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Infinite Loops
Parmita Mishra — How to Think About Biology (EP.244)
01:30:55
Parmita Mishra is a computational biologist and the founder & CEO of Precigenetics, a company aiming to become a rocket to precision medicine. Parmita is deeply knowledgeable about cutting-edge biology, particularly epigenetics — how behavior...
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- [00:02]
A
Hi, I'm Jim o' Shaughnessy and welcome to Infinite Loops. Sometimes we get caught up in what feel like infinite loops when trying to figure things out. Markets go up and down, research is presented and then refuted, and we find ourselves right back where we started. The goal of this podcast is to learn how we can reset our thinking on issues that hopefully leaves us with a better understanding as to why we think the way we think and and how we might be able to change that to avoid going in infinite loops of thought. We hope to offer our listeners a fresh perspective on a variety of issues and look at them through a multifaceted lens, including history, philosophy, art, science, linguistics, and yes, also through quantitative analysis. And through these discussions help you not only become a better investor, but also become a more nuanced think thinker. With each episode, we hope to bring you along with us as we learn together. Thanks for joining us. Now please enjoy this episode of Infinite Loops.
- [01:14]
B
Well, hello everybody. It's Jim o' Shaughnessy with yet another infinite Loop. Today's guest is somebody I'm very excited to chat with. It is Parmita Mishra, the founder of Pre C Genetics. I love that name. A combination of precision and genetics. You were a former research assistant at Penn Medical. You have a degree in computational biology from the University of Pennsylvania. You have A levels with high distinction in math, economics and biology. You are a triple, maybe quadruple threat type of woman. Parm, welcome.
- [01:55]
C
Thank you so much. Very nice being here.
- [01:59]
B
So I have a particular interest and full disclosure. O' Shaughnessy Ventures is an investor in Parmita's company. The reason that I was intrigued, in addition to sharing a lot of your beliefs that we need to get to individualized treatments for people and understanding of the epigenetics of your particular human body, was a 2020 paper that you wrote on the role of epigenetics in autoimmune diseases. That's very near and dear to my heart because my eldest sister, Lael, died from lupus in 1971 when I was 10 and my mother had lupus did not die from it, thank God. But back then it was really the dark ages of understanding autoimmune disorders at all. Most of my siblings and I have the autoimmune gene. Luckily in most of our cases it is presenting only in a very mild format. In my case it's some skin problems and others and my sister's also super, super mild. But why don't we start assuming, I don't know if you're a movie fan, but there's a great movie where it's about Wall street during the crisis and all of the quant geeks are trying to explain something to the CEO, who's Jeremy Irons, and he goes, no, no, no, no. Please present this to me and make me understand as if you were talking to a golden retriever. So let's start with some, let's start with some definitions. Genetics first, epigenetics. And there's a major difference and maybe our listeners and viewers would love to hear what that is.
- [03:47]
C
So I think first of all, I'm so sorry for your loss, I must say that, and I'll get into this soon, but I fundamentally see disease as an engineering problem from the perspective of the person treating the disease. And it. Every death that I hear about makes me very angry and I'm really sorry that that happened. And I hope that we can make impact in the world collectively as well as within Parsi Genetics to ensure that this incident reduces over time. With that said, regarding epigenetics, I'm going to be saying some things that full disclosure, I learned from online from Dr. Manolis Kallis, who I believe is one of the greatest biologists, living or dead. Like he's currently the head of computational biology at mit. He's a computer scientist and a biologist, and here's how he describes it. So he's Greek and he says in Greek, EPI means on top of. So you have your genetics and then you have things sitting on top of your genetics literally as well as metaphorically. And there's something beautiful actually about how genes work. So back in Schrodinger's what is life? Schrodinger predicted, correctly, actually to a very great degree, that there is this sort of part of your cell that's now known to be your chromosomes and it has something called your aperiodic crystals, which are basically contain non repetitive sequences. And that according to him, he believed was the recipe, so called for life, or the way I would describe life would be the cell. And he himself said this, that it's not just about what you have inside of that crystal or that chromosome, it's also about how it is expressed. So interestingly, every single cell in your body, barring, you know, some cells that don't have genes like roughly speaking, like red blood cells. And then of course, barring your germline cells like your egg or sperm, which have a different makeup, they roughly have the same genes. And here I am saying your genes describe how your cell is created, but your cheek cell is Very different from your eye cell. And the reason for that is the way in which your genes are expressed. And that is based to a great degree on what is sitting on top of your gene, including how your gene is configured. And so epigenetics, in short, includes anything. There's a lot of definitions, but a definition I ascribe to is anything that is not explained by just your genes themselves. Now if I'm telling you that all your genes are the same, roughly speaking, but you have completely different cells all across your body, then there's a lot that's not explained by your genes. And I guess the best example I can give is a switchboard. So if you have a switchboard in your house, right, like where you have all these switches, they're on or off. Well, when you're, when you have a relatively simple cell, then a lot of those switches tend to be off. And then as a cell becomes more and more complex, let's say it becomes what we call a terminal neuron, which is a very complex looking cell. It doesn't really look like a blob anymore. There's more and more and more genes that have turned on there and they're specific to that cell. And so the idea is that when something is turned on, it is expressed more. And then there is also some intermediate states where it's kind of in between being on, on and off. And then those are, you know, much harder to interpret. But the biggest issue, I guess, with epigenetics is that right now we entirely rely on sequencing to understand your epigenetics. So for instance, we look at something like methyl groups, so CH3, that's sitting on top of like epi on top of your gene, or rather the promoter that comes right before the gene. And the idea is that when you have this methyl group on the promoter, then that gene is likely to be off, depending on how many you have. And then if you remove them, then that gene is going to be read by your cell and you create the proteins, you know, sort of related to that gene. And it is my belief that the most fascinating part about epigenetics is that first of all it gives this level of free will. You could say when I entered college, I didn't know about epigenetics and I did not really. I wasn't convinced by biology because I could just tell that there's a lot of things that you can change based on different sort of choices you make in life. And then I saw that one slide on epigenetics and introbio and My mind was blown because that's exactly what I thought for the longest time, is that you can really control some things, or at least you have some control that you don't see. And the other thing that's very exciting about epigenetics is that it is reversible by nature. So the idea is that when you turn on a gene, there's no reason from a science perspective why you cannot turn it back off. And that adds a level of reversibility. And that's something that we were really missing when we were only thinking about crispr, because that's something that's hard to reverse. So.
