Episode 32: ARCH Venture Partners' Bob Nelsen

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Hello, everybody. Welcome to this next episode of BioVenture VoiCes. Really excited about the guest today. He's well-known, probably more well-known than most biotech VCs out there, if not at the top of the mountain in terms of what people think of when they think of a biotech venture capitalist. So we're here today with Bob Nelsen. He's the managing director and co-founder of ARCH Venture Partners. And really excited to have this conversation with you, Bob.

Thank you.

Great. So, Bob, I'd like to start off. We have a diverse audience that tunes into this. And we have a lot of young people who are just trying to learn about venture capital. They don't know who all the major players are. The good ones have done their research and kind of know who the players are. But how would you describe yourself if you met somebody at a conference and they said, 'Hey, what do you do? Who are you in biotech? Why are you here?'

I think I do the same thing I've been doing for 40 years, which is just hanging around scientists and trying to find, you know, hopefully world-changing technologies and either investing in them or, or more often, creating companies around them with others and then investing in that. So it's really looking for disruptive things that are going to change industries, mostly biotech, but not completely biotech.

Yep. And so we're going to get into a lot of that and why ARCH really sits alone in some regards, maybe often compared with Flagship, but there aren't that many that are doing the big swinging, you know, high-risk projects. And I'll just say, I think many of us in industry appreciate what ARCH does, what Flagship does, because we need that kind of pushing the envelope of science. And you've done that and you have a track record of that. So we're going to get into that. I like to start off with origins and influences from folks. Now you've done a lot of interviews. I'm not going to cover some of the same ground, but you grew up in a relatively small town in Washington, Walla Walla. And you mentioned that you had some experience picking strawberries and how everybody should have to learn how to have a good work ethic like that.

You were quite successful at doing that at a young age and then started even trading stocks at age 11. But tell me a little bit about—I think you had a homemaker mom and your dad was a pediatrician. I imagine in a small town, the pediatrician probably knows a lot of families and was well-connected to a lot of people in the town. But how would you describe—what were the early influences you had that even led you to have that kind of work ethic with picking strawberries and, you know, wanting to start trading stocks? What were the big influences there? Was it mostly your parents? Did you have other outside influencers as you were growing up?

Yeah, it's interesting. You know, you always look back and say, like, how much of it, you know, it's like nurture versus nature, right? Like, I'm—I'm pretty sure that I had some kind of gene, the risk-seeking gene or something. I think I was selling gerbils when I was seven. So I was always selling something or doing something. In the early days, it was about getting money and then saving money, not about spending money. And my mom was pretty influential. She was a nurse and then kind of planned a lot of summer enrichment programs and things like that. So she was pretty influential in kind of allowing me to kind of take risks as long as I behaved myself. And so I kind of came from one of those families that didn't have a lot of rules.

Um, so I was, you know, kind of running around the neighborhood most of my life unsupervised, uh, but, you know, had some set of, uh, principles. So I didn't, uh, I was very much, uh, I decided on my own that I was a rule follower, but I was never told to be a rule follower, um, which is kind of interesting. If you decided on your own, then, then you're probably more religious about it.

Did you have siblings? Where did you...

If so, where did you fall in the... Yeah, I'm a middle child. And, you know, we kind of grew up in this... It seemed idyllic at the time. When you look back on it, there was definitely some, you know, pathology in the town. But, like... And, you know, I always joke that like even even today, it's not clear that people in Walla Walla know that the village people are gay. You know, it was very, very kind of a small eastern Washington town. But. and I used to joke that people should, you know, everybody I hired needed to work on a farm. And that was a limiting, that was a limiting attribute. So I had to kind of suspend that at some point, but the idea that, you know, I would go and move irrigation pipes at, you know, five 30 in the morning and the freaking called before calculus class and, you know, be covered with mud and, and, and then,

and then do it again after school voluntarily, right? To make, to make money was—it was at the time I kind of hated it, but like, it definitely was, was a good thing. And just working when you're young, you know, starting, I think my first Social Security statement came when I was nine years old. Right? And that's, that's kind of cool in the sense that—and I'm very much against these kind of overbearing child labor laws in the sense that it's actually really good to work when you're a kid and, you know, not forced work. So obviously there need to be railings on these kinds of things. But I think now, for instance, you can't do what we did and you can't get that experience because there's all these silly laws that, you know, 10-year-olds can't pick strawberries and that's just the dumbest thing, but it's a great character builder.

And I think this generation, You know, when I look at Gen Alpha and Gen Z and I just, I wonder if any of them have ever worked, you know, doing anything actually. And until they get into AI companies and then they work like 150 hours a week. But even the biotech ones, I think in some of our companies, you know, it's like they, it's a different sense of work ethic. And we had that issue at Juno actually early on. where people wanted to take off at 4.30 and go mountain biking. And we kind of had to hire a head of HR from Amazon who explained to people that we were trying to cure cancer and we didn't really give a shit if they wanted to go mountain biking, that we expected people to be there all the time.

So it sounds like you got not just metaphorically, but, you know, you were rolling up your sleeves, getting your hands dirty, which is, you know, uh, what you've tried to do and what you've communicated you still do to this day with the companies that you're involved in. Um, I couldn't help but draw the analogy to when I was researching Walla Walla that the Snake River goes through it, and I just remember growing up, the Snake River was mostly, um, famous for Evel Knievel trying to jump the Snake River Canyon in Idaho. And I looked at kind of your age would have been around, I think 12 or 13 or 11 or 12. Do you remember that growing up? Was that a big deal? And the reason I draw the analogy is that he was somebody who was an optimist.

He had ambition that was larger than what people thought were possible. He failed at some, but he always got back up and he succeeded at many things that people thought were impossible. So, you know, was Evel Knievel when that was happening? Do you remember that growing up?

