a16z Podcast - The Brutal Truth About Biotech: Why $2B Per Drug Is Killing Innovation

Episode Date: November 14, 2025

Two venture capitalists dissect why biotech burns billions while China runs trials in weeks—and why the next Genentech won't look anything like the last one. Elliot Hershberg reveals the "three horsemen" strangling drug development as costs explode to $2.5 billion per approval, while Lada Nuzhna exposes how investigator-initiated trials in Shanghai are rewriting the competitive playbook faster than American founders can file INDs. When the infrastructure that built monoclonal antibodies becomes the commodity threatening to hollow out an entire industry, the only path forward demands inventing medicines that are literally impossible to make without tools that don't exist yet—and they're betting everything on which approach survives. Resources:Follow Jorge on X: https://x.com/JorgeCondeBioFollow Lada on X: https://x.com/ladanuzhnaFollow Elliot on X: https://x.com/ElliotHershbergFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that 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. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.   Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that 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. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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. So when George Yonkopoulos 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. Everyone will be using AI in biotech industry five years from now. Can it take two and a half billion dollars to cover with drug and make it into 500 million dollars? 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. We had this enormous wave of access. 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. And that's where we have to go to really keep winning. The biotech paradox.

One fifth of public biotech companies are trading below their cash balances. C. Browns had 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 carbon 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 Nuzana founded General Control, a startup tackling aging after writing the definitive 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 GOP-1'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. 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? Yeah, if you and I buy ideal society, It's been quite a few interesting years in biotech. I mean, early this year, we had something like one-fifths of public biotex trading at or below their cash balances. They had like record low number of bi-tax raising their seat rounds. Platform dream kind of judged more harshly.

And 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 Erem's law, which is more slow, spelled backwards. We now spend more than $2 billion per approved drug. We have a rise of Chinese bag act scene 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 DeepTag broadly because it 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 we'll 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? Okay, so you have a lot of reason to be pessimistic. Yes. Okay. At least as of now. As of now, as of today. I want to hear, Elliot, your take.

I think there's never been a bigger disconnect between both sides of the market, right? So as a lot of was saying, we had this enormous wave of excess. Our last actual boom cycle in this industry was COVID. You had an 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 a lot of pointed 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 logjam that goes from the public markets to the growth investors to leader 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. So you have people developing zero shot antibody design in labs. you have incredible virtual cell projects,

an enormous amount of sort of transitional 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 disconnects in the market between sort of Publix and what's happening earlier.

Sort of a tale of two worlds. 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? So my PO's happening, or these people are preparing to file, some very successful MNAs. The biotech index is above, starting to get well above the famous $100 mark

for the XPI. Right. 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 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? 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 it easier to develop

and approved new 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-st-reput screens for new small molecules and antibodies are like billion times more efficient than they were 20 years ago. And what Elliot said really is an age because it feels like the science continues to get better and the state of science continues to get worth. 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 a huge strategy, I think was drug. telling them why that pregnant women were taking that led to a 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 attention between safety and efficacy. And if we to regulate the process we would have to take on some type of safety risk.

I think it's interesting. There's 100% 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? When you say we, you mean at Amplify? At Amplify. Yeah. Oh, none. 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 outsource 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, it's 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 cultural component of biotech, that we just assume that these things are expensive and take a lot of time. So that argument would be that the challenge is not technological, that in some level the challenge might not even be the regulatory bodies.

Yeah. It might be something structural, something incentive-based, where the way the industry is structured, you have various parties, in this case, the groups that help run the clinical trials that may or may not be incented to be more efficient. Is that the argument? 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 percentage at east and I think it is a composite of all three. Okay. So now let's add to the mix here. Let's add to the soup. The China question.

Yeah. 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 U.S.-based biotechnology industry? So I think it's worth just backing up and saying, you know, how is the 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 textiles. And they decided to take their sort of chemical manufacturing and distribution and a apply it to making drugs. It's talking about Germans. That's right.