- [09:43]
B
Yeah, so I love your switchboard analogy because the first time I came across it and really thought about it, I was actually reading. It's a broadly applicable concept because I was reading about people doing IQ testing or G testing for G, and the author was making the statement that, like you just said, it's not that simple. Right. So. And then they went into the environment that someone that had like a. What would would be considered a classic high IQ, maybe that doesn't get expressed if that person doesn't grow up in a house with lots of books or doesn't have access to a local library or any of that type of thing. So it's much more prosaic, but I think it's very understandable for laypeople to understand. Oh, okay, I get it. Right. So the environment or what sits on top of you're talking about it from a biological sense, but it can also include our broader environment.
- [10:49]
C
Yes, absolutely. So I think when you're thinking about a cell, then you're often think, you know, biologists use the term environment and people assume that it's just the environment of the individual. It can be, but it's usually a molecular biologist is talking about microenvironment. Right. Which is all obviously related to each other. I think there is, though, a place for, I guess there's a little bit of convolution there because people assume that, you know, if I am around folks, then that's going to turn on my IQ gene. But then the question I have there is what is an IQ gene? We always like to say that, that our genes are affiliated with, you know, different phenotypes, but that's not really how the cell works. Interestingly, if you think of height, maybe one third of all of your genes are involved in height. And that's not the only thing they're involved in. It's really interesting how people immediately thought as a result of crispr that we're going to have designer babies and maybe we can change eye color, which I personally don't think that that's what CRISPR should be used for, at least in the beginning. But if you go anywhere further than that, you are, you know, you're flying blind. You have no idea what, what gene is related to what. And for the most part, you know, a lot of traits are what we call polygenic, which means that they are associated with a whole lot of genes. So it's really hard to say or measure from a scientific perspective if something is going only towards intelligence. Now, let's say that I find gene 100 is actually something that is very correlated with intelligence. And then I CRISPR it so that the person becomes more intelligent. Okay, well what if that also causes them to lose lung function? We have no idea. The closest thing we have is something called gene ontology, which is a project or consortium that is associated with understanding what every gene's so called function is. And the problem of course, being that these so called functions are not about traits, they're about proteins. A gene is just a recipe for one protein. And I think, yeah, it's very important to remember what we don't know. And the thing that got me excited about epigenetics is I realized we don't know most things. And frankly, that's a better place to be when you're trying to make changes in the world that are positive than feeling like we're at the end of biology and we just cannot, theoretically speaking, resolve any further things in biology.
- [13:51]
B
So, yeah, that is very insightful because I've talked to lots of people doing genetic studies and they make the same point that you just made. And is that one of the reasons why, for example, there's a lot of work being done around sickle cell anemia about male pattern baldness. And I've had that conveyed to me that the reason I joke that the male pattern baldness one is they're looking for a trillion dollar industry.
- [14:20]
C
Yeah.
- [14:21]
B
But despite the joke, is it because those are not polygenic and those are single genes or is that wrong?
- [14:30]
C
Sickle cell anemia is one of the simplest diseases. From the perspective of genetics. It is what you would call from our current understanding almost guaranteed to be your single gene. And with the set of genes like affiliated, which is actually why some of the greatest ideas in biology of this century have come as a result of sickle cell anemia. So if you think of crispr, highly related sickle cell anemia, why did someone pick up that disease and not cancer. It's quite simple to me, if you ask me. It's because it's simple enough like you know what to sort of target and you know, like a lot more about it than you know about, say 30 genes related to one other disease. And the reason why it's like fairly clear that sickle cell anemia is related to this one gene is because if you look at genetic crosses as well, and you can kind of very perfectly predict, you know, probabilities of someone having sickle cell anemia and so on and so forth. And with male pattern baldness, though, it's very interesting you picked up those two examples because male pattern ballness is on the opposite side of the spectrum. It is, you're completely right that it should be a trillion dollar industry. If there's anything in the world that we should be, or at least capitalism should be trying to solve, it is meal pattern baldness. But why is it not solved is a very interesting question. It's because we don't know anything about it. There's no way that I can go in and I can crispr in a baldness gene. There's no baldness gene. I can say that with near certainty. In fact, one of the studies that I Read found 71 genetic loci that was like related to male pattern baldness. This was done in the uk and then immediately after there were like five papers commenting saying, this is wrong about this study. It's not that many genes, so it's really complicated and it is probably like epigenetic at least to some degree because it seems to be associated with stress and so on, so forth. But luckily with male pattern baldness we do have some like transplant techniques that are just almost certain to work. And also no one's died of male pattern baldness.
- [17:07]
B
So yeah, yeah, when I made the joke, it was in service of the fact that it's often very difficult for laypeople who have an interest in all of these fields to disambiguate. I mean, like, unless they're reading the journals, right, which tend to be pretty daunting for just your layman. Right? I think the media doesn't do the best job in the world in translating the actual science right over to, you know, oh, what, what, what kind of story is going to get a million clicks? And that's why I made the joke about male better movements. There's also a serious side, right? If, if there was some huge money maker, then guess who gets interested? All the capitalists. All of the other thing which which then hopefully supports what I would view as much more serious work in things like sickle cell, other genetic disorders. What do you think about that? What do you think about the way that. And complicated scientific information, trying to get it into an understandable format that people, let's just say, let's say our target audience is intelligent humans who have an interest in that. Right. Are there any great popular books and, or other formats that people like that could use to get a reasonably good understanding of this? Because this is all really complicated stuff.
- [18:48]
C
I love that question. And a big part of why I started posting these threads on Twitter is that I realized that at least when it comes, I very much stand at the intersection of computer science and biology. And a lot of my friends happen to be engineers. They get so stressed out when they think about biology. And it's funny because that's probably where their skills would be most sort of scalable. Biology has so many low hanging fruits and every biologist in a lab is looking for engineers who can like, you know, accelerate their work. And I thought that maybe if I'm able to post some things in a way that's understandable, that could make a change. And to be honest, it really did. I've never received any negativity or hatred from any scientists or any layman about, you know, those threads that I've written because it's just so. It might seem simple to me what I'm talking about, but for some reason, to most people who have not been used to that way of thinking, it's like this fresh new perspective. I'll try to, I guess, give the most cohesive answer because I have a very meaningful thing to say here, which is that these texts written by biologists and papers, they are daunting and they're also not addressed towards someone who is trying to learn about something. They're addressed towards expressing exactly what their method was to basically prove or disprove a hypothesis. And they tend to be very verbose, a lot more than actually any physics or even chem paper that I can think of. I don't think that that's the best resource for someone who's trying to learn. Right. I think the most important thing when you're thinking about biology is to start thinking about it from first principles. I know that that sounds really scary and you're like, no, but your living body is always changing. And that's very true, but you need to find some structure in the chaos. So there's some fundamental frameworks that anyone can use to understand any life. The first Being that life is, as far as we know, it's cellular and it has metabolism. And the second is that a lot of complex life is actually the brain of the complex life is in the nucleus. It's really, really hard to. To find examples of, I guess, like eukaryotes or more complex organisms where these statements are not true. And after that, it's. I think the best person to read from is actually a physicist and not a biologist. And that's Urban Schrodinger. The reason being that, I mean, people forget that he predicted things that ended up winning Nobel Prizes decades after. Right. And those Nobel laureates gave credit to Schrodinger. So how is that? Well, it's because, frankly, a physicist can do the best job at expressing biology and analyzing biology, because a biologist is more of a person who is looking at statistics and who's looking at big amounts of data, for example, while a physicist is someone who is incredible at looking at something very complex and abstracting away and simplifying it. So I think that Schrodinger has probably made. He's probably one of the top five people in terms of contributions made to biology. The other, I guess, thing that you would want to keep in mind is never look at your clickbait news articles. I guarantee you if you search is caffeine bad for you? You're gonna see it turns out caffeine is very good for you. Next article. Caffeine is gonna kill you. Next article. Caffeine affects your kidneys. Next article. Caffeine solves bolding. The problem with bio is that none of those statements can be true. The point of biology is it's complex. Anything in a headline that's too assertive, it's not biology because unlike matter, which has this, you know, kind of repetitive structure, your cell is necessarily complex. It's necessarily not binary. And. And so, yeah, I think it's important to remember that you're not going. There are no adults in the room when it comes to biology. There's no interview from one expert that's going to tell you everything. And I think that's what I enjoy and that's what frustrates a lot of people.