I remember it. I don't know. You know, he's definitely a risk taker and the snake's like 40 miles away. But, but basically, I think that the idea that you should take risk, right, as an investor or as an entrepreneur and that it's okay to fail is the strength of the American system, right? It is fundamentally differentiated from Japan and China and Spain and France and even the UK, in terms of being able to tolerate risk and failure and pick yourself up and do it again. And where I am today in San Francisco, it's an attribute, right? Having some scar tissue and failure and, you know, having done a startup like Sam Altman did and, you know, worked OK and then, you know, do another one. And, you know, maybe it's the third one that's, that's the real one.

There are very few places in the world where that happens or can happen without you being tainted. And it's the reason our innovation system works. And biotech has many of those attributes. I would say if there's a shortcoming in biotech, is that... it's not as risk-seeking and entrepreneurial as tech. It could be more lean, faster, and more impatient. And I actually think that as we are starting to back people after 40 years of scar tissue, we're starting to lean less into people who are experienced entrepreneurs, kind of managers from pharma, right? Those people aren't good CEOs, usually. We're starting to lean into people who are hungrier, who are impatient, and, you know, work a hundred hours or 120 hours a week and never stop.

And, and that's—I just want to ask, are you trying to—yeah, go ahead. No, and I agree, that kind of a passionate, persistent, right, little crazy ideas, but do you manage that entrepreneur from the board oversight, or do you try to surround them with maybe some more experienced or, I don't want to say level-headed, but, you know, who might, um, make sure that they're reined in the right way? Or how do you, how do you do that with the years and decades of experience you have? Because there's a lot of people who are passionate, and not all of them turn into successes?

Yeah, I think it depends on their experience level. Some of the people we backed before, so we know that they're going to just go and kick ass. We have a stealth company right now where I hired a CEO that I backed before. I don't have any worry that he's taking Saturday off. Yeah. And I think many times with more kind of hungry but less experienced CEOs, we bring in kind of an exec chair or chairman that has a lot of scar tissue to be able to, um, help them, help them build, and, and a board that can be supportive. So I think, you know, a combination of those things, but if you look at somebody like Daphne Zohar, right, she is just a natural at being a CEO and she just needed a shot or, you know, or John Evans, uh, same way, um, where they were, um,

kind of building all of the attributes, but they also had that kind of entrepreneurial itch built in. And they just needed a set of board members and mentors around them to be able to give them the kind of, I don't know, I call it, it's like building a nest, you know, for people to kind of recruit into that they have that support structure around them of a lot more experience, you know, having done an IPO or having, you know, built a company. And I think that that's the kind of CEO that we want. So we're tending to look at people that are very, very experienced and have done it before, or very, very passionate and can... can, you know, have like an exec chair around them, and that what we're not looking for is people who are managers.

Yep. Yep. So that removes a lot of large pharma execs, not all. Steven Paul is a good example of a good pharma exec. But, you know, oftentimes the one who has spent 20, 30 years in pharma doesn't fit that category. Is that fair?

I mean, there's some great people in pharma, some very, very smart people in pharma. And, you know, most of them don't know how to, you know, be in a small company, right? And they're looking like, 'Who's going to take out the garbage, right?' It's like, 'Hey, you're going to take out the garbage. Garbage is there. You should empty it, right?' And that isn't necessarily an attribute that is... rewarding in pharma. And also, you know, the biggest problem with pharma is the disconnect between actions and rewards, right? So, you know, you might be getting the fruits of the labors of somebody 15 years ahead of you, uh, in, you know, a big pharma company. And so figuring out, like, in these long-timeframe builds, you know, who's good and who actually had, you know, actions that resulted in some increase in value is a very difficult thing.

So you end up, you know, you know, we've seen this in pharma all the time where, like, they will literally—this is 10 years ago, but, you know, we have heard stories about somebody—they will run a clinical trial that they know is going to fail, and because the person, to get promoted, needs to have started a trial. Literally, they will just waste $100 million or $20 million of, of pharma money because it gets a bonus in their resume, right? And, you know, that is getting moved out of pharma as it becomes a little bit more efficient. But I think in general, you know, as we all know, the R&D organizations of those companies, you know, they spend a lot of money doing something and then they buy biotech companies, you know, to get products, with a few exceptions.

Yeah, so before we get into the genesis of ARCH, and again, some of this has been told already, you went to University of Puget Sound in Tacoma, just south of Seattle, in economics, if I read correctly, and biology. Of course, your mom was a nurse. You said your dad was a pediatrician. What was the early interest in pursuing that? It didn't come from picking strawberries, I presume. So what made you say, 'I want to combine economics or business and biology'? Did you know early on that, like, this was something—because a lot of your career opportunities seem to have come about somewhat opportunistically, you know, in terms of, you know, your trajectory—but did you know early on that you wanted to kind of be doing almost what you're doing now?

Yeah, I think a lot of my career events are just like anybody's, I think, are just kind of random, right? You know, you... I got a job at the Chicago Board Options Exchange on a chairlift in Lake Tahoe in 12 minutes. And it was just a random thing. And I was very interested in options trading at the time. And then I decided I didn't want to be an options trader. But it was a great experience when I was like 18. Um, and that was before you pursued the University of Chicago MBA, is that right? Yeah. But when you, when you look back at, like, you know, I was interested in very early, you know, I was interested in kind of the same, in, in some sense, just breaking down the system, right? So if it took 400 points to get

you know, an A-plus in, you know, seventh grade social studies, you know, like I got 800 points, right? Because I wanted, you know, the professor promised—I mean, the teacher promised—to buy me a cheeseburger if I got 800 points. If somebody sold $300 of magazine sales in eighth grade, I would, you know, sell like $8,000 of magazine sales, you know, just to, whatever it was, to break the records, to make money. Um, and I would say the early stages of my career, I was very interested in making money as a metric. And, and, you know, once I got into venture capital, interestingly, like money is not the metric. Um, and, um, and that's what people don't really understand about kind of especially what we do at ARCH.