And the first drugs were incredibly crude pharmacology, right? So this was heroin, this was cocaine, this was morphine, higher attention than die stuffs, right? You know, like 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 medicine. listens, 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

to sub-research startups and 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 armamentary of drugs. So that's kind of the setup, like, how biotech works, right? These companies divested their R&D, or, you know, 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 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 with 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. We're on speed and cost, China can enter the equation and compete for these types of ideas to deliver the medicines. 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 assets now. And what

really happened is like several ways of deregulation that probably about the curing, 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 files your I&D, unless they issue a proactive hold on your I&D, it will be default approved in certain days. US has the opposite model where you have to proactively approve every ID 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 AS 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 AS, but I don't know if it's more efficient and then just running trials in New Zealand or Australia. With investigator-initiated trials, your view timelines are cut 5 to 6-X. 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 model of people used to view China as like a need to buy a printer

where they print the medicine that would already otherwise exist. I think it's somewhat outdated view. They're now leading in VWKRTs. They're leading in gene editing and gene therapy and partially due to this ability to do those investigator-initiated trials. Okay, so given that that's a reality today, what does that imply for the long-term future

of the U.S. 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 U.S. At some point, it becomes difficult to fund that innovation here. We talk about things being I are negative. It becomes increasingly difficult to fund that innovation here

if we know it's going to get out-competed over the longer terms from China. So does our industry get hollowed out? No. 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 U.S. is 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 U.S. thing, the birth of immunotherapy, which is in Texas, right? 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 spend a lot of time with Michael Fishback. incredible scientists at Sanford, 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 Schiffer and Georgiancopolis, these scientists that are actually sort of going to tell us where the future is. Yeah, 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, U.S. biotech invests, sorry, invents, and, you know, global biopharma invests, right?

They in-license it, they acquire it, they partner with it. Right. And 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. Talked about this a little bit, right? Where 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 U.S. 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. 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 U.S. biotech should differentiate themselves on. It's like new biology, new modalities. Immediately started a company well-funded.

They developed the asset, we're 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 AAS. So I do think that secrecy really matters. I think many people are starting to add themselves, whether they want to present at conferences,

so they want to publish papers, whether they want to file patents, which wasn't the case when Jen and Tech was created. Back then, people were just, like, putting everything out there for everyone to see and share. And that's a real negative externality, right? In terms of just the mean substrate of communicating science, of open source, 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 trend that we have to think about. So speaking of inventions, one of the great inventions that we've seen over the course the last few years is the rise 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 the invention that actually makes biotech competitive again, that makes biotech an investable asset again? Yeah, I think it's sort of not the question of whether AI will be useful. definitely in the camp of like everyone will be using AI in biotech industry five years from now. For me, it's more a question, can it take two and a half billion dollars stopper with drug and make it into $500 million stopper with drug? Can it make it like 4X more efficient in terms of Thailand?

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 validating safety and efficacy in humans. It's banned on commercialization stage, which is what happens after phase three clinical trials. And I think so far, and maybe at stake would be different from mine, a lot of the efforts that we are seen are concentrated on the preclinical stage of doing toxicity. Can we make toxicity studies in mice much faster? Can we have in silica talks 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 like, how can we make it useful for predicting efficacy of drugs in humans? Yeah. I mean, I think that I think lot is right. The answer is probably unequivocally yes. It's like it's becoming consensus.

that AI is a pretty important new experimental tool for biology and biologists, right, just as software was. The way that I like to evaluate where it's useful right now is if you sort of break down like the three horsemen of Erun'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, right.

And we can't predict what's going to work and what's not going to work with high quality. 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 a third pillar of why it's really hard to make exciting new medicines. For all the reasons we talked about, it's sort of hard to dramatically change the time and cost if you're doing preclinical 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 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 the portion of Eroom's law 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 datasets, new modeling tools and capabilities. is, and I'm really excited about the sort of categories of medicines that could be made with this type of approach. So just let's talk about the three horsemen of your room's law. I like this. I like this, the way you've framed it.

The structural problem we have with getting drugs approved is 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 and our ability to make moly. Is that a big horse or is that a pony? You know? I mean, I think it's pretty substantial, right? So we've gotten really good at making monoclonal, right?

We've been making monoclonomy 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 polyspecific, molecule that's hitting multiple components. You know, you see the beauty of multivalency with PD1 VEGF. 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 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 PD1 and VEF and, like, that's beating Ketruda, right? Like, that's, like, this enormous step change. And so our ability to sort of potentially get those types of results from these models seems possible to me. Yeah, I think there are many targets on pharma's most wanted list, been on that list for many decades now.