- [24:08]
B
So, yeah, yeah. And Schrodinger's book, which he wrote in 1944, he also applied statistical mechanics to biological systems. Right. And he reasoned that the law of large numbers would in fact hold broadly, but that at the molecular level, it was still all very probabilistic. And I love that book for a variety of other things because, like, you know, he came up with the idea of negative entropy and where, where living organisms extract free energy from environmental sources etc and he did, you know, the aperiodic crystal predicting DNA? The Crick and Watson cite him in their work. And I do find that interesting because like that was kind of one of my early loves was quantum physics. And I didn't have the training to go on to the more in depth book books until I kind of learned that math is just a language like other languages. And if you look at math as a language, it helps quite a bit. I'd love your advice on avoiding any of the clickbait heavy assertions because that's exactly what they are. And you're absolutely right. And it's such a challenge because one of my main hypotheses is that life is not binary. Right? Deterministic thinking? Yes.
- [25:40]
C
No.
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B
0, 100 black white, life doesn't work that way. Life is mostly in the maybe category of many of the things that you cited as well. One of the things that I do that has proven somewhat helpful is I'll take academic journals and I'll put them in a large language model and I'll say explain this to me at an eighth grade level. And that can be really, really helpful because you're right, many academic papers, they're really terse and often using lots of words that people have to look up. And then there's another guide. Have you read James Summers I should have loved biology article?
- [26:28]
C
I have not, actually.
- [26:30]
B
Okay, I'll just briefly tell you. He's like, man, we don't teach biology, right? Because he's saying I had to memorize chemical formulas, but nobody talked about evolution from a single cell. And he goes, finally when I read Go to Leisure Bach, which is one of my favorite books as well by Douglas Hofstadter, he said he used this evocative language where one of the examples was cells are recursively self modifying programs. DNA makes rna, RNA makes proteins, Proteins regulate the transcription of DNA to life programs. He goes, this is like a Lisp program and you know it's. And. But the outcome is kind of the source code of life. What do you think?
- [27:16]
C
I think that that's a very interesting way of putting it. One analogy that I made on Twitter just randomly with about how if you were to compare, let's say protein as your hardware and your DNA is your software, then your RNA is kind of like your machine code and the epigenetics is kind of like this programmable array like an fpga. And I think thinking about genes as Code is very fascinating, but maybe it's about the time when I came into biology, being this very Precise, like late 2000 and tens, to be clear. I've been a biologist since I was 5. My parents are doctors. That's all I care about. But more academically, when I came into it, I got very frustrated because everyone was talking about genes and genes and genes. And I understand that genes are important and the code and, you know, like this idea of thinking of it as a recursive mechanism across dogma. It's important. Information theory is important because it's kind of like you're even across time, across generations. It's the transfer of information. But nothing about any of that felt convincing because it completely lacks the dynamic aspects of life. And this even goes down to how we measure life, which is a big part of what prasigenetics is about. Because when you think about measuring life, you want to think about genes, you think about sequencing. No one ever just sits down and thinks, we have the sequence of this cell, but the cell is gone. We just got one time point and the cell is gone. The only way that you can look at a cell at a subcellular level, that's popularized being your electron microscopy, you dry the cell up. You cannot look at it without drying it up. Where is the dance that is actual life? We're looking at cellular autopsies every single day and calling it life science. And it just feels like there's something fundamental missing there. And I think the same thing applies to looking at, I guess, how research is done right now. Right. So this is kind of like on a tangent, but I think about how every single research paper today is kind of inspired by Illumina, because Illumina came in early. Well, 1998, it started for the first year, four years, it was doing its scan as a service. It was. It basically created a way of sequencing that kills the cell. And it's incredible what they did. Don't get me wrong. But imagine if there was no Illumina, like, no one thinks about what would we be doing in biology if there was no Illumina, if there was something else that happen instead of Illumina. And I think in general, I realized that we are kind of completely dependent on the people who come up with the hardware. We're completely dependent on people who come up with the way we measure things. And we never see another version of reality where we have another measurement. If we did, then all these brilliant minds who are in the MIT road, who are at Penn, who are across the world, they might have a much better lens into life, and we might find that all of our analogies just don't mean anything. And we might actually go back to the theoretical and rethink how we think of life. So, yeah, I think that, you know, it's a bit of a tangent, but it's important to remember how many assumptions we make and then forget about, because we keep putting ourselves on that same system. And so we forget that passing thought we might have had in our heads, which is, oh, wait, all of this data, like, all two petabytes of this data, is it. It killed the cell.
- [31:40]
B
You know, I do. And that's what attracted me to you and your company. I always think I've used the metaphor a lot, that most of the things that we make decisions on are, in fact, snapshots. And a much better way to make decisions broadly, not just in biology, but in business, in a variety of things in life, is to look at a movie, right? And so, for example, that informs our hiring process at osv. Everyone starts out on a contract. As you know, they'll be there for six months. That gives us a much broader scope of their talents, their deficiencies, how well they fit in, et cetera. Because, like, what happens if you. To make the analogy of doing a single cell and killing it? What happens if you found somebody that was absolutely, like, perfect? They're going to make a great teammate, they're going to be ideal, they're going to fit in perfectly. And you happen to interview them on a bad day, and that snapshot guides all of what you think about them. And these are in many respects, very unconscious processes that we aren't even aware of ourselves. And so this gets to also what I found really interesting about your research. You're looking for a way that lets us generate comprehensive data across spatial and temporal dimensions, which I think is obviously incredibly important. And you had a quip that I actually liked, which is, think about it as, like, developing a very, very good camera. Talk a little bit about that, please.
