The Brutal Truth About Biotech: Why $2B Per Drug Is Killing Innovation

Summary

---

Episode Overview

Title: The Brutal Truth About Biotech: Why $2B Per Drug Is Killing Innovation
Podcast: a16z Podcast
Date: November 14, 2025
Host: Andreessen Horowitz (a16z)
Guests:

• Lada Newsuna, Founder of General Control, biotech entrepreneur and author
• Elliot Hirshberg, Partner at Amplify, biotech investor

Main Theme:
This episode dissects the mounting challenges in biotech innovation, particularly the skyrocketing costs and inefficiencies intrinsic to modern drug development. Despite breakthroughs in biological science and AI, regulation, industry structure, and global competition are stifling progress. The conversation probes why these misalignments persist, what China’s rapid rise means for the U.S., the promise (and limits) of AI, and why the next generation of biotech giants may look nothing like Genentech or Amgen.

---

Key Discussion Points & Insights

1. The State of Biotech in 2025

• Market Disconnect:

  • Huge advances in biotechnology (AI-designed drugs, virtual cells) coexist with economic malaise—over 20% of public biotechs trade below cash, early-stage funding is near historic lows, and few IPOs have launched in the past year.
  • Lada Newsuna: “The science continues to get better and the state of things continues to get worse.” [07:01]

• Structural Downturn:

  • Elliot Hirshberg: “There’s never been a bigger disconnect… Our last actual boom cycle was Covid. Now, we’re sitting on the other side of that.” [04:52]

---

2. Regulation & Industry Structure

• Ever-Tightening Regulatory Regime:

  • The only major period where U.S. drug approval got easier: the AIDS crisis of the ’80s, driven by activist pressure.
  • Increase in safety and efficacy standards (since thalidomide tragedy) has made clinical trials increasingly complex and expensive.

• Entrenchment of Middlemen:

  • Dominance of clinical research organizations (CROs) creates inertia; they have little incentive to cut costs or speed, even when the FDA modernizes trials or allows electronic data.
  • Elliot Hirshberg: “When the FDA says we want to modernize standards… you have to get CROs to adopt [new tools]. And they aren’t incentivized to.” [10:08]

• Not Just a Regulatory Problem:

  • Structural and cultural inertia is equally at fault. “It’s a composite of all three: regulation, culture, and tech implementation.” [11:26, Elliot]

---

3. China's Rise as a Biotech Power

• Regulatory & Speed Advantages:

  • China overhauled trial approval: “Implied approval” (INDs approved unless proactively held) speeds up trials drastically vs US’s proactive approval.
  • Parallelized reviews and effective use of investigator-initiated trials give China a 5-6x speed advantage for new modalities.
  • Lada Newsuna: “They are now leading in B-book RT, gene editing, gene therapy… due to this ability to do investigator-initiated trials.” [17:05]

• Strategic Threat:

  • Most U.S.-born innovations are first trialed in Australia or Asia, not the U.S.: “We’ve just come to accept… everyone goes [abroad] to do their studies because the things we invent here, we can’t actually test here.” [09:10, Elliot]
  • Third-player disruption: Traditional U.S. “invent, others invest/acquire” equilibrium undermined.

• Shorter Shelf-Life for Innovation:

  • Pressure to keep new inventions secret to avoid being scooped:
    • Lada Newsuna: “Before they were able to initiate their clinical trials, Chinese biotech… beat them to the clinic…” [22:17]

---

4. Can AI Fix Drug Development?

• AI Is Inevitable—But Limited:

  • Lada: “Everyone will be using AI in biotech five years from now. But can it make $2.5B per drug into $500M? That’s the question.” [24:16]
  • Most AI advances cut costs at the preclinical/toxicity stage—where least of the capital is actually spent.
  • Real bottleneck: human efficacy/safety; clinical failure rates in Phase 2 remain highest and poorly predicted.

• What AI Can Unlock:

  • Elliot: “The answer is probably yes—AI is a pretty important new tool… but the challenge of Phase 2 failure is a readout on how little we understand biology.” [26:09]
  • AI’s largest promise: creation of drugs that were previously impossible; platform as product (e.g. personalized mRNA vaccines).
  • “There are medicines we just genuinely can’t get to with our existing discovery technologies.” [29:13, Elliot]

---

5. The $2B Question: Why Are Costs So High?

• Structural & Incentive Issues:
  • Cost per patient has ballooned to $500,000; there’s no law of physics that requires it.
  • Clinical research middlemen, slow regulatory updating, and “cultural assumption that these things are expensive” perpetuate the problem.
  • Elliot: “It should almost be a stat that the FDA cares about… There is no law of physics that requires it to be $500,000.” [45:19]

---

6. Blockbuster Drugs & Where the Next Trillion Dollars Lie

• GLP-1s as a Case Study:

  • Their success hinged on taking a huge contrarian bet that obesity was a real market and that patients would use injectables.
  • Lada: “It was a big contrarian take on what indication to pursue… Biology is one of the areas where you don’t want to be contrarian about the target, but maybe about how you treat it.” [54:46]

• Aging & Longevity as the Big Prize:

  • Incentive misalignment: U.S. insurance (Medicare after 65) leaves no one motivated to pay for costly preventive drugs early.
  • “I think we would be able to treat aging before we understand how to measure it, what it is, or why it happens.” [40:29, Lada]
  • Medicare’s refusal to cover GLP-1s for obesity: “So can we cover GLP-1s for aging diseases? Not super clear.” [36:16, Lada]

• Need for Novel Incentives:

  • Orphan Drug Act-style incentives, but for high-failure, high-impact chronic diseases, including aging.
  • “If 50% of drugs are approved for rare diseases… How about every disease that people actually die from?” [49:19, Lada]

---

7. What the Next Iconic Biotech Company Will Look Like

• New Modalities, New Infrastructures:

  • Biotech’s future “iconic” companies will come from unlocking new platforms/modalities (gene editing, epigenetic editing, information-rich delivery, etc.).
  • “If you look at the history, there’s enormous value in unlocking new types of medicines… I’m really excited for platforms where the platform is the product.” [56:59, Elliot; 32:53]

• Possibility of ‘Hyperscalers’ in Biotech:

  • Will an infrastructure company akin to Nvidia or Illumina emerge in biotech?
  • “At one point Illumina sold zero of next-gen sequencing. That turned into $10B of sales…” [59:17, Elliot]

---

Notable Quotes & Memorable Moments

On the core problem:

• Lada Newsuna:
  “The science continues to get better and the state of things continues to get worse.” [07:01]

On China’s threat:

• Elliot Hirshberg:
  “We’ve just come to accept that everyone goes to Australia, everyone goes to Asia to do their studies, because the things that we invent here, we can’t actually first test here.” [09:10]

On the cultural, structural, and regulatory deadlock:

• Elliot Hirshberg:
  “It’s a composite of all three.” [11:26]

On keeping innovation secret:

