33)

So right now, if somebody comes to me and says, jay, I want to replicate your work, I've trained myself not to think this way, but it's really hard not to given the structure we're in. I'm going to think of that as the threat. What if they don't find what I've, what I found now I'm a failure.

Co-host (114:51)

Right?

Jay Bhattacharya (114:52)

The failure to replicate is seen as a failure of the scientist rather than the fact that science is hard and it's difficult to get results that are true even with the best of will. And we punish scientists for that. So we essentially reward scientists for a set of things that creates incentives for the replication crisis to happen. I see, right. So the solution to the replication crisis is to address those things, measure the pro social things that scientists could do, recreate the incentives away from simply influence and volume. I'm not saying you shouldn't reward influence and volume. I'm saying you should reward a fuller set of things. It's like in baseball, you know, you reward a hitter for home runs, but you don't also measure strikeouts. Well, you're going to get a lot of strikeouts and not necessarily, you may get a lot of home runs, but that may be bad for the team in total. So you want a full set of statistics measuring the things you actually want scientists to do in order to solve the problem. So let's say we had statistics that said, look, do you share data with others in your published research work? And we have that as among the baseball statistics we put in Google Scholar.

Co-host (116:17)

Right.

Jay Bhattacharya (116:18)

Let's say we ask, is your work subject to replication? Actually, if your work is subject to replication, you have ideas that are worth replicating, looking at by other scientists that's a success no matter what they find. How frequently do you publish your false results, results that turn out to be not true.

Co-host (116:36)

Right.

Jay Bhattacharya (116:37)

Imagine we had those statistics. We would have a fuller picture of what scientists like, the capabilities of scientists, the outcomes of scientific work and we would reward the pro social things that would solve the replication crisis. So what you have now is a real problem that's not been addressed. We've known about this now for decades, but had not been addressed adequately. There've been a number of efforts by the NIH over the last last several couple of decades to try to address it, but it hasn't solved the problem.

Andrew Huberman (117:05)

Well, I feel like that the issue that really cracked this open, the reason the general public might have heard of the so called replication crisis is this idea that there were some findings in the field of Alzheimer's research that were false, but they were wrong potentially for the wrong reasons. As a scientist you learn it's okay to be wrong for the right reasons. Meaning your measurement tool was inaccurate, but it was the best you had at the time and you thought it was accurate. You know, better tool comes along, you get a different measurement, new result. I guess you were wrong for the right reasons, but you're not fudging data, you're not hiding data. There is this idea that in the field of Alzheimer's research that somebody might have fudged data, made up data, and that the field kind of went along with it. That's not my understanding of what happened. My understanding is that somebody fudged data and then nobody went back to check the primary data in that paper. And as a consequence, many years down the line, a number of subsequent findings were nested on a false finding and the whole thing tumbled like a house of cards, more or less.

Jay Bhattacharya (118:06)

The process you just described is the replication price is playing itself out, right? So you make investments built on a house of sand, on a foundation of sand. And you eventually get fancy drugs that are supposed to, to prevent you from getting the disease that you're trying to prevent. You know, in this case, prevent you from being able to, you know, prevent you from like progressing to where you can't remember the name of your kids and you can't live your live a normal, you know, full life as your memory goes away. The drugs don't work for those things. And your question is why? They're built on the best science going all the way down. It turns out the best science all the way down is not replicable. The, the fraud aspect of it is actually not even the most. It's important, but it's not the most important part of it. It's almost just an afterthought. Ask yourself, why have there been so many scandals brought down? The former Stanford president, the nih, again just within Alzheimer's. There was a director of neuroscience who apparently had 100 or more papers with this Photoshop fraud. So the question is, why have so many prominent scientists been brought down where their like work has been shown to be fraudulent? It's not a moral failure on the part of any individual scientist. The structure of incentives we've created produced those behaviors.

Andrew Huberman (119:32)

We created them is what you're saying.

Co-host (119:33)

Yes.

Jay Bhattacharya (119:34)

We said you will get advances in your career if you publish a lot of papers that have a lot of.

Andrew Huberman (119:40)

Influence and if you admit that you were wrong about something, your life is over, career is over. Yes, I think one of the most beautiful things in science was when Linda Buck, co recipient of the Nobel Prize with Richard Axel for the discovery of the molecular structure of olfactory receptors, retracted. I think it was three papers from her laboratory, a postdoc, either with sloppy or fudged data. She retracted the papers because the papers were wrong. People told her this stuff doesn't replicate. Not only did it not hurt her career, it helped her career. She was right about the olfaction work that got her the Nobel Prize, but she was willing to admit a mistake. Someone in her laboratory made a mistake, ergo, she needed to retract those papers. What happened in the case of our former colleague still, well, you're not at Stanford anymore, was, let's just put it this way, in every major laboratory that's publishing at a phenomenal rate inside the field, there is always discussion. Postdocs talk, graduate students talk constantly. And people know that work is solid. And other work, like there's something just gets said at meetings like, no, nobody believes that when somebody says and that gets passed around. So then no one follows up on it. But it's rare that somebody goes and whistle blows the way that those papers got whistleblown. And then the right thing to do, in my opinion, okay, is you correct or retract the paper. If you make a mistake, you correct the mistake. There are ways to do that. People publish corrections all the time. Or you retract the paper if it's wrong. I think that the system, as you pointed out, has made it feel very dangerous for scientists that are approaching the pinnacle of science, like within reach of Nobel Prizes winning Laskers winning international awards, as was the case in all these instances that they could admit that they were wrong.

Jay Bhattacharya (121:30)

Andrew, it's all up and down the system. Imagine you're a postdoc and you have to get your paper, you retract your.

Andrew Huberman (121:35)

Paper, you're essentially starting over or leaving science.

Jay Bhattacharya (121:38)

Yeah, you're leaving science. It's existential, the structure. So the problem of fraud in science then is a symptom of the broader problem of the replication crisis rather than the main driver of it. So the right solution then is not root out the fraud. The right solution is change the incentives of science so that we have as scientists engage in pro social behavior. Pro social in this case meaning behavior that rewards truth rather than rewards volume and influence alone.

Andrew Huberman (122:11)

Music to my ears. How is NIH going to do that?

Jay Bhattacharya (122:14)

So we were talking about the innovation crisis. That's a much more complicated crisis. This one actually I think is doable within the context of the nih. I think you have to do three things. So. So first you have to make it a viable career path to engage in replication work in creative ways. To some extent there's some of this with like meta analysis. Meta analysis is the science of analyzing the scientific literature to ask whether what the scientific literature as a whole says about a particular question. Right. That's what meta analysis is. And so there are people who make careers on meta analysis, but, and so that's in a sense a kind of replication work.

Andrew Huberman (122:55)

Studying studies.

Jay Bhattacharya (122:56)

Yes, studying studies.

Co-host (122:57)

Right.

Jay Bhattacharya (122:57)

So, but it's really difficult to make a career out of doing replication work as a general matter within science. You can't win a large grant at the NIH currently where you say, oh, I'm going to do meta analysis, I'm going to do replication work, which means then you're not going to get tenure at a top university, you know, because you can't win the large grant that require that you're required to get in order to win. So you're not going to focus on replication work as a young scientist, even if you are very good at it, even if you could think creatively of how to do it at scale.

Andrew Huberman (123:32)

But it is discovery. Right. Like I think, you know, we need to reframe it. Right. Replication is kind of a dirty word. It shouldn't be. But you know, years ago when gene arrays first became available where you could look at gene expression in cells or tissues, now you do single cell sequencing and you can do deep sequencing. And this has really evolved. None of those, dare I say, are experiments. You're not testing a hypothesis. They are hypothesis generating experiments. You get a bunch of genes and you go, well that one's much higher in the cancer cell and that one's much lower in a non cancerous cell. I think I'm going to go do like a knockout of that gene or overexpress that gene. I mean that's testing hypotheses. But you. There is work that's necessary but not sufficient. And what you're describing in terms of meta analyses, AKA replication, maybe should be recast simply because branding matters. It shouldn't, but it does. And incentivize it as discovering whether or not discoveries are actually discoveries. What's more important than that?

Jay Bhattacharya (124:33)

Yeah. Like essentially saying, is the scientific literature true? Like assessing the truth of the scientific literature.

Co-host (124:43)

Right.

Jay Bhattacharya (124:44)

That's what that is. And that's a real fundamental actual advance.

Co-host (124:48)

Right.

Jay Bhattacharya (124:48)

Exactly the way you say. But we don't reward it. The NIH doesn't reward it. That will change.

Andrew Huberman (124:54)

Well, drug companies, it occurs to me, should be incentivized to do it because it will save them. Perhaps they do it extensive. Well, but perhaps they won't have to do it as extensively because if the work that they're getting down the funnel has been checked multiple times by multiple laboratories, they have an increased confidence that molecule A, B or C does A, B or C. Sure, they'll test it again because they're about to put dollars behind it. No one wants to put dollars behind something that they aren't absolutely sure is true. But you'd like the funnel to be narrower.

Jay Bhattacharya (125:24)

Yeah. And right now they test it. They do the replication work. Drug companies, before they make those investments, do the replication work, but it's private. So that only they know which results are true and false in the literature.

Co-host (125:36)

Right.

Jay Bhattacharya (125:37)

So if the NIH does it, the knowledge about which results are true becomes public, which makes the entire scientific literature much more reliable as a basis not just for drug discovery, but also for individual behavior. Which, which of you know, which health behaviors should I. I mean, what food should I eat to make myself healthier?

Andrew Huberman (125:58)

Well, that no one can agree on that.

Jay Bhattacharya (126:00)

I know, but part the reason why.

Andrew Huberman (126:02)

You can only agree on what you shouldn't eat.

Jay Bhattacharya (126:03)

Eat.

Andrew Huberman (126:04)

And even there.

Jay Bhattacharya (126:05)

Yeah, I mean, I shouldn't beat the skittles with the prolonged.

Andrew Huberman (126:08)

I heard that processed foods are bad, but the other day I saw. You're not going to believe this, but there's a kind of a. A emerging movement in one sector of the media that the demonization of highly processed foods is a conspiracy theory, which is like. Like if that so. But that's a perfect example of sort of what we're talking about more generally, which is that language matters. You can throw something in the trash bin very quickly by calling it a conspiracy theory until somebody makes or a group makes the effort to bring it out over and over again and determine if it indeed is. You can also throw something in the trash bin very quickly if you just call it just a replication study or a so called negative result. A negative result says this particular pathway, molecule, mechanism, et cetera, is not doing what we hypothesized it would.

Jay Bhattacharya (126:56)

And that's a real advance in scientific knowledge.

Andrew Huberman (126:58)

Absolutely without question.

Jay Bhattacharya (127:00)

So the reason why we don't have consensus on what's the right thing to eat is because the scientific literature. Well first it's a more complicated question than just science. But like part of it is that the scientific literature around it is not replicate, replicable.

Andrew Huberman (127:13)

And those studies are really hard get people to eat the same things. You know, people are. People are probably sneaking skittles. People lie about what they eat.

Jay Bhattacharya (127:21)

People, by the way, I don't like skittles. I've always. I was more of an M and M person just for the. Whatever. Let's just leave that aside.

Andrew Huberman (127:27)

Well, it's clear that yeah that the new administration both champions healthy unprocessed foods, but every once in a while you'll see one of them consume it.

Jay Bhattacharya (127:36)

I've cut down the skittles since I've joined the MAHA movement, whatever the M&Ms. Okay, so let's go back to what we were talking about. How do you ask, how do you fix this? Right, so one is you give large grants to people in the scientific community who do replication work in creative, important ways, scalable ways. You farm out to the scientific community. The question of what results in the scientific literature really need replication. The key sort of rate limiting step kind of results, we need to know if they're true to advanced science and advance human knowledge on questions of health. So you reward large scale, large grants for scientific scientists. So now all of a sudden their status is lifted compared to where they were before, which is down in the basement.

Andrew Huberman (128:27)

Will there soon be an institute or a set of grants set aside specifically for meta analysis? And to resolve this, to help resolve some of this so called replication, I'm.

Jay Bhattacharya (128:37)

Planning to do that.

Andrew Huberman (128:38)

Fantastic. I don't think you'll get any pushback on that. However, every dollar spent one place is a dollar not spent elsewhere.

Jay Bhattacharya (128:44)

Yes, but at the same time making the entire scientific literature more liable is money well spent.

Andrew Huberman (128:49)

That is my belief as well.

Jay Bhattacharya (128:51)

Second, you have to have a place where you can publish this work. Right now if you send your replication result to a New England Journal of Medicine or Science or Cell or Nature, they will not look at it at all. The NIH can stand up and will stand up a Journal where these replication results can be published and made searchable in an easy way so that you have some scientific paper, you ask yourself is this something that other people have found? You can go to the scientific journal that we're going to stand up, you can search it very easily and ask where are the other papers that look at the same question and what do they find and get a summary of it.

Andrew Huberman (129:31)

So this is a little bit like community notes on X in a way.

Jay Bhattacharya (129:35)

But it's the scientific literature producing this community notes. Right.

Andrew Huberman (129:38)

These are formal papers with method sections and credentials.

Jay Bhattacharya (129:41)

Yeah.

Andrew Huberman (129:42)

Not just anyone doing this work, it's.

Jay Bhattacharya (129:44)

Part of the community of people that are looking at this question in rigorous ways.

Co-host (129:47)

Right.

Jay Bhattacharya (129:47)

So, so the point is that you'll have kind of a Cochrane Collaborative. Cochrane is this group in the UK that grades scientific evidence on a whole bunch of different health questions in a way where they elevate rigorous randomized control studies is the highest level of evidence and then N of one kind of studies is the lowest level and a whole bunch in between. And they'll produce reports to say, well, there's weak evidence suggests this is true, there's excellent evidence suggests this is true. There's no evidence suggests one way or the other on this. They're very, very nuanced in summaries. You should be able to do that. But with the published replication work as the core of it.

Co-host (130:31)

Right.

Jay Bhattacharya (130:32)

And a scientific journal put out by the nih, a high profile journal, will then make publishing replication work a high profile scientific, high prestige scientific activity. And the journal could also publish negative results. I tested this idea, it didn't work. Published in the journal and now it's discoverable. It's no longer the threshold of you have to have a statistically significant result in order to get your result published. You just publish the result because it's interesting and true, even if it was a negative result.

Co-host (131:01)

Right.

Jay Bhattacharya (131:03)

The journal then that the NIH will stand up, will plug a hole in the literature where we don't reward, where we punish failure. Instead we would reward it where the constructive failures are published and communicated to the scientific community at large. We reward replication work, so fund replication work, create a place where it's publishable and essentially rewarded. And then third, this is probably the most important measure pro social behavior by scientists. Make it part of the suite of statistics we use to measure scientific productivity. Not just publication, not just influence, but also, do you share your data? Is your work, has it been subject to replication? Do you cooperate with those replication efforts? Do you yourself engage in replication efforts of others and make that part of the suite of statistics we measure for scientists to measure their productivity. And now all of a sudden, replication becomes something you want to participate in even if you yourself are not doing. Fundamentally alters the culture of science so that rewards truth, truth, science. Scientific truth is determined by replication, right? By independent research teams rather than influence. It's hard to think about as scientists, we think about scientific truth as, or you published in the New England Journal, or you published in Science Cell or Nature or whatever, that's truth, peer reviewed papers. But in fact, the ground truth of science is determined by something really much more humble than that. It's by replication. We need to reward the things that produce the ground truth rather than the things that reward just pure influence. And we don't do that. It's hard and it's almost impossible as scientists that have grown up in a community of people that reward influence as the primary measure of success, to think what it would be like if we were to reward truth. But I think if we do these three things, it'll completely transform the nature of science. Why would you want to commit any fraud? You're not going to get a reward for it. Yeah, you get a published paper, you might even be a top journal, but no one's going to replicate it. You won't want to share your data with people because they'll find out you committed some fraud. All the incentives to commit fraud will just dissipate. It'll be liberating for scientists to be able to focus on the things we actually care about, which is learning about the world, true things about the world. The reasons why we went into science to begin with, rather than this sort of like competitive process of trying to get climb up a ladder that doesn't necessarily produce any truth.