I mean, targets like 253 that so many companies try to target and no one really managed to get the molecules that really works or like it worked by 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 JLP1 story definitely altered my perception of how much people are willing to do like injectable drugs on themselves. Yeah, maybe like 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 with them. Yeah, it's also true that new modalities often struggled, even though they were better in some shape of 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 PCSK-9, the question is like, do you really want to do a gene editor or do you, is a repasta or enclaser on actually good enough? So I think many new modologies will be a bottleneck by the Beatles, but there's a Beatles problem. Yeah, it is a fascinating thing because the armamentarium, as you were saying, has gotten like 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 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. 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 Biointech'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 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?

yeah so speaking of indication basis big indications um you talked about gopi ones um 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 um it's also a drug that you know if we talk about you know uh 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 um you in your piece on the where are the trillion dollar biotechs talk a little bit about well 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 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 solve 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? Yeah, I think unfortunately, the incentive to develop aging drugs

is still not quite there because if you look at the U.S. payer system, the payer that pays the most for diseases of aged population as Medicare, which kicks in after 65. Before then, we have a multi-payer 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. 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 JLP1s. I'm probably not the first person in aging space to say is that maybe JLP ones would be one of the first agent drugs. I think this month, Lily is really not their semaglite 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 JLP wants for obesity care.

So can we cover JLP ones for aging diseases? this is not super clear to me. I do think there's one interesting component of incentives where it's like a commercial better than the Beatles where once you have such an enormous revenue and 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 property of sort of driving and sort of pulling on the ambitions of the industry where it's, you know, people are honestly thinking. at Lillian Novo, like, what is it going to take to actually fill the patent window? What's the Act 2? What's Act 2? And I think that, you know, there is a component where it's these, it has to be something that is a large enough indication to take that vision seriously.

Yeah, I think it's a good, I mean, it's a great argument that GLP wants to have really achieved two important things. It's, you know, 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's 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, you know, this product with the next big idea. 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, Lily Direct, where these are so big that you'd actually break the payer system if you were distributing something

for weight and metabolism for aging, where the sort of arc of our business model, I did not expect this year to have John Merrickanora 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. Where is this, what is the state of the science when it comes to, to aging? Because you talk about some of the, the structural challenges, uh, 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? Like what, do we understand what aging is and do we have credible theories as to how to intervene? Yeah, I wouldn't say we know what age.

is or even how to measure it because if we had the way to measure it, we would have clinical trials run based on surrogate endpoints and maybe we would have multiple agent clinical trials run in parallel. Right now, the way we approve or like move in the direction of approving agent medicine is we run multiple trials for multiple diseases the way we are doing with JLP ones. And then we are sort of deriving the conclusion that, well, maybe if it delays unsat of multiple diseases at the same time, maybe it's an agent drug. I do think regulation is lagging behind science. I think we have multiple drugs that extend lifespan in mice and monkeys.

It's never been tested for lifespan indications in humans. I think some companies they do 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 agent drug for humans. I think we would be able to trade agent before we understand how to measure it or what it is or why it happens and the way I really view

the future reveling of life spend 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 and 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 genetic editors, gene editors, maybe gene therapies. And as we progress, it will only get, I think the variance of medicine and therapeutic modalities that we apply to aging will increase over time. if you guys could wave a magic wand what would be the the aging stack that you take every day you know like you know you have the brian johnson blueprint um 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 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 on people from, like you can take antibodies, SRNAs, small molecules, sunken editors, we have full stock for that. And heart attacks is, I think, the primary cause of dust 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 is close to 80. So that's plus 10 years to lifespan. I think most of the sense would be the sense that they're already approved. JLP wants is obviously a big, big one. Like the only documented effect for life spend that we have in monkeys is coloric restriction. We know that we can add about two and a half years to 25 year median life.

in monkeys by calorically restricting them. It really depends on the controls that you use in your study. I think there were like two big studies that were run. One of them used monkeys on high-fed diet is 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're likely monkey on a Western diet. So I think JLP ones will be broadly impactful for everyone. All right. So magic wand, do you put Lipitor and Jopi 1 in the water? PCSK-9 inhibitors and heat up you want in the water. 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 work, being more proactive 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. Speaking of magic wand, 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? I think sort of two being the cost per patient for trial, that should almost be a stat that the FDA cares about. So when George Yonkopoulos started progenera on, 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 Jeune, who's the early developer of Carty Therapy, was asking this in a workshop recently with the FDA. Why do we not have investigator-in-issued trials for cell and gene therapy in the U.S.? If there is this distinction of them being the engineering state and us being the lawyer state, we should actually sort of say, 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. Well, the reality is that even if you run your trial in China, you still have to come back to the gas.