You know, we actually don't. And it's really true. We don't start our fundraising talking about money or returns or anything like that. And if you do it right and you cure people and you prevent disease and you disrupt the system, you're going to make money. But it's very interesting doing these companies in tech as well. Everybody thinks of these people as kind of billionaires, and all of the billionaires I know in tech actually don't care very much about the money. It's nice to have a plane or a yacht or whatever, but that's not why they do it, right? They do it to disrupt the system. They do it to make things better. And, and that's why Elon Musk, you know, sleeps on a cot and works like 150 hours a week and has no life, just because he's like always trying to disrupt the system.

He doesn't absolutely not care that he's a trillionaire. Right. And it's interesting to see people go after all these folks. The folks who care about money are the people in New York who are in real estate and LBOs and whatever. It's where the metric is actually money. Um, and, and they're worried, you know, they're comparing the year-end bonus and the, the this and the that, and, you know, constantly calculating their net worth. And the thing, people I know that build companies don't care, like they don't do that. Um,

And did your experience at the Options Exchange and even your MBA at, you know, you know, the storied economics programs at, at University of Chicago, did that, does that still influence, or was there any influences early on that made you think about risk and reward differently?

I went to University of Chicago because of, you know, Milton Friedman and George Stigler and all of those folks. Like, I was and still, very much a, you know, individuals, uh, motivated the right way, make a difference, and, and that's how, um, the system works. And, you know, it's not this kind of socialist fantasy of modern-day New York, you know, where, you know, everybody else seems to have read history and seen, sees what happens. You know, I saw a great, I think I retweeted a meme of, you know, the kind of like the, uh, the Venezuelans figured out that socialism, uh, doesn't work by taking, you know, one of the richest economies in the world and cratering it in, in a decade, and, uh, the New Yorkers haven't quite figured that out yet, but the Venezuelans in New York kind of understand it. Um, even the illegal Venezuelans in New York are like happy now, uh, but, but I think that the, um

the kind of free market principles, um, of and, and risk-taking that, that I saw in, in, you know, building companies or, you know, selling blinking hats at the county fair, um, were definitely—led me to believe that individuals can make a big difference, um. And I still believe that. I don't think there's kind of a 99-to-1 rule. I actually think it's a 10,000-to-1 rule or 100,000-to-1 rule. And you can see that in somebody like Elon, right? There are people that make really big differences and they make orders of magnitude more impact than the next person. And we found that in our companies as well. I mean, there are just people that are going to go change things, and there are people that should just manage incremental stuff.

But when you look at what ARCH does, like, we're just not interested in kind of the incremental things very much. We might be interested in one incremental thing in the context of two or three other products, right? But it's very rare that we'll invest in kind of a single thing. We did that in Karuna mostly because I saw the clinical need as being so high and Steve Paul having such a good idea that it was easy to make that bet. But interestingly, no one else wanted to make that bet when we decided to make the bet. But it wasn't very much like the classic ARCH deal where we're backing, kind of, a platform or a series of three or four different assets where we're doing these asset-nucleated companies in a very high clinical needs space like Cardurion.

And recently, Metsera was a big win that was pretty quick turn for ARCH. So, what's the story behind that one for you?

I think Kristina and Paul built that, you know, based on having a kind of portfolio of assets in metabolic disease, right? So, you know, it was ultimately... is kind of a unifying principle around three or four different really interesting things and some smart people like Clive. And so, it just came together in a way that needed real money, right? And that's one of the things that we could bring to bear is this idea that we can take big risks and create companies, um, either small or big, and some of these things kind of need a lot of money, right? And there aren't very many groups in the space that can create a company and put in a couple hundred million to nucleate it, and, um, sometimes you really need to do that. And so, we've been doing some of these asset-nucleated companies,

you know, like Treeline or like, um, and, and mostly Paul and, and Kristina are doing these, um, but kind of cuts across the firm where, you know, they need several hundred million to start, and there are multiple assets in a space that has a lot of clinical need. So, you can see us doing stuff in oncology and, and neuro and kind of metabolic disease, cardiovascular disease. And those companies tend to move a little bit faster because they have multiple assets, and some of them might be clinical assets. It's not a requirement. But, you know, those complement these big, early-stage platform swings that we do as well. And then we're doing some things completely out of healthcare, as we always have, but a little bit more right now in AI.

So, just to bring back a little bit to the genesis of ARCH, and you sound like you had a lot of, like, innate, like, desires to do what you're doing now, but the early days of ARCH came out of University of Chicago, is my understanding. And really, this was in the late '80s, right? Early '90s is when it was formalized. But you've mentioned Steve Lazarus as an early influence. Do you want to talk about those early days? And what were the plans of what the vision was to turn ARCH into versus what it is today?

You know, in some sense, it's the same thing that we do today, which is really like hang around smart professors and innovators and, you know, back cool technology. So, literally, our motto that we tell people at the LP meeting is, "Do cool shit." And that's kind of fundamentally what we do today. What happened is basically there was a physicist who was provost of the University of Chicago, a guy named Walter Massey, who ultimately ran the National Science Foundation and was head of Morehouse College. And, um, he was also in charge of Argonne National Labs, which the university operated. And they were kind of looking around at Boston and especially Palo Alto and saying, "Hey, our folks are just as smart as those folks."

Actually, the University of Chicago people probably think they're smarter. And how come we don't have all these companies? There's lots of answers to that, but Chicago is more like Europe, right, than Palo Alto. So, it's, you know, the City of Big Shoulders, it's big companies, it's distribution. It's not a risk-taking place, even today. And, and they haven't cultivated this kind of risk-taking. They've cultivated politics as an outcome. And you can see what a shit show it is with Brandon Johnson as an example, where it's this kind of... a, you know, it's not the place where you think about like, "Hey, I want to build my AI company," or, "I want to build my biotech company," but the universities are amazing.