Andrew Huberman (133:38)

Listen, amen to all of that. I feel very blessed that I had a graduate advisor who said, she said it was wild. She unfortunately passed away young as well. But she said, you know, why would any scientists make up data? It's crazy, right? You're trying to figure out what's true. So that essentially means they're willing to lie to other people about their data and to themselves in some sense. Right. The other thing is, I'll never forget revising a paper with her and I remember thinking like, oh, well, we have this, this. And she said, whatever we do, we can't give the reviewers what they want. And I thought, that's a weird statement. All you ever hear is, you know, you got to give the reviewers what they want. But It's a very dangerous statement. And the reason she was saying, don't give the reviewers what they want is you have to stay, you know, wholeheartedly committed to what you know and observe to be true. And you were closest to the data, so you would know. The other thing that I learned from her, and this relates to what you're saying, is that it not only is okay, but it should be encouraged to publish papers in an array of journals. I think the pressure to publish in high profile journals in order to get a really great job is so great that it leads some postdocs, as it did in some of the cases we were talking about earlier, to either make up data or to throw away data that didn't fit in order to please the boss. Then the boss gets pulled into it, then the boss tries to dissociate. This has been going on for so long. I feel very blessed that I was encouraged to publish some papers if they had a chance in Science and Nature, but other papers in fine journals like the Journal of Neuroscience, where the accuracy and in some sense the volume of data was also encouraged. You could put a lot more data there. But now with online publishing and electronic formats, there's no limit to the amount of data you can put. So you can no longer use the excuse, well, you know, the high profile journals, you only can have four figures. So I think everything you're saying is very reassuring and should be reassuring to people. It's music to my ears, frankly. And I think it will be music to the ears of graduate students and postdocs who feel this immense pressure to make a major discovery, to make the lab head happy so that then they can get promoted to getting a job. Because most of the job process is powerful. PIs picking up the phone and saying, I've got this postdoc, you should hire them. That's like, it's a lot of it. It's not all of it, but that's a lot of it. So having an elder that supports you is huge. The other thing that I just am so relieved to hear is that the system has been around a long time. And it sounds like from what you described, it worked really well up until about the 90s, mid-80s 90s, and that at some point something happened, something changed. And I don't doubt that scientific fraud took place a long time ago. There wasn't replication, but I feel like, like some of the pure essence of science that you were alluding to earlier, people tackling new issues that there isn't really. It's more survivalist, careerist now than it is about the spirit of discovery, which is really about the spirit of finding out the truth. So any reflections on, on this notion.

Narrator (136:43)

That we're sort of in a more.

Andrew Huberman (136:44)

Careerist mode of science?

Jay Bhattacharya (136:46)

I think part of it is just the sheer funding levels have been, been so high. Well, I mean over the, over the, just I think over the time period you're talking about, there was a doubling of the NIH budget, there was all kinds of like increases and the sheer volume of research, I think the way that we manage, I think it's worthwhile investments to have those investments. Right, but to have such high volume relative to what we had in the 80s, to have such high levels of funding relative to what we had in the 80s.

Andrew Huberman (137:14)

Are you saying that we have too many scientists?

Jay Bhattacharya (137:16)

No, I'm not saying that. What I'm saying is that we have to create structures that are appropriate for the volume that we have have so that we produce in this volume. It's like a fundamentally different problem than we had in the 80s. So the structures that we had in the 80s where we rewarded publication and peer reviewed journals as the measure of success, it might have worked to create incentives for pro social behavior in the 80s, but it doesn't work at the volume and the levels that we have now. And so we have to change the structures we have have so that given this volume of investments, people have the right incentives to have those pro social. We have to change, we have to change how we think about, we structure the incentives in science to create the kind of pro social incentives that we once had.

Andrew Huberman (138:01)

All right, now that we're through the easy stuff, let's get to some of the harder stuff. Just kidding. You have a tough job, my friend. Let's talk about some of the recent changes in NIH funding that most people have heard about. And then we will segue to the barbed wire topics of vaccines and lockdowns. But before we do that, I heard, or at least my understanding was that when the new administration came in, they essentially went through and looked for the letters DEI and for the word transgender and basically halted or eliminated some lines of funding to particular labs. I also saw on social media and I, I didn't validate this, that some studies that were focused on transgenic, not transgender, but transgenic mice, which is a very common tool in biomedical research, got flushed in that process. So that maybe it wasn't a, a clean vetting of transgender versus transgenic. Look, every, every administration, every person makes mistakes. So I'm not trying to Highlight mistakes. But I think this blew up and it would be great because you have an opportunity here to reach a lot of people to just sort of clarify what the rationale of eliminating grants that had a dei or transgender component was. And then we can talk about this. What appeared to be a mistake.

Jay Bhattacharya (139:32)

Yeah. So first, let me just talk about the mistake first. Most of this happened before I became NIH director. There's, like, early April is when I started. I think much of the.

Andrew Huberman (139:40)

When did you start?

Jay Bhattacharya (139:42)

April 2nd. All right.

Andrew Huberman (139:43)

So don't come after Jay for anything that happened prior.

Jay Bhattacharya (139:45)

And it was actually quite frustrating to be on the outside looking in, going, I can. I can just look.

Andrew Huberman (139:49)

Yeah, they were waiting for you to step in so you could take responsibility anyway.

Jay Bhattacharya (139:52)

Yeah.

Andrew Huberman (139:53)

So they could blame you for something.

Jay Bhattacharya (139:54)

I mean, I don't mean to say, like, I, I, you know, like, this. I, I'm still like, responsible for, like, like addressing this going, like, going forward. So the trend. So I don't, I don't actually don't know specifically about the transgenic. That's obviously a mistake. The transgenic mice are a key tool for discovery. If, if that was cut, it was. I think we.

Andrew Huberman (140:15)

Maybe it might have been a wording in a public address from the present. I don't know that they actually eliminated grants simply for studying transgenic mice. I know that grants focused on. Look, I. Years ago, I studied sex differentiation in the brain and body. So not all studies where you give a male rodent estrogen or a female rodent testosterone are studies of transgender biology. Those hormones are active in both sexes. And, you know, there are a lot of grants that you can imagine that that got flushed that were studying hormones and sex differences.

Jay Bhattacharya (140:46)

My sense is there were some false positives like this. And we've worked, I've worked very hard to make sure that those are corrected. Like, there's an appeals process that I've set up so that researchers were stuck in this with a false positive. We've restored a whole bunch of grants like this where it's good science, but it got caught up in this DEI kind of focus on like, of refocusing the NIH portfolio away from sort of politicized ideologies and more toward things that actually advance health. So let me just address DEI specifically. Okay. First, this is really important to me. In my own research, I focused a lot on the health and well, being of vulnerable populations. A lot of my research is focused on the health of minority populations. And there are legitimate scientific questions that where somebody's race, sex matter, Pretty fundamentally to the biology. And so of course, as the nih, we have to be able to look at that.

Andrew Huberman (141:47)

Yeah, some mutations only exist in certain races or, or I mean, breast cancer. And the BRCA mutation, more common, much more common in women. I mean, you can't pretend this stuff doesn't exist.

Jay Bhattacharya (141:59)

Correct. And so like, that's part of science. And the NIH absolutely supports that kind of research still, despite all of the changes in dei. So I want to give you another example of an NIH success is the research on sickle cell anemia.

Co-host (142:18)

Right.

Jay Bhattacharya (142:18)

So, so the research on the strategy is this gene editing strategy essentially is to switch the cells so that they express the fetal hemoglobin rather than the adult hemoglobin that has this problem that causes sickling. That's a fantastic result that's going to, I think, result essentially in a cure for sickle cell anemia. Amazing, right? So amazing. And it's a, a thing that affects African Americans much more frequently than it does white Americans. It's just based on the genetics of the thing. So the NIH has in the past and will continue in the future to focus on research that advances the health and well being of minority populations. It absolutely must. If the mission is to improve the health and longevity of the American people. That includes people African Americans, it includes Native Americans, it includes, you know, women, it includes minorities, it includes people of all different sexual orientation. All of that is still part of the, of the portfolio of the nih. I want to distinguish that from dei. Dei, I think, is something where, just to give you a sense of this.

Co-host (143:32)

Right.

Jay Bhattacharya (143:33)

So in 2020, I was quite upset with Stanford, with the way that it was. We can talk about this maybe, maybe later in the podcast or different podcast, but I'd grown disillusioned with the academic freedom kind of that I as a scientist enjoyed at Stanford, despite being a tenured professor. And so I applied for job outside of Stanford, I applied to university. And one of the things they had me fill out essentially was a dei, a loyalty oath.

Co-host (144:03)

Right.

Jay Bhattacharya (144:03)

Where you had to say, essentially your commitment to the DEI ideology, which was.

Andrew Huberman (144:09)

I mean, just maybe we put up, as you would say, a finer point on it just because, I mean, I think these were, you know, these words, diversity, equality and inclusion, I think, or equity and inclusion are, you know, their words. But what, what are maybe like, what are they really talking about that you're committed to having a lab where you include a certain number of people of different backgrounds? Or is it just sort of saying I care about These groups.

Jay Bhattacharya (144:34)

The key thing is race essentialism, that what makes you you is your race first and foremost. There may be other things about you that matter, but the most important thing about you is your race. And nothing else matters of the same scale.

Co-host (144:48)

Right.

Jay Bhattacharya (144:48)

That. That essentially is the heart and soul of the dei. So just to give you another, again, a concrete thing, the idea that structural racism is responsible for the health outcomes of the. Of the minority populations, primarily. Really right now, if you think about that, you say, okay, well, maybe true. You may think it's true, you may think it's not true, depending on who you are, what you're listening to. But all I'll say is that I cannot think of a scientific experiment to do that would in principle falsify that idea. Now I can think of experiments that would say, okay, well, look, minorities are more likely to live in food deserts, so the food they get access to easily makes their health worse. That's a scientific hypothesis. You can test it. You can imagine the result being not true or true depending on the data you find. That's a scientific question. That's not dei. That's a scientific question about the health outcomes of minority populations. You can test scientifically. Whereas the idea that structural racism is responsible for the health outcomes of the minority population of the country, that's not actually scientific in the same sense.

Andrew Huberman (145:54)

You mean there isn't a clear variable to focus on?

Jay Bhattacharya (145:58)

Well, you can't do.

Andrew Huberman (145:59)

There are a lot of variables that could support or refute that idea.

Jay Bhattacharya (146:03)

I don't think so. I think the problem is one of the demarcation between what is science and not science. I think it's like a structural. So like Karl Popper had this demarcation. He's a philosopher of science in the 20th century, probably one of the most important philosophers science in the 20th century. He had this demarcation criteria that said, look, is your scientific hypothesis in principle falsifiable?

Co-host (146:32)

Right.

Jay Bhattacharya (146:33)

So the structure of the atom involves certain hypotheses about what you can and can't observe, about the momentum and the position of an electron at a particular time. What's falsifiable? Now there's falsifiable questions. You can do an experiment that in principle could have falsified the Heisenberg idea.

Co-host (146:51)

Right?

Andrew Huberman (146:51)

Yeah.

Jay Bhattacharya (146:53)

Versus, for instance, Freudian psychology.

Co-host (146:56)

Right.

Jay Bhattacharya (146:56)

He made the point that there was in principle, no scientific experiment that was outside the system so that you could falsify the Freudian idea. Everything inside the system was. So it's not scientific.

Andrew Huberman (147:08)

Yeah, I see exactly where you're coming from the. I will just push back a little bit in service to the conversation, which is for descriptive work in science, there's no hypothesis. Billions of dollars of NIH money went to gene array single cell sequencing. Those were hypothesis generating experiments. Could you falsify those experiments? Okay, a given cell, let's say a cancer cell and a non cancerous cell from the same tissue express gene list A and gene list B. Could you falsify those lists? Well, you could run it again and get a different list, but at some point you're running statistics on those. And did you falsify the first one? Not really. So does anything descriptive, like an electron micrograph, for instance, of a nerve cell, you see lots of stuff. Wow. The mitochondria are there, the vesicles are there. Now I get a more powerful microscope and I look and I go, oh. What I thought was one thing is actually two things. Did I falsify it? In some sense, yes, But I actually just separate it with a better tool. So a lot of descriptive science upon which, like many of the great truths rest, including the double helix, Right? Crystallography, define the double helix structure. It's still a double helix, thank goodness. As of this morning, I think it's still a double helix. No one's proposed different yet. But most science isn't subject to this idea that you could just falsify it with a counter hypothesis or I would say a lot of science doesn't quite work that way. Now, what you're describing is a merge of sociological phenomena and scientific principles. And so maybe I'll just pose the question a little bit differently in an area that falls squarely in your course. Up until, I think pretty recently, maybe still now, But I think this was eliminated. If I had a grant from the NIH and someone was potentially coming to my lab who was an underrepresented minority, I could call up my program officer. It's not a parole officer, by the way, but they're kind of similar in that they control a lot of your life. And I could say, hey, listen, I've got a terrific young scientist coming to my lab. I don't even need to say that. I'd say, hey, I've got a scientist who wants to come to my lab that's an underrepresented minority. And they would say, say, great, we will now add funding to your grant specifically to fund that person. I mean, they have to be what we call above the bar. They have to be capable of doing the work, et cetera. That has been eliminated I'm neither advocating for that nor fighting against it. But that's something that lands squarely in your camp. And it is clearly dei. It's not a question of whether or not they're the best person for it. It's just more taxpayer money specifically to fund a researcher who would not otherwise have the opportunity. That's key because they are an underrepresented minority.

Jay Bhattacharya (149:45)

Okay, so let me. You have two items there. Let me address them both, per usual. Yeah, so the question about, like, hypothesis driven science. So like inductive versus deductive science, the NIH funds both and it should fund both.

Co-host (149:59)

Right.

Jay Bhattacharya (149:59)

So the idea of a scientific project demonstrating differences based on race or some other variable that's biologically relevant for some health outcome without necessarily having a hypothesis, that is good science.

Andrew Huberman (150:16)

Often women get breast cancer more often than men.

Jay Bhattacharya (150:18)

So there's nothing wrong with that. And there's no policy at the NIH not to fund that. Now. In fact, the NIH still funds and will continue to fund exactly that kind of science.

Co-host (150:28)

Right.

Jay Bhattacharya (150:28)

Because it's still science. It's part of the scientific method. Whereas, like purely structural racism causes your health. Health problems for minority, I don't believe is science.

Andrew Huberman (150:39)

That's more of a psychology question than a biosciences question. Right.

Jay Bhattacharya (150:43)

I don't even think it's a. I don't. Even if it's a psychology question, not a scientific psychology question. I don't think it's science. I just, I think it fails the demarcation problem. It's a.

Andrew Huberman (150:52)

Again, that's falsify.

