In the latest episode of Precision Signals, Sean Khozin speaks with Peter Kolchinsky, founder and managing partner of RA Capital Management.

Peter’s perspective is shaped in part by his experience as the child of Soviet Jewish immigrants. His parents brought him a deep appreciation for education, hard work, entrepreneurship, and the opportunity to improve the systems around us.

That mindset has guided his journey from scientist and virologist to biotech investor and institution builder.

In this wide-ranging conversation, Sean and Peter discuss:

• How Peter moved from studying biology to helping scientists translate discoveries into medicines

• Why the biotech industry needs stronger institutional memory, including a willingness to learn from failed experiments

• The limitations of AI in drug development, where generating a promising molecule is only the beginning of a years-long clinical learning process

• Why China’s expanding clinical trial infrastructure may have a greater near-term impact on the pace of R&D than AI

• How the FDA can be understood as a community of people working within a complex institution, rather than as an opaque gatekeeper

• Why CEOs must define their role by what it takes to advance the mission, including advocacy for patients, innovation, and better policy

A substantive discussion about immigration, science, entrepreneurship, AI, clinical trials, regulation, and what it means to build organizations that keep learning.

Ideas are like organisms.

They're like viruses, maybe, right?

They infect us and we can't shake them.

If that idea has merit, if it's the cure to a disease, you would want it to infect someone really competent and for that person to not let go and to fight like hell to bring that idea into the world.

I felt grateful to my parents for getting me out of, you know, the Soviet Union.

I'm from a country that doesn't exist anymore anymore because of some really big mistakes that it made, right?

And I'm very much an American.

And what I love about this country is the opportunities that it gives all of us to improve.

We're trying to develop a culture where people do not fear that AI will, you know, take their jobs, but will recognize that their job is to add value.

On top of that AI.

I gotta say, at the moment, not too hard, AI still has a lot of limitations.

For those who are wondering why we changed our wardrobe, we're not making a fashion statement, but this is the second part of our discussion and we could sell later.

China bringing its clinical trial infrastructure online in the last 10 years, but especially five years, is more impactful to the pace of R and D than even AI.

AI is not going to change the rate of enrollment of your clinical study.

The greatest threat to Americans getting drugs that don't exist yet comes from Americans.

They vote for politicians who keep banging the drum on price controls.

I think that a leader should be a thought leader.

Define your job by whatever it's going to take to complete the mission, not by what was in the job description or what is even normal for that title.

Hello and welcome to Precision Signals.

I'm Sean Kozen.

My guest today is Peter Kolchinsky, founder and managing partner of RA Capital.

I've known Peter for over a decade and I've known him to be a systems thinker, a relentless student of science, and someone with a rare ability to connect big picture ideas with the details that determine whether those ideas succeed.

Peter's own success has been unusual in both its speed and its range.

From writing a respected guide to biotech startups at just 23 to becoming a successful investor early in his career, to building RA Capital into a major biotechnology investment firm.

His journey has been defined by curiosity, discipline, and an extraordinary willingness to keep learning.

Peter grew up as the child of Soviet Jewish immigrants.

Born in Kyiv and raised in the United States.

His parents had experienced discrimination and hardship in the Soviet Union and.

But they also brought with them a deep belief in education, hard work, and the Possibility of progress.

His father was a mathematician and computer engineer who eventually started his own company.

His mother was trained as a mathematician, became a computer programmer and repeatedly reinvented her career, even starting a flower design business at one point.

From both of them, Peter inherited two powerful instincts.

The confidence to become excellent at something and the willingness to change direction when circumstances demand it.

Peter studied biology at Cornell, influenced in part by his father's belief that biotechnology would be the next great technological wave.

After seeing the movie Outbreak, he became fascinated by viruses and began working in virology, including HIV research, going on to earn his PhD from Harvard.

But over time, Peter realized that he was less interested in being the person who made one great scientific discovery than in helping great scientists turn their discoveries into medicines.

That insight led him early in his career to launch the Harvard Biotech Club and at just 23, write the entrepreneur's guide to a biotech startup.

His path then took him into investing.

He began working with Rich Aldrich, learned from both extraordinary gains and humbling setbacks, and gradually developed a philosophy centered on rigorous thinking, institutional memory and efficient decision making.

That philosophy became the foundation of RA Capital, the biotechnology investment firm.

Peter built around rigorous scientific analysis, deep institutional knowledge, and a willingness to make bold long term bets on transformative ideas.

It also led to Tech Atlas, the firm's evolving knowledge engine for mapping scientific fields, competitive landscapes, emerging technologies and failed experiments so that every new opportunity could be evaluated in the context of everything the field had already learned.

Today, RA Capital has grown to more than 200 team members and over $14 billion in assets under management with a track record that includes financing dozens of approved drugs, supporting more than 100 initial public offerings, and creating more than 30 companies.

In this conversation, we talk about Peter's background, his remarkable journey from scientist to investor, his experiences with the fda, the promise and limits of artificial intelligence in drug development, his definition of true leadership, and what it takes to build an institution that can keep learning.

Let's step into the conversation and trace the signal beneath the noise.

Hi Peter.

Welcome to Precision Signals.

Thanks for having me, Sean.

Happier.

It's great to have you here.

You know, over the years I've known you as a man of many things, but I think if I were to describe you with one phrase, it would be a systems thinker.

You're certainly look at the big picture, but you also have a keen eye and keen attention to detail, which is a very interesting combination.

But before we get into your professional sphere and your accomplishments, I'd like to start from the very beginning and Your worldview.

What I think may have helped shape your worldview.

You come from a Soviet Jewish family, and your early writing, in fact, has elements, I think, of your upbringing.

You talk a lot about utopias and when idealism meets reality.

Can you tell us about growing up as an immigrant in the US and what kind of influence your family background had on you?

Yeah, it's interesting, and I do hope that we.

When you said, let's go back to the beginning, I thought maybe you were going to go back to the beginning when you and I first met.

Actually, I questioned that for sure.

Yeah.

I definitely would love to share with your audience what I remember of you, you know, growing up as an immigrant kid.

I don't know if my experience is all that different from, like, anybody else who grew up as an immigrant kid, but your parents are always talking about, you know, how much easier, you know, I've got it compared to, like, how they.

They had it.

You know, they're always reminding you of, like, how special this country is and the opportunities and, you know, if you're not working hard to take advantage of it, then you're squandering, like, the awesome potential.

You know, my dad was like a Math Olympiad winner in Moscow and had perfect grades and, you know, being Jewish, heavily discriminated against.

And one of the big stories that I grew up with was how he basically had to do somebody else's master's work for them so that they could get a master's degree before his work could count towards his own.

And, you know, literally had to do twice the work to get the same credential.

And I did not grow up feeling like I had to deal with any of that kind of discrimination.

I felt grateful to my parents for getting me out of, you know, the Soviet Union.

You know, people now will sometimes say, like, oh, are you.

Are you Russian?

Technically, it says Ukraine on my passport.

I was born in Kyiv.

But the way I think of it is I'm from a country that doesn't exist anymore because of some really big mistakes that it made.

Right?

And I'm very much an American.

And what I love about this country is the opportunities that it gives all of us to improve.

The whole country is basically a country constantly trying to figure out how to improve.

People have voices here, and when they use them, like, there's actually hope of progress.

Place like the Soviet Union, if you tried to use your voice, I mean, good on you, but not much hope of progress, right?

So it took a whole lot of courage to.

To, you know, speak up over there.

And it was just the whole system that was designed to.

To beat you down, right, and scare you into submission.

And the U.S. you're, you're taught to question things.

You know, that's probably also part of the Jewish tradition.

You know, question things, don't accept anything.

Question, question, question.

So I grew up, you know, with my parents constantly encouraging me to debate things, unless it was their directives.

And then it's like, don't debate us.

We're your parents.

So I, I grew up with some of that.

And then, you know, seeing my parents evolve, I mean, they were 25 when they came here, like, seeing what they made of themselves, that was quite an example.

You know, my dad came, he worked super hard within his field.

He's a computer hardware engineer, and he reached pretty much limit of where he could reach within a fairly large company and left to start his own company.

And, and he became an entrepreneur.

When I was, I think in, in high school is when I remember really seeing him be the CEO of his own company and design machine vision systems and, you know, deal with customers and fly around and, like, win contracts.

And, like, you know, our family became better off as a result of that.

My mom was a mathematician by training, taught math, became a computer programmer in the US and then, like, changed careers repeatedly.

Like, just kept pursuing things that both were, were financially rewarding for our family in order to support her family, particularly when my dad took a big risk in starting a company.

It was my mom's income that, you know, really, you know, helped shore up our family, but also just made sure that our own life was interesting.

Like, at one point when she felt like becoming a flower designer, she did.

She just started her own company.

Like, started making flower arrangements and, like, would, like, land weddings and got big contracts and would enlist me, you know, to help, you know, prepare everything in the basement.

And then when she got tired of that, you know, she changed careers yet again.

Right.

And so I grew up with both that example of becoming really good in one thing and, you know, having confidence that you can rise up and that you can be CEO of your own company, like, within that your chosen field, within.