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 farmers that people are selling to you. All of the farmers that are buying Chinese assets are U.S. farmers, are European farmers that would then go and run those trellos here. So, yeah, I do think we need to solve that question because eventually everyone will be running trails here either way. My magic wand, I would cast a spell 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 less than 40 approved orphan drugs for patients that have a population of less than 10,000 patients. And today, 50% of drugs approved in 2024 were all orphan drugs. So drugs for 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 the early stages. It's an interesting concept, an orphan drug designation for more chronic disease. Yeah, yeah. The original spirit of the orphan drug, of course, was to create an incentive for people to develop drugs that face small populations

because maybe the market potential is there and so you'd have to, but in this case, for chronic diseases, the market potential is enormous. Yes. Excuse me. The market potential is enormous. And so in your mind, the thing that needs the most incentive

is to incent companies to go through the difficult development process because the failure rate high. Yes, I think there is a little bit of disconnect when like what types of diseases affect humans and what types of diseases we approach 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 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 the US has had now.

Okay, so 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. How about your magic wand? I think, look, I think if I had a magic wand,

it would be a combination of figuring out how we incent, 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 go from that invention to an actual product still takes a lot of time and money, and 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 an approved drug, to run that relay race more quickly.

And can we copy 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 will 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 to to to really innovate to modernize I think that's very promising I think when it comes to um some of the other challenges we have geopolitically whether it's with China or just in the rest of the world um what a lot of the um the administration is pointing to is saying how do we incent invention innovation to stay here how do we incent um the supply chain to stay here to or to re onshore you know

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 run the race as quickly as other countries can, I think that would be extraordinarily promising for the industry, for society, and arguably for the world. So that is my reason to be optimistic, and that would be what I would do with 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 GOP ones as a drug class are this incredible example I've heard it be described as the most important consumer product that we've seen in the last several

decades for obvious reasons the impact it's having on societal health. What makes a drug blockbuster in your mind? Why is it that some drugs are so incredibly successful? Why don't we see more of them? 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 and that each happy family is happy in its own way. And in case of JLP1s, they weren't the first smeglite and transapetite weren't the first JLP1s to be developed or be approved. Just that in this case, Lillian Nob took on the very contrary and 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 having 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 JLP1 program because internally they decided that actually, like, chronic disease, injectables. I don't think patients want that. that. Humira was also not the first TNF alpha antibody out there. It was like third to market, third TNF 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 this cases, it wasn't a biological tag that was unique. The targets were pretty consensus. And I think biology is like 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 these cases, it was either a big modality differentiator in case of Humira or a 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 is a real indication. because it's sort of 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. 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? Yeah, I think our take is more of a model. to take. Every time I think about where the biggest breakthroughs or successes in biology came from, it was always sort of 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. If you look back at something like human genome project, it took us

several decades and several billion 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 inside. It's a massive multifactorial disease. And if we rely on existing modality approaches, it would just be an uphill bottle 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. Okay, so we started this conversation talking about

where the trillion dollar biotech companies are. You guys, you are both students of history of this industry. Where do you see the next wave of iconic biotech companies coming from? Where would you see them coming from? Where's the next? Obviously, the industry started with the genetics. and the hemgens 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 biotic companies emerging? 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, you know, unlocking new types of medicines. So I'm really excited for the fact that you have all of 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 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, you know, 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 we have to go to really keep winning. Okay, so your bet is the next wave of great companies

in the form of some type of new modality. One of those options, right? Okay. I mean, what about you, Leda? Recombin and DNA gifted us the first off-the-shelf insulin, MRI vaccines gifted us vaccines that we can synthesize in less than a month

produced from the genomic sequence of the virus. First, human monoclonial antibodies gifted us a wave of cancer, precision medicines that we have now. And I think something similar has to happen for chronic multifactoral diseases. I think we are starting to see light at the end of the tunnel with gene editing and biogenic editing. More tailored targeting approaches where 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. There is something really interesting in just this argument right now within biotech if there are hyperskillers 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 um i think that there's this really interesting component where we have to believe in like net new market creation right so at one point alumina sold exactly zero dot zero dollars of next generation sequencing technology to the industry right that turned into over 10 billion dollars

of sales and you know independent large listed companies where their uh cost of goods sold were primarily going to to aluminum 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 the, 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 in state of bio. Biotech is dead and long-loop biotech. What would be your bet? 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 on a value creation on both of those axes. And we're very, very optimistic about that feature. Long live biotech. Home live by the... Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe,

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