Jay Bhattacharya (150:53)

Right, so there's no problem then with hypothesis driven science if it's actually sort of focused on health problems that matter, rather than just purely trying to demonstrate sort of sociological outcomes that are outside the purview of the NIH to try to address. Right, okay, so let's leave that aside before we do.

Andrew Huberman (151:12)

There's an old saying that I learned from a very famous excellent scientist, also deceased.

Jay Bhattacharya (151:20)

He used to say, great, dead scientist.

Andrew Huberman (151:23)

All my advisors are dead. So the joke in my field is you don't want me to work for you.

Jay Bhattacharya (151:26)

Oh, my gosh.

Andrew Huberman (151:26)

Okay. But I didn't have to deal with competing with, with my mentors, and I did not have to deal with disappointing them or pleasing them. So there you go, you know, But I would do anything to have them back. Truly, they were wonderful people. I was very blessed. But there's a saying which is, a drug is a substance that when injected into an animal or person, produces a scientific paper which is basically to Say that there are many things that when you. Many studies that when you introduce a variable, you're sure to get a difference. Like if I want a paper, I give a drug to a person and I measure the amount of rapid eye movement sleep, because basically every compound alters rapid eye movement sleep, usually for the worse. It's kind of wild. And aspirin will do it. You know, I don't want to discourage anyone from taking aspirin, but it's so easy to tease out effects when you just introduce a dramatic variable. So I think that's what you're referring to.

Jay Bhattacharya (152:21)

Yeah.

Andrew Huberman (152:21)

And it's not junk science, but it's not.

Jay Bhattacharya (152:24)

Not.

Andrew Huberman (152:24)

It's not great science.

Jay Bhattacharya (152:25)

Yeah. I mean, so like, Right. For instance, that you don't have a control group. You're like, okay, what's the.

Andrew Huberman (152:30)

You're just looking for differences so you can publish a paper.

Jay Bhattacharya (152:32)

Yeah. Okay, so let's just leave that aside. So some of it's good science, some of it's not good science, some of it's not science. The DEI shift has been in terms of like, funded science has been to try to excise from the portfolio things that are purely ideological boondoggles.

Andrew Huberman (152:46)

Can you give me an example of some of these grant titles? Because I'm. That. That no longer exist.

Jay Bhattacharya (152:51)

I don't want to signal. Single anybody out, so I don't want to.

Andrew Huberman (152:55)

But just sort of have a general flavor. I mean, I'm having a hard time.

Jay Bhattacharya (152:59)

Like structural racism is, Is the. Is the cause of. Of worse cardiovascular disease in African American populations.

Andrew Huberman (153:09)

Okay.

Jay Bhattacharya (153:10)

Something like that.

Andrew Huberman (153:10)

Okay.

Jay Bhattacharya (153:11)

That would be an example. That's not actually a specific example. I can. Again, I don't want to point.

Andrew Huberman (153:14)

No, it's a thematic. Thematic example.

Jay Bhattacharya (153:16)

Exactly. So that would be an example.

Co-host (153:18)

Right.

Jay Bhattacharya (153:19)

Now let's talk about the support for underrepresented minorities and the set asides. The position of the administration is that we should follow the civil rights laws of the country. The civil rights laws of the country say that we shouldn't be discriminating against people based on race. When you have an institution like the NIH that essentially says, we're going to consider your race when we decide whether we're going to give you support, you can understand why for a large part of the American public, they say, well, why are you doing that?

Andrew Huberman (153:49)

With their tax dollars.

Jay Bhattacharya (153:50)

With their tax dollars.

Co-host (153:51)

Right.

Jay Bhattacharya (153:51)

And. And actually I should say, like, from the perspective of, of a minority student, it's, it's. It's actually quite condescending. Like, I believe very fundamentally Based on lots and lots of experience with, with some excellent students I've had that minority students are, are often if they make make the right investments in the time and effort they put in, they have become excellent scientists. Sure, there's no barrier to that in the scientific. The only barrier of the structural problems with what the incentive scientists had to make those investments in young careers and so on. But those are common across race. I think that if you solve those problems so that we invest in young scientists not just at the level of whether like competing for NIH dollars, but even before, where everyone has access to those kinds of resources that the URM scientists used to differentially have first, you're going to end up with better a set of scientists that actually are more capable and you're also going to have minority scientists represented in proportionally to the the kind of desire that people have to become scientists. There's no field of human endeavor where you say, well, I have to have exactly the right proportion of race. I mean, if that's true, then what you have to have is Indians and Chinese represented all the time. That's like almost 3 billion people, the 8 billion people of the Earth. The. But justice isn't that, isn't that kind of like race essentialist representation? Justice is our people who want to make the investments to become scientists have the capacity, the resources that we as a society providing it so they can become excellent scientists. That has to be the case, right? And we're not by shifting the investment portfolio toward this race essentialist thing. All that matters is a URM underrepresented minority. It doesn't matter if you're an excellent scientist. It doesn't matter so much. It may matter some, but that's not the key thing. It doesn't matter if you have a fantastic idea that challenges entire fields. All that matters is what's your race? It moves the emphasis in science away from what really matters in science. Like what are your ideas? Are they advancing human knowledge? Are they translating into health for like large populations? Are they true? Are you working in things that advance our knowledge and reliability of the entire scientific literature? I mean, those are the things that matter really for scientists, right? Why are we caught up then in this idea that somehow we can address? I mean, I want to be very, very clear. There are real problems that minority populations have faced based on the history of the country. There are real injustices that have happened as a consequence of them. But we're essentially asking the scientific like the scientific institutions of the country to somehow solve these deeper problems. Of essentially cosmic injustice in ways that we don't actually have the capacity to do and in some ways A distort the investments we make and B cause large chunks of the American people to distrust us. Say, look, you're not really focused on the things that really will improve my life. You're interested in sort of cosmic justice rather than actual science. I think it's the right thing to do to say, let's focus on the mission. The mission is how do we advance, how do we make investments in research that advance the health, health and longevity of the American people? And there's, I don't believe there's any place for this sort of race essentialism in it.

Andrew Huberman (157:50)

So you've talked about the DEI topic slash issue from the perspective of which science does or does not get funded. Okay, so testing race as a theory, a non falsifiable theory, is not something that the NIH is going to continue to support. We are also discussing DI in terms of which scientists get to be called scientists and which ones get funded. I suppose the universities decide who they hire and then NIH plays a major role in deciding who gets funded. So if I understand correctly as now, the funding of a given grant can't have anything to do with somebody's race or background, to which I say, why not just make it blind to who the investigator actually is? Now I realize when people write grants, they say previously we've shown, or my lab does this, but why not just eliminate identity entirely and just say what is the best proposal on the table? Let's fund those proposals.

Jay Bhattacharya (158:50)

When we talked about earlier, we talked about early career scientists and providing support to them. That's essentially along the same lines.

Co-host (158:57)

Right.

Jay Bhattacharya (158:57)

So we're saying we're going to de emphasize the track record of scientists in deciding what, which scientific projects to fund. That's essentially what you're saying when you say we're going to fund early career scientists because early career scientists tend to have less of a track record. I agree with that. I think the key thing is the ideas. Are the ideas powerful? Are they promising? Are they worthwhile in terms of being able to translate to improved health for populations? I don't know if it's possible to get rid of some elements of identity. Like, you know, you kind of want to make sure that they've had training as a scientist. Sure.

Andrew Huberman (159:37)

Well, they could check some boxes. I'm not here to solve every aspect.

Jay Bhattacharya (159:42)

Of the mechanics, but I guess relevant identity, like relevant, like your race, is not relevant to whether you have excellent scientific ideas. I'VE learned from people of all races, scientific ideas that have changed how I think about the world. And it doesn't matter. The race was not the key element in deciding whether they knew had a great idea or not. What really mattered was the idea. Now, it may be the case that some people have, based on their background, will have an idea, more likely have an idea in a particular field than a different, with a different background.

Co-host (160:16)

Right.

Jay Bhattacharya (160:17)

So allowing people of lots of different backgrounds to have their say matters.

Co-host (160:23)

Right.

Jay Bhattacharya (160:23)

But rather than focusing on the race, focus on the idea. Is the idea important? Is it likely to translate improved health for populations?

Andrew Huberman (160:31)

Well, having sat on a fair number of study sections over the course of like more than 10 years, either as an ad hoc or regular member, I don't recall ever feeling in the room or anyone explicitly saying we need to fund this grant because it comes from somebody who's an underrepresented minority. There were grants that came from underrepresented minorities, some of which are, were terrific grants and some of which didn't get funded because they weren't as terrific. So are you telling me, and it's been a little while for me, not a long while, but that there has been a recent pattern. I'm not trying to, you know, see the question, but are you telling me that some grants were getting funded specifically because of the identity of the person writing the grant? I always thought grants were funded or not funded on the basis of the science in them. And I, I never saw that to not be the case.

Jay Bhattacharya (161:19)

I mean, I think there are markers of that that were increasingly emphasized. You already mentioned one actually, Andrew. You said like you could call up your, your, your program officer and say, look, I've got a great, a great postdoc, who's a, who's a urm, which essentially means a minority, and would you like to fund him? And the answer would be yes.

Andrew Huberman (161:37)

No, there was a pool of money. It was, it was always a, it was a if. No, it actually ran in the other direction. It was well communicated from NIH that if we had someone who was underrepresented minority who wanted to join under grant, that there was additional money to be had. Yeah, that was a, there was a state, I think there was a website. It told us this. And you know, okay, well, it's clear that NIH, as it stands now in the new administration, it's clear where their stance on DEI is. I am relieved to hear that grants that might have been caught in the filter of this recent change can be, that did not qualify for what you're describing people that there's an appeal process. Because I think that shocked some of us in the science community were like, oh my goodness, it could be terrific grants that just got the ax.

Jay Bhattacharya (162:26)

Yeah, you know that. So there's an appeals process to fix that, I think. Let me just make an analogy to something that happened during my career. I think it was around 2010, the NIH put out a priority statement that said they were not going to fund health economics research, more or less. It was in the wake of Obamacare, there was a whole fight over cost effectiveness research. And cost effectiveness research became this political football where and the United said, look, we're not going to fund this kind of work anymore. Actually impacted my career. Some of the work I'd done previously had to do with like the relative cost effectiveness of various drugs or whatever. And so the question was. So I had to like, I had to pivot away from that research. If I wanted research support from the nih, it actually impacted my cure quite negatively. There's priorities. And the thing is, I don't want to argue the wisdom whether that was right or wrong to do. I personally think it was wrong, but let's just leave it that aside. I think the thing is, it's normal for the NIH to put out priorities that reflect the social circumstances that are around us here. I think what we have is a shift to priorities that focus on the quality, the ideas the science has done rather than the racial identity of the people doing the science. I think fundamentally it's more healthy both because we'll end up having a set of scientific ideas that are more likely replicated and more likely be able to translate it into advances for health. And also it's better from a sort of social point of view because it de Emphasizes things that are irrelevant to the progress of. Mostly irrelevant in terms of the progress of science.

Co-host (164:20)

Right.

Jay Bhattacharya (164:20)

It shouldn't matter if you're a minority student, a very promising minority student, or if you're a very promising non minority student for the NIH to support. You both should get support. It shouldn't make any difference whether you're a minority or not. And for the American public at large, I mean, a lot of there's a sense of like, unfairness, right. Where like, why are you, like, I just. Let's leave. Let's move aside from the NIH and like, move to like Harvard University and the case that it lost over the admissions. I'm sure you remember this case, right, where Asian students were found to be at a disadvantage in Admissions into Harvard. Actually, the facts of this case are really shocking. So what happened was Asian students who applied to Harvard and non Asian students would be evaluated by alumni interviews where the alumni would evaluate their personality. Asians and, and African American kids were both had roughly the same average personality score as evaluated by an interview with alumni. Then the Harvard admissions officers would find similar kinds of scores based on essentially personality. But the admissions officers had never met the kids. And Asian kids routinely had much lower personality scores than African American kids that applied. That's what led the Supreme Court to say that was an illegal act of discrimination by Harvard against Asian kids. I think this focus on race, I can understand it because we have a history where race has been the crux of so much pain and suffering and injustice in this country. Legacy of slavery that goes to back, back, you know, centuries. We have, you know, laws against that discriminate against African Americans in, you know, like the Jim Crow laws. We have this painful legacy of the slow progress in civil rights that goes back, you know, generations, centuries. So I understand that that's the backdrop of, I'm not naive about that. What I'm saying is that, that these kinds of scientific, these kinds of like using the NIH to solve that problem is an inappropriate use of taxpayer funds. And actually I think it makes things worse for those problems than better. And in particular, and for me as the director of the NIH is the most important thing. It doesn't allow me to meet my mission. The mission is to do research to support research that advances the health and longevity of the American people. All of the American people, whether you're minority, whether you're American Indian, whether, no matter who you are, we should be doing research that advances your well being. And that means to me, I shouldn't be using the NIH for these sort of cosmic justice purposes for which the NIH is poorly suited. But instead we should be using the NIH for the purpose it is well suited, which is to advance science that advances the health and well being of the American people.

Co-host (167:32)

People.

Andrew Huberman (167:33)

Yeah, I can see the parallels to something like, you know, the space program where, you know, the space program is incentivized to try and figure out the best way to meet the, the, the specific goals of the program that year and in subsequent years. And if the public thought that taxpayer dollars were being diverted according to a social justice issue in order to try and advance the space program in that way as opposed to getting onto Mars or whatever it is, maybe that's a bad example. It's so specific to Elon, but you get the idea. So it's very clear based on what you've said that you believe that the best way to serve everybody in the country in terms of health and longevity is to make the discoveries, verify those discoveries, and then distribute the devices and therapeutics for those discoveries and behavioral tools that will allow for the health of all Americans. And anytime someone says all Americans, it sounds like a political statement. I realize that, but. And to leave aside social justice issues en route to that goal. That's what I'm hearing.

Jay Bhattacharya (168:37)

Yeah. I mean, except. Except to the extent that there are the social justice issues can be articulated as clean scientific hypotheses that actually matter.

Co-host (168:48)

Right.

Jay Bhattacharya (168:48)

So like, you know, race differences in biological variables, fact that matters.

Andrew Huberman (168:54)

Certain mutations run in certain populations, so certain advantages run in the NIH population.

Jay Bhattacharya (168:58)

Still supports that kind of research. But again, that's in service of the scientific goal, not in service of some social justice goal that the NIH is ill suited to achieve.

Andrew Huberman (169:07)

Yeah. As somebody who worked on vision science for many years, glaucoma is much, much more common in darker skinned races. There's certain areas of the world where glaucoma is at an outrageously high percentage of the population and it's not lost on people that there's a genetic inheritable component and some of the treatments might be need to be tailored to those specific populations or.

Jay Bhattacharya (169:28)

My grandfather went blind from glaucoma.