But at the same time, have that sense of, like, be nimble, you know, evolve, don't just follow in whatever the standard track is.

Like, invent your own career if you like.

Right.

That's how I think about what my parents gave me.

Very, very interesting, Peter.

Clearly your parents were academic in foundation, but they were also entrepreneurial, it seemed.

Your.

Your father was an entrepreneur who became successful.

It Seems.

And your mom?

Yeah, both.

Both of them real entrepreneurs.

Yeah.

Your mom was quite comfortable with risk taking in a way.

So you had sort of the risk taking, entrepreneurial background and gm, let's say.

Um, but you ended up going to Harvard or Cornell, I'm sorry, for undergrad.

And you studied biology.

How did that come about versus business?

Well, I mean, you know, certainly following my parents exam footsteps.

You wouldn't study business even if you want to go into business.

And entrepreneurialism, like you have to learn something.

You know, business is what you do with what you know.

Right.

It's not a thing unto itself.

Even when somebody studies business and then like goes and creates some business, odds are they'd probably tell you that.

No, I studied everything about whatever, warehouses.

And then I became the world's biggest warehouse owner, you know, but it's very difficult to just be a business person unless you're helping somebody else with their big business idea.

So like, what was I going to be good at?

And my dad gave me the idea.

You know, he's like, I caught the computer wave.

I think maybe that might be passing.

And the next wave is biotech.

You should go into that.

And I'm like, okay, so you know, I like science and I just figured my dad gave me a vector and I would just adopt that vector as my own.

And off I went.

And I, I saw the movie Outbreak when I was in college and I'm like, viruses look cool.

I want to play with viruses while wearing a spacesuit.

Just really dumb idea.

Nobody should actually want to do that because it's hot and sweaty and stinky and your experiments are very slow.

But that's not what they show you in the movies.

Right.

So I, you know, went and did a lot of work in a virology lab and I did HIV research.

HIV was a simple enough virus.

I kind of had a plan.

I wanted to get my PhD done as efficiently as possible.

And you know, herpes has 200 genes.

HIV at last.

Last I looked at 11 and some more straightforward.

And I think like just in that decision alone, like, you know, I should work on HIV.

It's probably simpler.

I'll be able to get my Ph.D. none faster.

You start to see that maybe I was never quite a scientist.

Maybe I was more of an engineer.

What is the most efficient path for getting, you know, from A to B.

And in my laboratory I really was intrigued with, you know, what is the most efficient way to do experiments?

You know, you talk about like not sleeping.

I didn't sleep when there were experiments that, you know, some people would do in a six well plate.

I would do it in a 96 well plate.

I just wanted more data.

I would shrink things.

I would, you know, get as close to automating as possible and just going to the extremes to iron out all the inefficiencies.

Great science is about having an insight and understanding your experiment and the data you're generating and formulating the next hypothesis.

But I feel like the.

The efficient execution of science was almost of greater interest to me than the underlying science itself.

And I kind of realized that.

And I realized that the odds that I was going to discover something great myself were slim.

But I thought I could help others who had great insights do something with those insights.

And I wanted to make a difference in the world.

Like, I knew that the application of biology was ultimately medicines, Right.

And so I wanted to be a part of launching a new medicine.

To be able to look back on my life and say, like, I help people.

You know, that was important to me.

But the odds that I was going to invent a medicine myself were slim if I'm really more of an engineer than a scientist.

And so I started thinking about how can I learn about the business of biotech and go into biotech and help, you know, truly great scientists turn their ideas into medicines?

So that's sort of the journey.

Interesting.

So you drift towards the business of biotech when you were at Harvard.

Yeah.

And you started the Harvard Biotech Club, right?

Yeah.

Clearly you had a keen interest.

But as a footnote, Peter, it's very interesting you mentioned the movie Outbreak because one of the best and one of the most elegant ways of characterizing viruses that I remember was.

Came from Dustin Hoffman when he was promoting the movie on one of the talk shows.

He says something to the tune of a virus is nothing more than bad news wrapped in protein.

And I was like, wow, that's an elegant way of describing it.

And really bad news wrapped in protein.

Yeah.

Stuck with me.

And I've actually mentioned that in my talks before.

Sometimes a lipid bilayer, you know.

Well, he had to simplify it.

But, you know, if we, we can convert, it can swap in some good news.

That's what Zol Jensen is, right?

Good news.

That's true.

That's.

That's true.

Yeah.

So Harvard, you started the Harvard Biotech Club, and you also tried to start a company with a postdoc.

One of your peers.

And, and you.

Then you realized that it didn't have legs.

So can you tell us more about that?

So, so I started up the Harvard Biotech Club because I realized, like, if I want to learn about the business of biotech, you know, I'm not going to get that from the graduate school, you know, virology curriculum.

And there was another student group that, that was sort of holding events, inviting speakers.

And I tried to work with that group, you know, to pursue some of the ideas that, that I had.

And they were like, well, we already know what we want to do and we've got our budget.

And so I realized I'd need to start up a different organization, raise the money to pursue the things that I want to do.

And I want to do more case study work.

I didn't just want people coming and giving lectures.

I wanted more hands on learning and sort of supplement the PhD program with some of the Harvard MBA case study method.

So over that first year, um, I organized so many events, invited so many speakers, did, you know, so many case study reviews.

Like it was a whole separate curriculum.

And so there was this postdoc in my lab who came up with an idea for a business plan or to start up a company.

And because I had been involved in starting up a business plan competition for the Harvard Biotech Club, he asked me could I help him?

And I was like, sure, why not just say yes to stuff, right?

Like the, the absurd confidence of a graduate student, you know, who learned a little bit.

And so I, you know, researched like, you know, what I needed to know about his technology to formulate something of a business plan.

His basic idea was that he'd found a way to reconstitute a lipid bilayer with purified membrane, you know, protein, so that you could have a bead with like a GPCR and its native confirmation on the surface of the bead, like just that one pure GPCR in it, which you could imagine if you injected such a bead into, you know, a mouse, you'd be able to, you know, derive antibodies against that one gpcr.

Up until that point, people were injecting like whole cells or partial, you know, sort of GPCRs embedded in sort of fragments of layers.

Lipid bilayer.

Right.

And so cleaner.

Yeah, it was supposed to be cleaner, but fundamentally, at its root, it was a platform technology, right?

It's to help you, you know, try to generate antibodies.

But the big lesson from the genomics bubble, uh, there's not that much value in a platform Technology, uh, you know, the industry was just going through its first lesson of the values in your drug.

So companies like Gene Logic would crater and die.

Nobody remembers that name anymore.

Whereas companies like Insight or Xelixis would pivot to what would eventually be their own lead drug.

And they would survive and prosper and become, you know, successful companies that still exist today.

And so in three months, I discovered, by meeting with venture capitalists and like, pitching this idea, you know, I discovered how much I didn't know.

It was such a great experience.

And so I told the postdoc, after three months, I'm like, yeah, I don't think there's going to be a business here.

Biotech was already starting to crater.

VCs were asking harder questions than ever before.

And so I came out of that thinking, like, man, do I have a lot to learn.

And I, I, I decided, like, why don't I parlay that really important insight, like, I have a lot to learn into an actual project that I thought I would make it part of the Harvard Biotech club, like, to go and learn what does it take to start up a biotech company?

And I invited like a dozen people to join me to brainstorm, like, how can we break up the work of researching what it takes to start up a biotech company?

There's probably a book like that would need a chapter on patent law, corporate law, raising money, you know, hiring people, you know, market research.

And a different person claimed each of those topics.

And then it's like, great, we'll all go research it, then we'll staple our findings together, call it a book, you know, we'll be done in a couple months.

Nobody actually followed up and did anything, right?

And I was just like, hey, guys, come on.

Like, why aren't you, why aren't you following up on this totally gratuitous volunteer project that's going to involve a ton of work that none of us have any idea how to, like, actually do?

And because, you know, that's how it goes.

Like, volunteerism is tough.

It's hard to get people to follow through on what they, in a, in a fit of sort of inspiration, you know, say, yeah, I'll do it.

But then, you know, when things cool off, they're like, who am I kidding?

I got my thesis I gotta work on and this and that.

And so as the people fell off, you know, I realized, well, why don't I just put one foot in front of the other and just start researching this and see how it goes.

And so I just committed to using what contacts I had, the various CEOs and VCs I'd met.

I would just interview two people a week.

And I figured if I just commit to that plan, like just uh, each person I meet with, I ask them to introduce me to two more and then just schedule it.

And just two people a week just keep bouncing around town, you know, Boston's a great place to do this and just interview them for an hour and extract everything that I can get out of them on what it takes to start up a biotech company.

See where I get.

And I interviewed about 40 people in, in parallel with doing my, my thesis research and writing that up.

I then wrote up all my notes.

And people were so generous.

I mean that's the other thing.

Like I was 23, you know, just a kid going around asking how do you start up a biotech company?

And people were generous.

And I remember that I'm so grateful to the people.

Like their names are still in the book that I, that I wrote from all that.

And I, I still know some of them, they're still around, you know, and, and I think about that and I try to be generous back.