• Lada Newsuna:
  “…they developed the asset, were taking it to the clinic. And before they were able to initiate their clinical trials, Chinese biotech with the same identical mechanism beat them to the clinic and launched trials not only in China, but also in the US.” [22:17]

On AI:

• Lada Newsuna:
  “Everyone will be using AI in biotech industry five years from now. Can it make it 4x more efficient in terms of timeline? That’s the question.” [24:16]

On why costs skyrocket:

• Elliot Hirshberg:
  “There is no law of physics that requires it to be $500,000 in terms of complexity and cost to dose a patient in a trial.” [45:19]

On blockbusters:

• Lada Newsuna:
  “Biology is one of the areas where you really don’t want to be contrarian. You don’t want to be the only company pursuing some obscure mechanism. Usually you want to have some literature validation, but… it was either a big modality differentiator, or big contrarian take on what indication to pursue.” [54:46]

On aging:

• Lada Newsuna:
  “I think we would be able to treat aging before we understand how to measure it, what it is, or why it happens.” [40:29]

---

Timestamps for Key Segments

• [02:20-06:07] — Market Pulse: Biotech’s Economic & Scientific State
• [07:01-11:42] — Why Drug Development is So Hard: Regulation, Structure, and Culture
• [11:48-17:41] — China & the New Geopolitics of Biotech
• [17:41-22:01] — U.S. Innovation vs. Global Competition: Shrinking Shelf Life
• [23:31-31:34] — AI: Potential and Practical Limits in Drug Discovery
• [34:01-39:45] — Blockbusters, GLP-1s, and the Longevity/Aging Opportunity
• [41:43-44:55] — “The Aging Stack”: Preventing Disease and Increasing Lifespan
• [45:19-49:54] — Magic Wands: How Would They Fix the Industry?
• [52:46-56:24] — What Makes a Blockbuster Drug & the Modality Thesis
• [56:24-61:22] — Predicting the Next Wave: Infrastructure vs. Modality Giants

---

Conclusion

Biotech stands at a pivotal crossroads: scientific discovery and technological tools have never been more powerful, yet escalating costs, industry structure, regulation, and global competition threaten innovation’s very economics. AI is reshaping what’s possible, but cannot singlehandedly make $2B-per-drug development obsolete—unless deeper incentives, regulatory change, and platform breakthroughs emerge. The next trillion-dollar companies will likely be modality-driven or infrastructure-focused, but their success will require not just invention—but reinvention—of the industry’s core processes.

---

Transcript

[Lada Newsuna]

Since the birth of this industry, we only had increasing regulation over time. I think there was like only one time in history of biotech where we made it easier to develop an appropriate drug.

[Elliot Hirshberg]

So when Georgiankopoulos started Regeneron it cost about $10,000 per patient in trial that's ballooned to $500,000. There is no law of physics that requires it to be $500,000 in terms of complexity and cost to dose a patient in a trial.

[Lada Newsuna]

Everyone will be using AI in biotech industry five years from now. Can it take two half billion dollars to approve a drug and make it into $500 million? Can it make it like 4x more efficient in terms of Thailand? To answer that question, we really should go back and look where most of that money is spent right now.

[Elliot Hirshberg]

We had this enormous wave of excess and now we're sitting on the other side of that. We have an enormous amount of EV negative public companies. There was a stretch of seven to eight months where there were no biotech IPOs. And so I'm really excited about that sort of opportunity to make things that are just net new in the industry. I think that's where you have to go to really keep winning the biotech paradox. 1/5 of public biotech companies are trading below their cash balances. Sea browns have hit record lows. The industry spends 2 billion per approved drug and that number keeps climbing. And yet we're designing antibodies from scratch with AI we have drugs that are bending the curve on aging. The science has never been better. So why is the business of biotech collapsing while the technology is exploding? Today's guests have spent years studying this contradiction. Lada Newsuna founded General Control, a startup tackling aging after writing the definitive analysis analysis of why there are no trillion dollar biotechs. Elliot Hirshberg is a partner at Amplify, betting on the next wave of platform companies while watching American biotech companies flee to China and Australia just to run their first trials. Their diagnosis. We're competing on the wrong axis. China wins on speed and cost. The FDA adds friction while innovation accelerates. And the entire industry is structured around an equilibrium that no longer exists. But there's a path forward if we're willing to invent our way out. We cover why regulation might not be the real problem. What geopolit MP1's reveal about blockbuster drugs. Whether AI can actually fix drug development. And why the next iconic biotech companies will look nothing like Genentech. This is the state of an industry at an inflection point. Let's get into it.

[Host (a16z Podcast Host)]

Welcome Lada, welcome Elliot to the A6 and Z podcast. Very excited to have you here and I'm very excited to have this conversation because where I'd love to start is I want to talk about all things biotechnology and let's take a quick pulse check on the state of biotechnology as it stands today in 2025. So question one for both of you is how do you see the state of the industry as it stands today? And how do you see the state of the science as it stands today?

[Lada Newsuna]

Yeah, if you AI bio deal society. It's been quite a few interesting years in biotech. I mean earlier this year we had something like 1/5 of public buy tax trading at or below their cash balances. They had like record low number of buy tax rates in their seed rounds. Platform dream kind of judged more harshly and sort of if you take a step back and look at the bigger picture of it all and ask yourself like, oh, has it ever been different? It seems like this state has been ongoing for quite some time. So we have Eram's law, which is Morris laws felt backwards. We now spend more than $2 billion per approved drug. We have a rise of Chinese bioc seen that is threatening the state of yes, early stage biotech companies. And I guess the question is like did we expect it to be different? Because approving drugs is really hard. It's probably one of the hardest areas of deep tech broadly because it's takes not only on engineering risk but also on scientific risk. And it does seem like the biotech industry started on a more positive note a few decades ago. I mean we had Genentech, Amgen, IPOs, their investors making first huge exits more so than intact back then. And we had human genome projects that sort of promised that all the biotech will become precision medicine and will develop medicines as tailored to one patient. And yeah, it does seem like it led us to a slightly different ending. I mean I hope it's not the ending and I hope there are some positive things that we can find in it all. But in many private conversations during this past two years, mood has essentially been like will this industry ever recover?

[Host (a16z Podcast Host)]

That's okay. So you a lot of reason to be pessimistic.

[Lada Newsuna]

Yes.

[Host (a16z Podcast Host)]

Okay.

[Lada Newsuna]

At least as of now.

[Host (a16z Podcast Host)]

As of now, as of today, I want to hear Elliot, your take.

[Elliot Hirshberg]

I think there's never been a bigger disconnect between both sides of the market. Right. So as Lotto was saying, we had this enormous wave of excess. Our last actual boom cycle in this industry was Covid, you had enormous amount of value creation and success and now we're sitting on the other side of that and we're sort of objectively in a downturn. We have, as lotta point out, an enormous amount of EV negative public companies. That's starting to change and resolve a little bit. But there was a stretch of seven to eight months where there were no biotech IPOs. There's a log jam that goes from the public markets to the growth investors to later stage investors to early stage investors. That just changes milestones and makes everything super, super hard at the exact same time. There's never been a better point to actually see the progress of technology. Right? So you have people developing zero shot antibody design in labs, you have incredible virtual cell projects and enormous amount of sort of translational potential at the early stage, which I think is actually just for an investor, for a founder, an incredibly exciting time to be building a new company because there's this huge disconnect in the market between sort of publics and what's happening earlier. Sort of a tale of two worlds.