Andrew Huberman (169:29)

So get your pressures checked. Everybody take your drops. Get your pressures checked. I'd like to pivot slightly to some issues related directly to public health. We have a kind of fork in the road here as to whether or not we focus on issues of public health from the recent past for which you who became best known, AKA Covid and the lockdowns, or whether or not we focus on public health issues that are more relevant now. I was told by many, many people who are not scientists but care a lot about science that quote, until the scientific community acknowledges two things, they don't want to give another dollar to science. Those two things are one, the replication crisis. We talked about this and by the way, I think your plans to deal with that are fantastic. I love this idea and I think many students and postdocs will be excited to be part of the correction process that will evolve science. And the second one is an admittance of error in our past. I want to be very clear not to protect myself. I have plenty of work to do, no matter what. But these are not my words. But the words were the scientific community did us wrong. The Lockdowns were unfair to in particular working class populations. We were told one thing about masks, then told another. We got got a kind of loop de loop of foggy speak, politico messaging about vaccines and what they did do or wouldn't do. And basically I hear from a lot of the general population, not just people on the maga maha, whatever you want to call it side, but also a lot of stated Democrats. And people are truly in the center that they lost trust in science and scientists and they will not consider restoring that trust until scientists admit that they made some mistakes. And it took me a while to hear that message because I'm like, hey listen, I have friends trying to cure blindness, cure Alzheimer's, use brain machine interface to cure epilepsy and get paralyzed people to walk. And you're talking to me about something that happened, but I finally had to just stop and listen because they kept saying we don't care. And so it's almost like big segments of the public feel like they caught us in something as scientists and we won't admit it. And they're not just pissed off, they're kind of like done. I hear it all the time. And again, this isn't the health and wellness supplement taking anti woke crowd. This is a big segment of the population that is like I don't want to hear about it. I don't care if labs get funded. I want to know why we were lied to or the scientific community can't admit fault. I just want to land that message for them because in part I'm here for them. And get your thoughts on what you think about. Let's start with lockdowns, masks and vaccines just to keep it easy. And what do you think the scientific community needs to say in light of those to restore trust?

Jay Bhattacharya (172:51)

So first let me just say I don't think I'm the NIH director unless that were true. Unless what you said is true, otherwise I'm not the NIH director. So I was a very vocal advocate against the lockdowns, against the mask mandates, against the vaccine mandates, and against the sort of anti scientific bent of public health throughout the pandemic. I've also argued that the scientific institutions of this country should, should, should come clean about our involvement in very dangerous research that potentially caused the pandemic.

Andrew Huberman (173:23)

The so called lab leak hypothesis.

Jay Bhattacharya (173:25)

Right. So let's just, let's just stay focused on, on lockdowns and just, just to, I want to make the scientific case that they were a tremendous mistake and that was known at the time they were a tremendous mistake. And let me just focus on one aspect of it. We'll get broadened out to other lockdowns, just the school closures.

Co-host (173:43)

Right.

Jay Bhattacharya (173:43)

So what the public at large now sees is that American kids, especially minority kids, are two years or more behind in their schooling. We decided during the pandemic that children ought to learn to read as 5 year olds or 6 year olds remotely in zoom. We decided that in person schooling didn't matter anymore. My kids in California were kept out of school, public school for a year and a half. If they saw the inside of a classroom, it was with Plexiglas, separated from their friends, eating lunch, isolated, alone. The message, message to American school kids was essentially, your school doesn't matter, your future doesn't matter. American public health embraced that entirely. In Sweden, they didn't close schools for kids under 16 at all. That was not a policy of the Swedish. Anders Tegnal, the head of Swedish Public Health, explicitly made that a priority. In the summer of 2020, the Finns and the Swedes compared their results. The Finns had closed schools in the spring of 2020 and the Swedes had not. And they found there was no difference in health outcomes for Covid the teachers in the schools. In the Swedish schools, actually they had no worse outcomes than other workers in the population. And on the basis of that evidence and the fact that, that we know that closing schools harms the future health and well being of kids, even short interruption school, we knew that for a fact, based on a vast literature that existed before the pandemic, many schools around Europe opened up in the fall of 2020. The scientific evidence was abundant and clear, even by late spring 2020, that the closure of schools and kids was a tremendous mistake stake and yet, when I wrote the Great Barrington Declaration with Sunetra Gupta of Oxford University and Martin Koldor from Harvard University in October 2020, I faced vicious attacks by the scientific community and the medical community for being unscientific about school closures.

Andrew Huberman (176:13)

Were there threats to your job at Stanford?

Jay Bhattacharya (176:15)

Yes.

Andrew Huberman (176:17)

Like real threats or just people saying, we're going to take away your job?

Jay Bhattacharya (176:19)

Okay. In March of 2021, I was part of a roundtable with Governor DeSantis, a policy roundtable where he asked me whether there was any evidence that masking children had any impact on the spread of the disease. And the answer is there's not a single randomized study that looked at kids. The US was an outlier in recommending that kids as young as 2 years old get masked in Europe like 12 was the age. There were no studies. In response to that, 100 of our colleagues signed a secret petition essentially effectively asking the president of the university to silence me.

Andrew Huberman (176:53)

Were you contacted by the university administration?

Jay Bhattacharya (176:55)

No. I found out about the petition from a couple of my friends who leaked it to me. And then I went to the press and said, look, you should go ask the president about this. And then he had to say that he had this mealy mouth statement about academic freedom, but also essentially that it's really important that we, we obey public.

Andrew Huberman (177:15)

Health authorities or something like political, like boilerplate speak.

Jay Bhattacharya (177:20)

Yeah. And in 2020, I'd been subject to all kinds of sort of attacks on me. I mean, I don't want to relitigate this history, but I'll just say that Stanford failed the academic freedom test. It didn't hold a scientific conference on Covid with alternative viewpoints, with viewpoints that were anti lockdown until 2024 when I organized it, even though I asked to have a conference in, in 2021 and 2022.

Andrew Huberman (177:46)

But your job security wasn't threatened in any. In a direct sense?

Jay Bhattacharya (177:49)

No.

Andrew Huberman (177:49)

Yeah. Like, no one came along and said, hey, like quiet down or else you're going to lose your job. So in that sense, you had academic freedom from the top.

Jay Bhattacharya (177:55)

That's not true. So I was asked to stop going on The Press in 2020. I was out. I was at. I was by, by the dean of the univers. Dean of the medical school.

Co-host (178:03)

Right.

Jay Bhattacharya (178:04)

I was. My, my academic freedom was pretty directly threatened. Threatened. I wrote and published a study on measuring antibodies in the population, a study that now was replicated dozens of times around the world. And I was essentially ordered to redo that study. They interfered even before I had sent the paper in for publication. When I say they, I mean the administration of the medical school. School. I mean, my, my academic freedom was pretty directly attacked. And I wrote a piece with how Stanford failed the academic freedom test. You can go read about, read it if folks who want to read about it again, I don't want to relitigate the past.

Andrew Huberman (178:47)

No, I ask. Listen, I'm not trying to dig for dirt. I ask because. Well, I, I never saw a petition cross my email path. I did see a petition pass my email path about Scott Atlas, who was in our department of radiology. He's a physician, as you know, and was appointed Trump's coronavirus task force. Head of Trump's coronavirus task force. And then there was a petition basically asking him what to take away his job. I don't know what it was, but that passed through. But I see a lot of petitions passed through my email. And as everybody knows, and the press has pointed out, I'm not great at email and communications. But I guess the reason I ask is academic freedom means many things. Like, can you tweet what you want to tweet? I guess I don't call them tweets anymore at the time. Could you tweet what you wanted to tweet? Could you continue to do the science that you were doing? Could you. Did you continue to collect a salary? It sounds like you were able to keep your job, but there was some pressure to not communicate your ideas. Is that about right?

Jay Bhattacharya (179:44)

Yeah. I mean, there's a threat to my job as well. I think the issue here is one of, like, okay, imagine what a universe. There's a sense of, like, positive and negative academic freedom freedom. A negative academic freedom means there's no active attack on me and my capacity to do work. I think Stanford failed that as well. Like, there was an active attack on me. So, for instance, there was a poster campaign all around campus with my face on it, essentially accusing me of killing people in Florida for advising President Governor DeSantis that there was no evidence that masking children benefited anybody.

Co-host (180:19)

Right.

Jay Bhattacharya (180:20)

And essentially it was a threat. It's like I. At the same time, I was getting death threats from people. The former head of the NIH wrote an email to Tony Fauci four days after we wrote the Great Benton Declaration, calling for a devastating takedown of the premises of the Declaration. And then that resulted in essentially press propaganda pieces, the New York Times and elsewhere, essentially mischaracterizing what the Great Brench Declaration said, which was to protect. Protect older people better, and open schools lets kids go to school. Essentially mischaracterizing is in a propagandist way. We're saying we wanted to let the virus rip. And that led to death threats against me. Same time, there's this poster campaign all around campus. I called the campus police. I told the department, the folks in the department of the medical school that this was happening. And their response was to send me to a counselor to reduce my online presence, presence. So Stanford absolutely failed. During the pandemic in 2020, the former president, John Hennessy, approached me wanting to organize a discussion, like some sort of, like, panel where different perspectives on how to manage the pandemic, the lockdowns elsewhere could be had. And even he couldn't get this organized.

Andrew Huberman (181:42)

Hennessy couldn't?

Jay Bhattacharya (181:43)

No.

Andrew Huberman (181:44)

And he's one of the most beloved presidents of Stanford.

Jay Bhattacharya (181:47)

I have tremendous admiration for him, but the pressure was absolutely enormous. The fact that he approached me at all was actually a credit to him. He's one of the few officials at Stanford who approached me during the pandemic to try to allow me to have. I mean, I might have been right or wrong. It turns out I was right. But in principle, Stanford should have had those debates in 2020. We had prominent faculty people like John Iannidi, Scott Atlas and others, Michael Levitt, who were opposed to the lockdowns, and yet we couldn't get a hearing.

Andrew Huberman (182:18)

Yeah, Levitt reached out to me at one point. I've been criticized for before with this podcast. I mainly focused at that time on. We launched in 2021 on ways to deal with anxiety, circadian rhythm, sleep. But because people were dealing with those issues. I'm not a virologist, so I couldn't talk about virology or epidemiology.

Jay Bhattacharya (182:35)

But, Andrew, it wasn't on you to let, like, put us on a platform. It was on the Stanford University administration to organize discussions and debates on the top on the most important topics of the day. And that included in 2020 were school closures, the right approach.

Andrew Huberman (182:53)

I read comments enough and get calls and emails that I do read enough to know that when people hear this, their minds will go to questions about like, what is the incentive, financial or otherwise, for Stanford to not. Not allow you to have these discussions? Or let's broaden the discussion for any university, for that matter. Right. I mean, Tammer's not the only university on the planet for, you know, a panel, a discussion about these issues to. To be. To be held.

Jay Bhattacharya (183:20)

But we have a health policy department. What. What's the purpose of it if not to, like, empanel the most important debates about health policy of the day?

Andrew Huberman (183:27)

So. So what do you think was going on? I mean, the fact the. The vaccine technology was developed at multiple sites.

Co-host (183:33)

Right.

Andrew Huberman (183:34)

I think Stanford had something to do with the development of the technology. There were other universities that were involved in the development of the technology as well. Right. And I think in the back of this conversation, I know what's buzzing. Let's just be direct here. You and I were. It was. There was a vaccine mandate. Everyone that.

Jay Bhattacharya (183:51)

This is 2020.

Andrew Huberman (183:52)

This is 2020 a bit. But eventually there was a vaccine mandate. If you wanted to keep your job, unless you had a religious or other. What was a medical reason. Religious or medical reason, and you were told you had to take the vaccine, people did what they did. Some People did. Some people. I know colleagues that falsified cards. I know colleagues who got nine vaccines, everything in between. Right. But there were mandates. So to be clear, you were opposed to the lockdowns.

Jay Bhattacharya (184:18)

Yes.

Andrew Huberman (184:20)

And you were opposed to vaccine mandates. Were you also vocal about that?

Jay Bhattacharya (184:24)

Yes.

Andrew Huberman (184:24)

Cause that's even. I mean, that's even.

Jay Bhattacharya (184:26)

I was an expert witness in a number of cases on the vaccine mandates, including one that. That reached the Supreme Court and overturned the OSHA vaccine mandate. So, yeah, I mean, I was vocally opposed to the vaccine mandates. I was vocally opposed to the mask mandates on the lockdowns. I was vocally opposed to the school closures. I emphasized the harm that the lockdowns did to the world's poor.

Co-host (184:48)

Right.

Jay Bhattacharya (184:48)

So In April of 2020, there was a UN report that calculated that 100 million people would be subject to starvation as a consequence of the economic dislocation caused by the lockdowns. I was opposed to that. I think the idea that the lockdowns were the right strategy. Well, they're unique in world history of having lockdowns at the scale we had. And there were no part of previous pandemic plans where such a lockdown of such a length, of such a scale were no part of any previous pandemic plan or any previous pandemic management experience. And it was very clear to me, with my background in. In health policy, that we were going to harm the poor, we were going to harm children, and we're going to harm the working class. At scale, the lockdowns were a luxury of the laptop class, and that's what I was advocating at the time. The university wasn't just Stanford, you're right. But in fact, there were almost no universities that empaneled these kinds of discussions into 2022.

Andrew Huberman (185:57)

So what do you think happened? Do you think that there was a fear. I'm not seeding the question, leading the witness, whatever, but do you think that there was a fear among the academic and science community that if anyone, if it were allowed for people to speak out or consider different aspects, positive or negative, about lockdowns or vaccine mandates, that somehow their existence would be at risk? Like that this got to an issue bigger than the lockdowns and bigger than vaccines? Because I do. I think that this whole issue was really a question of whether or not we consider scientists experts. The word expert has become a very touchy thing, like who gets to be called an expert. Who. Who designates which experts are really the experts. I mean, it's all, you know, all you have to do is accuse someone of misinformation and suddenly they're experts card is taken away. Even if they hold a position in a given area that they've.

Jay Bhattacharya (186:57)

I've been a tenured faculty member at this, at Stanford School of Medicine for, for decades.

Co-host (187:02)

Right.

Jay Bhattacharya (187:03)

I've been a full professor with a long scientific back like history of published papers in some of the top medical journals, the top, like statistics journals, health policy journals and so on. Economics journals. And that wasn't enough.

Co-host (187:16)

Right.

Jay Bhattacharya (187:18)

The problem is like you have, have. Okay, let me just say one, one version of this that you can, you can go. There are other, other aspects of play for. Like for instance, I think people were genuinely scared. Scientists were genuinely scared for their own mortality, especially in the early days of the pandemic. And that, that clouded the way they thought about.

Andrew Huberman (187:37)

Especially since there's a lot of older scientists. I'm not trying to pick on older, but there are a lot of them.

Jay Bhattacharya (187:41)

Yeah, yeah.

Andrew Huberman (187:42)

And older people were dying more. Correct.

Jay Bhattacharya (187:44)

Yeah. I mean there's a. I mean that was actually the most important epidemiological fact. Fact about COVID was that was this very steep age gradient in the mortality profile. Young people, very low, low mortality risk. Older people, much higher mortality risk.

Andrew Huberman (187:57)

What was the rate of mortality among people 70 to 85 years old?

Jay Bhattacharya (188:02)

Roughly 5 to 7% somewhere in there.

Andrew Huberman (188:04)

Okay, so not a trivial number.

Jay Bhattacharya (188:05)

No, it's huge. Like 1 in 20 to 1 in, you know, 1 in 18 or whatever. 14.

Andrew Huberman (188:10)

And that was due directly from COVID itself. Not, not some.

Jay Bhattacharya (188:19)

But I want to leave aside the personal fear, although I do think that played a tremendously important role in the thinking of scientists, especially since scientists as a class tend to be part of the laptop class. People who have the economic resources to shield themselves for extended periods of time without any of threat to their livelihood. That's not true for most of the world, but that's true for scientists. So let's leave that aside and let's just focus on what I think was a core dynamic. So there's two norms, two ethical norms in science, and they competed with each other. In science, free speech is an absolute must. If you have an idea that's different from mine, you should be able to express it. And then we can, you know, we can test each other's ideas out. We can maybe devise an experiment to decide between us and whatever the experiment says, we'll say, okay, you're right and I'm wrong and I'll buy you dinner or something.