So when young people ask me for advice, I remember the people that, you know, were probably 50 back then, like I am now, that were generous with me.

And I try to find the time to, to do that.

And I actually try to do that at, at scale.

And that's what was the Entrepreneur's guide to a Biotech Startup.

You know, a book that no 23, 24 year old has any right to write.

It's absurd.

What did I know?

And soon after starting what became my RA Capital career, like within a year or two, you know, I was like, oh my God, the first version is so embarrassing.

Like I already learned how much I got wrong in that.

And I rewrote it and I ended up putting out several editions.

I have to write it well enough that it won't be embarrassing in 10 or 15 or 20 years.

And it's been 22 years since I put out that edition.

And I.

It's on a website of Alexa.com named for my parents, of Alina and Alex.

And people still download it and I, you know, still have people reach out to me occasionally telling me like it was useful but, yeah, that's.

Yeah, it's very interesting, Peter.

You know, the first time I came across your book was years ago when I was at the fda.

Somebody sent me a link.

It was part of a curriculum at Emory University.

And he was, oh, you should check out this book.

And I was like, oh, I know, Peter, but I didn't know about the book until then.

So it was very well researched.

And it seems like it's still being taught in a lot of places.

Still is.

Right?

So, Peter, what do you think is one lesson from the book that's still true today?

So I'm going to give this credit to Peter Hecht for this.

And if Peter ever hears this.

Hello, Peter.

You know, it's been.

It's been years.

He was the CEO of Ironwood for a long time.

When I interviewed him, he was one of the few CEOs, which is absurd.

Should have, like, been heavy on CEOs, but I talked to a lot of VCs and lawyers.

He was one of the few CEOs I got to interview.

And he said, starting a company should pretty much be the last thing that you do.

You should try to kill your idea, you know, countless ways try to do your idea as part of another existing company, like, whatever.

Do not just start a company because you want to start a company.

But if you can't kill your idea and you're passionate about it and you feel like you just have to know whether it can work, whether you can, like, bring it to fruition, and the only way to do that is to start a company, well, then start a company.

And I thought that is the right way.

And it resonated with me because I didn't intend to start the Harvard Biotech club.

I tried to do pursue the ideas that I had within an existing organization.

I mean, who needs all the headache of starting up a new organization and all that, right?

So I already had sort of natural inclination to not want to waste time on, you know, creating redundancies.

So when he said that, I was like, of course.

That makes a lot of sense, right?

And I found that over the years, some people are like, I want to start a company, but they don't have an idea yet.

And I think that probably is not a great way to go about things.

You should try to be a part of something awesome.

And if later you have an idea, but you just can't seem to persuade others to let you do that, pursue that idea within the company, you're already at.

And if you can't kill your idea, well, then, yes, you're going to have that burning need to know that an entrepreneur needs to actually persevere.

So conviction is really the starting point.

And do you, do you think that some people can convince themselves of anything, even the wrong ideas that they have?

And if so, how do you view the world of biotech when it comes to the original idea?

Is it better if you have a scientist as a founder or a business person that uncovers a great scientific idea?

What I would say is ideas are like organisms.

They're.

They're like viruses maybe, right?

They infect us and we can't shake them.

Maybe they corrupt us to where we really believe in them despite all the evidence.

And in order for such an organism to live, it has to infect someone that is going to passionately pursue it.

And if that idea has merit, if it's the cure to a disease, you would want it to infect someone really competent.

And for that person to not let go and to fight like hell to bring that idea into the world, to attract investors and infect them with the idea, to attract, you know, colleagues and recruit them to it and, you know, get them to fight for the idea.

Right.

If it's a bad idea, you know, and it's gonna fail and it's just wasting the life of its host, then you would hope that the host can shake it, that that person will spot that it's not a good idea.

Right?

But the value of a really good idea to the world, you know, a checkpoint inhibitor that it's possible to mobilize the immune system to kill cancer, like, holy crap, that is a valuable, profound idea.

And there was a time that people made fun of that, like, ah, that'll never work.

But someone couldn't shake that idea.

And it's so lucky for all of us that those people that were infected with that idea fought as hard as they did to bring it into the world.

And so I think that if you think of ideas in that way, and for all the bad ideas you think about the, the forever huge progress for humanity of the good ones that make it, I think that it's cool that we let ourselves be hosts to these ideas, that they infect us, and that we should all probably be okay with being really passionate about our ideas.

If we err on the side of sticking with certain ideas a little too long and wasting a little too much time on the bad ideas, that's not the worst thing in the world.

Because later that perseverance you know, is gonna be really essential to making sure that the really good ideas make it right.

How many people told us, a beta will never work?

Come on.

Those antibodies, like, that's not the right path to, you know, treating Alzheimer's.

God damn it.

Despite all the evidence, all the failed trials, some people just couldn't shake the idea.

Now it turns out they were right.

And so, like, I think it's important that entrepreneurs be a little extra passionate and inclined to defend their idea, you know, beyond the point of reason, to make sure that those good ideas don't die.

It's kind of my wish to see our whole community be better at recognizing when an idea is not worth our time and have the tools to persevere and succeed.

When the ideas are worth our time, if we can calibrate ourselves just a little bit better, then we can achieve so much more progress.

And that's back to the engineer in me, right?

It's how can I help others who have the great ideas to succeed so that I can look back on my life someday and say, I made a difference?

Right?

So that's the systems thinking that you're talking about.

Can we talk about when you and I first met?

Do you remember that?

Do you remember the conference?

We're certainly going to get into that, Peter.

All right, but you know, just to.

Follow up on that, I admire what stood out to me about you.

You know, I've learned a thing or two about the FDA since you and I first met.

Well, all right, let's.

Well, let me talk about the analogy, because it's a very.

It's a great analogy.

And then we talk about how we met.

You know, you're talking about having a symbiotic relationship with your ideas.

And I guess if you're not learning or failing fast enough, then that could become a parasitic relationship in a way.

So be a host.

But as long as the relationship is symbiotic, makes perfect sense.

And it's a function of, I guess, self awareness and really understanding how the world works.

What is feasible in today's environment versus what's aspirational and utopian.

I.

How do you remember it, Peter?

So I remember I was giving a talk at some conference where I was presenting one of our maps or tech atlas maps, right?

So about 15 years ago or so, we started to try to keep track of the.

These more and more crowded, competitive landscapes.

You know, like you're trying to research what is a good company to invest in.

You know, somebody pitches you a lung cancer drug and you're like, well, you know, is this really the best lung cancer drug in development?

Let me see.

And then you go, look out.

And you're like, oh, my God, there's like 70 drug programs aimed at lung cancer.

Like, what are the odds?

This is the best one.

So we would map it out and these would be mind maps, you know, and we, at this point, we've got over a hundred of them with, you know, many, many hundreds of different diseases, you know, maps of, you know, rheumatoid arthritis, multiple sclerosis, all the different cancers, but also maps of capabilities.

So antibody, antibody drug, conjugate maps, gene therapy, you know, AAV maps, you know, you've got certain concepts, like if you had an allele specific oligo, you know, what are all of the diseases that are caused by a dominant mutation where you would want to knock down disease?

So anytime that you can say to yourself, like, what is this landscape of opportunities or of tools, competitive tools?

In our brains, we have something that we call a mind map, you know, but a lot is lost when one person tries to explain their understanding of a complex landscape, you know, to another.

And when you're part of a large team, and we were a growing team, and you're trying to keep the whole team on the same page and you're trying to explain to somebody, I'm really excited about this company.

They've got the best Ms. Drug or several Ms.

Drugs that can be combined.

It's hard for them to share in your conviction unless they kind of see this landscape.

You know, it's.

It's kind of like talking to somebody about, like, the positioning of your chess pieces on a chessboard.

And unless they're like a genius, where you could recite to them the location of every chess piece and they can just hold it in their head, odds are they're not going to get it right.

Most people aren't that smart.

I'm certainly not that smart.

I. I can't visualize a whole chessboard.

And so it helps to see it, to actually like, you know, lay it out, be like, see how the pieces are here.

This is why this pawn is really valuable.

I know it doesn't look different from the other seven pawns, but because of its positioning, it's defending the, the rook.

And that's key.

And this is why it's part of the end game.

And somebody would be like, oh, I see now why this pon stands out, right?

Why this CDK4.6 inhibitor is better than the other ones.

And so I was giving this talk, you know, Maybe with about as much enthusiasm as you're seeing, you know, and hearing here in my voice as I talk about this.

Right?

And.

And you.

And I chatted afterwards, and you're like, these are really interesting maps.

And I'm like, and.

And you were from the fda.

And I'm like, holy crap.

I'm actually meeting a human being from the fda.

You know, because to me, the FDA was this monolithic gatekeeper, you know, that decides whether companies are going to succeed or fail.

That's kind of how it seemed to me, Right.

I would hold my breath when one of my companies was unveiling, you know, the.

The results of its pdufa.

And.

And I was like, you know, the RA Capital team would be honored to just donate all of our maps to the FDA if it would help the FDA ultimately see the totality, you know, of what is going on out there.

We're not in competition with the fda.

Like, I wouldn't hand all of our maps over to another fund, but it would be, you know, point of honor to.

