Formation Bio raises $600M drug development fund to solve the clinical trial bottleneck AI is about to make critical

Speaker 2: You fell for that one, Tyler. You fell for it hook, line, and sinker. Our next guest is the cofounder and CEO of Formation Bio with Ben Liu, launching a huge drug development fund. Ben, welcome. What's happening? Let's get this going ready. How are doing? Please kick us off with Thanks for having us. Yourself and the organization.

Speaker 7: Great. So Benjamin Liu, cofounder of CF Formation Bio. We're an AI native company at at building the next generation pharma company with this kind of core thesis that drug discovery is getting more and more efficient, and the fundamental bottleneck of bringing new medicines to patients is the cost and time of drug development. What's your stance on monkeys? What's your stance on monkeys? You got There's a Joel Lonsdale. There's gonna be a big shortage. There is. They're important. You know? That national security, we gotta increase the number of monkeys we have. It's, you know, the the similarity between our disease systems to kind of humans is probably one of the best predictors. Yep. Right? So you can imagine, like, solving, like, rat Alzheimer's is very different than sucky... Solving monkey Alzheimer's. Yeah. So But, you know, the biggest the biggest bottleneck is drug development in humans. And so, you know, you have this impedance mismatch where drug discovery is only getting more efficient. There's been a doubling of number of discovered drug candidates in the past ten years, even before AI. The number of approved drugs has kept, like, kind of constant 50 a year. Markets are rational, so discovered drugs aren't worth much till post phase two. Sure. So the company, we actually don't do any discovery internally. We look to acquire drugs that are discovered. Okay. And then we built all the technology, people, processes, AI systems to run clinical trials and drug development more efficiently, but also the best humans and AI systems that know what drugs to pick and what diseases to match them to. Yeah. And then we provide all the cap and capabilities to get the drugs from where they are. So it's usually two to four years away from a clinical trial, and we provide all the cap and capabilities to get it post clinical infection.

Speaker 1: Yeah. That's where we're bottlenecking. That's what doing. No. No. Totally. Yeah. What what are... What what were the pre... Like, talk about, like, costs around drug discovery pre AI and then where you think it'll go with new advancements and models and and, you know, Because continued it it feels like a $600,000,000 fund, I imagine you're gonna distribute it across, like, a bunch of entrepreneurs and teams that are focused on that discovery. Mhmm. But then each one of those individual drugs, if they're promising and they start going through trials, could still cost hundreds of millions of dollars to actually take Yeah. It all That's

Speaker 7: actually the fundamental bottleneck, right? So you have this like kind of drug abundance in discovery. But once you hit the clinic, you know, a clinical trial can cost a few $100,000,000. Like a phase two clinical trial can be, you know, 60,000,000 to 80,000,000, if not more. And so what's going to happen is if we don't develop more capabilities around the drug development period, that we're not going to be able to translate all these discoveries into new medicines. And as you alluded to, you're kind of looking at like all these great discovery companies and, and, you know, getting a drug from, you know, a discovered idea to a 90 is now costing just a few million dollars. And that's probably going go down over time, right? You know, with all this automation and, you know, the the the great work that, you know, folks like Anthropic and, you know, you got ISO CHI. Like, design is getting increasingly commoditized. But what is pretty rare is, like, the ability to prove that it works in a human, And and that capacity hasn't changed. So so historically,

Speaker 2: what was the origin of the capital for this particular phase? Because, obviously, a lot of drug discovery candidate selection might happen in the... In academia. And then once you're post phase two, phase three, you're probably working with a big biotech, maybe got acquired. But is this the sweet spot for companies that might go public, might be traded as sort of like risk on biotech public markets investors historically, and you're able to Okay.