Co-host (189:20)

Right.

Jay Bhattacharya (189:21)

That's good. That's how science advances, like through this kind of, like this process of people talking to each other, having free speech, the ability to come up with ideas and articulate them, defend them, is absolutely fundamental to the progress of science. Public health has a different ethical norm. Public health has an ethical norm of unanimity, of messaging. This ethical norm has as its moral basis that the communications that public health puts out are grounded in consensus science, right? So, for instance, if I were, as I was a former professor at, emeritus professor at Stanford, I go out and say, I'm the head director of the nih, I go out and say, smoking is good for you. Well, I've committed an ethical sin, right? I've done something really deeply wrong. Because the scientific basis for the idea that smoking is a terrible thing for you, it really harms your health in concrete ways. I mean, that's like rock solid in science. So the idea that I, as a person who works in public health shouldn't go out and say, smoking is good for you, that has a good ethical basis rooted in science. The idea that closing schools is good for you. The idea that wearing a cloth mask prevents you from getting Covid, the idea that immunity after Covid recovery doesn't exist, the idea that the vaccine will protect you from getting and spreading Covid forever, none of that was rooted in science. And yet the public health authorities of this country decided that they were going to enforce the same kind of ethical approach. They have sort of ethical constrictions on those topics as they do to smoking.

Andrew Huberman (191:13)

When you say none of it was rooted in science, are you saying the science was mixed or there was literally.

Jay Bhattacharya (191:18)

No evidence, There was literally no science. So, for instance, the idea that cloth masks prevent you from getting and spreading respiratory diseases. There were a dozen randomized trials on flu before the pandemic, and there was a Cochrane report looking at the literature on masking and influenza. And they concluded that the evidence was weak at best, that these kinds of cloth masking in population settings actually prevent anyone, that the spread of influenza.

Andrew Huberman (191:50)

I heard a number of people say, like, what's the big deal about wearing a mask? There was also that argument, it's not the same thing as a vaccine. It's like it's a mask. You could argue over inhaling excess carbon dioxide. You're not, you know, you're not getting smiles, you're not social interaction. Listen, I'm just opening this up for sake of, of consideration. So, like, why did the masks become such an issue? Was it because it was a mandate?

Jay Bhattacharya (192:12)

Is that what it's really the mandate mattered. But I'll say there. There were harms, some of which were recognized, some of which were not. So. Like, for instance, I heard from parents of autistic kids that the wear that. Or I'm sorry, hearing impaired kids, that the. That the mask wearing impaired the ability of the kids to learn to lip read.

Co-host (192:32)

Right.

Andrew Huberman (192:32)

So it seems logical.

Jay Bhattacharya (192:34)

Yeah, I heard. But. But it's also true that you adopt, if you adopt and embrace public health messaging that's self evidently not rooted in science, you're going to undermine the public trust in science and in public health.

Andrew Huberman (192:51)

I will say, based on these voices that I hear from a lot, that's what they're asking for. They're asking for the exact message that you're delivering now, which is, I'll say it differently. They want to hear the scientific community say we messed up.

Jay Bhattacharya (193:06)

Yeah. And we should. We should absolutely say that. Right. So, for instance, you wear a mask. Mask while you walk into the restaurant, you sit down to eat, and you take your mask off. And that protects you. Protects you from getting and spreading. Covid how like everyone could see that. You don't need to be assigned to see that. That was obviously ridiculous. Public health messaging.

Andrew Huberman (193:28)

It was a weird time.

Jay Bhattacharya (193:29)

And. And let's just say. Is it you asked is. Could. Could this public health messaging be dangerous? Well, yeah. Imagine someone who's like. Like 80 years old, they have a lot of chronic conditions. It's the height of the pandemic, like July 2020 or something, or June 2020, and they're told if you wear a cloth mask, you're safe. They go out in public and take risks that they otherwise would not have taken on the idea that they're safe wearing a cloth mask. And they get Covid, the recommendation, not rooted in science, actually could end up killing people. People and probably did.

Co-host (194:04)

Right.

Jay Bhattacharya (194:05)

So it's not. None of these things are just basically. Well, it's low cost. I mean, it may be low cost to somebody who's like, you know, who's not particularly, I mean, particularly bothered by mask wearing, but they can still nevertheless end up causing harm. And I think it kind of did.

Andrew Huberman (194:23)

Why weren't there panels of scientists as opposed to one individual, Tony Fauci, by the way, I invited him on the podcast. Did not get a response. This was a long time ago. I thought it would if I was going to hear about it, you know, these issues from anybody at that time, it made sense to contact him. And he apparently wasn't interested. We would have, of course, done it remotely. Why wasn't there a panel? So my feeling is when you have an individual, it changes the whole discussion. But when you have a panel that looks kind of like the United States and this isn't for like diversity reasons per se, this is about just a collection of smart people is way better than one person always, in my opinion. And they could come to some sort of consensus or maybe even disagree publicly. I think panels would have been better.

Jay Bhattacharya (195:18)

Well, I think, let's leave aside Tony Fauci, the. Because I think he was a very important figure and of course was basically a major spokesperson for the public health point of view. But there was essentially groupthink at scale. It was impossible to organize a panel with the kind of diversity of opinion that was needed. There were million or more. I know this from the set of people who signed the great Banshee Declaration. Tens of thousands of scientists and doctors who disagreed, but they were afraid to stick their head up for fear of getting chopped off. It's not an accident that Stanford didn't allow a scientific panel with this kind of point of. My point of view about the efficacy of lockdowns until 2024. The idea was that we needed to have unanimity of messaging. And if you had prominent professors in Stanford, Harvard, Oxford or elsewhere saying that the lockdowns were a bad idea, which they were right, then you're going to undermine public compliance with the orders that were being put out. You know, just. Actually, just a quick, quick diversion. How do I know the scientific. That the lockdowns are a bad idea? If you look at, if you ask which country had the lowest all cause excess deaths in all of Europe, all cause excess deaths, meaning deaths from all causes. Excess meaning, given the age structure of the population, how many people would die would you have expected even if there wasn't a pandemic, versus how many there were. Which country in Europe had the lowest all cause excess deaths? It turns out it's Sweden, which didn't follow the lockdown. So the lockdowns were not a necessary, necessary policy in order to protect human life. And they weren't sufficient to protect human life either.

Co-host (197:16)

Right.

Jay Bhattacharya (197:16)

So you had lockdown, sharply lockdown countries like Peru that had tremendous deaths. So the lockdowns were neither necessarily sufficient and they caused collateral harm at scale to the poor, to the working class, to children that we're still paying for, that people are still suffering from the long tail. For years in the United States, from 2020, 2021, 2022, the deaths from overdoses of drugs were like in the hundred thousand people died a year. This past year it was 80,000. We declared success. We went down 20,000 before the lockdowns. It was, you know, maybe 20,000 deaths a year. And that was a catastrophic failure.

Co-host (198:00)

Right.

Jay Bhattacharya (198:01)

So the problem here is that the scientific community embraced an ethical norm about unanimity of messaging and then enforced it on fellow scientists and then cooperated with the Biden administration to put in place a censorship regime that made it impossible even for legitimate conversations to happen. Like, so after the vaccines Covid vaccines came out, there are a community of people who were legitimately vaccine injured. The Biden administration went to Facebook and told them, essentially ordered them, that you need to shut down the patient groups that are discussing the vaccine injuries.

Andrew Huberman (198:37)

Or else what?

Jay Bhattacharya (198:39)

The threat was usually implied. Or else essentially destruction of your company. President Biden goes on national tv, says, and he has completely right to do this. He has the right to do this as president, say, look, Mark Zuckerberg is killing people. He did that. He actually did that. And then quietly behind the scenes, they, they pressured Facebook to censor patient groups that were discussing their vaccine injuries, even in private groups.

Andrew Huberman (199:08)

And no one was putting their stuff out on X. Then called Twitter.

Jay Bhattacharya (199:11)

X did the same thing, Right? So I joined Twitter in August of 2021. My first thing I posted was the Great Barrington Declaration. The day I joined Twitter, I was put on a blacklist to suppress the spread of my ideas on Twitter.

Andrew Huberman (199:26)

Twitter.

Jay Bhattacharya (199:27)

And almost certainly that's confirmed.

Andrew Huberman (199:29)

I mean, I'm not, I'm not questioning the validity of what you're saying.

Jay Bhattacharya (199:31)

I saw it with my own eyes.

Andrew Huberman (199:32)

But that was confirmed by the so called Twitter files.

Jay Bhattacharya (199:34)

Yeah, so the Twitter, when Elon bought Twitter, he opened, he opened up the, the databases, invited me to go see them at the Twitter headquarters. I saw with my own eyes, I saw my face and it said the word blacklist on it.

Andrew Huberman (199:48)

Which meant what? That when you would post, no one would see your post. Well, it was a shadow band.

Jay Bhattacharya (199:52)

It was a trans blacklist. So admit. Yeah, it was a shadow. Make sure I didn't know I was on this. Just made sure that only my followers, strict followers, would see the post and nobody else had any chance of seeing it. I mean, the whole reason I joined Twitter in the first place was to engage with people that didn't know my ideas. And the blacklist made sure that my ideas were not seen by those people.

Andrew Huberman (200:14)

So this is part of the reason why I think podcasts like the Joe Rogan podcast were, became such a lightning rod for, for this discussion. What's interesting is that, remember they used to put a little tag on podcasts, you know, it would say, this may contain misinformation. What they forgot, whoever was imposing that, because I, I don't think it was from, from the podcast houses themselves, but whoever directed that.

Jay Bhattacharya (200:43)

The federal government.

Andrew Huberman (200:44)

Yeah. Forgot about the 90s when there were explicit lyrics and albums and they would say, warning contains explicit lyrics. And everyone goes and clicks on those or listens to those. They sort of forgot. Human psychology.

Jay Bhattacharya (200:55)

That's the beauty of the American people.

Andrew Huberman (200:56)

We, we are we like rebels.

Jay Bhattacharya (200:58)

Yeah, exactly. It's so pinheaded, it's almost unimaginable. Like we basically the public health authorities of the country and the, and the, and the, and the, and the government around it decided that it knew best, that it was going to control the conversations of the public at large, essentially propagandize them.

Andrew Huberman (201:21)

The real question is why? And people are probably thinking, ask them about Big Pharma. Ask them about the amount of money that Tony Fauci was made. You hear these theories, right? But most biomedical scientists running labs at universities aren't going to make a dime from pharma. Most just there. If you saw their salaries, most people would be unimpressed by those salaries. If you look at the salaries relative to their hours worked, you would be even less impressed. So sure, some people stood to get really rich, but I can't imagine that's the reason. So what? So the question becomes why? Why all this suppression? Why all this group think, what were people so darn afraid of?

Jay Bhattacharya (202:01)

I think, let's put yourself back in 20. 20, 2021. I, I think that while again, I'm not naive, I do think monetary factors played a tremendously important role. I don't think they.

Andrew Huberman (202:11)

Who was making money besides, I don't.

Jay Bhattacharya (202:13)

Think they were the central reason. I agree with you about that. I think the central reason is that the scientists that supported the censorship efforts, the scientists that embraced the sort of omerta around opposing lockdown, that supported that, essentially the vilification of fellow scientists who disagreed with them, were doing it because they thought they were doing good.

Andrew Huberman (202:36)

They thought they were doing good.

Jay Bhattacharya (202:38)

Yes. I think essentially what happened was that rather than thinking like scientists, they were thinking like propagandists. And in this case they were public health propagandists. They thought that their job as scientists was to echo public health propaganda rather than act like scientists and ask questions about the messages that, that the public health authorities were putting forward.

Andrew Huberman (203:02)

I'm going to push back a little bit in Fairness, perfectly valid hypothesis. And you were at the center of this and I wasn't. But many of these people are very, very smart people. I mean we can talk about universities as like these places, but these are places made up of people. And while not everyone is brilliant at these places, some of them are truly brilliant people. And they are, dare I say, enough on a, on a sort of a left, left brained, ish spectrumy type phenotype where they're not pulled into emotional issues the same way that we might think they are. And so it's hard for me to imagine that really smart people would join a dialogue that didn't consider all aspects.

Jay Bhattacharya (203:46)

And yet that's exactly what happened. Andrew, like think about that.

Co-host (203:49)

Right?

Jay Bhattacharya (203:49)

So like, I mean I've thought about that quite a bit. I don't think it had anything to do with being smart or not smart. I think there are a lot of really smart biologists in the Soviet Union. When Lysenko told Stalin that Mendelian genetics was a capitalist plot and that Lysenko was the way forward, a lot of excellent biologists for fear of not wanting to be sent to Siberia kept their head down and said nothing about even in areas where they were like directly in their field.

Andrew Huberman (204:29)

So it was fear of being ostracized and shamed by one's community.

Jay Bhattacharya (204:33)

And it took just a few examples. So you mentioned, I think I mentioned earlier, Scott Atlas, who's a colleague of mine and friend. In 2020 the Faculty Senate of Stanford voted to censure him. Stanford has a history of censuring three professors ever in his history. One was a man named Edward Ross who was a eugenicist in the early part of the 20th century. He was one of the leading eugenicists in the country. And Jane Stanford hated him and worked to get rid of him for the faculty.

Andrew Huberman (205:07)

He was fired.

Jay Bhattacharya (205:08)

He was fired. Was. Or resigned or left. I'm not sure exactly, but it was, he was, he was let go. I think it was assistant professor then Bruce Franklin who was a English professor at Stanford. I think he like worked on science fiction but he was a anti Vietnam act war activist and he brought essentially a terrorist group to campus. And he was given, he was like just, just like there'd been like massive public focus on it. So he was given a chance to like defend his points of view. It eventually was like censored by the Stan.

Andrew Huberman (205:36)

By Stanford for being anti Vietnam War.

Jay Bhattacharya (205:38)

For bringing, for bringing the terrorists on the campus.

Andrew Huberman (205:40)

Yeah, I mean bringing terrorists on campus and bad.

Jay Bhattacharya (205:42)

Well, in any case there was Kind of due process around both of those things. Like they got. They got their say. Scott, his major sin was he advice advised President Trump during the pandemic. And he advocated for keeping schools open again, consistent with what was happening in Sweden, and for protecting older people better because they were higher risk of dying if they got Covid. That was his sin, that he was seen next to President Trump and that led the faculty senate of Stanford for something they haven't taken back to issue a censure of him that has, if you look at it, religious language. They declared him anathema. They effectively excommunicated him. His family essentially was ostracized by their neighbors. He lives on campus. It was an absolutely disgusting act. And it was meant not just at Scott, but generally to send a signal to anyone who agreed with Scott to keep their head down. And it succeeded.

Andrew Huberman (206:43)

He's hired Hoover, right?

Jay Bhattacharya (206:44)

He's Hoover. But he was formally at the medical school as the head of neuroradiology. He's a very accomplished scientist and has a textbook on leading textbook in neuroradiology. For a decade, he'd been advisor to presidential candidates on health policy policy. So he understood from a broader point of view. He also comes from a working class background.

Andrew Huberman (207:03)

So it was guilt by adjacency.