To know that our maps are of any service at all to the fda.

And you're like, that could be cool.

So you invited me, you know, down to the fda, and I brought, like, a whole stack of maps.

Right?

But then later it turned out that you and I, despite our effort to bring those maps to the fda, we discovered how difficult it is to get a bureaucracy to do anything with that, that it.

It deviates from the process that they already have, that it's very difficult to change.

And that was an early experience that I had with how difficult it can be to try to change something really big, even if you think you have a good idea.

Yeah.

Your talk at the FDA was remarkable, Peter.

I refer back to it from time to time because it was amazing to see you going head to head with the primary reviewers of an application.

And I think you knew as much, if not more, frankly, in some cases, about that specific application.

So it was remarkable to see that exchange.

I hear you about the FDA as a bureaucracy.

The institution sometimes behaves.

It has emergent properties.

It behaves different than the people in it.

And that's been one of the things that is, frankly, very difficult to tame.

And it's a journey that continues to this day.

What I also learned was that there are people within the FDA that are constantly trying to make it better.

Right.

And that it is possible to have a conversation with someone from within the FDA and to see how your conversation leads to them trying something.

Right.

So to me, the FDA was Previously inscrutable.

Right now that's changed.

Like, at this point, you know, I've had conversations with a lot of people that are, know, senior, not so much the current fda.

A lot has changed at the current fda.

But, you know, certainly people that have been at the FDA in the last several years, and, you know, that's come probably from my own tenure on seniority and realizing later that actually senior members of the FDA have for a long time, you know, made an effort to get out there into the community and to, you know, talk.

But it's something I would wish to impart, I think, to more people in the biotech ecosystem, that the FDA is not some monolithic bureaucracy.

It's made up of people that are trying hard, right?

And it is not any one person.

And it's, you know, it's kind of like a brain, right?

If each person's a brain cell, then, you know, uh, you can have a conversation with one brain cell.

But it's gonna take more than that, you know, before you can sort of influence the whole brain.

Sometimes a brain cell may disagree with the decision of the whole brain, right?

So it's worth trying to have those relationships and those interactions.

And if we can do that at scale, then the FDA does not need to be kind of this opaque gatekeeper that just seems to have a mind of its own and surprises us with its decisions.

You know, the sense that I had was that the FDA doesn't want to be a source of surprise.

It wants to be understood.

The people at the FDA would like to be understood.

Right?

And for me, all that started when you and I met.

It's really.

We just had that happen, actually.

We.

So we had a case where one of our companies was dealing with a.

A mechanism that had some risk to it, but it was a rare disease and it, you know, was potentially, you know, worthwhile.

And the FDA basically said, look, we just saw something with another program that was similar enough that confirms that what you guys are dealing with, amazing.

Is for real.

Like, it's not going to be something you're going to be able to surmount.

And so the company killed it.

And, you know, as much as it sucks to get that bad news and have to shut that down, it's way better than, than burning what money the company had on something that was never going to work.

And I hope that we can do a lot more of that.

I would argue that it's also our role to do that.

Right?

So we've had things fail in the past, and we're a Repository.

We've got institutional knowledge, you know, we've studied other things that have failed.

I mean, those maps are particularly useful.

Like, now that we've got some that are, you know, over a decade old, I can pull up, you know, what today's map looks like versus what it looked like five or ten years ago.

And we can show you, like, hey, don't just pay attention to the chess pieces that are here.

Would you like to see all the stuff that's failed, you know, in the last decade and why?

Right.

And make sure that you don't repeat those mistakes.

Like, there's a lot to be gained, a lot of efficiency to be gained from studying those mistakes.

And as much as we're a huge institution that is, you know, learned a lot of lessons, and we can share those with our portfolio companies.

There's nothing larger than the fda.

Right, I agree.

And again, you know, a journey that continues.

And I, I share your philosophy that I think biotech companies and founders and really anyone who's engaging with the fda, they should look at the FDA as a partner versus a regulator.

That's just there to give thumbs up and thumbs down to things, have a scientific discussion with the fda.

And unfortunately, what happens is that there's lack of consistency across the different review divisions.

And that's something that the FDA has been working on for a long time.

But one way to bring consistency and to minimize surprises coming from certain divisions is to build consensus outside the agency and take that consensus to the agency.

If everyone has the same expectations.

Yeah.

From the reviewers, from how they engage with the fda, then the FDA would have to respond accordingly.

So the, the advocacy that the, the work that you're doing, Peter, beyond investing, all the advocacy work goes in.

No patient left behind.

Stuff like, yeah, we can.

We can get into that has been enlightening.

Yeah.

Yeah.

And so, Peter, still a lot to unpack.

We didn't even go into how you got into investing after Harvard.

Methodically.

So let's start with that.

So you found yourself closer to the business side of things, as you mentioned, with the biotech club at Harvard.

So what happened after that?

How did you find yourself?

I did.

I applied for a job at Vertex Pharmaceuticals by emailing Rich Aldrich.

He was a chief business officer there.

He was the first business person to have joined Vertex, you know, shortly after its founding and had a great reputation for doing a ton of really creative deals that helped build Vertex up and get it really well capitalized.

And I had met him at an investment conference.

I traded my Harvard biotech Club business card for his much more valuable Vertex card.

And I hit him up for a job as I was nearing graduation.

He emailed back and he was like, yeah, I'm not at Vertex anymore.

If you want a job there, I can connect you the right person if you like.

But I was curious to know what someone like him was going to do next.

And so we chatted, met up for a coffee, he kicked my tires.

And he gave me an offer to join him on whatever it was he was going to do next.

A little consulting, investing in some private companies.

He had an account with some public stocks and cash in it and maybe I could help him pick some stocks, whatever.

And I was like, holy crap, this is amazing.

I mean, if I had joined Vertex, maybe I would have had a chance to interact with the big boss once every couple months or something.

But here I get to just work with him on whatever, right?

He was going to do next.

And he was.

He was like 48 years old, something like that.

So he was just a little bit younger than I am now.

That is when I pivoted to focusing on not just which stocks were cheaper than they once were.

Like, I love Decode genetics.

Oh my God, they sequenced everybody in Iceland or did a SNP analysis on everybody in Iceland.

That's so cool.

And they're cheaper than they once were.

Well, that's a terrible investment thesis.

But, you know, I lost money on Decode because that was my investment thesis.

And so I flipped to now paying more attention to like, what would actually make a stock go up.

And I made back the losses and ended the year flat.

And I did better than just the market.

So I recovered losses in.

And I got the bug.

You know, I no longer want to someday, like, train and for to be a CEO and become a CEO.

Now it's like, ooh, I want to be an investor.

This is fun.

And I think I'm awesome at it.

And.

I think maybe I was up like 14% or something.

And I'm like, wow, to be go from being up over 200 to.

Being up, like, 14% is very different.

Suddenly you realize, like, maybe I've got a few things to learn.

And that's important too.

I think to become an investor, you have to be humbled at some point in order to figure out how do you deal with that?

How do you deal with that setback and failure?

And I've done worse than be up only 14% since then.

So I've had plenty of humbling experiences in my career.

But the.

The point is, I was transformed by those first few years of focusing on Rich's account into wanting to be the best biotech investor that I could possibly be.

And I hired Raj as sort of my first whatever associate or something like that.

But just like I needed.

I needed to expand beside.

Because I couldn't cover all these names by myself.

So I knew Raj.

He had actually built the Evolexo website that the entrepreneur's guide is loaded on.

So he.

We got to know each other that way.

He would ask me about stocks now and then, and I would often, like, answer kind of in the Socratic method, because he clearly was smart enough and curious enough to get the answers on his own.

And he would actually follow up.

Other people would be annoyed.

They're like, just tell me what your best stock pick is.

Don't make me do work.

But Raj would go and, like, do the work.

And so he told me, like, that he was thinking of going to business school to eventually learn how he could be a biotech investor.

And I'm like.

Like, I don't know if that's necessary.

I didn't go to business school, and I'm at this point where I kind of need to expand, and I'm looking to hire somebody.

You want to join?

He's like, I don't know anything about biotech investing.

I'm like, I don't know anything about biotech investing either, but I'm figuring it out.

Like, you want to join?

And.

And Rich assured him that he'd write him a really good preference for business school if, like, things didn't work out.

And Raj was like, all right, I'll take a flyer.

And so I would say that RE Capital began when Raj and I started working together, because that was when Raj and I now needed to be on the same page.

We needed to communicate.

We needed to exchange ideas.

And it means that it was no longer enough for me to think that a stock was compelling.

I had to actually externalize.

Why?

And have it be gettable to somebody else.

Right.

And so we developed A.

A knowledge management system, a database.

Raj coded it up.

I learned to code off of Raj's code.

And we evolved the system to be able to track all of our notes and all the parameters that we would, you know, analyze about a company.

And it all began when Raj and I started working together.

Right.

So.

So.

Well, Peter in.

So it seems like the knowledge management system, the prelude to the tech atlas, was part of the fabric of Ari Capital from day one.

It's all about just staying on the same page.

Can you stay on the same page with other people?