So Chicago and Northwestern and Argonne and some of the other public universities are quite amazing. And you could even see kind of the internet, right, coming out of Champaign, right? I mean, Marc Andreessen and Netscape. And, but everybody leaves right afterwards. So, so they wanted to start an organization that would start companies. And the reason ARCH worked initially is because they were able to attract people—probably people like me and Keith Crandell and then Clint Bybee and eventually folks like Christina that wanted to kind of take risk. And the way they did that initially is they created this organization, recruited Steve Lazarus, who was a Baxter executive, but had been in, you know, kind of the government world for a while and was a curious person.

So I think curiosity is probably the most single attribute of ARCH that is the most precious, right, that we have maintained over 40 years. It's why we still have our edge is because we, we recruit curious people. And, and, and so Steve was curious and recruited Keith and I for basically no money as volunteers and then eventually employees to run around seeing if professors' ideas could be commercialized. And actually, the first company I started there was a K-6 math curriculum company called Everyday Learning, which became the largest math curriculum in the U.S. But it wasn't a biotech company. It was something fundamentally different. And then the next company I started was in physics. But what attracted us partly was this ability to have a guy like Steve, who is an amazing mentor,

who pretty much gave us a lot of rope and let us make a lot of mistakes. And then he was kind of in the background making sure we didn't fuck things up too badly. But we had a lot of, you know, a lot of rope. And we also got 20% of the equity.

I read about that. That's amazing.

And 10% of the license revenue to a bonus pool. So when I was 26, I think I made more money than the president of the University of Chicago because of Everyday Learning, because we owned a lot of it when we sold it. Even though we didn't sell it for a lot of money, it was still very material. So the idea that we were kind of aligned to go create companies with a bunch of really smart folks. So, you know, I did. I ended up getting lucky. And this is one of these kind of fortuitous things, right? I read an article in The Wall Street Journal about, about, you know, this potential job at ARCH. And I went in there and said like, "Hey, you know, I'll, I'll do it for free for a while." And then I set my own salary at like 1,200 bucks a month, down from 80,000 a year in, you know, 1987, which 80,000 a year in 1987 was like, you know, the top kind of B-school salary

number. It's via the code.

So Bob, I have to share this because I heard you describe that on one of the other interviews you did. And you had me beat because you're a few years older than me. But in 1989, I got a position and they said, well, what is your salary? And I was so scared that they were going to turn me down. So I said $18,000. And I got the job and it was great experience. But I didn't think anybody would beat me on that. But I think for twelve hundred a month, you got me beat on.

Yeah, it's definitely probably could have negotiated better. I learned to negotiate better over time. But but I think they you know, the idea that, you you know, the other kind of lucky thing was the university of Chicago had recruited all of these really smart biotech people. So in the early nineties, you know, I got to hang out with young Jeff Lydon and young Jeff Bluestone and young Craig Thompson and young Susan Lindquist and young Lainey Fuchs and, um, and, and older Bernard Roisman, uh, who was kind of, uh, you know, been around, uh, and Arthur Rubenstein, who is kind of running things and folks like Frank Fitch and, uh, And so on the biotech side, I was exposed to all these folks literally with their first patent and their first commercial deal.

You know, so I helped Jeff do his first commercial deal with Vical and, you know, helped Shizuan Liao, who is a great mentor of mine, do a deal with Ligand in the founding round, you know, early, early, early on. Um, and, um, I was very frustrated at that time because we had all this cool stuff and we were just getting our ass kicked by Kleiner Perkins and, and others. And I could never figure out like how, you know, we had better stuff, but like, how come they were able to build these companies and we weren't. And part of it is obviously having experience. Part of it is having money. And there's also a huge treatment effect when Brook Byers decides to do something. And I really did call Brook like 35 times when I was an undergraduate just trying to figure out how to get into venture capital and even what it was.

I didn't really know what it was. It seemed really cool at the time. I still don't know if I know exactly what it is, but, you know, the formative is, you know, being able to go hunting at University of Chicago and Argonne for cool technology and having all these volunteer business students that we use was really cool. And we built some great companies. We also, you know, made some huge mistakes, huge mistakes with small dollars at that point. Now we make huge mistakes with large dollars, but ultimately.

Yeah, so I want to get into that, the evolution of ARCH over 35 years or so. So first, just to connect the dots for the audience. So Steve Lazarus was at Baxter early on, and there's a well-known culture out of Baxter culture, which produced the Baxter Boys, which most famously has been applied to Henri Termeer, Bob Carpenter, and others. There was a book called Career Imprints that also coined the Baxter Boys. So there was something— And George Rathmann. That's right, George Rathmann.

There's a lot of great foundations of biotech that came out of Chicago, but what happened is everybody left. But Baxter could have been the biggest biotech company in the world. And they, you know, failed to execute on the last thing, right? I mean, it's very interesting to see. And remember, Lilly in those days was also pretty edgy, right? Buying Hybritech and I think they bought Hybritech. Somebody bought Hybritech.

I started my career in Chicago for Abbott and Baxter, Abbott, Searle. Those were the big pillars. And so, yeah, I know the culture you're talking about and I've gotten more involved recently. I know you're helping out Polsky Center for Innovation and have tried to help these other ecosystems. But you're right, it's really hard to get some inertia going because they're all on the coast. But let me ask you about ARCH and the evolution, because I was just looking at PitchBook and you guys have really led the pack recently. And just for the audience, you closed a fund in 2021 of about 2 billion, 2022, almost 3 billion, and then another $3 billion fund in 2024. And I was just doing the math on the history of ARCH, because before that you were raising $400, $600 million funds, and you've raised more

just in the down years that we've been having over the last four to five years, you raised more in those two funds than you did in the first 30 years, right? And so, obviously that means that you can pretty much do what you want. And you've talked a lot about risk-reward and that sometimes you need to put a lot in, especially when you're dealing with cutting-edge technologies. But you also were already making picks that are quite notable as early investors in siRNA, gene therapy, cell therapy. I mean, we can go down the list where you guys were first and early without having multi-billion dollar funds. And so just talk about what shifted. Was it wanting to put more capital to work? Was it position size?