Jay Bhattacharya (207:04)

Yeah. But it was aimed at silencing opposition to the lockdowns. And it worked in large part. I lost count of people from inside Stanford and around the country who would write to me saying, I'm glad you're speaking up on these issues. Please keep it up. I don't want to do this because I don't want to risk my job.

Andrew Huberman (207:25)

Well, you weren't completely alone. So Levitt has a Nobel Prize and.

Jay Bhattacharya (207:30)

Yeah.

Andrew Huberman (207:31)

And you had some buddies who were pretty smart and pretty powerful. I mean, they don't give Nobel Prizes to anybody.

Jay Bhattacharya (207:36)

No. Mike is incredible. He's a very brilliant man. But Stanford in that sense was better off.

Co-host (207:42)

Right.

Jay Bhattacharya (207:42)

We had a sort of underground that opposed the lockdowns. Very prominent scientists like John Ioannidis, Mike Levitt, Scott, there were people at places like Harvard and Oxford. Harvard, there was Martin Koldorff at Oxford, there was Sunetra Gupta. There were folks all over the world. But institutionally, the universities of the world made it almost impossible. You had to essentially decide, and this is what I decided in 2020, that I did not care about my career anymore, that I owed it to the people who are being harmed by the lockdowns to speak up more than I urged myself to preserve my career and that's why I continue to speak even after, even with the death threats, even with the vilification, and even with essentially the failure of my own institution to protect my academic freedom, I did decide I was willing to give all of that up. That's why I kept speaking.

Andrew Huberman (208:38)

So given your experience and given the same thing that I hear that, you know, people want to hear scientists admit that they are at least sometimes wrong, maybe not even a specific instance in which they're wronged. Will the nih, perhaps you be making a statement on behalf of scientists to, I mean, you have the opportunity to address the entire world here. You're doing some of this, obviously, but will this be part of the messaging of the nih? Like, we need to revise what we think of when we talk about academic freedom. We need to revise what we actually do. And, you know, God forbid there's another pandemic. We need to really be ready for the kind of discourse that is going to unify people as opposed to divide people.

Jay Bhattacharya (209:26)

You know, after, after a patient dies, often in a hospital, there'll be a conference, you know, where the doctors who manage the patient will have, will. Will say, we'll bluntly say to each other, often behind closed doors, what went wrong. And the goal isn't to, like, actually point fingers. The goal is to figure out what happens so that you don't make the same mistakes. We haven't really had that conversation as a country or as a world over the pandemic, and yet the harms from it still persist. I think what I would love to do as NIH director is, I mean, I want to inform the scientific community so that the values that I thought it had, which is the values of free discourse and academic curiosity, those are central to the way we function going forward. We want to make sure that those values are at the center. Because you can't do science if you don't have that. Just think about science in the Soviet Union under Lysenko, right? There was no real biology going on. If you couldn't say Mendelian genetics was real.

Andrew Huberman (210:37)

No, I actually can imagine that the small scale example that I'm familiar with of a laboratory meeting where you discuss someone's data is the perfect microcosm for what we're talking about, where you sit back, someone presents their data and the idea is to challenge the data. The idea is for everybody to try and punch holes in. It makes helpful suggestions, and sometimes, sadly, at the end of that meeting, you end up sitting there with a postdoc or graduate student and you're discussing what the next project ought to be, because that one is just an utter failure. Or you're discussing something much more interesting than you ever thought was possible in the data set that neither of you could have thought of because you needed some fresh eyes on it. But you can't have a culture in a laboratory where people can't oppose the person in charge. I mean, this is so important. If you can't tell the lab head, no, I think you're wrong. If you can't say that the lab can't progress.

Jay Bhattacharya (211:40)

The culture of American science has gotten away from that ideal. And in fact, it has this ironically weird thing where, like, on small matters, you can have that kind of discussion, but on large matters, you cannot. And that actually is anathema to science. That actually means that we cannot, as scientists, address the most important questions of the day without fear of essentially getting our heads cut off. We had this conversation about DEI earlier. Wasn't it uncomfortable? I felt myself being uncomfortable saying what I believe is true, because I know this one of those issues where, as a scientist, if you start talking about it, you better talk a particular way or else you're going to get your head chopped off.

Andrew Huberman (212:24)

Yeah. I mean, all these topics are uncomfortable, frankly, in part because I see them through a lot of different lenses. The audience lens, my role as a basic scientist, my role as a podcaster, the field of podcasters, completely transformed this kind of discussion and public health.

Jay Bhattacharya (212:45)

It's really healthy. We can have these conversations openly and in public. I mean, maybe I'll get my head chopped off again, but, like, you know, once. Once you've had. Once, I think you're safe.

Andrew Huberman (212:54)

I mean, maybe I have to remind you, you are the director. It is a. It is an incredible thing if you really think about it. Right. Given your position in 2020 and 2021, 22, 23, et cetera, you're now at the top of the pyramid. It is hierarchical, and I believe your intentions are. Are pure and good. I do. I think it's important to have checks and balances, but I really believe that you want to do right by people. I feel that's a felt thing. But, yeah, it's a remarkable arc that you're now in the position to make major decisions for the entire enterprise of science.

Jay Bhattacharya (213:28)

What I would love to do is I would like to make the lives of scientists who disagree with me easier. I want them to be able to disagree with me. I want to create a culture of science focused on developing truth rather than obeying higher like tops of hierarchy. If I can accomplish that, that would be a major thing in my view.

Andrew Huberman (213:47)

Well, I think that's a magnificent sub vision for the nih. I think it's super important that all voices are heard. It's kind of interesting we have these discussions about diversity and inclusion, but all voices need to be heard in the context of analyzing data. And certainly the revision of the entire structure of the science enterprise, as you point out, is sociological, it's financial. There are a lot of. A lot of different aspects to this. Vaccines are a very hot button issue these days, in part because Bobby Kennedy has been associated with the anti Vax movement. I've heard him say with his own words that he's not anti vaxx, but he's suspicious or very concerned about certain vaccines. Let's just start with a very basic question. You're an md. Do you believe that there are any vaccines that are useful?

Jay Bhattacharya (214:45)

Yes.

Andrew Huberman (214:45)

Okay. Well, I think it's just. Let's build up from there. Do you believe that some vaccines save lives?

Jay Bhattacharya (214:53)

Yes.

Andrew Huberman (214:54)

Okay.

Jay Bhattacharya (214:54)

Many vaccines save lives.

Andrew Huberman (214:56)

Do you believe that some vaccines that are given to children save lives?

Jay Bhattacharya (215:01)

Yes.

Andrew Huberman (215:02)

Do you believe that some vaccines are known to be harmful and yet still given.

Jay Bhattacharya (215:07)

Let me say the specific one, I think the COVID vaccine for children in particular, I don't think is net beneficial for kids.

Andrew Huberman (215:15)

But you said not net beneficial. Does that mean it's harmful?

Jay Bhattacharya (215:19)

Net harmful.

Andrew Huberman (215:21)

You believe that the COVID vaccine is.

Jay Bhattacharya (215:22)

Net harmful, especially for young men.

Andrew Huberman (215:25)

Can you define the age cutoff there?

Jay Bhattacharya (215:27)

We can argue about this like there's a scientific. But I think it's pretty clear that, I don't know, some between age 12 and 30 or something for, for boys and men, young men, the COVID vaccine is probably not harmful. Again, with boys who have no other underlying conditions and all that. There's.

Andrew Huberman (215:46)

There's not obese, no heart condition?

Jay Bhattacharya (215:48)

Well, I mean, even obese, you have to like, look at the numbers. I mean, there's lots of debates and fights over this in the scientific literature. So I hesitate to like actually give you a specific age threshold, but I think just as a general matter, there exist groups for whom the COVID vaccine was net harmful, specifically young men.

Andrew Huberman (216:05)

Do you think there's any reason to think that the adjuvants, essentially what the vaccines are suspended in, not the vaccines themselves, are potentially harmful? I've heard this. I am personally not aware of any strong evidence for it.

Jay Bhattacharya (216:20)

Right. I think these are the kind of things that ought to be investigated, but it's very difficult to investigate Just because of the sort of like political aura around vaccines where if you ask, if you really do investigate it and find something that the public health authorities don't like, you're going to have trouble. I think there, I don't know the answer to that question from a scientific point of view.

Andrew Huberman (216:45)

Let's start with COVID vaccine and dig a bit little further into that. The COVID vaccine was promoted, slash mandated, certainly was mandated at Stanford, but was promoted as the best line of defense for avoiding infection and reducing the symptoms of infection and reducing the probability of death. That's what I heard. What is the evidence for or against that, that statement now, given what we know about who took it, who didn't take it, and transmission and death rates.

Jay Bhattacharya (217:22)

Okay, so can we go back to December 2020?

Andrew Huberman (217:24)

Sure.

Jay Bhattacharya (217:24)

Because then I'll answer your question, I promise. Answer all the other questions you had. So In December of 2020, there were a couple of really important randomized trials published regarding the COVID MRNA vaccine. Vaccines.

Andrew Huberman (217:41)

Could you describe what one of these looks like? Because I'm not trying to slow your roll here, but some people get vaccines, some people don't get vaccine. And you look at who gets sick and who lives and who dies.

Jay Bhattacharya (217:50)

Yeah, basically. So the large scale randomized trials flipped a coin, said 20,000 people, I forget exact numbers, get the vaccine, 20,000 people get a placebo or some, something, you know, placebo like. And then you follow them for a certain number of months and you ask which groups more likely to get Covid have a diagnosed version of COVID which group's more likely to die, which group's more likely to be hospitalized. And if the vaccinated group is less likely to get Covid, you report that. If not, then you report that there are randomized trials then published for several high profile vaccines that were used during the pandemic in December of 2020. I guess November of 2020.

Co-host (218:38)

Right.

Jay Bhattacharya (218:39)

So the MRNA vaccines from Moderna and Pfizer, the Johnson and Johnson vaccine, the AstraZeneca vaccine, probably the four most important ones used in England and the United States or Great Britain, in the United States, Europe. Okay, so, so what did those studies show for the MRNA vaccines? In fact, all of these studies, they were run, these are studies that were done, again, randomized, high quality studies, large numbers of patients, but they were tracked for about two months. So you can't say from the randomized trials in December of 2020 what's going to happen after two months because the trials themselves only tracked patients for about two months what they Showed was that among patients who had never before had Covid because they excluded them from the analysis of efficacy. Among patients who never had Covid before, the patients who were randomized to the vaccine had lower rates of getting Covid in those two months. I'm sorry, symptomatic Covid in those two months. Then the people who were randomly assigned to the placebo.

Andrew Huberman (220:01)

Okay.

Jay Bhattacharya (220:02)

The MRNA vaccines had more deaths in the treatment arm than in the placebo arm, but the size of the samples were such that you couldn't say that that was a statistically meaningful result.

Andrew Huberman (220:16)

Okay.

Jay Bhattacharya (220:17)

Couldn't say it.

Co-host (220:17)

Right.

Jay Bhattacharya (220:17)

Because it's. And that made sense. The death rate from COVID was something like, you know, three, four out of a thousand. You would have had to enroll populations of. In the. In the hundreds of thousands or millions in order to get a significant result about deaths.

Andrew Huberman (220:32)

And age range really matters here.

Jay Bhattacharya (220:35)

Yeah. So the vaccine trials tended to focus more on younger people. It had some older people in it, but it didn't. And if I had designed the trial, what I would have argued for is to have the older population more represented because that's who was dying from COVID and then having the prevention of death or hospitalization as the primary endpoint. Instead, the endpoint was prevention of symptomatic Covid for two months. Okay. Now, they didn't ask whether you got Covid actually, because they're people who got Covid and never had any symptoms.

Co-host (221:12)

Right.

Jay Bhattacharya (221:12)

So they didn't ask in the trial about prevention of transmission. They could have.

Co-host (221:17)

Right.

Jay Bhattacharya (221:17)

So, for instance, the people who were in the placebo arm, you could ask whether their household members had Covid at higher rates than the household members of the people who were in the treatment arm. Compare the household members and ask. They didn't ask that. So what could you infer from the trial? Well, you could infer that for two months, people who had lower. Who had the vaccine were likely to have much less likely to get Covid for those two months. Symptomatic Covid for those two months. That's all you could say. You couldn't say they reduced death rates because it didn't actually in the point estimate. And there was not, again, any statistic significant difference in the AstraZeneca and the JJ vaccines. If you combine those, it turns out that you actually did get lower death. Death rates in the vaccinated arm than in the placebo arm. JJ vaccine had lower death rates. Statistically significant once you combine the trials.

Andrew Huberman (222:10)

Was the JJ vaccine an MRNA vaccine?

Jay Bhattacharya (222:12)

No, it's an adenovirus vector vaccine.

Andrew Huberman (222:14)

Right. And it was the single shot.

Jay Bhattacharya (222:16)

Yeah. And it was like the AstraZeneca vaccine, similar technology, adenovirus vector vaccine. Okay, so. But again, those were only two months long. And the death rate difference was like, you know, it's hard to. It was not statistically powered to find one, although it happened to find one in the adenovirus vaccines. Not the adenovirus vector vaccines, the MRNA vaccines. You couldn't say from the randomized trial one way or the other. Okay, so that's the information base we had in December of 2020. I wrote an op ed in December 2020 with Sinetra Gupta where I argue that that is sufficient to say we should give the vaccine or recommend that older people get the vaccine, but that we shouldn't give it necessarily to young people. The reason was that young people died at very low rates relative to young, older people if they got Covid. And so the thing you were protecting them from was less of a risk to them than was for older people. And so the benefit harm calculation would tilt toward. But if you have something that's a big threat and you have something that is known to prevent it for two, if it prevents symptomatic infection, then it probably prevents death in the older population. I can't say that for sure from the trial, but I can extrapolate. It's extrapolation.

Co-host (223:37)

Right.

Jay Bhattacharya (223:38)

Seemed like a reasonable extrapolation in December 2020. Then it makes sense to give it. Even if there are side effects which are not known in the trial, the trial is only. Only, you know, tens of thousands of people. If you give it to billions of people, you're gonna have very. You're gonna find out side effects you didn't know about.

Co-host (223:56)

Right.

Jay Bhattacharya (223:56)

So. But there are these unknown side effects. But it seems like based on the benefit harm expectation, older people, it makes more sense to give it to. Whereas the younger people, the benefit harm calculation runs in the opposite direction. There are unknown harms, some harms, actually, you saw in the trial itself. But, you know, if you don't know it once, you give it to billions and the benefit's small. So what I wrote is you should recommend it for older people and then lift the lockdowns. That's the op ed I wrote, published in the Wall Street Journal. Instead, what public health authorities decided to do was to take the vaccine and say that we could use it to eradicate Covid. They implied it. They didn't exactly say that, but they would say things like, well, if 80, 90% of the population gets the vaccine, then we will achieve herd immunity as if it were some permanent state rather than a transitory state having to do with the fraction of the population that are currently immune versus the. That's a. Herd immunity is a clear mathematical construct. In epidemiological models of disease spread, the public health authorities that were talking about 70, 80, 90% were using it as essentially a synonym for disease eradic, which it is not.

Andrew Huberman (225:17)

Was this message only in the United States or was this message kind of uniform across the world?

Jay Bhattacharya (225:22)

Yeah, now just consider the. I don't know if she's uniform. Like for instance, I don't think Sweden never mandated the vaccine.

Andrew Huberman (225:32)

Right. With the exception of Sweden.

Jay Bhattacharya (225:34)

I just sort of a few other places.