You know, but for a lot of early funds or new funds, it's very hard to distract themselves with developing peripheral projects and knowledge management systems.

How did you manage to do that?

And when did you start to actually talk about your thesis in the early days to the investors, to your LPs, and what was sort of the size of the initial fund, if that's the proper way of.

I started with 4 million of Rich's money.

You know, more than tripled it, and I think probably was managing about $14 million of Rich's money.

When we first opened ourselves up to other investors and, you know, we raised some money to 25 million performed well.

You know, within a few years, we were at 60 million perform well.

And, you know, every time we would open the fund up to new investors, I would just raise, you know, a little bit more, maybe 25% more than what we had at first, you know, because I couldn't believe how much we were raising.

I mean, back when I was just managing, like, you know, 12 or $14 million of Rich's money, I couldn't even fathom the idea of managing a hundred, $100 million.

But at every new level of assets under management, we were learning things, and we were learning how to invest more and we were learning how to cut bigger checks.

Like, we found a lot of companies on our maps that we were just starting to make, by the way.

Like, we had our own.

More like, not.

It wasn't graphical, but we were tracking competitive landscapes and we could see which private companies would make for great public companies.

And we would just reach through the IPO window and invest in them in these crossover rounds, and then they would go public.

And, you know, we did incredibly well, and we did scores of deals, and we, you know, discovered that, like, if you're really efficient and you have a team that stays on the same page, you know, and you.

You try to Minimize the bureaucracy, and you're just focused on transmitting conviction as efficiently as possible to the top decision makers.

There's Raj and me, right?

Then you can maintain a very high pace of deal flow.

If you're going to be bureaucratic and you're going to make, like, the person on the front lines or analyst who spots that company have to, like, prove everything to you because you don't trust their judgment, you know, and in the end, you have to meet the company yourself, and you've got to decide for yourself.

You're going to be slow, you're going to lose deals.

Right.

And so early on, what Raj wanted to do was to build RE Capital into an institution where we could train up people whose judgment we would trust enough so that once we saw that they and maybe a couple of peers that were on those front lines liked a company and we could read their thesis, we knew that that person was so well trained and already had enough pattern recognition that we really should just approve the investment.

And so that allowed us to invest much more efficiently.

And Raj and I discovered that where we were really most needed was maybe leaning in when there was a company that's like, no, this is really special.

Like, you've identified a company where really we should invest more.

Why not more?

And sometimes a person would say, well, I'm actually really nervous about this or that side effect.

Oh, okay.

That wasn't quite clear in the thesis.

I, I get why you want to keep it modest for now, but when the person's like, yeah, I guess you're right.

It is pretty special.

It's like, great, so let's cut a much bigger check.

And so, like, that was where we could add the most value.

And over time, we created a, A, A team of people, many of whom are now our partners, that were empowered to really make the judgment calls on the front lines.

And, you know, we could just read the investment thesis and we could just feel like we were there.

They were answering questions in exactly the way that we would, you know, want them answered.

And it made our job easier.

We were like all brain cells that were alive and doing our respective jobs and synchronized and able to be decisive.

You know, it's when all the brain cells of a brain are sort of aligned, it can be a very efficient brain.

Right.

Well, that.

That's your engineering mind speaking again, Peter.

And I would also Point out we're a 2 portfolio manager firm.

You know, Raj may have started off as my associate, but along the way he became my co PM and co founder.

And that means that we had four eyes on the portfolio, which means you can afford to take one or two off from time to time to do things like build a Tech Atlas division.

Or in my case, I wrote another book later, the Great American Drug Deal, when that seemed like something that might be necessary.

Uh, and we've been able to pursue a lot of different initiatives because Raj and I, you know, had some of that redundancy.

Um, yep, yep.

We'll have to also delve into no Patients Left Behind.

You're a nonprofit.

Going back to.

So Recapital is quite large.

200 Plus people working there.

And do you think your knowledge management system, the Tech Atlas foundation, has helped bring everyone to the same page since sort of harmonizing everyone's thinking is so critical in what you do?

So it's yes, but not just because, you know, there's knowledge in the knowledge management system, but because there's a discipline for how to communicate so that other people can understand.

And so when notes are written in a way that they're not just useful to you, because we can often read our own notes.

Right.

But when they're written in a way that's meant to be understandable to somebody else, when you put the bottom line at the top, you know, and you're empathic to how somebody who's busy and is looking for a clear answer is going to, like, read your notes and you make it easy for them to get it, then you're basically making it easy for all the brain cells in the brain to communicate cleanly with one another.

Right.

And that's the discipline that we've got, the maps.

We actually don't look at our own maps all that often because it's the updating of a map that causes the upgrading of knowledge systematically across, you know, certain members of the team that we then are able to pull in to analyze.

A company that comes along, you know, we were able to pounce on certain opportunities in.

In certain cancer fields or in neurodegeneration or whatever that we hadn't invested in for years.

We had no reason to diligence because there was nothing investable in them.

But we were still maintaining maps, and we had members of the team that were expert in those areas because that was their job.

It's like, that's okay.

Like, we recognize nothing's been done in Alzheimer's in a long time, but someday something will crack and will become compelling.

We need to be able to sense that.

So you keep updating the Alzheimer's.

So, like, when you spot something, it looks like hmm, this might be interesting.

And you pull in that person and they were able to ask exactly the right questions and probe deeply.

And the, the CEO and CSO of the company are like, wow, you guys are asking the exact right questions.

You're the most prepared investors we have met yet.

Then you know, when you get the answers that you need, you know, you're operating at the extremes of what you know, human knowledge can get to and that allows you to be decisive.

Right.

When you don't know anything about a space, truly you know nothing about a space and you meet a company that looks good, you know, you kind of hesitate.

You're like, I don't know that I'm smart enough to have conviction in my own, you know, positive bias towards this company.

Like, I like them, but I can't feel, I can't help but feel like maybe I'm missing something.

And so we didn't have that problem.

We knew that when we liked something after asking like some of the hardest and most appropriate questions, that we were allowed to like it and therefore, go ahead, make the judgment call, invest.

Right.

So we were able to invest in some things that took other people maybe a little bit longer to get comfortable with.

That was, I would say, our edge, that we were pre doing a lot of the diligence work.

Our first meeting with the company was closer to what somebody else's second or third meeting.

Interesting.

And I would guess probably there's a number of other firms out there that at this point are operating in a similar way.

Well, you know, Peter, I have to say you've been doing it systematically for a very long time and it's part of the fabric of what you do at RA Capital, which is quite unique.

And so a two part question.

Are you using AI to advance tech?

Atlas and if so, I think you mentioned that some of the insights and the benefits of the knowledge management system is actually in the process of uncovering the facts.

So if you are delegating that to, to AI, do you think you're going to lose that institutional memory?

Yeah.

So we tried and several years ago we spun up, you know, a, a team that we told like, just focus on building whatever you can with AI, try to create tools that are going to be useful.

And early on like everything they built was pretty bad and they were like, we can't seem to make it work.

It's like, no, no, that's the point.

See, that's useful knowledge to me.

To know that whatever you're creating with AI at the moment sucks is useful.

Right?

And then, like, three months later, it's like, how about now?

How about now?

How about now?

And, like, we would constantly check, and stuff got better.

And so we knew we had our finger kind of on the frontier of what AI could do.

And we were constantly comparing, like, what is the quality of an answer we were getting from one of our tech Atlas associates versus what AI would give us?

And that Delta was what told us where AI was.

We currently have a sense of what is the best that AI can do.

It's deeply unsatisfying.

Somebody comes along and says, my AI is going to give you molecules that, you know, are not going to have a 90% failure rate.

It's only an 80% failure rate.

And I've heard this pitch, by the way, like, instead of a 10% success rate, it'll be 20%.

Isn't that worth a lot?

Yeah, that would be worth a ton.

But how many molecules do you have to put into clinical trials and have them work before you're like, yeah, I'm confident that you're actually.

That you've got a 20% hit rate, right?

I mean, it's not five.

It's not like, look, you got one out of five, right?

That's not gonna be convincing.

Maybe it's 25.

Like, when you put 25 programs in and you see, like, five out of 25 worked instead of, like, only two, you might be like, yeah, I think this AI is good.

How long will it take a company that claims to have a really brilliant AI, you know, to get 25 drugs through its program?

Years, right?

Yeah.

And then, you know, how much is a will AI have evolved?

Right?

Because technically, you got to keep the AI static, you know, and then after, like, seven years, if you've got 25, you know, shots on goal, you can say like, oh, yeah, look, we're five for 25.

Great.

That model that you locked down six or seven years ago, we now know that it's, you know, possibly got a 20% success rate, right?

But by then, people will be like, no, no, I've got better models, and I. I think we're at 30%.

And so, like, it's just such a long time before you will ever place your faith in this model and say, you know, let's just defer to it.

It has a higher rate of being right than human beings.

And part of the limitation is that you're training these things off everything that's been done.

But by its nature, you know, biotech is constantly pushing the limits of what's known you know, about human biology, and we just need to take chances and have a high.

You know, we're willing to have a high risk of failure to learn new things.