Speaker 7: That's right. So either you have to go public or you're raised from a traditional, like, TradBio VC. Right? Flagship Like, pioneering or something. Or, you know, an Atlas or, you know, a lot of kind of great funds kind of finance these drug, you know, Arch Capital. Yep. You know, I think what separates our fund is we're not investing in companies, but individual drug assets. Okay. And so these are drugs that we put into Inuco. Yep. And we not only provide like the 60 or 80,000,000 needed, but all the capital, but also the capabilities. So think about like the ability to run trials cheaper and faster, best in class human drug pickers. So our R and D head was the R and D head at Biogen. He developed the first, you know, genetic medicine for ALS, the first, or a drug for SMA, the first disease modifying drug for Alzheimer's. And we have a guy who also discovered, a neuroscience at Roche. So folks really experienced in drug development, but also the AI systems allow you to, like, look at every single drug in the world, match the right drug to the right disease, design the right study, and then be more efficient in getting the drugs ultimately to a clinical balance option. Maybe kind of share a little bit more about how I got started. Know, I trained as a computational biologist, so I think like many, you're really excited about how all the genomic, proteomic, transcriptomic data mixed with machine learning AI can transform discovery. When I was a graduate student, we had the discovery of few candidate drugs in Alzheimer's and Parkinson's, and just bearing that you believe, we went to some pharma execs and said, hey, we discovered these drugs. Aren't you guys excited? And they said, you know, sorry to burst your bubble. And this is like ten years ago. There's already more good drugs discovered than we could afford to develop. When a single clinical trial in Alzheimer's across all the phases can cost like hundreds of millions of dollars, actually it's 500,000,000 per per shot, we just can't afford to prosecute everything we we discover. And now with AI, that's probably going to 10, if not 100x, right? And so if we can't like ultimately solve this throughput, we're not going to get more medicines to patients. And so this fund is dedicated for, you know, let's say a biotech and discover five, 10 drugs. As soon as they have a lead asset, traditionally, all the capital needs to go to that lead asset. That second, third, fourth month, not getting love. And so we're saying, hey. We can provide the capital Yeah. But also all the capabilities to enable that company to take more shots. And if it wins, we kinda share upside. It could be upfront royalties, milestones, and even equity. And so it's kinda a win win for for for the industry. Yeah. But it's maybe the counterintuitive thing. I don't think people appreciate that, like, you know, drug discovery has not been necessarily the bottleneck for a pretty long time. Yeah. And it's only gonna get more and more acute as you have drug discovery abundance. And and ultimately, it's like, how can you get them into clinical proof of concept? And that's what the market values too. Right? Because if you have an abundance of discovered drug assets, you really don't see value until you demonstrate human clinical proof of concept. And that's where... Maybe the heuristic to think about this, like, a discovered drug isn't worth much. Mhmm. Once it has clinical proof of concept, so in human trials in the disease post phase two, the heuristic is one x peak sales. So you can sell drug for... You know, if it's a $5,000,000,000 a year drug for 5,000,000,000. Once it's over phase three, past phase three, it's two to three x peak sales. Makes sense. And so, you know, it gives us an interesting... Like, we kinda ask the question, like, why hasn't there been a big pharma company really in our industry created since the nineteen eighties? Yeah. And one of the big challenges, if you're a venture... And that's kind of the Amgen's Vertex If kind of of the you're like venture backed company, it takes you like three to five years to get in the clinic, and then two to four years to run a phase one and phase two. Phase two is only worth 30% of the time on average. And let's say you're fortunate enough after you spend 60,000,000 to run a phase two, and it works, and a pharma company offers you $5,000,000,000 to take the chips off the table, you could, you know, not sell, run a phase three. There's a 40% chance it goes to zero, a 60% chance the phase three works, and then you can sell for two to three x peak sales. Risk adjusted, the rational thing is to sell. So we're structured as a company as a hub and spoke so we can sell in new co without selling the whole company. But if you can only take three shots and you hit a winner, you should probably sell. Right? Because if the expected value is 30%, you know, it's more likely your MOVE and IRR is gonna be diminished if you kind of run those two shots versus just sell off the first shot. So as a consequence, our industry usually has biotechs get acquired before they can become the next, you know, Roche or or or Novartis. Same exact thing we're humming from. Consumer packaged goods, honestly. Oh, yeah. Like, there there has been, like, a new Yeah. Yeah. Yeah. Yeah. There's no new guests in Humble. They buy... Yeah. Yeah. They buy the protein company. They buy the supplement company. They buy the cereal company, but there's no one that's... And there's been super ambitious founders that have gone after it, but all of them That's right. With point solutions. Yeah. And and that... And to to your point, like, the second thing that's important is you take enough shots. Right? Because if you can only take three shots, you should sell for the reasons we discussed. But if you can begin to take more than 10 shots Yeah. Your expected value is three out of 10. Now we have AI systems, and humans have done better three out of 10, but it's better to underwrite considerably Sure. And and kind of exceed on the upside. Once you run 10 shots, you you expect three out of 10. Yeah. So what the fund allows us to do is take more shots, number one. And we can increase the throughput of also the industry, but it also allows us to raise capital