Andrew Huberman (225:35)

Because for one public health science system to kind of collaborate in this, assume that they, the public messaging was, was they were about a bit out over their skis, so to speak. But for northern Europe to do that and for Brazil to do that and for Australia to do that sounds like there, there had to have been a, A, a collaboration of kind of massive scale. It's a little hard to imagine everyone collaborating in some sort of, you know, secret agenda that extends across international borders.

Jay Bhattacharya (226:06)

Which pushes out back in December of November 2020 when the news about the vaccine came out.

Co-host (226:12)

Right.

Jay Bhattacharya (226:14)

It was like a sense of joy that we've been a liberal, like the science had delivered us from this deadly plague.

Andrew Huberman (226:19)

It was definitely exciting.

Jay Bhattacharya (226:21)

Yeah. And so like. And there was this sense of hope, Right. That sort of like large numbers of people around the world, I think shared. Public health authorities shared that sense of hope. But that I think partly led them to extrapolate far beyond what the data actually showed and make promises to the public that were not in the randomized data that were available at the time.

Andrew Huberman (226:46)

The companies that made these vaccines, are they American based companies?

Jay Bhattacharya (226:51)

I think AstraZeneca is a UK company. J& J is an American. Pfizer, I think is an American company.

Co-host (226:56)

Yeah. Merck.

Andrew Huberman (226:57)

For some reason I thought Pfizer was overseas.

Jay Bhattacharya (227:00)

Moderna. Moderna has German roots, I think. I'm not sure. BioNTech is German, Moderna is American. I'm not sure exactly, because many of.

Andrew Huberman (227:08)

The people that are suspicious about vaccines or skeptical about vaccines argue that it's all financial incentives. I mean, was a lot of money generated from the.

Jay Bhattacharya (227:18)

Yeah, the billionaires were created out of this and a lot of. In fact, the NIH is collecting patent royalties from the licensing for the technology that went into the vaccines still now. Yeah, yeah.

Andrew Huberman (227:32)

But Project Warp Speed, the development of the Vaccine, AKA Project Warp Speed was a Trump program.

Narrator (227:39)

Right.

Jay Bhattacharya (227:40)

President Trump authorized the program in order to accelerate the development and testing of the vaccines.

Andrew Huberman (227:47)

I remember seeing him getting the injection on the news. So I think people forget that because of Maha and this sort of assumption that vaccines in Maha are. Are diametrically opposed in some sense that, you know, Maha is and Bobby Kennedy are. To my knowledge, it's the first time that anyone's forcing a look at vaccines with the kind of level of detail that they are doing it or going to do it. People assume that the Trump administration is not aligned with vaccines. But the Trump administration initiated Project Warp speak, correct?

Jay Bhattacharya (228:22)

Yes. Yeah. The idea that Bobby or President Trump is anti vaxx is ridiculous. This is frankly at odds with what the data actually show. Okay, let's go back to the COVID vaccine because I think the story is really important. Public health authorities, on the basis of an extrapolation that they should not have made, decided to essentially promise the public that if they got the COVID vaccine, that they would not ever get Covid again. That was the implicit IT public health messaging. You can become free. Just take this shot. You become free. You no longer have to worry about lockdowns and mask mandates or whatnot. It very quickly became clear that that was not true.

Co-host (229:11)

Right.

Jay Bhattacharya (229:11)

So I remember seeing the outbreak of cases in Gibraltar, which was like 95%, 90 plus percent vaccinated. And I look at them going, why is Gibraltar? I think they were using the AstraZeneca vaccines. Why are they seeing this huge spread of COVID I saw data from. Well, I forget which country. It was mostly using the Chinese vaccine, the Sinopharm, which had a more traditional technology, again with a huge outbreak of cases in February or March of 2021. Then Israel, country after country, they've been heavily vaccinated, seeing large outbreaks of cases. And that meant that the extrapolation was false, that the vaccine was going to stop you after two months from getting Covid and spreading Covid was not true. Instead of acknowledging that fact, public health officials decided that the problem was the unvaccinated. And they embrace the idea that you have to force people to get vaccinated for the public good.

Andrew Huberman (230:20)

So they double down on their high.

Jay Bhattacharya (230:22)

It was like July, August 2021 that the Biden administration decided to use OSHA to use cms. OSHA is the safety, safety. And then there's cms, the center for Medicare and Medicaid Services, to mandate the vaccine for populations that they had control over.

Andrew Huberman (230:44)

And when we talk about mandates, were there Criminal charges or civil charges if somebody didn't get it.

Jay Bhattacharya (230:51)

Just lose your job. Yeah, you just lose your job.

Andrew Huberman (230:53)

I recall at Stanford there was an insistence that everyone get vaccinated, but that if people had religious reasons to not get vaccinated or some special health reason that they could, could essentially not get it.

Jay Bhattacharya (231:07)

Stanford made it difficult to not get vaccinated, but possible, like if you had religious exemptions, they made it possible. Other. Other universities made it much more difficult. So, for instance, my colleague and friend Martin Koldorff, who's a tenured faculty member at Harvard University, got fired because he didn't take the COVID vaccine, even though he'd already had. Had Covid and recovered.

Andrew Huberman (231:26)

He is currently still fired.

Jay Bhattacharya (231:28)

Yeah.

Andrew Huberman (231:30)

So there were consequences for not getting it. Yes, because we hear this word mandates. Right. But I don't recall anyone coming around to my house like, you know, and insisting. I just recall that if I need to go certain places, I needed a vaccine card signed.

Jay Bhattacharya (231:43)

And so, I mean, essentially a widespread restriction on your basic liberties, civil liberties that was a consequence, including potentially your employment in other countries were even worse. Like, so Canada, you couldn't go on public transportation, you couldn't fly if you weren't vaccinated. You couldn't go to a restaurant if you weren't vaccinated. That's true in New York City, by.

Andrew Huberman (232:07)

The way, you had to bring a vaccine card.

Jay Bhattacharya (232:09)

Yeah. And if you didn't have one, you couldn't go in. Essentially. The regime was essentially to ostracize people who decided that they didn't want or need the COVID vaccine. Even though the scientific evidence was that. There was no scientific evidence that demonstrated that if you had the COVID vaccine, you were less of a threat to other people as far as spreading Covid than if you hadn't had the COVID vaccine. Specifically for people who had already had Covid and recovered and weren't vaccinated. Actually, there was quite good evidence from studies in Israel especially that you were less of a threat for someone who never had Covid and was vaccinated. And it's been three or four or five months since the vaccine. Evidence out of Qatar showed a pretty sharply sharp reduction in the efficacy of the vaccine against getting Covid by 4, 5, 6 months after the vaccination.

Andrew Huberman (233:04)

And what, if any, evidence was there that the COVID vaccine, any of them, caused any specific harm in adults?

Jay Bhattacharya (233:12)

Right. So in young men specifically, like adults as old as 35, 40 years old, there was evidence of heart inflammation, myocarditis, transient Myocarditis, yes, but also more severe myocarditis. In post the vaccine there was, I mean that was, that was clear, clear evidence.

Andrew Huberman (233:32)

Why just boys do we know?

Jay Bhattacharya (233:33)

I don't fully understand the biology of that.

Andrew Huberman (233:35)

A reason to do sex specific studies.

Jay Bhattacharya (233:38)

And I'm in favor of that.

Andrew Huberman (233:40)

Pass up the opportunity. Interesting. So was there any evidence that the vaccine had long term detrimental effects that we're still looking at now? You know, you hear this stuff, you see it circulating, you hear more about long Covid and we should talk about long Covid. But is there any evidence that the vaccine caused long term issues for people?

Jay Bhattacharya (234:04)

I think that likely that there's some people who have particular immunological responses or there's also like evidence that the production process for some of the vaccines involved using DNA plasmids which may persist in producing some of the products of the vaccine. I'm not actually, frankly not. I mean I've looked at the literature and there's a lot of like controversy around the literature and have not made up my mind fully on the extent of it. What I will say is that it's very difficult to ask questions about long term effects of a vaccine. Just generally you can't run a randomized trial that's done right. The vaccine trial was terminated where the placebo arm was vaccinated in January of 2021. And so you're not going to tell from the randomized studies about the long term effects. So now you're left with observational studies where you need to like have a real control group constructed properly. And it's been difficult to get the public health authorities who are supposed to do this to actually do this at scale. I've seen some of this like I think the FDA put out a report of babies getting the vaccine having epilepsy or seizures at slightly higher rates. I think it was a report in 2022. There's claims online I've seen about cancer, but I haven't seen anything where they've done a very careful people have done careful control groups. I don't know. I'm not leaving out the possibility. I'm just saying that the kind of studies that I would like to see done, vigorous studies that have control groups even in observational settings, it's hard to find them in the literature and whatever they're in the literature, they seem to get, get attacked sometimes for reasons that make sense and sometimes for reasons that don't. It's very difficult to like address this from a purely scientific point of view because the literature Itself seems like it's poisoned.

Andrew Huberman (236:05)

Do you believe long Covid is a real thing or is this something that people have constructed?

Jay Bhattacharya (236:10)

No, I think it's real. I think there's. So I do think that the extent of it is again, unclear, but it's very clear that there are some. So for instance, I've saw a study, I think it was in 2021 from France, where they looked at people who previously had Covid and previously never had Covid among kids. And then they were measuring subsequent long Covid rates at long Covid rates, comparing the matched people who previously never had Covid versus who did. And in kids, the rates of measured long Covid, which back in that study I think was like, did you have one of some number of symptoms? In the WHO list of long Covid symptoms three months after the COVID infection and the MATCH study were roughly the same rate for kids, but for adults, it was higher for the people who'd had Covid before then. And it was, I mean, so I don't know the exact rate, but it's certainly a real phenomenon. I mean, I've met people who've had it. Same thing with vaccine injury. Like, I've met people who have vaccine injuries who report having had concrete, discrete injuries after they've been vaccinated. And I believe them. I mean, I think that I generally tend to believe patients when they say things about themselves and, you know, especially when they have no incentive to dissemble about it. And yeah, so I think that these are real phenomena that we need to address, you know, with open minds.

Andrew Huberman (237:39)

Will the NIH and or CDC be making public statements about some of what you just described, that the messaging around vaccines was, in your view, inaccurate?

Jay Bhattacharya (237:51)

Well, I'm still saying this, and I've been saying this, I think that.

Andrew Huberman (237:54)

But in your new. I mean, you're saying it here and we hear you in your new role, like at the level of, you know, a country of 300 plus million people, like, hey, folks, you know, we've looked at this and you know, I wasn't in charge then, but. But here's the deal.

Jay Bhattacharya (238:12)

I mean, in my role, I have to focus on stuff going forward more than, I mean, the past, I think is worth addressing, but it has to be a broader look than just me coming out saying my opinion about it. This podcast is fun, but that's not the purpose is. So I'll just give you a specific thing. My colleague Marty Makary, who runs now, is the commissioner of the fda. He has issued a new framework for Evaluating Covid booster shots. Okay, so rather than just requiring to show that the COVID booster, the new variant Covid booster, whatever it is, in the future produce antibodies either in lab animals or in humans in order to approve the vaccine for use now, going forward, the boosters have to show some efficacy against preventing Covid and preventing deaths and hospitalizations.

Andrew Huberman (239:06)

I see.

Jay Bhattacharya (239:07)

In order to get approved. That's an evidence based framework to essentially say if you're going to sell the vaccines, at least show in humans that it actually works for something we care about. If you produce antibodies and it doesn't translate to reduction in morbidity or mortality, then why recommend it or why prove it?

Andrew Huberman (239:28)

Some people might want to take the vaccine to reduce symptom severity, not just to avoid death.

Jay Bhattacharya (239:33)

There's now at this point, not. There's not evidence. If you've already had Covid and recovered, there's no evidence that it would do that at this point for the boosters. I mean, again, like, I want to distinguish. That's why I wanted to start with December 2020. This was like, you know, we knew about these large scale studies from the vaccines that were new and we knew. I want to distinguish what we knew and didn't know. The boosters are a different vaccine and they don't have the same large scale studies behind them. They've been approved on the basis of relatively small scale studies asking whether they produce antibodies, not things that clinically matter to people. Is it going to prevent me from getting sick? Is it going to prevent me from being hospitalized? Is it going to prevent me from dying? The boosters don't have that kind of evidence behind it. And so I think it was just a couple weeks ago the FDA decided that it was going to ask the manufacturers to produce much better evidence for the boosters before it was going to approve them. It shouldn't just be a routine thing. This is not a flu shot. The framework, the regulatory framework that governs flu shots are based on decades of experience with, with, with, with flu vaccines.

Andrew Huberman (240:50)

Are you a fan of the flu shot?

Jay Bhattacharya (240:52)

I mean, I've had lots and lots of flu shots in my life. Really? Yeah.

Andrew Huberman (240:54)

Do you get it every year?

Jay Bhattacharya (240:55)

Generally, yeah.

Andrew Huberman (240:56)

And it's designed to guard against most of the, the most common strains of flu that year.

Jay Bhattacharya (241:00)

Is that how. Yeah, I mean, sometimes they guess wrong, it doesn't do much and sometimes it gets right, it does better. But I generally haven't gotten, I mean, I don't think I got it last year. Too busy, I guess.

Andrew Huberman (241:10)

But, but you don't it sounds like you don't have any specific concern, safety concerns about the flu shot for otherwise healthy adults, is that right?

Jay Bhattacharya (241:18)

Yeah, I mean, there's. As a scientist, I want the safety of these vaccines evaluated in a rigorous way. So I'm not. I wholeheartedly support that. And if the data show that they're bad outcomes, I'm going to say that.

Co-host (241:33)

Right.

Jay Bhattacharya (241:34)

But as a general matter, the flu shot, the technology used for it is, I mean, it's a traditional technology that has a long history behind it and the regulatory framework. While I do think that like the production of antibodies is, I think that's actually still the standard for the flu shot. It makes some sense.

Co-host (241:52)

Right.

Jay Bhattacharya (241:52)

The flu strain that circulates is a different one every year. And if you required this like long term clinical trial for the flu strain that's currently circulating, by the time you actually recommend it, it would be useless. Now you can say that's true for Covid as well, but we don't have decades long experience with the safety profiles and also the efficacy profiles. And the flu shot, it's hit or miss, right? Sometimes it works and sometimes it doesn't. What we need is an excellent universal flu vaccine, which there's still a lot of research to try to get. I think the key thing is, what I want to convey is if you are in favor of vaccines, you should not be treating this as a religious matter where vaccine is good and you believe that therefore you're a good person, vaccine is bad. Therefore if you believe that you're a bad person, you should be treating this the same way we treat other drugs that we recommend to the population at large. Evaluate the benefits, evaluate the harms in rigorous ways, including randomized studies. Understand patient nuances. It might be right for some patients and wrong for others. If you're going to say something, don't extrapolate beyond what the evidence actually shows.

Co-host (243:10)

Right.

Jay Bhattacharya (243:10)

Or else you risk losing the trust of the public, especially the public that would most, potentially most benefit from the thing. What I'm arguing for is an actual, honest, evidence based evaluation of vaccines. And that's essentially what Bobby Kennedy's asking for.

Co-host (243:26)

Right?

Jay Bhattacharya (243:26)

So that's what he's asked me to do. Not for vaccines generally, but for, but for the COVID vaccine. That's essentially the policy. Now, the problem that we have in public health is that you asked me earlier about do I think there are certain vaccines that are worthwhile? And the answer is yes, I do think that. I think that if we have a public health authority that's gotten it so deeply wrong about this one vaccine where people lost their jobs over it, people got injured, and they were silenced over it. People. People essentially felt, you know, felt like they were made to feel like, you know, remember like in 2021, where people would disinvite family members from Thanksgiving if they weren't vaccinated.