And so, you know, my firm, we're trying to develop a culture where people do not fear that AI will, you know, take their jobs, but will recognize that their job is to add value.

On top of that AI, I gotta say, at the moment, not too hard.

AI still has a lot of limitations.

There's a lot of work, a lot of tokens not there yet.

A lot of tokens.

How do you think about AI in biomedicine?

What's meta, as you've characterized it in the past, and what's real?

And how do you differentiate between the two?

Yeah, so I think that there's a lot of hype in the application of AI to biotech and drug development.

Um, I also have started to see that it's become more common to point out that it's.

There's a lot of hype, and so maybe there's now less hype.

Um, I think that you can come up with great molecules much faster, right?

Molecules that a human being would look at and be like, ah, this is a great molecule.

I wouldn't have thought to do that.

Great, you've got a molecule.

Still no guarantee it's gonna work, you know, because oftentimes you're pushing limits of biology.

You just don't know biologically what will work.

You know, I'd say physics is a lot better at, you know, sort of working as theorized.

You know, like, we still have things that don't quite make sense in physics, but for the most part, like, mathematicians can, like, anticipate that based on the math, there should be this particle.

We're going to call it the Higgs boson.

And if you just get your.

Your particle colliders to a high enough energy level, like, we should start to see, you know, tracks emerge that are indicative of the Higgs boson being real.

And if you get enough of those things, you're like, yep, there it is, just like we predicted.

Biology is not like that.

Right.

You know, you could predict all you like based on your pathways.

If we inhibit this, we should be able to cure that.

And then it doesn't work.

And you're like, God damn it, why not?

It's like, because biology is messy, and we.

We know such a small fraction of what it would take in order to make it predictable.

And so at the end of the day, like, you gotta just take those molecules that your AI is Like, oh, I swear to God, this is a great molecul.

And then you gotta actually put into an experiment, which is gonna take how long?

It's gonna take how many years to generate the clinical data to know whether your AI is right.

It is the absolute slowest learning loop that you could, you know, apply AI to.

It's deeply unsatisfying.

And so, you know, my firm, you know, it gets tons of stuff wrong.

We lose money on tons of experiments.

We don't consider them a loss.

We consider them the price, you know, to learn, you know, and ultimately, you know, change our.

Change what we look for.

So if today somebody came along and said, oh, we have a way of knocking down only the mutant allele in Huntington, I'd be like, yeah, I don't know that that's good enough.

See, the trouble is we've already done that and hasn't panned out as like, an obvious clear benefit.

Something's up with Huntington's Disease.

Same deal with C9 or ALS.

Like, certain things just are not working cleanly as, just like, observable outcome improvements when you knock down the one pathogenic, you know, allele.

Right.

We've already paid the price to learn that.

And, you know, maybe, you know, some entrepreneur overlooked those clinical data and was so focused on coming up with, like, a small molecule that can do that that they miss the fact that.

Yeah, but that won't translate.

That's not a single ARM trial.

We won't know that that works until you run a fairly large, controlled phase two program.

And even then, we won't exactly expect success.

So, you know, Huntington's to me is a little more like depression.

You know, like, I'll take a large outcome study before I believe that your newfangled mechanism of action is going to work.

You know, a lot of folks do not differentiate between the engineering success that we've had in the world of AI, RFD fusion, AlphaFold, and the problem that one would encounter when those AI designed molecules and monoclonal antibodies go into clinic.

We still don't understand human biology that well, and I think people are becoming smarter about that.

I think that was quite obvious at JP Morgan this year, that a lot of the AI hype was gone.

People were still talking about it, but it was much more grounded.

But probably a lot of wrong companies are still being invested in, and I think we're going to learn those lessons again, perhaps the hard way.

Yes.

Hi, Peter.

Great to see you again.

And for those who are wondering why we changed our wardrobe, we're not Making a fashion statement.

But this is the second part of our discussion.

A week or so later.

Yeah, we've had a little time to think about things, so.

Yeah, absolutely.

Comments now.

Excellent.

I think we had an amazing discussion.

We covered a lot of ground.

But, you know, one of the things you said stood out to me towards the end of our conversation.

You said that China's biotech ecosystem may be more consequential than AI, which is very interesting and bold statement to make.

So how do you think, Peter, we can best balance national security priorities with IP concerns and other concerns that a lot of people have regarding dealing with China with?

What you suggested is essentially an opportunity to learn from what China is doing.

Right.

So I think it's important to break each of those things down so that we were speaking in specifics because you could throw a term like national security around and, you know, people can nod and be like, yes, national security.

But like, what exactly do you mean?

What is the exact threat that one is envisioning?

And my guess is that it means different things to different people.

You know, if we're talking about creating bioweapons, special viruses or whatever don't exist yet.

Like, yeah, I'm with you.

We shouldn't be collaborating with anybody on that.

I hope we're not working on those.

I hope we're working on countermeasures against those.

Right, so no argument there.

Now, some people then say yes, but any kind of biotech collaboration surely teaches people, and then they can use that, you know, for harm.

Well, that's a slippery slope.

So tell me how making a small molecule against, you know, a given cancer target, you know, to hopefully shrink tumors, like, how exactly is that making somebody smart?

And they're going to make a virus that could kill everybody.

And so if you're going to make up a hypothetical threat that some sort of small molecule or antibody collaboration or whatever spills over into knowledge on how to make, like, lethal weapons, you know, and, and say, therefore, let's just not collaborate at all.

And it'll reduce this uncalculated risk of bioweapons.

It's not free.

We're, we're not reducing this risk for free.

We're concretely causing ourselves harm.

We will not make as much progress in the, our, our fight against autoimmune diseases and neurodegenerative diseases like Alzheimer's and Parkinson's and cancers, you know, that are killing, you know, thousands, millions of Americans.

Look at AI now, it's not even a question of international relations.

It's also what harm might AI cause?

Not sure.

We could scare ourselves into saying no more AI, you know, stop all that, but we don't.

And so let's be as rational as we can be.

And I think there's a ton of good that can be done with all kinds of biotechnologies that are far more relevant to curing diseases.

And we can maybe just put a hard ban around, do not work on engineering viruses, you know, that could hurt people.

There's other types of national security concerns.

We've got $300 billion per year of trade with China.

A lot of it is based on buying like, crappy plastic toys and clothes and all sort of tchotchkes and stuff like that that we don't need.

So.

So if it's like, don't send money to a country that could be our enemy, it's like, why don't we start with not buying all that crap, you know, if we're serious about that.

And then like, after we've completely stopped sending money for all kinds of stuff that's not important, then when the last few billion dollars left concern paying China for molecules that could cure cancer, we'll talk about whether that's, you know, indeed critical.

I would agree with China hawks that if we're worried that we might get into, you know, a tussle with China that results in China turning off our access to medicines that are part of today's standard of care.

Yeah, we should friendshore all that manufacturing.

It'll take a while.

Particularly, I'd say, in the realm of generic drugs.

You know, novel medicines make up only like 10% of all scripts, 90% of scripts are for generic medicines.

And China has a role in the supply chain of, you know, a lot of generic drugs.

So we should probably create necessary incentives to shift a lot more China free, you know, production.

You know, hopefully we maintain good relations with India because that's the other source of a lot of generic drugs.

And eventually, if we can say we are not at risk of any of today's standard of care or any future standard care medicines, you know, being choked off by any kind of geopolitical tension with China, we will feel more resilient, you know, against, you know, that threat.

Right.

If we ever get into some kind of beef with China.

But let's face it, Americans don't really care about the drugs that don't exist yet.

How do we know that?

Because the greatest threat to Americans getting drugs that don't exist yet comes from Americans.

They vote for politicians who keep banging the drum on price controls and saying, don't worry, we're going to price control those big bad pharma companies.

We create that threat here.

Internally, we disrespect the process of innovation and come up with policies that undermine it.

Makes sense.

You hit all the points that people bring up.

There's also the undercurrent of the dependency making us lazy and really compromising on the innovation and the innovative spirit that has made our biotechnology ecosystem what it is today.

And the argument there goes that, well, a lot of the assets that we're acquiring from China as part of that, some argue that there's a wealth transfer that's happening.

These assets are not really first in class molecules.

You know, they're fast followers.

They're not really enhancing the innovation ecosystem.

And on the manufacturing front, there's already a decoupling that's happening.

A number of biopharma companies, as you know, have made large investments in the US for manufacturing because of some of the tough lessons that were learned in the past few years, especially during the pandemic.

How do you respond to that in terms of the innovation ecosystem in China?

It's not really producing first in class therapies and the clinical trial ecosystem, sure, it may not be as robust as Australia yet, but it's getting there.

Eastern Europe is already rising to the occasion and making some steps towards being able to handle more clinical research, especially for proof of concept studies.

So that leaves a big question.

You know, what are we doing wrong in the US that we have to be even looking China and Australia and increasingly Eastern Europe.

How do you, how do you address those concerns?

Look, there are some things that we're doing that make conducting clinical trials in the US harder than it could be.

So in that regard, yes, I would argue it's wrong.

But at its limit, we've only got about 4% of the world's patients.

Like, there's only so much R and D you can do when you have, you know, such a small fraction of the world's patient population.