[Host (a16z Podcast Host)]

Well, what I was going to say is I think what's interesting is number one, there are a couple of reasons to be optimistic today, right? In terms of the market at least showing some of the famous green shoots of optimism, right. Some IPO is happening or these people are preparing to file some very successful M&As. The Biotech Index is above, starting to get well above the famous hundred dollar mark for the xbi. So there's reason to be optimistic. I think the fundamental question is what bridges that disconnect between all of the advance and promise we're seeing on the technology side and some of the fundamental laws of physics of the industry that have resulted in this not being a particularly effective industry to invest in over the course of the last several years. You wrote a great post. Where are all the trillion dollar biotechs? What's your diagnosis of the situation? What is it about the fundamentals of the industry that make it so challenging economically?

[Lada Newsuna]

Yeah, I mean since the birth of this industry we only had increasing regulation over time. I think there was like only one time in history of biotech where we made easier to develop inappropriate drugs. And that was during the AIDS crisis where AIDS patients were just laying outside of FDA and demanding drugs to be approved on a more accelerated timeline. And FDA did make a big change back then that allowed for certain accelerated approvals. But since the birth of the industry, maybe for good reasons, we were always making it only harder to develop new drugs. All while the science was improving over time. I mean our high throughput screens for new small molecules and antibodies are like billion times more efficient than they were 20 years ago. And what Elliot said really resonates because it feels like the science continues to get better and the state of things continues to get worse. And I think a lot of it is downstream of regulation. FDA just in history of regulation in general, like the way FDA started to crack down on drug development approval process is through like huge strategy. I think it was the drug thalidomide that pregnant women were taking that led to number of deformities in kids that were being born from those pregnant women. And since then FDA started to require not just safety but also efficacy in the approval process. And yeah, whoever would come to FDA to deregulate this process would have to take on like the way, enormous personal risk because regulation is a tension between safety and efficacy. And if we deregulate process, we would have to take on some type of safety risk.

[Elliot Hirshberg]

I think it's interesting, there's a hundred percent a growth of regulation, There's a bunch of low hanging fruit that would be just substantially better for starting trials. Right. So we have three companies in the next 12 to 18 months that will be starting first in human trials. Guess how many are actually doing their first studies in the United States?

[Host (a16z Podcast Host)]

When you say we, you mean at Amplify? At amplify? Yeah. Oh, none.

[Elliot Hirshberg]

Zero. Yeah. Right. And so we've just come to accept the fact that everyone goes to Australia, everyone goes to Asia to do their studies, because the things that we invent here, we can't actually first test here. So there is sort of a regulatory barrier. But I was writing about this business vial that was trying to innovate on a clinical research organization. And one thing that I sort of learned in terms of the machinery of translating regulatory innovation into actually cheaper trials. So let's say that there's a change, like whatever variable we think about for trying to actually decrease the costs of trials, how does that get implemented? So it actually turns out that there's been this enormous consolidation of the clinical research organization market that's come down to about a dozen providers who have each done roughly 40 acquisitions across 30 years to really consolidate into these large clinical outsourced providers that most people rely on. And so when the FDA says we actually want to modernize the standards for trials and have electronic tablets, you actually have to get the clinical research organizations to adopt those tools and technologies. And they aren't, they aren't incentivized to. Right. And so there is sort of a structure to the actual process of executing on the trials that lags sort of a lagging indicator from the changes in regulatory itself. So it's sort of a two pronged beast when you think about the cost of clinical development. It's actually sort of what the rule of law is and like what you can do and then also just all of the sort of industry entrenchment of what we are doing. And so I think there are some ways for people to just do things a lot faster, even within the bounds of the law than we're sort of used to paying for expecting. Which I think is in part just like a, a cultural component of biotech that we just assume that these things are expensive and take a lot of time.

[Host (a16z Podcast Host)]

So that argument would be that the, the challenge is not technological, that in some level the challenge may not even be the regulatory bodies yet. It might be something structural, something incentive based, where that the way the industry is structured, you have various parties, in this case the groups that, you know, help run the clinical trials that may or may not be incented to be more efficient. Is that the argument?

[Elliot Hirshberg]

Yeah, that's right. So like if you were to break it down into cultural tech solutions in terms of just implementations and regulatory, you'd have to sort of assign some, you know, percentage at east. And I think it is a composite of all three.

[Host (a16z Podcast Host)]

Okay, so now let's add to the mix here. Let's add to the soup the China question.

[Elliot Hirshberg]

Yeah.

[Host (a16z Podcast Host)]

So for folks that may not spend all their time thinking about biotech, what is going on in China as it relates to the biotechnology industry? What do we see as the impact that is having already and may have in the longer term to the US based biotechnology industry?

[Elliot Hirshberg]

So I think it's worth just backing up and saying, you know, how is the bio industry, biotech industry set up in the first place? How does this actually work? So at the very outset in about the 19th century, there were chemical companies that decided to get into manufacturing chemical drugs. Right. So these were actually dye manufacturers and making dyes for, for, for textiles. And they decided to take their sort of chemical manufacturing and distribution and apply it to making drugs.

[Host (a16z Podcast Host)]

You're talking about Germans.

[Elliot Hirshberg]

That's right. And the first drugs were incredibly crude pharmacology. Right. So this was heroin, this was cocaine, this was morphine, Higher retention than dyestuffs. Right. You know, like that, that's a pretty interesting business. But obviously it got a lot more sophisticated and specific over time. So these groups like Merck you know, in the 30s they set up vertically integrated research labs. So they're in the business of manufacturing and distributing their medicines and then also doing internal research to make new products. And then the FDA comes along, writes a lot of these top pharma companies predate the FDA and modern clinical development is formed. And so there's a three partite component for all these businesses where there is manufacturing, commercialization and distribution, there is internal research and then there's trials and clinical development. What happened is that as Lada alluded to, there's this eroom's law in the industry where it's just gotten exponentially less efficient to do the internal research and clinical development. And so it literally became the case that it was irr negative to actually do internal research. And so these pharma companies divested their internal research and clinical development out. This is the birth of these clinical research organizations and outsourced organizations in the first place. And the origin of drug discovery startups and in biotechs is that we are the lunatics that take on that irr negative business and say that we're in the business of making these new hits that could ultimately realistically get bought by pharma companies and become their next armamentarium of drugs. So that's kind of the setup, like how biotech works, right? These companies divested their R and D, biotech companies are doing that research. And what happened is that we're all doing that research with the same discovery technologies, right? So I'd argue that beyond the modernization of small molecule discovery, the growth of biotech and recombinant DNA technology, we haven't had, you know, in, in subsequent modalities, you know, we haven't had these huge changes in the fact that people have internal technologies that the rest of the industry isn't using. And so like any other technology, when it's becoming commoditized, you can compete on speed and cost. And this is where China sort of enters the story, right? So China has enormous speed advantages in terms of regulation for starting and running human trials, and enormous cost advantages in terms of the labor and the sort of work ethic and speed and volume of people that can be put together at these projects. And so what's happening is in this sort of loose social contract between big pharma and biotech startups, which are the ones supplying the drugs, biotech startups now make two thirds of the drugs that go to market. We have this sort of geographic arbitrage of where on speed and cost China can enter the equation and compete for these types of ideas to deliver the medicines.

