00:29:12 · Adam Miller, Sachin, Josh Meier
[00:29:12] S2: off? [00:29:12] S1: Is that the only case where this doesn't materially improve the world that we all live in? [00:29:17] S0: I mean, crazy thing is we've passed the point already where people are using the models on real projects, and those real projects will start in the lab, they'll go into animals, they'll go into people, they'll go through clinical trials, hopefully they someday get approved. So I think the impact is really being made there, and there's a lot that goes into getting a drug approved, you know, whether the idea was correct, whether the molecule really worked as expected, but I think there's a very good chance that even if we just shut down all the work in the company, the models that we have already achieved will probably have a massive impact, in FOMO, and, it's kinda crazy to take a step back and think about that, but then realize that there's still tremendous progress, from here, that's possibly to be made. [00:30:02] S2: And do you have case studies of specific examples of success stories that you can tell us about that you've worked with customers on?
00:30:09 · Josh Meier
[00:30:09] S0: Yeah. So internally, we do a lot of work as well to validate whether the models are working. We try to be, of course, really sensitive with our customers. We invest a lot in security, and their projects are off the top secret, but we've done over 100, 200 projects internally to really stress test whether the models are working. And by the way, that's like more orders of magnitude more than almost any other biotech company will do, which is very, or that then order to more than most biotech companies will do, which is really exciting. So some of the examples that we've gone after are molecules that are, they're very difficult to engineer. So, for example, we might want to generate a molecule, that binds to, to to two different proteins at the same time. Maybe it needs to bind both to a human protein and to a monkey protein. There was a certain case study we were looking at where a customer had spent, 5 to $10,000,000, on a project and, maybe about a year or two of of research, and they couldn't quite hone in, the, the details they needed on hitting both of these targets. And then with our models, we're able to literally zero shot, a couple of designs that actually fit that criteria. If you just think about the kind of impact that that can make, like, downstream for patients, you know, like, yes, they could have made something just for the monkey or just for the human, that really adds a lot of risk into the process, right? Like, what if it... The the the molecule worked for a monkey? Now I I need a whole different molecule to work for the human target. So being able to get all of this within the same molecule really allows us to accelerate that process and then get molecules, to facials a lot faster than before.
00:31:38 · Sachin, Josh Meier, Adam Miller
[00:31:38] S1: A fun one. If Jack came to came up to you and he said, Josh, we can get a drug all the way through regulatory approval like this. What was the one drug that you'd try one shot right now? [00:31:51] S0: I would do much more research to figure that out, right? There's gonna be a lot of constraints around that, right? What is the one thing? It'd probably be aging, right? If you could actually zero shot something right to approval, can we live forever? But that is a very sci fi idea [00:32:06] S2: of yours. Josh, I'm interested in the market structure of the industry, whereby if your models are significantly better than competitors and they stay above that, does this company then end becoming the monopoly for drug discovery? Why would any other institution use other models if this is always ahead of the curve? Will there be competitors that catch up? What's your hypotheses there? [00:32:28] S0: Yeah, I think that at the end of the day, this is an industry where the value that you can create is massive. [00:32:34] S1: Josh, we've explored this topic in a lot of depth, but let's say you're at the bar with your uncle that understands nothing about what you do and you're trying to explain to him what you actually do and what this means to the world, what is the most simplest way you'd explain this?
00:32:34 · Sachin, Josh Meier, Adam Miller
[00:32:34] S1: Josh, we've explored this topic in a lot of depth, but let's say you're at the bar with your uncle that understands nothing about what you do and you're trying to explain to him what you actually do and what this means to the world, what is the most simplest way you'd explain this? [00:32:49] S0: I think the simplest thing is to show how things that we build on the computer at the atomic level really just recapitulate in the lab, in many cases. I think if you just show, hey, here are like atoms that I see, you know, floating around with these models and we're kind of perturbing that with our product, and then you go in the lab, you shoot electron microscopes at this thing, it actually looks like that, it's pretty convincing to many people, right? And to be able to work in an atomic world when discovering these molecules makes a lot of sense that that's going to have some impact in how we create medicines. [00:33:20] S2: So the big question we have on our minds is when is the everyday person actually going to see the impact of chai in their lives?
00:33:27 · Josh Meier
[00:33:27] S0: Well, people often look at drug approval as the thing that people often think about. They're like, it's going to take ten years for these drugs to get approved. But the reality is the clinical trials will start way sooner than that, and patients are actually being helped already at that point. We're both doing an experiment with a trial, but we're also hopefully looking for some efficacy and actually trying to help people at that stage. And I think that's, you know, very possibly going to happen in a very small number of the next few years, It's one of the biggest industries. It's something where a ton of money is spent on any single, given program. And pharma's very competitive as well, right? If you work on a drug project and, you are even a year ahead of your competitors, that can turn into billions of dollars of additional value downstream, it's so an industry where people are very incentivized to use the best. I think it's almost different than something like cogeneration, for example, where it's like, well, maybe this model is like a little bit worse, but it's like a 100 times cheaper, so, you know, maybe I should try that instead. The dynamics of this industry are actually quite different, and I think that's why as a technologist, it's actually one of the most exciting things to work on, because, the cost equation is very different here. People are less worried about the costs, and they are actually much more focused on the upside that can be created, And as a team that wants to be very ambitious in terms of how we can push, you know, medicines and technology forward, it's it's a very good industry to be playing in as a result.
00:34:46 · Adam Miller, Josh Meier, Sachin
[00:34:46] S2: So we're also gonna be making a docker on sci quantum, and in quantum computing, one of the promises is that it'll be able to enable drug discovery to also be a lot faster. If that becomes true, does Chai then become obsolete? [00:35:00] S0: So I don't know a ton about about quantum, so I'm very excited to watch the episode, but I think that if we could really accelerate computation, it's actually hugely impactful to what we're doing here, right? We're trying to turn compute into molecules, and if we can get more of that or we can solve these problems in a more meaningful way, I think that could hugely accelerate what we're doing here. [00:35:19] S2: It's probably very good for you, given your probable very high NVIDIA bills right now. [00:35:24] S0: That's right. [00:35:25] S2: Yeah. How do you [00:35:27] S1: hypothesize that three is going to be received by the market and what are people going to think about these results?