And we are one of the wealthiest countries in the world, you know, which means that it's kind of an inconvenience for a lot of people to enroll in a clinical study.

Right.

If you've got cancer and you're dying, it's your highest priority, you'll do that.

You know, we can enroll, you know, patients in the US there, but if it's anything less than that, you know, you're competing with a really high quality of life that people have and asking to come in for repeat visits.

And blood draws and this and that and take risk like they're, they're not as eager, right?

And so we end up with traffic jams when we try to do clinical studies.

Like, it's near impossible to do a lupus clinical study, a, a phase two study for lupus in the US Anymore.

Um, once you have good phase two data and you're running your phase three, it's easier because now patients are like, oh, that, that drug's actually proven.

Like, I want to get into that clinical study, but in terms of the, generating the proof of concept data, that's really hard.

Whereas China, they're just coming online, you know, in the last five years, they've built out remarkable medical centers and have healthcare systems that aggregate data across tens of millions of people so that a doctor can pull up on an iPad, like, how many lupus patients do they have in their attachment?

And when they call those patients and say, I'd like to come see you, I want to talk to you about a clinical study, you know, I get the sense that there's, you know, much more engagement from the people at, like, oh, this looks like an opportunity rather than, oh, I can't be bothered.

Right?

And so China's got, you know, more than four times as many, you know, people.

And I would argue much more than that in terms of a multiple of patients, like, open to hearing about a clinical study.

And so the more people you can bring online, the more trials you can do.

And each trial teaches all of us.

So that's why I said before that China bringing its clinical trial infrastructure online in the last five, you know, 10 years, but especially five years, is more impactful to the pace of R and D than even AI.

AI is not going to change the rate of enrollment of your clinical study.

Right.

But, you know, what might change is the rules in the US about compensating patients.

You know, you could if, if you're poor and dependent on, on Medicaid, right?

And you know, there maybe you got housing pro programs that you're dependent on, you know, to help you with your rent.

If you get paid for a clinical study that counts as income, you might blow your qualification for these government assistance programs.

And when you consider that sometimes it's disease, you know, disease burden that drives people, you know, into poverty and keeps them in poverty so patients might be enriched among people who are dependent on, you know, these government programs, then to basically disqualify, disqualify them from these programs because you count, you know, the patient trial compensation as income.

It's kind of stupid.

There's also tort reform.

If you want to be able to accelerate a given clinical center doing an investigator led study and maybe not worrying about their local institutional irb by trusting some central irb, you also got to help them feel confident that they're not going to get sued if something goes wrong.

Right.

And if they, you know, try to act more like Australia and you know, try to be more quicker and nimbler, but then they get sued as a result, they get wiped out.

So, you know, we're pretty litigious country.

How are we going to pass tort reform?

I mean people talk about that all the time.

That's not easy.

So, you know, we should work on these things.

I don't know how long it'll take.

I don't know if changes that we're going to implement in a couple years or it may take a decade or more of debate and wrangling or whatever.

But this is the kind of country we are that debates things like this for a really long time.

You know, other countries, somebody snaps their finger and the rules change and you know, things just become easier.

Now some people would say yes, but what if they've basically crossed a line and they allow all kinds of unethical studies and, you know, that's why it's faster.

Well, you can look at that, you can look at what their rules are.

And China knows that if they ultimately generate data in an unethical way, it won't be accepted by global regulators like the FDA and emea.

And so they've actually harmonized their good clinical practices to be consistent with the rest of the world's.

Yeah, well, you know, clearly that's not stopping Congress from scrutinizing those ethical practices a number of.

And they should.

And if they do their analysis fairly, what they'll see is, yeah, this, this isn't the droid that we're looking for.

Yeah.

You know, and we'll see whether they care about getting to the truth or whether this is, you know, just a, you know, a political exercise with a foregone conclusion.

But you also asked like, what's the impact on US innovation?

And I think here people are missing two, two sort of consequences to China coming online.

One is fast followers.

You know, somebody comes up with a novel types of drug, you know, the first KRAS inhibitor that actually looks like it generates a clinical response, bang.

There's a flurry of interest and lots of companies try to develop better KRAS inhibitors.

That's been going on my whole career right These could be US companies, European companies, you know, and first in class innovators complained about the annoyance of having to compete with all these other companies.

But you know, that is the intent of the patent system.

Like you get a patent on your molecule but you also disclose how you did it so that others now are sort of able to see what you did.

And they have to come up with their own way.

Right?

They don't get to copy your way, but they have to work around it.

And if your patent is broad, you know, then it's, it might be quite hard for people to come up with a different way, but eventually they may.

And then that's a different drug, maybe in the same class.

And if it's better, well then society has gotten exactly what it wanted.

It spurred competition and you know, it got best in class rather than merely first in class.

Remember B, that was a twice daily drug that didn't even have much weight loss.

Imagine if that's all we had, you know, sorry, you're first in class.

You deserve to have the market to yourself forever.

No fast followers allowed.

Well, I'm glad that's not how it works because now we've got amazing drugs with tremendous weight loss that, you know, with the, that you give once a week, that is a markedly different profile.

You do not see people taking Baeta, you know, these days they're taking Ozempic and Mounjaro and other drugs.

So I'm not investing in that US company developing a not quite as good, fast follower to the Chinese best in class drug.

The fact that I even know that that drug exists in China anywhere in the world is basically going to keep me from investing in anything lesser because I know that eventually patients demanding access to that drug will win out and policymakers will change their mind.

I don't believe protectionism holds.

Right.

No, I'm with you.

What do you think, Peter?

Do you think it's unfair that a lot of US companies that are dealing with Chinese biotech ventures, they can actually take equity?

So there is a good amount of protectionism against the US coming from China.

We can't take equity positions in any of those companies.

Sorry, clarify for me what you mean.

Well, you know, it's not easy for US based companies to take a piece of a Chinese biotech company to make equity investments in those companies.

I hadn't heard that argument before for.

Actually, I think technically speaking you can.

The question is whether you'd want to, seeing as if that company is actually incorporated in China, subject to Chinese, you know, securities law.

Which we don't have very much experience with.

I don't know how I'd feel about, you know, my money being secure.

But the value of any such company is, I, I view is largely in its assets.

So when you license a drug, you're basically getting the asset that you want, right?

So maybe in the extreme you might think of it this way.

If a Chinese company has five drugs and you wish you could own 20% of it, but technically you really only like one of their drugs, you know, drug number three, you know, well then licensing drug number three and you know, essentially getting, I don't know, 80, 90% of the economic value of that drug, you know, is getting the best 20% of that company.

So I, I, I don't see, no,.

I think the argument there, you know, we can talk about this for a long time, but perhaps, maybe a thought experiment as we close the loop on China.

Let's assume that U.S. investors and companies cannot make equity investments in Chinese biotech companies.

And Chinese buy two companies start to produce more first in class therapies, then we may find ourselves in a few years in a very tough position where we cannot compete with China.

Well again, that suggests that US innovators are incapable of competing with Chinese innovators.

I don't see why that is.

We're smart.

And if there's some project where you say like, oh gosh, like Chinese companies are way better than me at, at, you know, drugging this particular target, you know, X, Y, Z, 7, well, go apply your skills to something that you know, they can't do.

But there's nothing like, you know, supernatural about Chinese biotech innovators.

They have learned all the same basic science that we have.

You know, they're hard working people, right?

And there's a limit to what they can do.

And Americans, you know, should push themselves to the limit of what they can do.

We've got a lot of advantages on China.

We've got some of the best academic institutions, right.

Our labs are incredibly well funded.

There are US companies right now that we are investing in that have better technology than anything that we see in China.

So like we will specialize now if Chinese companies come up with really great medicines and, and they say, and we don't allow US investors to invest in them, they want to keep like all the profits of those medicines to themselves.

Well, you know, there's no law that says that those companies have a right to market their drugs in the U.S. we could basically tell them, look, if you want to be able to sell your drugs in the U.S. a, they have to be manufactured outside of China.

Right.

We don't want you ever to get us addicted to a really great new standard of care, but then be able to shut off access.

Yeah, that's going to be interesting to see what happens over the next year or so.

Peter, I want to make a pivot to something you told me recently which was quite intriguing.

You said that most CEOs are not leaders, but project managers.

Yeah.

So.

And you know, so if we think about that statement, especially in the context of biotech and biopharma where there are sustained pressures on multiple fronts, including pricing.

So what do you think defines a real leader?

And why do you think that many CEOs hesitate to lead?

Yeah.

So think about leader.

I think that a leader should be a thought leader.

Now you can have a leader of something that is already really well prescribed.

Right.

You can have a doctor that adheres to standard of care and they are leading you through standard of care.

You think of them as a leader, I suppose, But a thought leader is somebody that's operating at the frontier of standard of care and understands how data are changing and how standard care may change.

Right.

So to the extent that we think of different doctors as, you know, some of them being thought leaders and others not, then consider what does that mean for a CEO of a biotech company?

Well, you know, there's a generally prescribed process for developing a drug and recognizing like, when is it smart to invest in a drug program and when might you like say, no, not this program, let's fund this other program.