- [33:24]
C
Some of this is actually inspired by what is life. Why I keep coming back to that book.
- [33:31]
B
Great book, by the way.
- [33:33]
C
It's a bible to me. Like, it's. It's like, you know, from a scientific. Like a scientific bible. To me, a lot of the. And I'm not saying it contains everything, right? Like, the mistake we make is we. We see a book like that, we think, oh, all of these predictions are already done. No, there are things there that haven't been predicted yet. Or we think this book contains Everything. There's no more thinking left to do. So I might not be any like Schrodinger, but there are things that I know that he did not know. So I can reason from that perspective. But I will say that one, there's this very small, like, you know, paragraph where he talks about how. And this is before sequencing, of course. Right. The way that you can interpret genes, there's only two. There's the genetic crosses, like Mendel did, that he talked about. And then there's microscopy. And then he, at some point, soon after, said the chromosomes are. They're definitely not static because some of the cells, they had swollen chromosomes. And I'm sure that that leads to, like, a, you know, different way in which they're read in the body and so on and so forth. And a lot of epigenetics, of course, being kind of also spatial as well as temporal force. I think that led me to realize that imaging, and also, like more advanced forms of imaging are probably the best way in which we're going to be able to reduce the observer effects and actually measure life. So if you think about it from the perspective of, say, your blood glucose monitors, they're becoming a thing now. And I mean, both my parents, they're both. My dad's a cardiac surgeon, my mom's a pediatric cardiologist. And doctors have a lot of stress, so they ended up getting type 2 diabetes. And what they have is a system where if they eat something and it's increasing their sugar immensely, then they know not to eat that specific thing because they have their freestyle Libra, and that's continuously telling them what's happening in their bodies. And that is kind of like a movie as well. But it's a movie where you are. You know, there are people who have autoimmune disorders. They completely avoid food as a whole because they went on a juice diet at some point and they stopped having irritable bowel syndrome. And I just wonder, maybe it's something very specific in your food, but you have no way of knowing at all. The best look into your body you have is your eye. We've not come up with anything better. And so I think that the point of calling it a camera is that even cameras are kind of very fit to the way your eye sees things. Meanwhile, if you have a camera that's more based on your first principles, understanding of matter and of cells, and uses, AI and machine learning, then you're able to basically just look at it not as red, green, blue, but as waves. And then when you reach that point, then you're able to basically understand things at a chemical specific level. And chemistry is something we understand way better than biology. Right. So I think the point of having a very, very good camera is that a camera does not, you know, it doesn't have a knife attached. It doesn't like, you know, the kind of. It affects what's being seen. Everything affects everything. But it does not stop it. It doesn't stop the process from happening. And then it being very, very good comes from the fact that you're looking at things from a chemistry perspective and then being able to correlate them with biological processes in a way that's, I guess, a more advanced version of a glucose monitor. So.
- [37:35]
B
Yeah, yeah. And what I like about that idea is the idea of like the lens you look through often determines what you see. Right. And for example, I'm a big fan of Bucky Fuller and he said that these things are often just the difference of being tuned in and not tuned in. And he used as an example the microscope. And he said before the microscope, we didn't know anything about microscopic light. And then the inventor was like, holy shit, there's a whole different world down there. And it takes us a long time to build in those insights. And I often think, wouldn't it be cool if we could give people glasses that would allow them to see the entire electromagnetic spectrum of light rather than what we see with just our eyes? That's why I've been a huge.
- [38:34]
C
The pit viper can see in thermal.
- [38:37]
B
That's right.
- [38:38]
C
Ir. And then the bee can see an ultraviolet. And it's just human beings. Why do we call it visible light? That part of the spectrum? Because we can see it. That's the only reason.
- [38:50]
B
Exactly. And that's a great jumping off point for or all we're missing. We tend to think that the visible light spectrum. Great example. Well, the visible light spectrum for human beings. Right. And it's very different for other living creatures, as you just pointed out. And so one of the reasons why I'm so excited about the current era is I think that we are gaining the tools, large language models, other AI models, the ability to make a better, for lack of a better word, camera that can interact with all of these other innovations as well, to open our apertures to be able to see much, much more and accomplish much, much more. You made the point earlier that we're really at the beginning and not the end. I could not emphatically agree with you more. I think that this idea that. Oh, yep, we know all there is to know about anything is such a crazy, crazy thing to say. I think that we know.
- [39:58]
C
So is saying like super intelligence will solve cancer. Okay, how will we reach there? How, how does even you don't know what cancer is? How will the super intelligence know what cancer is?
- [40:14]
B
Like, it's crazy. And it's like the meme from south park, right? Startup, get investors, then there's a blank at number three and then it goes bro down, right? So this idea that, I love that example too, right? It's like whenever I hear people going on about super intelligence, I know I'm listening to a marketer or somebody with something to sell because like of course, in the human mind, well, of course super intelligence will solve cancer. Really? How, how, how's that going to happen? And like we do not have a working definition that is testable. That's a testable hypothesis for human consciousness, right? Like there's a lot of competing ideas about it, but we do not have a generally accepted theory about why human beings are conscious. We have like no theories about qualia, right? Qualia is, you know, the smell of the rose or when you walk into a cedar closet, it brings you right back to your childhood. Or the one I love to use because people are familiar with it is the Pixar movie where the critic, ratatouille, the critic is sour and hateful and everything's bad and then they serve him the Ratatouille and he's instantly transported back to his childhood. So there are all these things, it's really easy to make these kind of bold, huge statements and they're appealing to people who are like, yeah, super intelligent is going to do that. Yeah, that's going to happen. Well, there's a lot of steps in between those. Which brings me back to your company. What are you hoping the first things that you're going to be able to work on, solve and then build on?