Andrew Huberman (244:19)

Yeah. Or worse. Or people were kind of excommunicated from families and workplaces.

Jay Bhattacharya (244:24)

Yeah. Essentially, we. We created a class of unclean people as a matter of public policy. You can understand why people who went through that would say, given that the vaccine didn't turn out to stop you from getting and spreading Covid, why should I trust you on anything else? That's where we currently are. The way forward isn't to force people to say, look, you must acknowledge how great science is on these other things. The way forward is to be utterly honest about what we know and don't know and treat people as partners rather than as subjects.

Andrew Huberman (244:59)

So in keeping with that, there's perhaps no issue more sensitive than the vaccine autism issue. My understanding of the current literature as it stands is that the Andrew Wakefield data, this British physician who was really the first to popularize the idea that that vaccines could, in his words, cause autism or were highly correlated with autism, those data were essentially retracted by the journals. He lost his medical license. And my understanding is there was evidence of fraud that he. That he was either made up data or contorted data. I've had guests on this podcast, including a colleague from Stanford, Karen Parker, who works on autism, who verified that, indeed, the frequency of autism is vastly increased in recent years in ways that cannot just be attributed to improved sensitivity of tests, et cetera. 1 in 32 births is the current number. And so you can understand why parents who love their kids more than anything and would do anything for their kids are understandably concerned about any possibility that vaccines could increase the probability of autism. My stance as a scientist is, well, if the data are robust that vaccines don't cause autism, then run a proper trial. The Wakefield data are clearly contaminated, if not outright, certainly by story and narrative. I mean, there's just no way that those data are going to be resurrected. And I don't think they should be resurrected. Right. I mean, unless there's something I'm not aware of. He said too many things that weren't true. And whatever happened are, you know, is. Is history. So what is the evidence, if any, that a vaccine, some specific vaccine, causes autism? And is the NIH and CDC and the new administration going to take a Serious second look at this.

Jay Bhattacharya (247:12)

Yeah. So I don't want to comment on the Wakefield situation because I don't know the ins and outs of it.

Andrew Huberman (247:19)

All we know is what happened. He lost his medical life.

Jay Bhattacharya (247:21)

And I should say like that. Like it's. We're talking about one study.

Co-host (247:25)

Right.

Jay Bhattacharya (247:25)

I believe that replication matters. And so, like, there are, I think, on the MMR vaccine, some excellent studies that failed to find a correlation or a causal link between vaccination, MMR vaccination, measles, mumpsorella. Measles, mumpsorella. A vaccine that's really, I think, important for the childhood for kids and autism. Like, there's a massive Danish study that tracks patients who were vaccinated, kids who are vaccinated matched with patients, similar patients who are not, tracks them for a year or longer and years and finds no difference or fails to find a difference in autism rates. There's people who, I mean, there's all kinds of. You look online and elsewhere, there's all kinds of fights over that. But to me, that's pretty good evidence for the MRI vaccine. For some of the other vaccines, there has been less of a focus to.

Andrew Huberman (248:32)

Ask whether it's correlates to vaccines such as polio vaccine.

Jay Bhattacharya (248:38)

I don't know this literature, so I shouldn't comment, but I don't remember seeing a study specifically asking whether the polio vaccine is linked to autism.

Andrew Huberman (248:46)

When I was growing up, every kid got the polio vaccine. Measles, mumps, rubella, I think dpt.

Co-host (248:52)

Yeah.

Andrew Huberman (248:53)

Yeah. And a couple others. Like there were probably four or five vaccines, as I recall.

Jay Bhattacharya (248:57)

I think that there's good evidence on the MMR vaccine that of failing to find a link with autism. There's, and I don't know the full extent of this literature, so I shouldn't comment too much, but I don't. When I've looked, I haven't seen quite the same level of evidence for some of the other vaccines failing. Just haven't. Again, they just haven't looked. As a general matter, I think it's an unlikely, just from a biological point of view, unlikely to be the main reason why the rise in autism, which is now well documented, that you talked about, has occurred. So to me, the question then is thinking about autism. You're asking, you want to answer for parents, well, what does cause it? What has led to the rise in the prevalence of autism? The honest answer is, I don't know. We focused now in this conversation on just one potential cause, vaccines. To me, it's unlikely that they are the reason for the rise in the cause of autism. But there are many other potential hypotheses for the rise in the prevalence of autism that I've seen. You know, so alterations, the gut microbiome. I've seen retinoids.

Andrew Huberman (250:17)

There was a paper out of Pashko Rakish's lab at Yale years ago looking at the migration of cells in the cerebral cortex and developing fetuses, primate fetuses. But it's a great model and he was exploring the idea that ultrasound was altering cell migration, which may lead to changes in circuit connectivity. Never really got followed up on because that would be.

Narrator (250:37)

Be wild.

Andrew Huberman (250:38)

He would be. Would be wild. I'm not suggesting that ultrasound causes autism, but there were a lot of interesting ideas early on that I thought ought to be explored.

Jay Bhattacharya (250:47)

Well, so the point, the point is that unless you know the etiology, it's very difficult to talk about the treatment. Now, of course, autism is a, has a very wide range of clinical presentations, right. You have kids who have, you know, some social awkwardness, but otherwise are well adjusted, have no problems. Think Sheldon from Big Bang Theory or something, right?

Andrew Huberman (251:13)

Or many of our colleagues, maybe me, I don't know.

Jay Bhattacharya (251:17)

And then you also have kids who have very severe disabilities, a lot of biologically driven co occurring conditions, apraxia, have difficulty toilet training for it will never live on.

Co-host (251:34)

Right.

Jay Bhattacharya (251:35)

And so you have a very wide range of outcomes. It's very possible that biology is very different for folks along the spectrum. And unless you understand the etiology, it might be different etiology for kids in different parts of the spectrum, then you're never going to have good answers, both for prevention and also for therapy.

Co-host (251:57)

Right.

Jay Bhattacharya (251:57)

So it's that question that Bobby Kennedy has asked me to answer or try to get an answer, and it's that President Trump has asked to get an answer. And I think it's appropriate because if you ask me what is, I mean, we just talked about vaccines as a potential cause. I think it's unlikely to be the cause. But, you know, you can see my mind is open depending on the levels of evidence I've seen. Now, this is not my area, I should say this, I'm saying this as someone who's now tried to wade into it some just to get a sense of it. But as I've waded into it, it's very, very clear that there is not a scientific question, consensus, answering the question of what causes the rise in autism or what is the etiology of autism.

Andrew Huberman (252:42)

But it seems that encouraging a spirit of open discourse about these other potential causes.

Co-host (252:50)

Right.

Andrew Huberman (252:51)

And I'm not suggesting, by the way, that ultrasound causes autism. I want to be very clear. But if you read scientific papers focused on brain wiring and you make the not so outrageous leap that autism has something to do with brain wiring, maybe gut and brain and a bunch of other things, but you come across a number of very interesting preclinical model hypotheses that hopefully will be tested at some point.

Jay Bhattacharya (253:13)

Well, things like environmental exposures to various kinds of chemicals, tens of thousands of chemicals in the, there, there's events that happen in utero, potentially. There's, you know, there's nutritional issues, potentially there's, I mean I've seen a, you name the hypoth. I'm just trying to wait in this literature from someone from the outside and it's just, it's, it's bewildering and I can't even imagine what a parent looking at this would look like. Oh, it's gotta be right. And to me, when there is no scientific question to an important thing that actually impacts health, the answer is let's do excellent science on it. Now I've seen a lot of excellent science about how to manage autism. Lots of fights over is psychotherapy the right approach? Behavioral modification, there's lots of fights over that. Do we address the co occurring biological conditions? How do we address that? Is it different? I mean I've seen lots of like, of literature around that which strikes me as more advanced and sort of closer to the right answers. Although again there's lots of controversies even there on the etiology of autism. It strikes me is that the literature is not all that far advanced, that there's lots and lots of competing hypotheses. The data are conflicting on many of them. If I could give you my most promising one but, but they would mean nothing really. The right thing to do in that setting is to have an open minded investigation to try to address this problem. And the question is why haven't we had that so far? And I'll tell you, I think the reason we have not had the kind of open minded, deep investigation by the scientific community at large on the ideology that parents deserve, the kids deserve, is because it's dangerous to ask that question. If you're a scientist all of a sudden you're going to be accused, often incorrectly of being an anti vaxxer and that's the end of your scientific career. That kind of sort of suppression of scientific curiosity means that we won't have an answer to this question.

Co-host (255:33)

Right?

Jay Bhattacharya (255:33)

So what I'VE done is I've organized an initiative inside the NIH to address this question of the etiology of autism.

Andrew Huberman (255:44)

Not limited to vaccines.

Jay Bhattacharya (255:45)

No, wide ranging. It includes basic science work, it includes epidemiological work, it includes environmental exposure work and will bring together data sets that we'll make available to the researchers. We'll have a competition among scientists, just like the normal NIH way, with peer review panels to ask who should get the awards. We'll have a dozen or more scientific teams asking the question, what is the etiology of autism? We'll have that. I think that normally it takes a year or longer to set up a thing like this. Well, by September we'll have an open competition for these scientific projects. And you can't brush science, but hoping within a relatively short period of time, you know, who knows how long exactly depends on how science works, we'll have a much better understanding of the etiology of autism than we have at this current moment.

Andrew Huberman (256:44)

Fantastic. I mean, just fantastic. I mean, regardless of where one sits on the vaccine discussion on vaccines.

Jay Bhattacharya (256:50)

Can I say one thing now? I don't want to, as the NIH director, I don't want to put my thumb on the scale on any part of these potential ideologies. Right. As I already said, I'm not particularly an expert in this area. And so, you know, if we were to put my thumb on the scale, it would be not from the point of view of expertise, it would just be the point of view of like, I just happened to read the literature and I was impressed by X, Y or Z. But if I were to put my thumb on the scale, I think it would make it more difficult, A, for scientists to ask the question honestly because they want to impress the NIH director or something and then B, for the public to trust the result at the end. I wanted open minded. So this is why like I, I was asked, well, well, if you don't believe that these vaccines cause autism, why would you allow people to ask that as a part of the research agenda? My answer is there are a lot of people, especially in the public and even some scientists who disagree with me and I want them to have their say. I want an honest conversation. I think that if you have an honest evaluation, you're not going to find that vaccines are the primary reason for the cause of the rise in hormones, autism. You're gonna be, it's gonna be something much more fundamental and complicated. But, but I don't want the results to be disbelieved because I put my thumb on the scale.

Andrew Huberman (258:08)

I eagerly await the results of the unbiased studies. Yeah, I really do. And thank you for spending that time, you know, explaining what that initiative is going to look like. And I'm delighted to hear that it's not emphasizing one particular hypothesis.

Jay Bhattacharya (258:25)

The other thing about the initiative, it's very important to understand. We're working with autistic parents, we're working with the autism community. Right. A lot of times scientists, when they study things, we put ourselves above and it's like we're examining amoeba or something on a slide. When you do population research, you have to work with the communities that you were actually trying to help. Help. And that's exactly the spirit of this. We're going to work with communities of autistic kids and parents and we're going to apply rigorous research methods with control groups and just the normal sort of high quality. The term of art now, it is gold standard science. We're going to apply gold standard science to this and subjects to it to the same kind of replicability standards. I want all science subject to.

Andrew Huberman (259:18)

Can we expect that the National Institutes of Health, which indeed is a plural statement, institutes, nimh, Mental Health, National Eye Institute, et cetera, will be restructured in some way, in part to reflect the MAHA movement, make America healthy again. And by the way, no one told me to ask that question. I'm asking out of genuine curiosity. There are these theories. I'm like, like part of the. I'm not. I'm. I'm politically in. I'm a free agent because the budget is limited. There's, it's not an infinite budget. Depending on how the IDC thing goes, there may be more or less money to devote directly to the laboratories around the country. And given that fixed amount of money, you can't, that can't do everything. I love the way you're encouraging innovative, exploratory science that's rigorous, with open discourse. But can we expect that the institutes of the National Institutes of Health will take on some new names? Maybe a new institute starting to emerge?

Jay Bhattacharya (260:24)

I mean, it's really Congress that determines that there's a process. The administration has put forward its suggestion for a reorganization. I think it's down to eight institutes from 27 or institutes and centers. Congress over the past decades have had several suggestions for how to do this. It's one of these things where, like, I could focus my, my efforts on things that I think are going to make big, big, big changes. Where I could focus my efforts on, like, reorganization efforts. I'll I'll do what Congress, the administration, asks, asks of me. But. But from my point of view, we'll let that fight happen as it happens and we'll respond to it as it happens, rather than like where I'm active. I think the key thing is not the structure of the institutes. To me, the key thing is the content of the research and the standards we hold ourselves to in the research. Those are the things I want restructured. That's really the fundamental question for me as an NIH director, if I can accomplish some of the things we've talked about during this podcast, having replicability be the core of deciding what scientific truth is, refocusing the portfolio so that we enable early career scientists to test their ideas out, that we aim big for trying to and we address the key health problems that Americans face. If we can do those things that I'll consider myself yourself a success.

Andrew Huberman (261:55)

Well, Dr. Bhattacharya, you have a tall task and you're clearly ready for it. I want to thank you for taking time out of your extremely busy schedule. Those aren't just words. You are extremely busy to come here and have this discussion and to tackle head on questions that were not all easy questions, some of them quite difficult actually, because there's a lot of, of nuance, a lot of different lenses one can look through. It's clear to me that you're a data guy. You love data. And it's also clear to me that you like dissent. Maybe because you've been in the position of, of that's been always true, actually. Okay, well, yeah, it's, it sounds like it's in your nature. I didn't know that the younger you. But I love that you encourage dissent. I do believe that great science emerges from discourse that includes sometimes even just outright arguments, provided it doesn't get physical or cruel, that are aimed at getting at the truth, if it's possible, getting at the truth. And it's also very clear that you care about exploration. And I must say especially warmed by your enthusiasm for protecting and promoting the science of young investigators, meaning in the first 10 years of having their labs as well as trainees, I think. I'm not trying to speak in nomenclature. This is so important.

Jay Bhattacharya (263:20)

It's vital that it's so important.

Andrew Huberman (263:23)

And yes, there are some older labs doing some wonderful work, but even they will eventually retire and die. We all do. And the younger generation of scientists in this country, it's so key. And so I just really appreciate you coming here to share. I do want to check back with you in a year or two, see how things are going and science and public health really need you and to really get behind discovery and the mission statement of the nih. So thank you for coming here today. You didn't have to do it and I look forward to more discussion.

Jay Bhattacharya (263:56)

Andrew, thank you so much for having me. Really a pleasure.

Narrator (263:59)

Thank you for joining me for Today's discussion with Dr. Jay Bhattacharya. To learn more about Jay's previous work and to find links to his current post at the nih, please see the show Note Captions if you're learning from and or enjoying this podcast, please subscribe to our YouTube channel. That's a terrific zero cost way to support us. In addition, please follow the podcast by clicking the Follow button on both Spotify and Apple. And on both Spotify and Apple you can leave us up to a five star review and you can now leave.

Andrew Huberman (264:25)

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Narrator (264:28)

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Andrew Huberman (266:26)

You for your interest in science.