Is the cost of driving innovation greater today? And so just maybe talk about that evolution to these mega funds where you really can put $300 million into a company if that's what they need.

Yeah, I mean, this is a conversation we have with our limited partners all the time because size isn't necessarily, you know, it can be inversely correlated with returns if you do it incorrectly, right? So I think Bruce Booth would argue, like, you know, if you get too big, you know, you're not going to make money, right? And, you know, I think you have to be really careful as investors you get later in a venture firm that two things don't happen, right? Number one, that the leaders of the firm, like, still work and take risk and, and, you know, kind of the people who have made money are still working. And, you know, in ARCH's case, that's absolutely true. And, you know, we all work a lot and enjoy what we do.

And have made money, and the people that have made the money are still working. When that changes over time, you see some of these firms kind of lose their edge. And you can see that in Silicon Valley a lot. The other thing where people lose their edge is getting too big, right? So they get too much capital. And, like, a good way to get fired at ARCH is to talk about putting money to work. Like, we don't give a shit about that at all. Like, it is not a metric. It's, it's like a banned word because, and it's also why we don't model returns. We don't model the portfolio. We don't do any of that. And, you know, it should be that if a company needs a billion dollars, we put a billion dollars in. And if it needs $2 million, we put $2 million in.

And, and, and some things need a lot of money to be able to get the quality of management team that can manage multiple assets to come together, right? So you're just not going to get, whether it's a Clive Meanwell or, you know, a Josh Bilenker or, you know, some of these folks, like, need money, uh, real money to be able to do what they want to do and recruit the people that they want to do the get. So I think it's a lot of the bigger things that we do are about human capital. It's about, 'Hey, these, this team or this person is willing to start a company, but they don't want to mess around with VCs very much.' And they, you know, they've done it before.

They don't want to be handheld or overmanaged where you get tranches for every little milestone. Just give us the money. We know what to do.

Absolutely. Absolutely. And that kind of money in biotech is big, right? It's a hundred million, 200 million, 500 million. It's not 20 million. And that doesn't mean that there are definitely some companies that need $2 million, $5 million, $20 million to wring out the risk and then kind of turn up the volume the classic way. And we do both. But some things need a lot of money. And generally, one of our biggest issues is finding people to syndicate with that can write checks like we write. So literally writing, you know, 100, 200, 300 million. Like when I was doing this AI company recently, and I called Vik Bajaj and said, 'I want to do a science AI company.' And he said, 'I know exactly what to do.'

I've been thinking about this for 10 years. And I'm like, 'Okay, well, we'll put a few hundred million in to nucleate it. Let's go do it.' And then, you know, call Jeff Bezos. And then, you know, the rest is kind of history-ish. But, but you need to be able to go big in some things and say, 'We are going to do this.' And that's the difference between us, you know, 30 years ago is we don't have to sell as much, right? So, and there are some dangers of that where you can have too much money, and we've fucked up companies by having too much money. And, you know, actually, it wasn't... that having too much money is actually not the problem. It's the management team, right? So if you hire the wrong person with too much money, you're going to waste money, you're going to spend money that you shouldn't be spending, and you're probably not going to get the outcomes that you want.

And we have made many errors in that space. We've also underfunded companies, and I would say, in general, in our business, it's an underfunded business where, over time, more of the rents go to pharma, right? And so the problem with biotech venture capital over a 30-, 40-year period has on average, the venture capitalists have made a lot less than the pharma companies, right? And part of that is because they got out too early, right? And part of that is because they didn't have enough money to tell the pharmas like, 'Hey, we're not going to sell to you.' Right? I mean, you remember Bill Gates, you know, could have, could have sold to IBM for a billion dollars and he didn't. You know, I think all of those tech companies have that story, right, where they could have sold and didn't.

And, you know, one of the reasons where there aren't really big biotech companies is because they sell too early, right? And even today, right? And it's tempting to sell, right? You know, we could have kept Metsera and see what happens, right? But, you know, there's enough money at the table, you eventually have to get money back to the LPs. And so there's this equation of risk-taking and money where I think our impact, we've looked at this, you know, quantitatively. We don't really think this is a good metric, but our companies actually are better at raising money than most companies. So if you look at the amount of money that ARCH-founded or seeded or Series A companies raise, it's, in some years between 2018 and now, it's 15% to 20% of the total world's private capital in biotech.

It's just two or three X larger than any other firm in terms of the money that our companies raise outside of us, right? And that's partly, you know, that isn't a good metric in the sense that, you know, they might be raising money and not having success, right? They may be just good at raising money, but there's usually some correlation with the ability to raise money and something positive, right? But we don't really view that as a metric, although as an impact metric, I think, from an industry perspective, it is...

Well, let me ask you more specifically. I mean, if you have enough money around the table to put $300 million into a company and you have specific designs on what you want to achieve, is there any exercise to say, 'Can we do this with $200 million? Do we need $300 million?' Does that enter? Because I have to say, I'm on the other end of the spectrum where I'm like, 'Okay, I just want to take a lead product that's a development candidate, get it to clinical proof of concept.' And I'm thinking everything is ROI. Like, if we're going to do this large animal study, let's do it right. Let's do it well. But let's not spend, you know, twice as much than we need to if we can do it with quality for cheaper. Does that—and that's a small-money issue, right?