- [42:11]
C
I think some of that is things that I guess my lawyer has made it very clear that I should be a little bit more abstract about at this point, which is why I like to discuss it from an approach perspective. What I do aim to from a more high level sort of express, is that the reason why ChatGPT and large language models worked so well and why they were able to work on something like code specifically really well is very well understood. It is because all that information sits on the Internet. If it did not sit on the Internet already, if code was not something that a computer was so easily able to interpret, because that's Quite literally how you interact with a computer, then it may not be half as good at understanding code and being able to help with code or solve code. And we might find that there's much better frameworks for coding and AI because it's expensive from a compute perspective to use LLMs for that. But the reality is that the biggest flaw in the statement that ESI is going to solve science is that we don't have the data to give it for science. The barriers to data collection are so incredibly high that you have to kill the sample to measure it. That's where we are. This is, I mean, if I were an alien and I were told to, you know, come to Earth and this is what I saw, I would just think, how did you solve any disease at all? How have you done anything whatsoever? And it's a great question. And I think that the other thing is all of your greatest biologists are fundamentally also constrained to mice, right? Like, there's a lot of regulations that come into the picture. And as much as I respect the fda, I will say that the way that regulations and thinking in general works in medicine is very different from biology. You might think they're the same thing, they're fundamentally different. And I think that if you're able to create non invasive techniques to be able to dynamically measure disease states, or what I would like to call is life states, then you're finally entering a new era. And it's just the beginning. Like, you know, there's a lot to build on top of it where you even have any shot at an asi, you know, solving cancer. Right, Dallas? I mean, as someone who has worked on a lot of cancer data, you have one or two time points per patient in the cancer genome Atlas. If you have more, then they're still not very continuous and they often are not very whole because that kind of data is very expensive. And so I think that being able to start seeing biology from a first principles perspective, being able to reduce your barriers to data collection involves the use of something that does not need a biopsy, it does not need tagging, it does not need staining, and it kind of leaves something unperturbed. So I think that's what we're working on. And then the specifics of it are things that I guess, Jim, you will know before anyone else. And then of course, the world would, you know, find out soon after.
- [46:08]
B
So, yeah, that leads me to another question, which is the intersection of regulatory bodies who, let's face it, are populated by people who basically don't have very deep knowledge of the various sciences, et cetera. I have a friend who proposed the idea of setting up specific. His idea was for courts, but I think it's more broadly applicable. It could be done for regulatory bodies as well. The idea he had for courts was like in medicine, let's. Let's have people with deep both theoretical and practical knowledge in the matters that the regulators are trying to write regulations around. At least that would be an improvement from where we are now. What would you see as a good way for those that regulate the type of research that we are doing to refocus and understand that maybe they're doing more harm than good with a lot of their regulations that are promulgated on research in this particular area.
- [47:21]
C
As someone who's been speaking with the kind of FDA as well as people who are involved with it, you know, of course that's a big part of my job and to respect them. You know, even if I want to see reforms, I'm the kind of person who wants to do things as robustly as possible. From what I get from, you know, my interactions, and this is just my intuitive sort of sense, I think they want our job to be harder. I think they want to increase the complexity as much as possible so that once the clearance occurs, everyone is convinced that the high standards are met. And I don't think that that's an approach that will stand the test of time. One of the reasons why it's hard to have a biologist be a part of the FDA outside of the wing that deals with mice and non humans is that FDA is not interested in mechanisms of action. So this is the biggest thing that really shocks me. But FDA is only interested in efficacy and safety. The problem is that safety and efficacy tell you nothing about mechanisms of action. It's all statistical. So it's all about what results you get from a trial. There's very little foundational biology involved if you think about some of the most popular drugs in the market. And just to be clear to anyone listening, this is not to say that, you know, there's not like, there's not high standards. And I am not of the belief that everyone should just say no to any medication. I mean, both my parents are doctors. I definitely don't feel that way. But this is just to like, you know, try to have a more balanced opinion. If you think of SSRIs that are used for, you know, depression medication, if you look at even your skin care products that are prescribed, anything that you can think of, even Tylenol, we Don't know how these things act in the body. Again, you need a very good camera to fix that, by the way. But we don't know anything about how any of this works in the body. And all they're interested in is in this cohort you showed efficacy and this cohort you showed safety. Many times a lot of the medications that we use for one purpose were actually, you know, made for another purpose. So for example, retinol was, you know, made for more acne related concerns. And then people who were, I believe were making it, their hands started looking a lot younger. And that's how they realized that this is an anti aging sort of medication, minoxidil, which was for hypertension and you know, cardiac issues. Suddenly people started growing hair like crazy. So it's really important to remember that the FDA is more of like a health thing than biology thing. We don't use most medications approved by the FDA in our biology labs on zebrafish because there's just too many factors that we don't understand about how it's going to act inside the zebrafish. So I think that for that there's a much more frame shift change needed to even in the philosophy of the FDA for us to ever get to a point where it is able to, I guess, be willing to have any changes. And so with that said, I will fake them for at least ensuring the safety of human beings by not, you know, approving absolutely anything by, you know, as someone, someone who comes from a country where there's a lot of corruption in, you know, other ways. I'm grateful that you cannot just bribe the FDA to like, you know, get them to approve something. But I think that it's going to require a lot more than scientists to change how things are structured.
- [51:52]
B
So yeah, that's the ever political interaction with the sciences is a very difficult thing often to disambiguate and promulgate better regulations, better guidelines, et cetera. Because everything you said is true. The same is true of aspirin, right? I had a doctor once say to me, I don't know if this is correct or not, but I love the reference. He was like, yeah, if you put aspirin in front of the FDA today, they wouldn't approve it. And I'm like, wow, really? And he's like, yeah. And then I had an anesthesiologist tell me, don't even get me going on anesthesiology in terms of the various compounds and why they work. That's why I'm excited by efforts like yours that Understand this and understand that we need to build better processes, better cameras, to use that metaphor, to not just simply follow along the way it has been, because I think you're absolutely right, non invasive. Now that we have the tools that we can use non invasive techniques, it just seems to me like what a better way of looking at a lot of things, right?
- [53:12]
C
Yes.
- [53:13]
B
What would you like? Like if you had a wish list, what would be several non invasive technologies or innovations that could profoundly affect the way we understand things like diabetes, like a variety of the diseases that people struggle with on a daily basis.
