BridgeBio Oncology Therapeutics, Inc. Common Stock Morgan Stanley 24th Annual Global Healthcare Conference

Yeah. Thank you, Sean, for the warm welcome. Yeah, great question. Obviously, we're super excited about what's going on in China. I think it opens great opportunities for companies like us that are innovating. I think the way I would summarize the current environment would be maybe two buckets, right? One would be the innovation part of the drug development process, and the other one would be the speed, right? I think on the speed perspective, the economics of speed are changing dramatically, and China's playing a huge role there. Competing against that, I think, is going to be very difficult, right? On the other side, on the innovation mechanistic side of things, I think we're still highly competitive there. How does that apply to BBIO, I think is a key point.

If you look at the China environment, maybe in the last few months, you'll see three G12C off inhibitors that have been approved. I think when a mechanism works and people believe in it, I think China is very good at moving at super high speed, making molecules, and those can come back, and people can take advantage of that proven mechanism. But I think on the innovation side, I think it's a playing field. If you look at what we have done with BBO-8520 being an off-on inhibitor, the ability to target that GTP state, that has now been replicated.

Sure. Our breaker molecule, which is first-in-class breaker of the PI3Kα and its RAS interaction, that also has now been replicated.

I think, as long as we stay very much focused on the things that we can do new, China will be, and it is very competitive on that, but the innovation part, I think, makes you be able to compete well. If we just try to compete on speed, trying to do a mechanism that is already validated, I think that's a big advantage that China is showing today.

Yeah. We obviously are trying to incorporate AI, and then maybe Idan Elmelech can follow here, on a daily basis into our workflow. I'm certainly surprised from what I see from my team, how faster we can do things. I think from a research perspective, from my biology background, I would say maybe three things. The first one, really putting together co-folding tools. So the ability to reiterate hypothesis on a structural basis. Instead of having to make every single compound and test the hypothesis, I think AI has a huge advantage in trying to test this hypothesis in silico. So we do a lot of that for our early research programs.

AI coding, I think it's another place where a lot of the team are using that to try to put our, maybe a smaller data set in the context of a much bigger data set, and trying to see where there are synergies, what can we learn from what's in the literature, and also reiterate that process and that affects the time at which we can build hypothesis and test hypothesis. Then I think one maybe a little fun one is the agentic AI part of debating with AI when you have a hypothesis, and you can do that in a couple of days, really narrow it down to a much better clinical hypothesis or biology hypothesis.

That, I think there's at least a couple of examples at BBIO where we have narrowed down the trial design or other key center hypothesis for one of our assets in a much shorter time that it would have taken to send a group of people to do this and search the literature and come up with a refined hypothesis. I don't know if you want to add anything to that, Idan.

Yeah. No, I think the impact here is really on cost reduction and cycle time. Especially if you look at a big part of the cost we don't talk about in biotech, we talk about per patient cost in clinical trials. But a lot of the fundamentals of the ongoing business, right, everything from accounting to finance, regulatory submissions, all of those pieces, I think you're already seeing a high impact.