[Lada Newsuna]

Yeah, I think what's interesting is China didn't start in this place 10 years ago. 10 years ago no one was talking about going and running their trials in China. In fact they were more regulated 10 years ago than the US is now. And what really happened is several ways of deregulation that probably about the current modern clinical trial infrastructure that everyone goes to Shanghai for. And some of the things that they implemented were the implied approval which is when you file your IND, unless they issue a proactive hold on your IND, it will be default approved in 30 days. US has the opposite model where you have to proactively approve every IND document that comes to fda. They also parallelize the review of different components of that ind. So you can review CMC section, you can review clinical trial design all in parallel, while in the. Yes, you have to review them in stages. I think what's even more interesting is this whole model of investigator initiated trials which is actually what most people go to China for. The actual CFDA process is it's more efficient than in the us, But I don't know if it's more efficient than just running trials in New Zealand, Australia. With investigator initiated trials your review timelines are cut 5 to 6x. It's very fast process and it's really specific to new modalities, high risk indications, cell engine therapy, and that's what everyone goes to China for. I think the mod of people used to view China as like a need to buy a printer where they print medicines that would already otherwise exist in the us. I think it's somewhat outdated view. They are now leading in B book rt, they are leading in gene editing and gene therapy and partially due to this ability to do those investigator initiated trials.

[Host (a16z Podcast Host)]

Okay, so given that that's a reality today, what does that imply for the long term future of the US biotech industry? Right, because you can make the argument that if we're competing on scale, speed, cost and there's still a lot of great innovation happening here in the US at some point it becomes difficult to fund that innovation. Here we talk about things being IRR negative, it becomes increasingly difficult to fund that innovation here if we know it's going to get outcompeted over the longer term from China. So does our industry get hollowed out?

[Elliot Hirshberg]

Does no? I think, I think the answer is somewhat simple. I think we have to invent stuff. So there's this really good China analyst named Dan Wang who just wrote a really good book on the whole structure between China and the United States right now. And the one sentence meme version is that China is an engineering state and America is a lawyer state. And I think that's simplistic. Right. That's not Dan's full argument, but we forget that we're also an incredible inventor state. Right. So some of our founding fathers, we have Benjamin Franklin as one of the US's founding fathers. Right. We have the American research universities that are the envy of the rest of the world. We're incredible at going from zero to one. And so I think that to compete on this, if you're talking about something where it's fast followers and sort of a specific arbitrage opportunity that's super challenging in terms of speed and cost, if you're talking about inventing totally new modalities and sort of growing the pie things on the scale of the recombinant DNA revolution, which is a fundamentally US thing, the birth of immunotherapy, which is in Texas. Right. You know, like these are these types of things that I think get us out of it, where we have to just invent our way and actually change what's possible. With biotech, I think when you get those big unlocks, that's when you start to really deliver value. So it does ship. The risk profile though, where I think that fundamentally, like part of where you go is really pushing the boundaries of new modalities. I spent a lot of time with Michael Fishback, incredible scientists at Stanford. We're always talking about what's the next big interesting set of modalities, what's the new interesting mechanism in biology. And so I think that risk profile shifts and like, you know, at amplify, that's what we always think about those technical founders. Right. Because it starts to be the case that, you know, it's like the regenerons of the past. Right. Leonard Schaefer and Georgian Copulist, these scientists that are actually sort of going to tell us where the future is. Yeah.

[Host (a16z Podcast Host)]

I do wonder though, to what extent like I look, I think it's a very compelling argument, obviously very aligned with that. The counter argument to that would be that something you said a few minutes ago, there was this nice equilibrium that the industry has had for decades, which is, you know, US biotech invests, sorry, invents and global biopharma invests. Right. They in license it, they acquire it, they partner with it.

[Elliot Hirshberg]

Right.

[Host (a16z Podcast Host)]

That equilibrium basically meant that the inventions that come out of biotech had time to develop, but now you have a third player in the form of China that could disrupt that equilibrium meaningfully. So yes, we can invent the next great modality, but we have to implement it faster too. So effectively the shelf life of an innovation has gotten far shorter before we deal with competition.

[Elliot Hirshberg]

Talked about this a little bit, right. Where it sort of, it changes one of the dynamics, which is like, of secrecy in the industry is like secrets become more important. Is like when you want that longer time horizon to actually invent something, you probably need to keep it a little bit closer to the chest initially. I do think that there's some nuance in terms of how we think about regulation for this. Right. It's probably not biosecure, where you are totally trying to restrict relationships and transactions between the US and China, because that's just sort of net negative. But if there's, you know, really direct, fast followers, you know, and like you're saying that sort of half life on an initial invention we might need to rethink like what that actually, like how to extend that horizon for inventions.

[Lada Newsuna]

Yeah. And sort of to push back. With one example, I keep thinking about this. Professor Irvin Weissman, who is a legendary sort of cancer biologist and stem cell biologist from Stanford, launched a few companies into existence five years ago. He published a new paper on the new cancer targeting mechanism, which is what ultimately we think that US biotech should differentiate themselves on is like new biology, new modalities. Immediately started a company, well funded, they developed the asset, were taking it to the clinic. And before they were able to initiate their clinical trials, Chinese biotech with the same identical mechanism beat them to the clinic and launched trials not only in China, but also in the as. So I do think that secrecy really matters. I think many people are starting to ask themselves whether they want to present at clinic conferences. So do they want to publish papers, whether they want to file patents, which wasn't the case when Genentech was created. Back then, people were just like putting everything out there for everyone to see and share.

[Elliot Hirshberg]

And that's a real negative externality.

[Host (a16z Podcast Host)]

Right.

[Elliot Hirshberg]

In terms of just the mean substrate of communicating science of open source, of these sort of, this proliferation of technologies. A lot of technologies are built on other technologies. And if everybody has to keep it closer to the chest for that exact reason that like your time to actually commercialize your own invention shrinks, that's probably one of the, that's like a consequence of this, this trend that we have to think about.

[Host (a16z Podcast Host)]

So speaking of inventions, one of the great inventions that we've seen over the course of the last few years is the Rise of, of artificial intelligence. Artificial intelligence is obviously being heralded as being transformative across a broad range of industries, a broad range of applications, creating new experiences, new consumer products, all kinds of things. Lots of use cases that we would have never imagined. Where do you view the impact of AI when it comes to developing new drugs? How is that going to, Is that going to. Is that the invention that actually makes biotech competitive again? That makes biotech an investable, an investable asset again?

