Since the birth of this industry, we only had increasing regulation over time.
I think there was like only one time in the history of biotech where we made it easier to develop an appropriate drug.
So when George Yancopoulos 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 500000 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...
$2.5 billion 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.
The biotech paradox. one-fifth of public biotech companies are trading below their cash balances.
Seed rounds 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 Nuzinah 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 GLP-1s 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 A6NZ 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, a few AI buy deals aside, it's been quite a few interesting years in biotech.
I mean earlier this year we had something like one-fifth of public biotechs trading at or below their cash balances.
They had like record low number of biotechs raising their seed 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 Erum's Law, which is more slow, but backwards.
We now spend more than $2 billion per approved drug.
We have a rise of Chinese baguette, a 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 deep tech 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.
They're investors making drugs first, huge exits, more so than Intac 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?
And that's Okay, so 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 Lotta 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 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, 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 disconnect 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 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 $100 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?
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 inappropriate drugs.
And that was during the AIDS crisis, where AIDS patients were just laying outside the 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 a huge strategy.
I think it was drug telethonide 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 a tension between safety and efficacy.
And if we deregulate 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, 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 this 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.
Yet
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 you know 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 you know percentage at ease.
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 US-based biotechnology industry?
So I think it's worth just backing up and saying 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 apply it to making drugs.
You're talking about the Germans.
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 dye stuffs, right?
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 part 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 e-rooms 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 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 of how biotech works, right?
These companies divested their R&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 and then 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 where, 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 US is now.
And what really happened is like several waves of deregulation that happened.
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.
It's 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 US 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 NDIS, but I don't know if it's more efficient than just running trials in New Zealand or Australia.
With investigator-initiated trials, your view timelines are cut.
5 to 6 acts.
It's a very fast process and it's really specific to new modalities, high-risk indications, cell and gene 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 a medicine that would already otherwise exist.
And so, yes, I think it's somewhat outdated view.
They are now leading in vivo CAR-Ts.
They are 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 US biotech industry?
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 IR negative.
It becomes increasingly difficult to fund that innovation here if we know it's going to get out-competed over the longer term in 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.'
'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.
Mm-hmm.
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 Fischbach, an incredible scientist 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 Scheiffer and Georgian Coppola, these scientists that are actually sort of going to tell us where the future is.
Yeah, I do wonder, though, to what extent... Like, look, I think it's a very compelling argument.
I obviously am 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 you know global biopharma invests right.
They in-license it, they acquire it, they partner with it.
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 sort of it changes one of the dynamics which is like of secrecy.
In the industry, it's like secrets become more important.
It's 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.
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.
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 US.
So I do think that secrecy really matters.
I think many people are starting to ask themselves whether they want to present at conferences, whether 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.
And that's a real negative externality, right?
In terms of just the main 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 of 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?
Is that the invention that actually makes biotech possible, competitive again, that makes biotech an investable asset again?
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 operate with drug and make it into 500 million dollars to operate with 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 spent is not in the preclinical stage.
It's spent in validating safety and efficacy in humans.
It's 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 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 We solve 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 Laura 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 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 a lot there.
Regulation culture.
Um one layer deeper, you have uh, the challenge of, 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.
Exactly.
Yeah.
So sort of efficacy, prediction on on on net, new targets um 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 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 the 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 platform. will go up.
I think that's also really important, right?
Because like 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.
Mm-hmm.
And that stacks up and up and up over time.
We're sort of continually in pursuit of beautiful medicines.
Mm-hmm.
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 type of approach.
So just let's talk about the three horsemen of Irum'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, are we design limited in our ability to make molecules?
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 monoclonals, right?
We've been making monoclonal antibodies for 50 years, half a century.
Um and we've got exquisitely good experimental tools for for sort of panning and finding um these types of molecules.
And so if you sort of have a specific no nonsense target um, 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 PD-1, 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 PD-1 and VEGF, and like that's beating Keytruda right.
Like, that's, like, this enormous...
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 top 53 that so many companies try 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 GLP-1 story definitely altered my perception of how much people are willing to do like injectable drugs on themselves.
Yeah, every quarter you take an injection and you don't have to think about it.
You don't have to sort of adherence risk of a small molecule.
I think some of that is... is totally right that that's not always the canonical rule of thumb.
