A coordinated effort could map cellular health and disease in five years

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 46:05

   allow verification in the laboratory. How do you think about time scales? I mean, that's, that's another way in which there's like orders of magnitude problems, right? It's one thing to perturb a cell look at it an hour later a day later but what i really care about is like how am i going to live to be 120 right and that's a very long-term question so how how do you think about this kind of you know prediction this kind of goes back to the like you know million brian johnson's idea do we have enough right now to go on to say like this cell state you know predicts good outcomes or is that also like a you know big part of the climb of the grand challenge yeah i think that's still a really big big part of the climb. But I think at the same time, it's a scaling challenge. I think it's one that can be addressed with technology that we have today. I mean, I guess what I really think

2. 47:07

   about is kind of creating atlases of cellular biology in the context of health and disease. And I think that we, you know, the technology that could really allow us to do that is just starting to really become scalable. This is a big part of what we're trying to do with the Virtual Biology Initiative is, you know, see cells across, you know, this wide range of physiological contexts and really, really understand, you know, what differentiates disease from health at a cellular level. And I think, you know, that's going to really start to show us, you know, both, you know, what makes different diseases unique, but also shared common causes across different classes of disease. So I think that's really within reach. I think first drafts of that within the next one or two years, you know, within five years with a really

3. 48:00

   focused coordinated effort, we can have, you know, a pretty comprehensive map there. And that would have enormous value, not just for AI, you know, just for kind of classical analysis. And I imagine a lot of analysis is going to be agentic in the future. So also you can really imagine just kind of scaling analysis to these very large classical analysis to these very large data sets. But also I think you can start to build a model from that that's going to really identify precisely the different cell states that are relevant to disease. And if you have that model, then what you can start to do is ask the question, how do I intervene to reverse a state that's pathologic and bring it, bring it into, bring it into a healthy state. So I think, I think that that's something, you know, those are questions that we'll really start to be able to tackle in the

4. 48:56

   next five years. How big of a deal do you think just like human health records will be as a part