[Lada Newsuna]

Yeah, I think it's sort of not a question of whether AI will be useful. I'm definitely in the camp of like everyone will be using AI in biotech industry five years from now. For me it's more of a question, can it take two and a half billion dollars to approve a drug and make it into $500 million to approve a drug? Can it make it like 4x more efficient in terms of timeline? And I think to answer that question, we really should go back and look where most of that money is spent right now. And most of it's spent is not in preclinical stage. It's spent in val safety and efficacy in humans. It's bent on commercialization stage, which is what happens after phase three clinical trials. And I think so far, and maybe Elliot's take would be different from mine, a lot of the efforts that we are seeing are concentrated on the preclinical stage of doing toxicity. Can we make toxicity studies in mice much faster? Can we have in silica tox for cell lines? And a lot of those things are valuable, but they don't necessarily bridge the gap and they don't necessarily improve the failure rate of clinical trials. Which is like the highest failure rate right now is phase two, which is efficacy. So if we were, if I started to see those same companies use and generate more human data to apply to those models, I think I would become more optimistic. But I actually think many big bio problems and open questions will be solved with AI way before we can predict efficacy for drugs. But I think virtual cells is actually not that far out. I think we have all the necessary data to generate something like that. The question is how can we make it useful for predicting efficacy of drugs in humans?

[Elliot Hirshberg]

Yeah, I mean, I think the, I think Laude is right. The, the answer is probably unequivocally yes. It's like it's becoming consensus that AI is a pretty important new experimental tool for, for biology and biologists. Right. Just as, just as software was the way that I like to, to, to evaluate where it's useful. Right. Now is if you sort of break down like the, the three horsemen of Irun's law of the time and cost of clinical development. Right. That's an enormous pillar that's sort of hard to tackle. We sort of talked about that of tech. Probably software 1.0 can help help a lot there. Regulation culture. One layer deeper you have the challenge of phase two failure which is basically a readout on the fact that we don't understand biology. Right.

[Host (a16z Podcast Host)]

We can't predict what's going to work and what's not going to work.

[Elliot Hirshberg]

Yeah. So sort of efficacy prediction on net new targets or sort of hypotheses for a mechanism and then the third being that there's an enormous amount of interesting ideas that we have but we actually can't express those ideas in molecules and sort of make new drugs. So that's sort of the, the a third pillar of, of why it's really hard to make exciting new medicines. For all the reasons we talked about it sort of hard to, to dramatically change the, the time and cost if you're doing pre clinical discovery when it comes to clinical development but when it comes to making things that are otherwise impossible medicines. So either finding really interesting new targets and having higher confidence in the predicting the efficacy of a drug there are some exciting directions. And then especially when it comes to expressing ideas in molecules, I think that a lot of these platforms and capabilities to take new interesting data sets to take what's coming out of molecular machine learning and just make things that are, you know, unequivocally impossible to make without these tools make some really, really exciting medicines. And so I think that like the ambition of a TPP will go up. I think that's also really important. Right. Because like the portion of Eroom's law is, is predicated on the better than the Beatles problem. We keep adding to this armamentarium of medicines that we have and that stacks up and up and up over time. We're sort of continually in pursuit of beautiful medicines and to actually make something more beautiful and more potent at this stage of the game the alpha probably is in really interesting data sets, new modeling tools and capabilities and I'm really excited about the sort of categories of medicines that could be made with this types of approach.

[Host (a16z Podcast Host)]

So just let's talk about the three horsemen of erom's law. I like this, I like this the way you framed it. The structural problem we have with getting drugs approved is one. It's a big horse totally. The lack of understanding of biology and the ability to predict efficacy seems Like a very big horse. Is the ability to, are we design limited in our ability to make molecules? Is that a big horse or is that a pony?

[Elliot Hirshberg]

You know, I mean, I think it's, it's pretty substantial. Right. So we've gotten really good at making monoclonals. Right. We've been making monoclonal antibodies for 50 years, half a century. And we've got exquisitely good experimental tools for sort of panning and finding these types of molecules. And so if you sort of have a specific, no nonsense target, but if you're talking about a really complex poly specific molecule that's hitting multiple components, you know, you see the beauty of multivalency with PD1VEGF. What else is out there that is like two, maybe three interactions that exquisitely tunes the immune system or the state of a cancer. As we learn more about moving cells around on, on their sort of manifolds of different cell states, I think that there actually are target product profiles and medicines that we just genuinely can't get to with our existing discovery technologies that could be really, really big products. Right. So you see this like very low hanging fruit, like without this tool combination of PD1VEGF and like that's beating keytruda.

[Host (a16z Podcast Host)]

Right.

[Elliot Hirshberg]

Like that's, that's like this enormous step change. And so our ability to sort of potentially get those types of results from these model, these models seems possible to me.

[Lada Newsuna]

Yeah. I think there are many targets on pharma's most wanted list that been on that list for many decades now. I mean targets like 53 that so many companies tried to target and no one really managed to get the molecules that really works or like it worked but the target product profile wasn't desirable. Yeah, I think until we clear out that list, there's definitely a bottleneck on the ability to design certain therapeutic modalities. The question is like, do we always want to have an oral for every antibodies that exist out there? Maybe antibodies are actually not that bad. I think the whole GLP1 story definitely altered my perception of how much people are willing to do like injectable drugs on themselves.

[Elliot Hirshberg]

Yeah. I think every quarter you take an injection and you don't have to think about it. You don't have the sort of adherence risk of a small molecule. I think some of that is totally right, that that's not always the canonical rule of thumb.

[Lada Newsuna]

Yeah. And it's also true that new modalities often struggled even though they were better in some shape or form. I mean the whole generation of CRISPR companies, I don't think we've really seen through the CRISPR dream quite yet. Ten years ago, when the first CRISPR companies were launched, the dream was really we will develop a tailored gene editor for every rare disease that exists out there. And it's partially bottlenecked by the regulation. But even for well known targets like PCSK9, the question is like, do you really want to do a gen Ed or do you. Is rupatha or inclisiron actually good enough? So I think many new modalities will be bottlenecked by the Beatles better than Beatles problem. Yeah.

[Host (a16z Podcast Host)]

It is a fascinating thing because the armamentarium, as you were saying, has gotten so large that now you're really slicing at specific patient preferences. Right. Someone may prefer an oral to a weekly injection, someone may prefer an infusion, you know, once, you know, once a year to, you know, taking an injection every month, that kind of thing. It starts to get very challenging to tease out which product profile wins in the market.