Yeah, 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 JIN editor, or do you are?
You is a Repasta or an Inclaser run actually good enough?
So I think many new modalities 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 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 once a year to 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 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 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 bases, big indications you talked about GLP-1s, obviously one of the most extraordinary drugs in terms of the impact it's had 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 uh, health span uh 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?
Um, 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 um, rare diseases where you can have a big impact.
Um, 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, 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?
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 aging diseases of age population as Medicare which kicks in after 65.
Before then we have a multiplayer 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 GLP-1s.
I'm probably not the first person in agent space to say that maybe GLP-1s 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 And 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 GLP-1s for obesity care.
So can we cover GLP-1s for aging diseases?
It's 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 it at Lillian Novo.
Like, what is it going to take to actually fill the patent window?
What's the act two?
What's act two?
And I think that there is a component where 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-1s 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 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, 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 GLP-1, 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 um business really seriously where you think of uh, you know, lily direct, where these are so big that you would actually break the pair system if you were distributing something for um, for weight and metabolism, for aging.
Where the sort of arc of our business model.
I did not expect this year to have John Maragonore talking about a direct-to-consumer biotech company.
But that's kind of where the vibes are right now, which is actually exciting.
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?
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 we would have multiple aging 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 GLP-1s.
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 agent drug.
I do think regulation is lagging behind science.
I think we have multiple drugs that extend lifespan in mice and monkeys that have 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 agent drug approved for dogs and maybe it's not that far out for our program the first agent drug for humans.
I think we would be able to treat aging before we understand how to measure it or 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 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 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 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 in people from like.
You can take antibodies SRNAs, 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.
I think the median lifespan there is close to 80, so that's plus some years to lifespan.
I think most of the signs would be the signs that are already approved.
GLP-1 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 median lifespan 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 fat diet as controls.
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 a monkey on the Western diet.
So I think GLP-1s will be broadly impactful for everyone.
All right, so magic wand, you put Lipitor and GLP-1 in the water.
PCSK9 inhibitors.
PCSK9 inhibitors and GLP-1s in the water.
Okay.
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 um of you know people actually doing a lot of uh longitudinal self-measurement doing blood uh blood work um being more proactive in their in their care um 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 wands, we've 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 per trial.
That should almost be a stat that the FDA cares about right.
So when George Yancopoulos 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 500000 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 and Asia.
And Carl June, 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 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.
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.
U.S. 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 pharma that are buying Chinese assets are U.S. pharma.
They're European pharma that... but then go and run those trellis here.
So yeah, I don't think we need to solve that question, because eventually everyone will be running trellis here either way.
My magic wand.
I would cast a spell and ask for something that...
It 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 10000 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.
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.
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 to incent companies to go through the difficult development process, because the failure rates high.
Yes, I think there is a little bit of disconnect between 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 a small fraction of populations.
I think that's important, but
How about every disease that people are actually dead 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 U.S. has had it now.
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.
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 of what Elliot was describing, where 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.
Um and uh, you get a lot of uh incredible novel approaches to 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.
Um, and there's a 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 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 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 innovation to stay here?
How do we incent the supply chain to stay here 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.
Uh, in terms of being able to to um 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 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?
Like 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, in that each happy family is happy in its own way.
And in case of GLP-1s, they weren't the first.
Smaglutide and trisapatide weren't the first GLP-1s to be developed or be approved.
Just that, in this case, Lilly and Novo took on the very contrarian bat 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 is 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 GLP-1 program because internally they decided that actually chronic disease injectables.
I don't think patients want that.
Humira was also not the first TNF-alpha antibody out there It was like third to market 13F-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 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 those 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 if 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 modality take.
Every time I think about where the biggest breakthroughs and 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 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 with...
So 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.
So where do you see the next wave of iconic biotech companies 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?
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 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, etc.
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, you know, 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?
What about you, Lara?
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 and genetic editing.
More tailored targeting approaches where we're 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?
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 Illumina sold exactly 00 of next generation sequencing technology to the industry right.
That turned into over 10 billion of sales and you know independent large listed companies where their cost of goods sold were primarily going 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, 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.
Mm-hmm. in the state of bio.
Biotech is dead and long live 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 in 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.
Long live biotech.
Long live biotech.
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