As a big-money company...

Right, that you fund, like, does that exercise take place? It depends. Um, it takes place at the CEO level, right? And, um, and so where we make mistakes there in overfunding tends to be in finding the wrong CEO, right? I'm not worried about, you know, the—many of the folks that we're backing in that context because they know the equation, right? They want to create scarcity and, and not, like, piss away a bunch of money. Um, still happens, right? So it's 100% a risk. Um, but there is no right answer in budgeting or trade-offs or any of that, right? I mean, the third product that you decide to cut is probably the one that's going to make your company. I mean, you look at Amgen, right? They started doing chicken antibodies and, you know, George Rathmann tried to kill EPO multiple times.

And they still did it, right?

And so I think— Or Vertex CF is a good example as well, right? Yeah, yeah.

I think there's many stories like that. And so part of it is getting the right team and making sure they have capital. Every single biotech company is going to take a billion dollars, right, or two billion dollars eventually, right, if it works. So whether it's in a biotech company or whether it's in the hands of a pharma at that point, this is an expensive business. And that's one of the problems of the business, right, is that. And one of the reasons that China and other innovation axes, whether it's regulatory innovation or pushing the cost down, I was talking to Vik Bajaj last night and we were just talking about this. He's like, 'Look, it's still an empirical business, right? The entire biotech pharma ecosystem is—'

—is still just empirical and not systematic relative to other businesses. So it's still a big guessing game for biotech and pharma. It's not a systematically approached business, and it won't be until AI kind of penetrates this and AI plus data penetrates it. So when you have an empirical business like that, if somebody can reduce the input costs a lot, they're gonna win, right? And so it basically, ultimately China's gonna win unless the U.S. can have a systematic approach to biology using AI, right? And also develop alternative systems that are not China that have low input costs, just as has happened in electronics or other places. So if you believe that you can't have your biotech security vested in a China supply chain, which I do.

And I think actually China would agree with that, right? They would probably say, 'We don't want our supply chains vested in the U.S.'

And Resilience, just to be clear, it was part of that vision, right?

Right, but if you think about it as now from a discovery or data perspective paradigm, um, the U.S. should be really interested in developing alternative low-cost, um, places that can generate data, can generate first-in-man. We do that in Australia now, right? You do it in Spain and a few other places, but we should very much want to systematize, you know, maybe it's India or other places to diversify our ability to get quickly into humans, aside from changing our own system and making our own system much, much faster, more streamlined. But we're probably not going to be able to compete against the input costs of these other places. We'll be able to get more competitive over time, but we have to do it fast.

We don't have a lot of time, right?

Well, I would argue, Bob, and I would love your opinion on this. I think if the FDA could allow first-in-human studies much more rapidly, efficiently for U.S. biotechs, I think most would be willing to pay 30%, 50% more. If they're not compromising the speed, I don't think just cost alone will make them go to these other countries. I just think it's speed. It takes too long. The FDA has made it really hard to get quick data. And whether it's PK, safety, exposure, can you look for higher doses before you go into your patients?

But it's all of it together because if you have lower costs, you can take more shots on goal and try more things and try more molecules. So it's—it's absolutely number one, two, and three for the U.S. should be regulatory reform in the FDA, pushing things out to be able to make more decentralized, faster. First-in-man is what we have to do. It's not a question. We have to do this. It has to be done quickly. And we need to create different incentives even within CMS to reimburse clinical trials and enroll people much faster. So we need to get rid of all of these data barriers in FDA and CMS that just create all of this bullshit bureaucracy that just, you know, it's like a Somali daycare center, I think.

It just needs to go, uh, a lot faster, a lot, um, you know, needs to be a revolution. And I think this administration kind of gets that. I think they're having problems implementing it, but, um, we definitely need to go to a decentralized system. Even in China, the centralized system is very slow. It's modeled on the US FDA. It's when you get out into the provinces and the hospitals that all of this innovation happens. So we need to have universal IRBs, and we need to have things that you can go very, very rapidly into humans without all of this manufacturing burden happening to be able to see if stuff works, or we're not going to be in the game, right? And it's very clear that pharma actually doesn't care, right?

I mean, there's a few pharma CEOs, I think, that really care because they're patriotic, but ultimately they're still going to go pay for something in China that's one-third the cost instead of buying a US biotech company, right? So I do think we need to consider the fact that most of the China projects today are still based on science and technology that's coming from the US. I don't think that's gonna be the case over the long term, right? I mean, China's science is real and— They're catching up on innovation, on the innovation curve, yeah. And I've had a lot of experience over there as well, and there's really good science. But we need to do regulatory reform, and we need to really invest a lot of money in AI and data.

And that's the way that we're going to play. And we probably should... make sure that we're enforcing our IP. I don't think we should really let pharma just use US IP in other nations and then get cheaper stuff without some penalty. I do think we should look at that and just see. It doesn't have to be targeted at any specific nation. It just can be like, 'Hey, our IP is valuable. Let's make sure that people aren't trying to get around it.' But in general, I think that we need to compete. We need to move quickly or we're going to lose.

Well, it is interesting to hear you with that perspective, because what I've thought previously is that China is really good right now at fast followers, right, taking known targets, and that US would still win the day on innovation. I agree that they can catch up quickly, but what I've surmised is that if pharma goes right to China, similar, the GSK-Hengrui deal as an example, if they bypass US biotech and acquire there, to feed their 50% of pipeline gaps that they have, that that's gonna push venture capital further upstream on the innovation curve, which means greater risk-reward, which is really where ARCH sits, right? At that, you know, cutting edge at the tip of the spear of innovation. And so I think that all of the other VCs who are maybe generating some decent returns with, you know, a best-in-class instead of a first-in-class, they may lose out the most versus an ARCH.

But you're saying that, hey, China can catch up and we may lose even on the innovation, the early innovation.