Speaker 2: and then always have to raise equity. Yeah. So it lowers our cost of capital over time. Yeah. And, you know, like, right, so you'll have, like, diversified cash flows so you can actually start scaling, like, the internal mechanism of the business. Like, the OpEx at an Amgen is what makes it a biotech biotech company, a big pharma company. It's not just that they have one... Yes. They have cash cow drugs, but they have a cash cow drug every ten years that cycles out so that they can actually sustain the business, get the headquarters, get the teams, get the, you know, the whole flow flowing. And if you're just like a one trick pony, a one hit wonder, you're gonna see this, you know, sort of up and down round tripping of your cash flow. Do you think public opinion do you think public opinion around pharma will be better or worse in ten years?

Speaker 7: I'm very optimistic it's gonna be a lot better, specifically because I think we're beginning to pursue drugs that just help you live longer and healthier. And you guys know about the GLP ones. GLP ones. You know, the two top GLP ones did more revenue than OpenAI and dropped the combined, and and also kinda did it profitably. And we think we're in early innings of things that just help you live longer and healthier. So things that help you walk longer Yeah. Like muscle. Right? Cartilage, bone density increases. Yeah. But I think you bring up a point. Like, biotech's really an efficient stay because, you know, you're you're really scaling with humans, and there's an opportunity to build AI systems that do the work work work of entire teams. And so a pharma company is a 100,000 people because in order to prosecute one idea, you need a team of people to go after that. And and so we built, like, AI systems that let you exhaustively look at every single drug and target indication pair, and then, you know, design the right try... Trials, run it kind of cheaper and faster. But you also don't have to create a separate team for each asset. And so biotechs today, like, you almost have to have, like, you know, a CMO, chief development officer, head of quality, and and and they're underleveraged in some ways. Sure. So if you can kind of have the best human talent with these AI systems, you can prosecute 10, 15, 20 Yeah. You know, 50 drugs and not have to be, you know, a 100,000 person company. It's a few 100 people. That's what we're really excited about. $100,000,000.

Speaker 1: Gong. Gong.

Speaker 2: Thank you so much for coming on the show. Congratulations. Final... Last last last question. This is fascinating. Please. Would

Speaker 1: you rather have 30,000 monkeys or 30,000 Bitcoin?

Speaker 7: I think the monkeys will ultimately...

Speaker 1: I think buy and hold the monkeys. Think they might I think they might... I think the monkey market might rip harder than... You think monkey... There... There's gonna be the flipping. Because... That's what they call it, flipping. With with crypto, you have so much, like, just, like, cyber risk right now whereas

Speaker 2: Oh, so if you're so if you're you're holding on a bored ape, you wanna get out of bored apes and get into real apes. Yeah. I think that might be the future. A lot of monkey business going on. Well, thank you so much for coming on the show. Very cool business, Ben. Have Coming back on soon. Rest of your day and congratulations.