- [53:37]
C
I'm very grateful because I'm probably one of the handful of people in the world who has deleted my wish list and added all of them into my to do list. And I think that it is the most incredible thing that's ever happened to me. There are some things though that I definitely am not, you know, I guess we are not as a company touching and I can definitely talk about those. The greatest thing or the greatest sort of challenge that we have for non invasives when it comes to cognition and thinking and neurodegenerative disorders is the skull. And there's, you know, I think Sam Altman is someone who got quite interested in like doing something similar to neuralink, just without the invasion. And that's fantastic. But there is really, unless it's a, it's first a measurement company and not like immediately going into trying to change how the brain works, it is going to not be able to do that many things at this very moment. The most important thing that I wish that, you know, we could understand better is the brain and, and how it works dynamically. It is shocking to me that a person has to go to, you know, a psychiatrist to check for, say bipolar disorder or ADHD or N number of diseases. And we are using DSM 5 to figure it out without doing a single PET scan, without doing. Because we don't know how to calibrate, how to, you know, kind of ensure that we, I guess to ensure that we have the right sort of, you know, look of things. Everything is fundamentally limited by the fact that there isn't an Illumina equivalent. That is like a platform that someone's created that's scalable, that's manufacturable, that every lab has, you know, to like look at the brain scan without also causing mutations or a possibility for cancer, for example, which X rays recently have come under fire because surgeons are beginning to see some tumors on one side of their brain. And that is, you decide that was more exposed to X rays over time as they did those scans for people. So, yeah, I think that that would be the most important thing that would make the most difference. But I do think that if neuralink takes that direction, because they're already adding something to the brain, they might be able to get us a little bit forward in understanding brain dynamics just by virtue of having that in the brain. Other than that, I think the main other thing that I would look for is ways to completely, and this is something we are struggling with, but have been able to actually overcome, which is different skin colors. Right. So if you're looking at anything non invasive, like the Apple Watch has come under fire for this, it doesn't work as well for certain skin colors. One of the most important things for our mission has been to ensure that everything works equally well for every skin color, because that's the bare minimum. Like, after that, you want to make it work for any organism. After that, you want to make it work for through the fur of a mouse. So, yeah, I think those are the two things that are incredibly important and have really made me realize the importance of physicists and hardware engineers and getting us to the next stage of, I guess, our future.
- [57:43]
B
So, yeah, I was thinking as I was listening to you. This is your first startup, right, that you're the founder of. How has that experience been where you're talking to potential investors who have varying levels of understanding in the sciences and in the particular way you want to pursue your goals? How's that gone for you? And what has surprised you the most about some of the reactions that you've received, both positive and negative?
- [58:21]
C
Oh, that's. That's a great question. I think that I'm the kind of a person who almost was made to start a company. I feel like I remember this one time when I was really concerned about making my next decision in life. I had an offer that was, you know, very lucrative in like, computational biology for a job. But I just, I was very kind of confused. And Gary Tan, who's the CEO Y Combinator, and I've known him through Twitter for a while, was gracious enough to get on call with me. And he just kept saying, you need to start a company. It's like very obvious. You just need an idea and you need a co founder. He said that three times. Get an idea, get a co founder, get an idea, get a co founder. And I just ended the call with, I've had an idea for three years, so I have an idea. And I just thought, if Gary Tan is telling me to start a company, that I better start a company. Right. So I. When I did, I was so. Every day has felt like a gift. I finally feel like I'm. I'm doing exactly what I needed to be doing. Everything is culminated in this moment. And the most rewarding part about it is that from a scientific and technical perspective, although I haven't talked about too much about what our techniques are, I have them. I have them. The minute that I started the company. I had been thinking of them for multiple years. And I think that the most. The biggest thing that I've felt is gratitude and energy and ability to write. It's almost like getting a better pen to write the future. You had a pen that was skipping, and then you're able to get this, like, you know, Mont Blanc, like, kind of fancy fountain pen that you're using to write the future. And autonomy, which has been something that I've. I've ended up doing better at than I realized because I didn't. I think I'm. I'm good at making decisions, but also making them in a measured way. So that's been great in terms of the things that surprised me and how it's been going. So I'll start with the latter. How it's been going has been a lot of, I guess, overdoing things, working a little too hard. Yeah, I know I sound like, you know, one of those people who's in a job interview and someone says, what is your negative trait? And they just say, oh, I work too hard. I'm like, that's not actually a negative trait. But. No, I mean, it. It's like I'm a person who's very obsessive, and I. I have been kind of like, you know, working a little too hard and learned balance. And that's. That's been interesting. But it's in terms of the things that shocked me. First of all, people are a lot more open to things even before they're fully made than I realize. I come from a science background where everything cited, everything already is done, done, and then you're like, citing it. But here I needed capital to be able to create something. It's not a science. It's an engineering thing. And people are very receptive to that. People understand that, and people are willing to support a mission by its team and by the rigor of the science involved. So that's been very fascinating. And I did not think that I. I guess funding would go so well so quickly. I thought there would be a lot of impossible tasks to get to that point. And it's really been really, really kind of rewarding experience to learn to have the confidence to put an idea out there. Not even having the citation in hand yet, but explaining how it is obvious that it's going to happen kind of a thing. The thing that that's been difficult has been how a lot of investors would ask, is there regulation involved? And then immediately it's like, okay, we can all talk further. And it doesn't make any sense to me because when you're thinking about sort of, you know, venture capital and you're thinking about ideas that are going to change the future, you cannot have a short, short term thinking because if something's easy to make, like you know, the next day, then someone else is going to make the same thing. But if there's, you know, IP involved, there's regulations involved, and it becomes a medium term thing, then it's more. It's like, you know, the idea is protected, the company is protected, and you're working in something so essential that no matter what, the demand is going to exist. So it was, it's really shocking to me how even venture capital can be risk averse, which I understand it's because a lot of people have been burned by, you know, like something not working out or someone being dishonest. But for people who are very honest and very fired up about an idea, I think that regulation should not be, you know, sort of, yes, a binary thing where if there's regulation involved, we're not interested, you know.
- [64:08]
B
For that very reason. We call what we do at o' Shaughnessy Ventures, Ed, Venture capital, which was one of the earlier definitions of venture capital. Because I agree completely with that notion that once something becomes like a big asset class like venture capital has become risk averse, things start to kick in. And to me it's kind of like that it's losing the whole point, right? From our perspective, the reason we're interested in you and your company and other companies that are quite speculative is because they are quite speculative, because how can you tell until somebody goes on a mission to discover that new thing? And another one of the earliest terms for venture capital, which I love, was Liberation Capital, because it was the idea that there are a lot of people with great ideas who just aren't going to fit into the corporate environment to the hedonic treadmill, who are, you know, very, very different than, you know, the average person who wants to go out and get a great job and whatnot. And so that's the very essence of what you're doing that intrigues us and why we invest it in your company knowing full well that if you fail in this, okay, what will we learn? Will some learning come out of it? I think absolutely yes. And so this whole idea that people who shy away or fear failure, I think failure is a ladder. It is the only way that you can climb and see further and see further and see further. Right. And I just don't get this inherent fear of failing. Like every, every successful person I know has had a long series of failures by some included. I even wrote a thing about it that I called Mistakes were made and yes, by me.