And I would argue that for a long time we got to simply trust that if you had a patent, you know, you could then count on, on average about 14 years of protection after launch.

You know, because of Hatch Waxman, 5 year patent restoration limit, 14 year cap or whatever, the average has been about 14 years, then you would engage in market based pricing.

You didn't even need to know what that was.

If you were more of a scientist focused on phase one, phase two, you know, development of your drug, you sort of know that, well, comparable drugs sell for about 150,000.

So I think my drug might sell for 150,000.

You didn't even need to know what market based pricing actually is.

You could just plug in 150,000 as your projected price.

You could do your assessment of how many patients there are.

Investors would be like, yeah, we can multiply the math.

We can look at your probability of success.

They'd give you money and you just needed to execute right?

Now you were CEO.

CEO, that's an impressive title.

When I was a teenager, my dad was CEO of his own company.

I wanted to someday be a CEO.

That felt like the epitome of, you know, of one's career.

Trouble is, sometimes these axioms that are processes are based on like, these processes work as long as, you know, there are things called patents, as long as there's a thing called market based pricing.

Well, when Congress starts proposing something like Medicare negotiation that, you know, has certain exemptions to it and all that, they're basically altering the rules.

You know, it would be as if somebody started altering the laws of physics, right?

And altering gravity, where suddenly gravity, you know, goes a little bit to the right instead of straight down.

Like, how would that change the world?

Well, somebody who really understands the world would immediately know what the consequences are of gravity starting to be a little to the right or, you know, whatever, right?

Whereas somebody who doesn't understand, like, even though they were perfectly able to predict how an apple will drop before, simply because they've observed it a bunch of times, the moment you start changing, you know, the laws of physics, they don't know what that means and they assume the apple will still keep dropping straight down.

And so what I witnessed was how some people didn't think Medicare negotiation was a big deal.

They didn't see the importance of nine, the nine year pill penalty as we call it now.

You know, they said, well, I would still have my patent.

I'm like, what is the value of a patent if you can't negotiate your own price?

They didn't see the linkage between a patent and market based pricing.

Well, there were some people who understood the consequences and they said, that's terrible.

Wow, that would be really bad for innovation.

And so at least they could, like, they had an agile mind, they could understand this, right?

But they chose to do nothing.

They said, well, it's not my job.

I don't get political.

And then it's like, well, wait a second, you're a CEO.

Like all these people that work for your company are dependent on, on you for your leadership and if this law passes, like, you will be defunded.

They said, yeah, that would be terrible, but it's still not my job.

I don't get political.

And then there were others that said, I'm the CEO of this company, I am the leader of this team of people that has a mission to like develop this drug and make a dent in the universe and like forever leave this disease better treated.

And this, this law, it's coming from a place of misunderstanding.

I'm gonna advocate on behalf of everybody who cares about this project that I'm.

I'm overseeing this company, that I'm CEO.

Like all the patients that are dependent on us, I will do what it takes to see the mission through.

And so to me, that's what being a leader means.

You, you know, ultimately define your job by whatever it's going to take to complete the mission, not by what was in the job description or what is even normal for that title.

Yeah, interesting.

Do you think that's the responsibility of more established companies?

Because you probably, as an investor, wouldn't want one of your portfolio companies to all of a sudden start to think too much about advocacy.

Distracting.

No, I want them to.

I mean, look, we.

We helped build no Patient Left Behind.

We started it, and then every time.

Right.

Yeah, it's a nonprofit that advocates for certain reforms, you know, first dollar coverage, encourage your CEOs.

Yeah.

When.

When we write letters, which, you know, I often do with thought partnership of others in the biotech industry, including people who may.

May be CEOs of our companies, we then put them out, you know, and ask for others who read the letter and agree, like, sign on.

And of course, I put it out to our portfolio companies.

And, you know, sometimes I get responses from people like, well, we don't get political.

We don't sign.

I also get that from investors who will say, like, well, my LPs don't want me to get political.

Like, really?

Because I've got like 600 LPs, probably a lot of them are the same as yours.

And none of my LPs seem to mind that I'm out there actively defending innovation.

I mean, it's not like we're debating, you know, drinking ages or something like that.

I don't know what the scientific or economic basis is for saying it should be 18 or 17 or 19 or 21 or whatever.

You know, we're talking about things that have, you know, mathematical consequences for, you know, whether or not innovation is worth funding.

And so I do think that, you know, if policymakers start to mess with, you know, things that are first principles, I mean, can you imagine if, like, policymakers said we're going to outlaw covalent bonds?

Are we going to call that politics?

I'm not going to, I'm not going to come to the, you know, get political about that.

It's like, no, dude, we would go to them and be like, you don't want to do that.

Literally, the fabric of the universe would Fall apart.

Like you don't want to do that.

Right.

And so why is it that people hide behind this, you know, seemingly rational response of, well, I stay out of politics now.

You're hiding because literally everything's political.

Right.

It just means you don't care enough.

And if you don't care enough, I don't know that you're a leader.

Yeah.

Or they're afraid, which could speak to the fact that, as you said, it may not be the right leader for the job.

But, Peter, you.

You mentioned the advocacy work that you've been doing through no Patients Left behind, the letters that you've been writing.

One of the letters was supporting Rick Pasder as the new FDA commissioner.

Can you tell us about how that come about and what do you think about the FDA today and the leadership that is currently at the fda?

Yeah, well, so the FDA right now is sort of in a transition period.

Right.

We don't have a commissioner.

We're not really sure what the future leadership will look like.

And it appears that that is way better than having Makaryan Prasad at the top.

So it's an improvement, for sure.

And, you know, we had written letters before calling out what, what we saw as evidence of bad leadership under Makary, which is not quite the same as attacking Makary.

But, like, when you can't keep your own people in their seats and people are leaving the FDA in droves, that's generally not a good leader.

Right.

And so we were pointing to the fact NPLB wrote these letters, I helped write them.

And people signed on saying, we really need the FDA as an institution to achieve some stability and to value consistency.

I tell you, any one call is right or wrong.

When we see that, you know, internally, like, when we get glimpses of what's going on internally, there's a radical shift in the perception of, like, what is the basis for accelerated approval or whatever.

Then we can't project forward.

Right.

Suddenly we don't know what to count on.

And that's bad.

First principles of regulatory risk that the FDA has to behave like an institution that ultimately shifts slowly.

And if it's going to shift radically, it better shift in a clearly, like, better way.

Right.

And what was happening there felt more chaotic.

What you saw was people at the top come in, say, this is how it's going to be.

And anybody who disagrees with me, I, you know, it was sort of chaotic.

You know, I think Marty had some good ideas.

It's just the implementation some, but he.

Didn't bring people clearly didn't bring people along.

You know, not enough people along the.

Way was involved in this letter.

And did he want to go fda?

So, well, we wrote the letter, but we.

I talked to Rick.

Others in our community talked to Rick, and like, we felt him out, you know, to understand, like, what would you want to do with the fda?

What are your views at the fda?

Would you come back to the fda?

You know, mind you, like, there are other people that are.

That I think are great and are no longer at the fda.

And we understood that ultimately some of them just could not.

Like, they.

They couldn't be candidates, right?

Like, they.

Things were too polarized.

The Trump administration was never going to, you know, bring him back in.

Like, I think Peter Marks is terrific.

But with all of the, you know, polarization around vaccines, Rick Pazder had stayed longer than most.

Like, he was the most qualified, experienced person who had, in fact, modernized oncology at the fda.

So it's not that all he was was a steward of the same process, like, for decades.

Like, he had experience with changing the fda.

He was willing to serve.

And it seemed like he.

He had, and I think still has enough of a relationship with the people, administration that he looked like somebody who could be in that role.

And he was the only person like that that we knew.

And.

And since then, other names have been floated, but they are pretty far removed from, like, people with deep, you know, experience at the fda.

And so how could we, as industry insiders have thought of anybody else right now?

There's other people who know the.

The fda, like Ned Sharpless.

I know Ned well.

He was head of nci.

He was temporarily head of the fda.

I could have just as well have written that letter about Ned Sharpless.

But the purpose of the letter was not to come up with an exhaustive set of candidates.

Right.

It was actually to say, here's someone who would be great, you know, Rick Pazer.

We would love to have Rick Pazder at the head of the FDA signaling that, you know, here is a bridge between the old FDA and what the FDA could become.

He could change the fda, but he still comes from within the FDA and could bring people along.

Like, he would be a stabilizing force, but at the same time an evolutionary driver.

Right.

This letter is not just saying it's, you know, Rick or bust.

You know, it's saying here are the principles on which we base our recommendation of Rick Pasder for this job.

We're looking for consistency and experience and, you know, proven leadership and ability to bring people along.

So whoever you end up shooting, choosing.

If it's not.

Rick, please at least apply you know, the same criteria to selecting that person.

Right.

Well, Peter, so much more to talk about.

But time goes by fast when you're having fun.

It's been an hour and it's been fantastic discussion.

Maybe we should do a part three sometime soon.

I'm game to chat.

All right.

You know, so hit me up anytime.

Let's do it.

It's been a pleasure.

Thanks for your time.

All right, take care.