01:40:40 · John Coogan, Ben Liu, Jordi Hays
[01:40:40] S1: having us. Yourself and the organization. [01:40:44] S6: Great. So Benjamin Liu, co founder 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. [01:41:01] S1: What's your stance on monkeys? What's your stance on monkeys? You got There's a Joel Lonsdale. [01:41:05] S6: There's gonna be a big shortage. [01:41:06] S0: There is. [01:41:07] S6: 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. [01:41:52] S1: Okay.
01:41:52 · John Coogan, Ben Liu, Jordi Hays, Amiram Shachar, S2
[01:41:52] S1: Okay. [01:41:52] S6: 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. [01:42:04] S1: Yeah. [01:42:04] S6: 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. Yeah. That's where we're bottlenecking. That's what doing. [01:42:17] S1: No. No. Totally. [01:42:18] S0: 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, [01:42:36] S1: a bunch [01:42:37] S0: 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 [01:42:50] S9: Yeah. It all [01:42:51] S6: That's 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 [01:43:01] S2: few $100,000,000.
01:43:01 · S2, Ben Liu, John Coogan
[01:43:01] S2: few $100,000,000. [01:43:02] S6: 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 [01:43:28] S2: a few million dollars. [01:43:29] S6: 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 Isomorphic. 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. [01:43:50] S1: So so historically, 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. [01:44:21] S6: That's right. So either you have to go public or you're raised from a traditional, like, Trad Bio OVC. Right? Flagship Like,
01:44:21 · Ben Liu, John Coogan
[01:44:21] S6: That's right. So either you have to go public or you're raised from a traditional, like, Trad Bio OVC. Right? Flagship Like, [01:44:26] S1: pioneering or something. [01:44:28] S6: 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. [01:44:42] S1: Okay. [01:44:42] S6: And so these are drugs that we put into Inuco. [01:44:45] S1: Yep.
01:44:45 · Ben Liu
[01:44:45] S6: 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
01:46:32 · John Coogan, Ben Liu
[01:46:32] S1: Yeah. [01:46:32] S6: 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. [01:46:45] S1: Yeah. [01:46:45] S6: 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. [01:47:36] S1: Makes sense.