I mean, how do you... Well, there's randomness, right? So, I mean... Whoever wins AI in the long run probably wins the space, but biotech is also the hardest place to systematize. It's much, much harder, and nobody's done it.

It's not just engineering and physics. You've got a dynamic biological system.

It's really complicated math. Right now, we're still in an empirical world. And the pharmas are bypassing, you know, they're going to go to the cheapest and best, right? But a lot of these things are me-too, me-better. So, you know, we should make sure that everything is appropriately priced, right? So that... That if there is US IP and stuff, that there needs to be a price for that, right? People can't really just take it. And then we also need to make sure that we compete. So both of those things have to happen. Um, in the long run, whoever wins AI is probably going to win. Um, but, but that is, you know, I can't tell you if that's five years or 10 years or 15 years, I can tell you in the rest of the industrial world, it's going to happen really fast.

Right. And, and biotech may, may be the slowest and hardest, but a lot of it depends on what kind of data that we can capture and create, um, to get longitudinal population and clinical data and things like that, where there probably is signal. There probably will be models that can predict new biology.

Well, I saw your post recently just on sleeping, and you reposted the number of diagnoses that this large longitudinal study with tens of thousands of folks... I mean, that's interesting.

The more data is what— Yeah, it's not clear that it's real, but there are hints of some really interesting things as you get into— longitudinal data. I mean, clearly, like when you're thinking about the brain, there's all kinds of signal that we're not picking up and systematically picking up that we could be picking up, um, whether it's, you know, mental health or whether it's neurodegeneration, uh, I'm sure these things are, you know, measurable much earlier and, and also in the blood, right? So whether it's things like Grail or, or whether it's other things where you're looking at, you know, tau or, um, or, or things, you know, I, I had a, uh, blood test where I had a high tau measurement and it turned out to be an assay problem, but you know, I'm, I get my tau, uh—

—like that every six months, right? And, um— Well, you famously were profiled in Business— It's very low now, with your MRI and your dermatology tests and like— so you're, you're at risk of a lot of false positives, but you can make that choice. No, but that's the thing is, you're not at risk with a lot of false positives if you have a lot of data. I have 18 years of MRI data. Yeah. So I know like if something changed, you can go back and look at, you know, one, two, three, four MRIs and say, 'Well, is it really changing?' And, and then, you know, you can see the same thing with blood data, right? So it's like, 'Hey, my tau, you know, Aβ42 ratio is X. You know, why is that?' And, you know, looking at— and imagine now if an AI is looking at that, you're going to—

—fundamentally change the clinical practice of medicine. That's going to happen, right? With a radiograph and some proteomics data and some basic sequencing, you're going to be able to sequence everything all the time. And when you combine that with all of this other longitudinal data, that's going to be the medical system, right? And it's already... better than your doctor. The AI is just, you know, better.

I think all of us already have examples in our friend network or family where they've had to go back after two opinions from a doctor, right? And they got it right. AI got it right. So I know several examples. Can I ask, Bob, I know it's in stealth, but it sounds like what you're describing is a little bit of the goals or objectives of Project Prometheus. Is that fair to say, that working on kind of these solutions and how AI can win the day for biotech, is that a big part? No.

So Prometheus is not related at all to healthcare.

Okay.

It's completely related to AI for the physical world.

Oh, wow.

So it's not—there's zero healthcare. Now, you know, could it impact healthcare eventually? Like, I think if you understand physics and understand, um, you know, it may impact healthcare through, uh, insights into instrumentation and, you know, other ways of thinking about healthcare, but it's probably not, you know, you know, it's much more likely to impact the rest of the physical world first. And, you know, how kind of what I would call hard science happens, but it's more engineering than it is the rest.

So Bob, I wanted to get into one other question related to venture investing strategy. So when I look at ARCH, I see the term platform versus product, that ARCH is big, even though you do some products, as you mentioned, like Karuna, it's very big on platforms, but I describe that in almost two ways. There are platforms like Resilience or Vir or Neumora, which are like, let's own a category and let's find the best technologies and assets. Let's have a portfolio approach in a category versus Prime Medicine, right? Or, you know, a new technology. And my question is on the newer technologies where often the debate is, do you invest heavily before you know if that first product will work? Or do you really singularly focus that technology to say, what is the right proof of concept we want to show?

And this gets into the how much exposure, risk exposure do you want on a new technology? And maybe the corollary to that is any lessons learned from going into all of these other technologies where ARCH was first and got it across the finish line? What lessons have you applied to, let's say, a Prime Medicine or some of these newer technologies where many will say you better pick one or two good applications and show that that works before you invest hundreds of millions of dollars?

Yeah, I mean, I think the problem is you just don't know which one to pick, right? So if it was that easy, then these things would be very easy. But, you know, you look at companies like Prime, Sana, Lyle. um, that, you know, could all be really successful or it could all be failures. Um, you know, I think sauna is going to cure type one diabetes, right. Um, and probably that's worthy of focus, but even though the technology is much, much broader than that. But the lesson is you have to stay in these things a long time to get the rents. We're still in those companies, and we're sometimes below our seed investing price. with a couple hundred million dollars so it's not like small money um and um yet they're still under capitalized right so it's it's a very very tricky balance between you know pushing the envelope on a platform then figuring out um what to focus on and then figuring out um

how to fund the company. And I don't think we have any of the right answers there other than some of these things are absolutely worth, um, doing right to cure type one diabetes is going to be a really cool thing. And I think it's going to happen. And, um,

Last question for you. No, I totally get it. Sometimes you need to explore a lot of different applications to figure out what the right one is.