- [66:28]
C
Yes. I was going to say that, you know, the minute that you sort of had mentioned that if I fail, then there will be a lot of learning. I think that I have the right mindset in this, which I try to convey to everyone that I know. As someone who I don't know, I had a very sort of perfectionistic mindset going into college. Moved countries before I turned 18. I was like in a. In a whole new country and got misdiagnosed with a disease, needed a surgery, needed to take a year off. Covid happened. Lots of traumas happened in my life and I. The only thing that kept me going was I'm never going to regret anything. I did not know how to code coming into college. I ended up, you know, taing multiple grad level computer science classes. The only reason is because I got misdiagnosed, needed a year off. And I thought people will pity this that I had such a perfect, you know, like, understanding of what I wanted to do. And then, you know, this sad thing happened. But I don't want to regret a single thing in my life. That's the only ask I have of myself. So I ended up learning how to code. That's the only thing that felt right in my heart. And I coded the entire day. That's all I could do from a hospital bed. I would code the entire day and ended up making that my whole life in many ways. And if I go back, I would never change anything. I would want to go with that path. And, and I think that in many ways the values of a company are not defined by how things are. When things are going well, what is said on a website, they're defined by how the company acts in an impossible situation. And I don't think that there will be a failure because for that you would have to say, okay, this is a failure, we give up. Meanwhile, as you said, every single thing has, you know, a learning involved and there is always a way to create leverage out of any circumstance that you know or any hand that's dealt to a company, to a person. And the mission is so broad that if an engineering concept doesn't work, it's not like we're creating a drug for a specific kind of cancer. Right. That's something where you fail or you don't fail. Well, that's arguable too, but you can come up with something else. But when you're really, truly every day you wake up and you're blinded by your mission, then you're not married to a technique, whatever, it works best. You go with that. Our advisors are some of the smartest people in the world in our field. And if they say you're making a complete mistake and you genuinely care about your company, you're not going to keep going. You're never going to go to someone and say, hey, this is working, when you know it's not working because you don't care about where you are. You care about where you want to be. And as long as we have that going, I cannot come up with any reason why this company is going to fail. Personally, I don't think that I'm supposed to have any other attitude to it either.
- [70:24]
B
Like, you know, I do, and I like your because I identify with it. I'm a kind of a burn the ships kind of guy. When I start companies, I kind of burn all the other ships and go all in and get on that boat. And that can be seen from outside as being rather reckless and not having a plan B and whatnot. But I definitely think that I love your philosophy around what you did with coding when you were in the hospital. That resonates with the Nietzschean view of amour fate. Love your fate, and the idea that that which does not kill you makes you stronger. Also Nietzsche. But the thing that we found as a trait in founders that we really like and have succeeded is agility is the ability to recognize, you know what? This idea that we were trying doesn't work. But here's what we learned. Now let's pivot and try it this way. Right? We have an author because we have a book company too, Infinite Books, and we have an author who has a great line, which is Perfection is a 100% tax. So I was happy to hear you say that. You kind of cured your perfectionist ways. I was an obsessive perfectionist when I was younger too. If you can't get over that, you're not going to accomplish much, I think. But also the idea of obsession, that's another thing. We do a lot of studies on what makes an entrepreneur very attractive to us, and obsessiveness is definitely on that list.
- [72:15]
C
It's very easy to be obsessive when you're trying to approach disease states, right? Especially. And this is something actually, at some point, I wanted to mention in this podcast, which I brought up earlier, about disease and how I see it as an engineering problem. Right. I think that I'm an only child, and both my parents are extremely accomplished doctors. But my dad comes from a village. He didn't know English. At the age of five, he decided that he's going to be a cardiac surgeon. Specifically, he has seven degrees, including three honorary degrees now. But no one in their right mind could have seen him, out of all people, reaching that level. That did come, however, with me kind of seeing that, seeing both my parents be extremely busy all the time and feeling like it's my birthday, but someone's dying. So I'm not celebrating because my, my, my. Both my parents are busy. And in India, I mean, the number of patients you see is unbelievable. And a lot of people, I guess when I was growing up, saw all of that and thought that I was kind of, you know, someone they should pity because even though I have this sense of monetary security, my family is super busy. I don't, I don't agree. What I saw every day was miracles happen. My, my. My grandfather is 107, and he is one of the healthiest and happiest people I know. And he also lives in our house. And having my parents around has been very helpful because if he's ever feeling unwell, my mom is able to, you know, point that out before it gets too bad. And in total, my mom and dad combined have saved 50,000 lives. My dad has done tens of thousands of cardiac surgeries and gotten people out of circumstances that would basically mean a death sentence at another time in history. And, like, there's no question about it. And after seeing that every single day, sometimes being in the hospital, after going to school and seeing. And many times, you know, their failures as well, and a patient, you're able to see your parents, like, think through that and why that happened and use the. That to ensure that, you know, they can offer the best care possible. And after seeing those kinds of miracles for so long, I can't sit here and say that death is a given thing. I've seen people be saved from the mouth of death since I was born. And so I think that when you're working on something this meaningful and trying to approach it from a different angle. And you look around and you see that everyone's just creating drugs, they're creating therapeutics, but no one knows what they're treating. There is no failure or success at all involved. It's just data, it's just knowledge. And yeah, I think that that's been the biggest blessing of my life, is being able to see how meaningful biology is, being able to see how meaningful medicine is and seeing impossibilities and realizing that they're not impossible because one day you didn't even know that a disease existed. Right? So I think, yeah, I think it's the kind of thing where as long as I believe that I was destined to be working in this, and I want everyone to be working in this, I don't think that there's anything that I will ever worry about.
- [76:27]
B
That's wonderful to hear. I just absolutely have such admiration for people like you because the idea that we are even at the beginning of understanding, I just think that's one of the most poignant, poisonous ideas that can pollute a mind, right? Like that, that. Oh, no, no. We know all there is to know about and fill in the blank. Right? Especially in, in much more complicated fields like the one you're tackling. But like, you know, if, if, if we had a time machine, right? And we could go back, call it, let's not even go back too far. Let's go back 400 years and we could collect like the smartest, most learned people in the world. Guess what? We're going to find almost everything they spouting and saying was wrong. Right? And it's so weird to me that we can understand it historically, but we can't understand it for ourselves. Right? Like, imagine, let's go forward 500 years instead of back 500 years. I mean, maybe, maybe they're going to look at us and think, what a bunch of barbarians. How could they have ever done like that? Like your point about, yeah, you're killing the cell to study it. And so I'm very motivated by projects and companies and missions like yours because I love seeing and helping where I can, people who, who have that attitude about things, your attitude, which is, come on, we're just starting in our understanding of this. We're at the starting line here. And so I find it incredibly exciting. And we are delighted to be part of your adventure here. Well, I'm getting the. I have an electronic. You know, how they give the hook to people on a stage. And so I can't believe that We've already been talking for an hour and a half. But before we go, I have just a couple other questions. The other thing that's remarkable about you, and I think you did a Twitter thread on this, is you moved here from India. And that was another thing, by the way, when we were deciding that we were going to invest in you. There's a fun idea that's mostly apocryphal, I think, but there might be something there which is there's a book called the Hypomanic why America Is the Way It Is. And the book makes the point that, hey, people who were the original people, not, not Native Americans, but the people who came here, did they share any characteristics that maybe weren't typical of people from the country they came from? Well, yeah, they were willing to get rid of, leave their family and friends, leave the world that they were on, that they knew well, and come to an uncertain future to having to make a whole new group of acquaintances and friends. In other words, these people maybe were quite a bit different in the selection sample than the people who stayed at home. What was your biggest, and I know you did a thread on this, but like, when, when you came here to America, what was the, what were, what were the biggest surprises for you in the country?