[Elliot Hirshberg]

This is where I'm sort of an unequivocal platform bull still is that I think like one of the most exciting opportunities for AI and biology is this sort of world that we're going to where the platform is the product. Right. So if you think of like Moderna's and Biontech's cancer vaccines, this is a product that's in clinical trials where it is part next generation sequencing, part AI and machining. There's actually a neural network that processes the sequencing data and then there is a specific MRNA cancer vaccine designed for that patient. Right. And so in that case, it's hard to even disentangle like it, it totally breaks our conception of what the target is, what the drug is. The drug is, you know, part information product, part diagnostic. And that in theory, that type of really personalized approach could sort of open up and actually be a total pan indication solution, again in the limit. And so one of the really exciting things is like if you have a fundamentally generative platform that is the product, does that open up a much wider indication base?

[Host (a16z Podcast Host)]

Yeah. So speaking of indication basis big indications, you Talked about the OP1s obviously one of the most extraordinary drugs in terms of the impact it's had on, on the broader society that we've seen in a very, very long time. It's also a drug that, you know, if we talk about, you know, health span, longevity, all of these things, it might actually be bending the trend, right. In terms of some of these chronic diseases, whether it's metabolic disorders, obesity and the like. You, in your piece on the where Are the trillion dollar biotechs. Talk a little bit about, well, where, where will the next big wins for the industry come from? And you talk about, you know, the genetic, you know, finding diseases based on genetic basis rare diseases where you can have a big impact. You have a couple of other examples. But really if, if, if I read your conclusion correctly, where you land is the real big nut to crack for the industry is to go after the disease of aging and to, to solve to the extent that we can, longevity. What's your view on what the industry is doing right and where the industry is still lacking when it comes to all things aging and longevity?

[Lada Newsuna]

Yeah, I think unfortunately the incentive to develop aging drugs is still not quite there because if you look at the US payer system, the payer that pays the most for diseases of aged population is Medicare, which kicks in after 65. Before then we have a multipayer system where patients tend to rotate their insurance every few years. And so there's really not much incentive for someone to cover preventative medicine early in life. And once you hit 65, it's no longer preventative medicine, it's treating the disease itself. But I think a lot of it would be downstream of fixing how we pay for aging drugs, how we pay for preventative care. I don't know if we have a way to do that now. Not for chronic medicines, especially not for one and done solutions to age related diseases. I do, I am very excited about JLP ones. I'm probably not the first person in aging space to say that maybe JLP ones would be one of the first agent drugs. I think this month Lilly is reading out their semaglutide in Alzheimer's trial which is to me is a real test of whether it's an aging drug or not because it's well outside of the metabolic spectrum of diseases. And yeah, at the same time Medicare refused to cover GLP1s for obesity care. So can we cover GLP1s for aging diseases is not super clear to me.

[Elliot Hirshberg]

I do think there's one interesting component of incentives where it's like a, it's like a commercial better than the Beatles. Where once you have such an enormous revenue in sort of sales generation from a product, you're going to fight like hell to have something in your pipeline that could potentially replace that. And so it does have this, this property of sort of driving and sort of pulling on the ambitions of the industry where it's, you know, people are honestly thinking it at Lilian Novo, like what is it going to take to actually fill the, the patent window.

[Host (a16z Podcast Host)]

What's the Act 2?

[Elliot Hirshberg]

What's Act 2? And I think that, you know, there is a component where it's, it's these. It has to be something that is a large enough indication to take that vision seriously.

[Host (a16z Podcast Host)]

Yeah, I think it's a good, I mean, it's a great argument that GLP1s have really achieved two important things. It's potentially given us ways to treat some of the most endemic, challenging conditions that affect society, whether it's metabolism and obesity and other factors. And the second one is at some level it's given the industry its mojo back. Right. To go after big problems, to go after the big indications, to find the act Twos. Because you're absolutely right, you're going to have to replace at some point this product with the next big idea.

[Elliot Hirshberg]

I mean, Alex Telford's written a great piece on this of the sort of cyclicality of trends of what produces a blockbuster. Right. Where you had like the Lipitor era of these enormous pills for big indications that were phenomenal products. And then we sort of moved into this era of specialty medicines, the birth of biologics, Very, very big focus on rare diseases, so sort of making up for smaller population sizes with larger price tags. And I think in terms of the general pressure on pricing, plus the sort of carrot of the success of GLP1, there is this big swing back into big indications and potentially there's such big indications that you have to take being a direct to consumer business really seriously. Where you think of, you know, Lilly Direct, where these are so big that you would actually break the payer system if you were distributing something for, for weight and metabolism for aging. Where this sort of arc of our business model. I did not expect this year to have John Maraginore talking about a direct to consumer biotech company. But that's kind of where the vibes are right now, which is, which is actually exciting.

[Host (a16z Podcast Host)]

What is the state of the science when it comes to aging? Because you talk about some of the structural challenges in terms of reimbursement and maybe even regulatory. But let's go all the way back to the beginning. What is the state of the science when it comes. Do we understand what aging is and do we have credible theories as to how to intervene?

[Lada Newsuna]

Yeah, I wouldn't say we know what aging is or even how to measure it, because if we had a way to measure it, we would have clinical trials run based on surrogate endpoints and maybe would have multiple agent clinical trials run in parallel. Right now the way we approve or like move in this direction of approving agent medicines is we run multiple trials for multiple diseases the way we are doing with GLP1s. And then we are sort of deriving the conclusion that, well, maybe if it delays onset of multiple diseases, at the same time, maybe it's an aging drug. I do think regulation is lagging behind science. I think we have multiple drugs that extend lifespan in mice and monkeys that never been tested for lifespan indications in humans. I think some companies are doing very exciting regulatory groundwork, companies like Loyal, where maybe for the first time we would have an aging drug approved for dogs. And maybe it's not that far out for approving the first aging drug for humans. I think we would be able to treat agent before we understand how to measure it, of what it is or why it happens. And the way I really view sort of the future reveling of lifespan drug is it should come in several waves where the first wave is sort of small effect sizes, very established therapeutic modalities, small molecules. If it's preventative medicine, it has to be squeaky clean, very safe, because if you're preventing some future disease, there is no room for side effects. After that, we would have more exciting therapeutic modalities, maybe epigenetic editors, gene editors, maybe gene therapies. And as we progress, it will only get, I think the bearings of medicine and therapeutic modalities that we apply to aging will increase over time.

[Host (a16z Podcast Host)]

If you guys can wave a magic wand, what would be the, the, the aging stack that you take every day? You know, like, you know, you have the Brian Johnson blueprint, don't die sort of protocol in your mind. What, what should the average person be thinking about that they should be taking on a regular, maybe not every day on a regular basis.

[Lada Newsuna]

And it does seem like we kind of hit a point where actually like our generation shouldn't die of heart attacks. It seems like we have everything to prevent high cholesterol in people from like, you can pick antibodies, SRNA small molecules soon Gene editors, we have full stack for that. And heart attacks is I think the primary cause of death in the United States. It's like people die around 72. Remove that, people would start living to 75, maybe 80. I think a good benchmark is Japan, because in Japan people don't die of heart attacks, they die of cancer. And I think the median lifespan there year is close to 80. So that's plus 10 years to lifespan. I think most of the things would be the things that are already approved. LP1S is obviously a big, big one. The only documented effect for lifespan that we have in monkeys is caloric restriction. We know that we can add about two and a half years to 25 year medium lifespan in monkeys by calorically restricting them. It really depends on the controls that you use in your study. I think there were two big studies that were run. One of them used monkeys on high fat diet as controlled. The other one used healthy monkeys. And if you compare it to healthy monkeys, caloric restriction doesn't add that much. But I think if you live in the United States, you are likely monkey on the western diet. So I think GLP1s will be broadly impactful for everyone.