But if you look at something like Altos, we've done that in a way where we kind of took capital off the table early so we could take a fundamentally different approach. So when it's like the most exciting biology, people ask me like, "What are you most excited about?" I'm most excited about the biology of Altos and AI. And we—that will create a world of preventive or disease-reversing pharmaceuticals, which we don't have. It'll fundamentally change healthcare. And if you look at what GLPs did just a little bit, and Lilly has figured this out, right? It was like the, "Hey, you know, we can make these drugs that we can go direct to consumers and kind of prevent things." That's what the future healthcare system is going to look like.

It's going to be direct, it's going to be data-driven, and it's going to be, you know, with a lot less hospitals and a lot less of this big infrastructure. I'm just going to be able to cure your disease by, you know, flipping a switch. And that's what, you know, that's what I think we will end up with and we'll go to, and it will be part of interesting biology like Altos that's new and part AI figuring out stuff and making data-driven decisions, both in clinical medicine and in discovery.

One rapid-fire question for you is you've talked about how you surround yourself with really smart people, Nobel Prize winners, to talk about the science. The nature of biotech investing, though, early investing, is you have a little bit of data, and there's that old adage, 'the less you know about a product or technology, the better it looks,' right? How do you... do that gut test, right, of, other than listening to smart people, what are you personally looking for in that small data set where you have—are trying to extrapolate that to a big vision of what it can become? What guides that, because there's a lot of good, quote, science out there, and not all of it are going to become these amazing multi-billion-dollar companies.

Yeah, that's a really good question. I don't really know the answer. I think it's a gut thing, right? Ultimately, when you look at Kristina or me or Paul or any of the partners at ARCH, we're gut investors, right, more than systematic investors. And Peter Kolchinsky and I laugh about this because Peter wants to systematize everything.

But ultimately, you can systematize everything, but you still have to pick. And there is a gut... aspect to all of this. There are too many degrees of uncertainty and multiplicative probabilities to actually believe any of the data. If you think that you can use IRR or NPV in biotech or pharma, you're fucking crazy. And it's just wrong. And real options theory might be a better way to think about it. So what we're doing is managing a set of options, some which are related to the other options. And, you know, you're trying—you, you want high variability, right? And because the high variability gives you outcomes that can lead to excess returns. And that's the only thing, you know, your limited partners only give you money to get excess returns.

They're not giving you money to, like, not take risk; otherwise, they can just invest in some lower-risk fund, right? So, so they're—they're backing us to take these big swings. And, you know, ultimately, that is—you see something, right? So, you know, in Altos, Rick Klausner saw this just crazy data from Juan Carlos, and, um, and that's what got him interested. And, you know, I trust Rick's judgment, so that got me interested. And, you know, ultimately, I asked David Baltimore this at a dinner. I was like, 'David, why are you spending time on this?' And he's like, 'Because I think it's real biology that we missed. Like, you know, for 50 years, we missed, like, a fundamental aspect of biology.' And that's enough, right?

That's enough to say, 'Okay, like, you know, if David Baltimore thinks that we missed a fundamental aspect of biology, that's worth 100 million or 200 million or 500 million, probably.' And that's how it works, right? You have to have some set of faithful beliefs, right? It's more like religion than it is like option trading.

Yeah. Well, Bob, look, I could easily ask you questions for a few hours, like a Joe Rogan podcast, which, by the way, I listened to Ben Lamm's Colossal interview with him, and you were mentioned. And so I just thought to myself, it's only a matter of time that you're going to be on there in a three-and-a-half-hour discussion. So I wish we had that time today, but I really appreciate you kind of walking through a little bit of the history of yourself, your career arc, and the evolution of the firm. Yeah, this has been really great. I think our audience will really enjoy it. Anything—I always try to leave with something personal—anything you want to share that, because everybody knows you very well

as loving science, loving innovation, loving risk-taking. What else interests you outside of this industry? I know you've got a couple adult sons now. And—but what do you want to share that the audience might not know, that you have an interest beyond biotech?

I'm very interested in, like, the biology of happiness, you know, like what, what ultimately makes people happy and really understanding how to get there. So I spent a lot of time in Africa with my wife taking care of these teen moms who have stories that are just the most brutal, terrible things you've ever heard in your life. Yet, fundamentally, their mindset is one of happiness in the face of tremendous, tremendous adversity. And, you know, when you come to the U.S., we are literally whining about everything all the time, and everything is a microaggression, and, you know, the world is falling down all the time. And it turns out when you travel around the world, you know, it's actually not that bad here.

And, you know, so the kind of division that we have and being unhappy because we're worried about all these things. And like, you know, we go to Africa and spend three weeks a year, maybe a month a year. And, you know, people are pretty happy, you know, to have their first hot shower ever in their life, you know. And that's just a minor piece. So I think it's understanding the brain and how to intentionally make yourself happier in your life, not just experiencing life as it goes, but to be able to change your brain chemistry and the way that you process the world to be in a happier set state is a huge interest of mine, because I think it addresses a lot of issues in mental health, but it also addresses a lot of issues

you know, that we all face kind of as a world. So I think that that's an area that I'm interested in.

Well, I want to tell the audience, you have one of the more interesting Twitter feeds or X feeds out there. And what—the theme I see goes back to maybe your economics training, which is that you have this kind of pragmatic approach to problem-solving, and you very much want to understand incentives and the law of unintended consequences in a lot of situations. So I'm trying to find a theme, but there's one of those where, like, "This is really stupid that they're doing it this way, and here's why." So I've enjoyed your posts from science to politics to what you criticize out there. I encourage everybody in our audience to follow Bob on X if they are not already. But Bob, hey, I really thank you.

I know it's a busy week right before JPM. And thanks for taking the time to do this. I think the audience will really enjoy it. And I know you've got a busy week ahead, like we all do at JPM. And I wish you the best. And thanks again for taking the time here.

Yeah, thank you for the opportunity.

All right. And thanks to our audience for tuning in again to this episode of BioVenture VoiCes. We look forward to seeing you on the next show as well. Take care.