- [80:02]
C
So I was very lucky to be able to come to America by going to Penn. And even after coming to America, I will say that I had the option of comfort, which would be frankly, like, doing what, like the force of nature at like these Ivy League universities is go do a consulting job, just go and become a consultant. But luckily, because I also have some, I guess, like neurodivergence and I just couldn't, cannot do things that aren't exciting to me. So I ended up becoming more and more technical. And when I first came here, I was worried that I'm going to be treated differently because I'm from another place. But what I realized is that when you're involved in sciences and technology and just intellectual things, then the most beautiful part about it is that people forget who they are talking to, who they are themselves, because you're talking about something a little higher. And I frankly have never experienced any thing overtly kind of dismissive of me, not even once. The only thing that I think I experienced a little more was a different way that some peers would look at me as a woman in STEM as compared to a man stem. But like, I guess some of that is I'm benefited from the fact that a lot of stem there's a lot of Indian people who are interested in stem. But even outside of that, I think everyone's very objective and interested and, you know, productive things. That, that's what I noticed. So I think that I was pleasantly surprised by the fact that there was. It's almost like the culture of America to not care about your background, but care about, you know, things like for example, part of the Constitution is that religion is not governed by the country, right? That doesn't mean you cannot be religious. That actually means that you can be freely religious and however you want to be religious. And that is none of the business of the government. So if you start a country with that mindset, then you think, oh my God, the church was everything there was. So what are you going to be thinking about as a country? It ends up being ideas, it ends up being the people themselves. That's like absolutely beautiful part of America. And I think it was hard especially, I guess it's just like I was very young, you know, and I thought I knew everything, as every 18 year old thinks. And so there were lots of learning experiences, lots of, I guess, traumas like needing a surgery and all these things. And. But the most important part of it was that I, I was able to come out of them. And in America you're actually very much. If you fail in America, then that is part of being American or that's part of being in America. And that's a unique thing about America is that as a country it's so open to failure because that's how the greatest stories are written. Finally, I would say that I realized that I can not rely on anything outside of myself in America. But not in a bad way. In a way that's like this country is accepting of all the crazy ideas, right? It's accepting of all the wildest people and wildest dreams. But at the same time it requires your 100% focus on your mission, on your goals. In America, there's not as much of a family focus as there is a focus on, say, working with people. There's an individualistic mindset, but that's up until you reach something you're building. When you want to build something, you're going to find people who are going to put that above anything else. And I think that's what makes America so productive. That's what makes America so beautiful. And it is something to preserve, is the privilege of being able to, in a very undistracted way, just give everything away and work on exercising your freedom to create the future. That's the way I would put it.
- [84:50]
B
Lovely. And I've always often said to really understand America is what the words you use, you need to understand that America is above all else, an idea first. And most of the countries of the rest of the world didn't start out as ideas. Right. They started out as this monarch or that monarch and this church or that church. And like, the idea of America is really what makes it special, in my opinion. And it's definitely an idea that is worth preserving and expanding and all of the above. Well, this has been a tremendous amount of fun for me. I hope it has been for you. If you've listened to the podcast, you know that we have a final question which is we are going to make you the empress of the world. You can't kill anyone, you can't put anyone in a re education camp, but what you can do is we're going to hand you a magical microphone and you can say two things into it. That the entire population of the world is going to wake up whenever their tomorrow is and they're going to say, you know what, I just had two of the best ideas ever. And unlike all those other times, I'm going to actually act on these two ideas today. What are you going to incept the world with?
- [86:16]
C
So I think that. So just a clarifying question that like this would be basically the same idea everyone's getting and they would basically be working on it. So you're kind of controlling this thought that's put in someone's head and then they are convinced by it and they're.
- [86:36]
B
Like building, acting from and acting on it.
- [86:39]
C
Yeah, I think that the first thing that I would tell everyone to do is to. Oh man, there's too many. I have in my head. And I've seen the section that I wanted to have it like extempore. But the first thing I guess would be to connect with your heart. Think that you have the mic that I have and tell yourself what you would say into the mic is a change that you want to see in the world and implemented yourself. Imagine you are the one having the mic. Because the fact of the matter is that I'm as much of a human being as anyone else. But being able to give someone the power to realize that their ideas matter, that like I would tell them that whatever you have in mind is going to come true. And like, you know, that would be the first thing I would say is like, you know it's coming true. So what are you going to do now? And I guarantee you 100 out of 100 times, it's going to actually come true. Because intentionality, even from a logical perspective, is a big thing. The second thing I would say is that if there is a war where you are, then think of the children on the other side of the border.
- [88:11]
B
I love both of those and the first one's very clever because what a great concept. You're incepting them, incepting themselves. I absolutely love that. I absolutely love that. And yeah, thinking about that, there are people on the other side of any war and we often try to dehumanize them and other them and we're all humans and they probably love their kids too, and they probably want their kids to be safe too. So I think that's.
- [88:46]
C
The kids. Did not. Did not ever make an aggression towards the other side.
- [88:52]
B
Yeah, yeah, exactly. I love. I love both of those people. Looking for more information on you can find you on Twitter, but does the company have a website or is that a working front?
- [89:04]
C
It's kind of like a coming soon section. If you're looking for more kind of official updates, then we have at Presley Genetic Pure E C I G E N E T I C for the. Going to be uploading the talk from the World Biotech Congress coming up in Singapore soon and probably going to be, you know, kind of finally revealing the website after. And the website's pressing genetics.com and then I also have a LinkedIn and yeah, we have a. We have a blog. We. We're going to be adding things to it that's part of the website. But I think that you're going to find more than enough things on my Twitter. I like Twitter a lot, so you don't have to worry too much outside of that.
- [89:50]
B
Terrific. Well, we're delighted to be collaborating with you on this. Very excited to watch you and very excited to watch what you make happen. We are along for the ride and think you're going to do fantastic things.
- [90:05]
C
I think that I'm going to ensure that you, like, are going to be the happiest person. Yeah. So I think that, yeah, I have faith. And not just faith, like I know the power of a human being to make something happen. So I think it's gonna happen. But. All right. Thank you so much for this opportunity. It's been beyond incredible. Sa.