[Host (a16z Podcast Host)]

All right, so magic wand, you put Lipitor and GLP1 in the water, PCSK9 inhibitor, PCSK9 inhibitors and GLP ones in the water. Okay.

[Elliot Hirshberg]

I think it's, I think it's like the 104 year old lady who's like, it's just one cigarette a day and like one piece of chocolate. No, I think it seems to be the case that caloric restriction is important. Right. You know, moving. We're a very sedentary society, so I think there's just a lot of benefits in just being active. And it's interesting just seeing the level of personal health monitoring like downstream of whatever Brian Johnson's sort of cultural movement is of, you know, people actually doing a lot of longitudinal self measurement, doing blood, blood work, being more proactive in their, in their care and then I think, you know, even being more proactive in cancer care. Right. Early stage screening and having types of medicines that have the right risk profile to actually dose people with. If you are able to detect extremely early stage cancer. Right now, it's just an ethical question if, you know, for our fairly barbaric approaches to cancer care, that's actually a meaningful roi. Whereas if we had different types of medicines, that would be pretty phenomenal for longevity and health.

[Host (a16z Podcast Host)]

Speaking of magic wands, we spent a lot of time talking about the industry and some of the challenges that I think the industry faces in getting drugs to patients. If you had a magic wand and you could change something around the regulatory environment, if you could change something around the sort of laws of physics of the industry, what would those be?

[Elliot Hirshberg]

I think sort of two being the cost per patient per trial, that should almost be a stat that the FDA cares about, right? So when Georgian Coppola started Regeneron, it cost about $10,000 per patient in trial. That's ballooned to $500,000. There is no Law of physics that requires it to be $500,000 in terms of complexity and cost to dose a patient in a trial. If we want to see the next regeneron, we want to meaningfully care about that as sort of a KPI for regulation for industry. I also think like we talked about earlier, it should not be accepted as the default that innovative American companies go to other geographies to run their first in human studies. There is low hanging fruit when you think about the regulation that's in place for in Australia, in Asia. And Carl Jun, who's the early developer of CAR T therapy, was asking this in a workshop recently with the fda. Why do we not have investigator initiated trials for cell and gene therapy in the US if there is this distinction of, of them being the engineering state and us being the lawyer state, we should actually sort of say let's, let's win on regulatory innovation. Let's be really creative in terms of the way that we actually regulate this industry. We should still be the beacon of where people do their clinical development and where trials are approved.

[Lada Newsuna]

Well, the reality is that even if you run your trial in China, you still have to come back to the US Even for Chinese companies that run their trials in China, they all come back to the US because that's the biggest market. And even if Chinese population will continue to grow, US will still remain the biggest market for biotech companies to exit at. There is no Chinese pharma that people are selling to. All of the farmers that are buying Chinese assets are US farmers, they're European farmers that would then go and run those trellis here. So yeah, I do think we need to solve that question because eventually everyone will be running trellis here either way. My magic wand I would cast as well and ask for something that would be a version of orphan drug designation but for common diseases. Orphan Drug Act I think was enacted around 1980s. Before then we had like less than 40 approved orphan drugs for patients that are, that have a population of less than 10,000 patients. And today 50% of drugs approved in 2024 were all orphan drugs. So orphan drugs for like very, very small population. And I think we are at the stage of biotech development where we really need something like that to incentivize development of drugs for age related diseases or for longevity itself. Right now age related indications have some of the highest failure rates in terms of drug development because there are no genetic drug variants. The process is much longer, the trials are way more expensive. So we need some kinds of those incentives to make sure that more biotech companies go and develop drugs for cancer where phase ones kill half of the companies at early stages.

[Host (a16z Podcast Host)]

So, yeah, it's an interesting concept. An orphan degree. Orphan drug designation for more chronic disease.

[Lada Newsuna]

Yeah, yeah.

[Host (a16z Podcast Host)]

The original spirit of the orphan drug, of course, was to create an incentive for people to. To develop drugs that face small populations because maybe the market potential isn't there, and so you'd have to. But in this case for chronic diseases, the market potential is enormous.

[Lada Newsuna]

Yes.

[Host (a16z Podcast Host)]

Excuse me, the market potential is enormous. And so in your mind, the thing that needs the most incentive is to get to incent companies to go through the difficult development process because the failure rates high.

[Lada Newsuna]

Yes. I think there is a little bit of disconnect between, like, what types of diseases affect humans and what types of diseases we approve drugs for. If 50% of drugs are approved for rare diseases and rare diseases affect only small fraction of populations, I think that's important. But how about every disease that people are actually done for from? And I think the fact that population is aging should be a big push to do something like that because age population is a less productive population, and that's where us is headed now.

[Host (a16z Podcast Host)]

Oh, okay, so that. I get that. So that's a great argument that if you actually could address aging in a meaningful way, you could have massive societal benefit. And so therefore you have to find a way to incent that, because it's not happening today.

[Lada Newsuna]

How about your magic wand?

[Host (a16z Podcast Host)]

I think, look, I think if I had a magic wand, it would be a combination of figuring out how we incentivize, continue to incent the innovation that happens here, to stay here. So a bit about what Elliot was describing. Where, you know, what we know is we have this wonderfully effective pipeline where a lot of innovation happens in universities and happens in startups that get funded through investors like us. And you get a lot of incredible novel approaches to tackling disease that comes from that. But the challenge we have is to, you know, go from that invention to an actual product. Still takes a lot of time and money, and there's. There are a lot of hurdles there. And so I like this idea of being able to say, why don't we see what works in the rest of the world in terms of being able to run that relay race from, you know, an invention to a. To an approved drug, to run that relay race more quickly? And can we copy those. Those processes to make sure that our lap time is at least as fast as the rest of the world's lap time? Because if we do that I think we'll find that we can maintain a lot of innovation here. And one thing that is promising is at least if we look at where things stand today, the regulatory agencies, the FDA is at least signaling that they want to find ways to really innovate, to modernize. I think that's very promising. I think when it comes to some of the other challenges we have geopolitically, whether it's with China or just in the rest of the world, what a lot of the administration is pointing to is saying how do we incent invention and innovation to stay here? How do we incent the supply chain to stay here or to re onshore? How can we do this in a way that our industry remains here within the United States? If I had a magic wand and could replicate all of the things that are working elsewhere and bring them here to get us back up to speed in terms of being able to, to, to run the, run the race as quickly as other countries can, I think that'd be extraordinarily promising for, for, for the industry, for, for society and arguably for the, for the world. So that is my, my reason to be optimistic and that would be what I would use my magic wand for is that's how to figure out how we can make all this innovation get to where it needs to go. So the GLP1s as a, as a drug class are this incredible example. I've, I've heard it be described as the most important consumer product that we've seen in the last several decades, or for obvious reasons, the impact it's having on societal health. What makes a drug blockbuster in your mind? Like why, why is it that some drugs are so incredibly successful? Why don't we see more of them?

[Lada Newsuna]

Yeah, I feel like people tend to generate certain wisdoms around what it takes to develop a successful drug. Sometimes it's oh, you have to be first in class or first to market. But I think successful drugs are kind of like the opposite of that Tolstoy wisdom in that each happy family is happy in its own way. And in case of GLP1s, they weren't the first. Semaglutide and tirzepatite weren't the first GLP1s to be developed or be approved. Just that in this case. Lillian Novo took on a very contrarian bad that obesity is actually a real market. Which now seems obvious, but 10 years ago, if you were a company trying to raise for obesity as a disease, you're probably had much success. I think many companies terminated their obesity programs because it wasn't clear that the market was there, and especially it wasn't clear that people with obesity would be injecting themselves with drugs. I think Pfizer terminated their GLP1 program because internally they decided that actually like chronic disease injectables, I don't think patients want that. Humira was also not the first TNF alpha antibody out there. It was like CERT to market certain F alpha antibody to be approved, but it was the first human monoclonal antibody, one of the first ones to be approved, and all the previous ones were antibodies from mice. So I think in both of those cases it wasn't a biological take that was unique. The targets were pretty consensus. And I think biology is one of the areas where you really don't want to be contrarian. You don't want to be the only company pursuing some obscure mechanism. Usually you want to have some literature validation, but in both of cases it was either a big modality differentiator in case of Humira, or big contrarian take on what indication to pursue. And I think aging might be a contrarian indication to pursue for some. I think muscle is in a similar space right now where for a while people weren't treating sarcopenia as a real indication because it's muscle loss in elderly. But there is now a similar race to JLP wants to go and develop drugs for muscle, and we'll see it succeeds.

[Host (a16z Podcast Host)]

Okay, so you, with all the time you've spent studying and focusing on the industry, have decided to jump into a startup. Still stealth, as I understand it, but to jump into a startup that's going to tackle aging? What are you thinking?

[Lada Newsuna]

Yeah, I think our take is more of a modality take. Every time I think about where the biggest breakthroughs and successes in biology came from, it was always served from some type of technology or process or technique and rarely from discovering a new target. So we are developing a new modality that should make it easier to tackle aging. And if you look back at something like Human Genome Project, it took us several decades and several billions of dollars to sequence one human genome. And once we discovered better sequencing approaches, we can now do it daily for a few hundred bucks. I think aging is in a somewhat similar space in that it's a massive multifactorial disease. And if we rely on existing modality approaches, it would just be an uphill battle to try and treat it. If we develop modalities that allow us to go and target this complexity without much additional engineering, every time we want to start a new program, I Think that would be sort of a big catalyst for success.

[Host (a16z Podcast Host)]

Okay, so we, we started this conversation talking about where the trillion, trillion dollar biotech companies are. You guys, you are both students of, of history of this industry. Where do you see the next wave of iconic biotech companies come coming from? Where would you see them coming from? Where's the next. You know, obviously the industry started with the Genentechs and the Amgens and the biogens of the world. Then we eventually got the vertexes and the regenerons of the world. Where do you see the next wave of iconic biotech companies emerging?

[Elliot Hirshberg]

I'm a big believer in modalities also. I think that if you look at the history of the industry, there is an enormous amount of value that's created from unlocking new types of medicines. So I'm really excited for the fact that you have all these new generative design tools and sequencing technologies and delivery tools that can all start to be stitched together into sort of a composite specific product. So there are these sort of waves within technology, right, where there's specific problems that are solved and you start to bundle a bunch of different components together and then there's new ideas that come and it sort of unbundles the stack and this sort of happens across the software, different markets. I think that in biotech we're in this sort of moment where there's a lot of opportunity in rebundling. The types of platforms that I see that I'm super excited about are this composite of incredible synthetic biology and genomics tools, plus modeling, plus other tools on top of them that just unlock things that otherwise weren't possible. And so I'm really excited about that sort of opportunity to make things that are just net new in the industry. And I think that's where you have to go to really keep winning.

[Host (a16z Podcast Host)]

Okay, so your bet is the next wave of great companies in the form of some type of new modality, one.

[Elliot Hirshberg]

Of those options, right? Yes.

[Host (a16z Podcast Host)]

Okay.

[Lada Newsuna]

I mean, what about you? LADA recombinant DNA gifted us the first off the shelf insulin MRNA vaccines, gifted us vaccines that we can synthesize in less than a month produced from the genomic sequence of the virus. First, human monoclonal antibodies gifted us a wave of cancer precision medicine that we have now. And I think something similar has to happen for chronic multifactorial diseases. I think we are starting to see light at the end of the tunnel with gene editing, epigenetic editing, more tailored targeting approaches were no longer do our LNPs just go to the liver we can now target HCCS, we can target kidney, we can target potentially brain. And yeah, I'm bullish on new modalities.

[Elliot Hirshberg]

There is something really interesting in just this, this argument right now within biotech, if there are hyperscalers that emerge, there's this question, there's a lot of AI and biology companies that are raising a lot of capital and some just have no aims to make drugs. And there's this continual again for sort of like the background cynicism or discussions in the industry. A lot of people are asking like, what is that all about? I think that there's this really interesting component where we have to believe in net new market creation. So at one point illumina sold exactly 0.$0 of next generation sequencing technology to the industry, right. That turned into over $10 billion of sales. And independent large listed companies where their cost of goods sold were primarily going to, to Illumina. Right. And I think there's this interesting question, right? Where the largest company in the world, Nvidia, is an infrastructure company, is it possible for there to emerge a really large and sort of fundamental infrastructure company in biotech? And so I think there's sort of questions of either going where others can't and making something that people can't make, or making the sort of final arc of commoditization and building these sort of consolidated platforms that do all of discovery for sort of small molecules and antibodies as this technology matures. And so it's kind of like two different possible poles of value creation in the end state of bio. Biotech is dead and long live biotech.

[Lada Newsuna]

What would be your bet?

[Host (a16z Podcast Host)]

Well, my bet is we'd make the orthogonal bets. I agree. We're big believers in new modalities and we're big believers and there's going to be modern infrastructure that drives, that underpins the ability to make modern drugs. And so I think there's a ton of value creation on both of those axes and we're very, very optimistic about that future along with biotech.

[Elliot Hirshberg]

Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes go to YouTube, Apple Podcasts and Spotify. Follow us on X1 6Z and subscribe to our [e-mail] thanks again for listening and I'll see you in the next episode episode. As a reminder, the content here is for informational purposes only. Should not be taken as legal, business, tax or investment advice or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see a16z.com forward slash disclosures.