# Virtual cells could move much of biology research in silico

Markdown copy of https://realalpha.app/s/virtual-cells-could-move-much-of-biology-research-in-silico/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Demis Hassabis](https://realalpha.app/builders/demis-hassabis/) · Demis Hassabis is CEO of Google DeepMind and Nobel Prize winner.
- Host: [Lex Fridman](https://realalpha.app/people/lex-fridman/) · Host, Lex Fridman Podcast · Robotics and AI researcher at MIT; started the show in 2018.
- Show: Lex Fridman Podcast
- Episode: [Demis Hassabis: Future of AI, Simulating Reality, Physics and Video Games | Lex Fridman Podcast #475](https://realalpha.app/v/-HzgcbRXUK8/), Jul 23, 2025
- Moment: 41:03 to 45:55 of the episode (5 min), playing on https://realalpha.app/s/virtual-cells-could-move-much-of-biology-research-in-silico/; the episode from there: https://realalpha.app/v/-HzgcbRXUK8/?t=2463

## Quote

> “maybe you could **100x speed up experiments** by doing most of it in silico the search in silico and then you do the validation step in the wet lab”
> — [Demis Hassabis](https://realalpha.app/builders/demis-hassabis/) at [43:05](https://realalpha.app/v/-HzgcbRXUK8/?t=2585) · Lex Fridman Podcast

## Takeaways

1. A virtual cell could make experiments much faster.
2. Start with yeast, a well-understood single-cell organism.
3. Model at the protein level to capture useful dynamics.

## About this segment

Demis Hassabis lays out a path from protein interactions to simulating a whole yeast cell. If researchers can model the right level of biology, virtual experiments could sharply reduce wet-lab work.

From “Demis Hassabis: Future of AI, Simulating Reality, Physics and Video Games | Lex Fridman Podcast #475”, Jul 23, 2025. [Watch the full episode](https://realalpha.app/v/-HzgcbRXUK8/)

## Transcript

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

[41:08](https://realalpha.app/v/-HzgcbRXUK8/?t=2468) search process um and using that information in in you know very helpful ways so to go to your dream of modeling a cell what are the big challenges that lay ahead for us to make that happen, we should maybe highlight that alpha fold, I mean, there's just so many leaps. So alpha fold solved, if it's fair to say, protein folding, and there's so many incredible things we could talk about there, including the open sourcing, everything you've released.

[41:37](https://realalpha.app/v/-HzgcbRXUK8/?t=2497) Alpha fold three is doing protein RNA DNA interactions, which is super complicated and fascinating that's amenable to modeling. Alpha genome predicts how small genetic changes, like if we think about single mutations, how they link to actual function. So it seems like it's creeping along to much more complicated things like a cell, but a cell has a lot of really complicated components. Yeah. So what I've tried to do throughout my career is I have these really grand dreams.

[42:12](https://realalpha.app/v/-HzgcbRXUK8/?t=2532) And then I try to, as you've noticed, and then I try to break, but I try to break them down. You know, it's easy to have a kind of a crazy ambitious dream, but the trick is how do you break it down into manageable, achievable interim steps that are meaningful and useful in their own right? And so virtual cell, which is what I call the project of modeling a cell, I've had this idea, you know, of wanting to do that for maybe more like 25 years.

[42:38](https://realalpha.app/v/-HzgcbRXUK8/?t=2558) And I used to talk with Paul Nurse, who is a bit of a mentor of mine in biology. He founded the Crick Institute and won the NOAA Prize in 2001. We've been talking about it since, you know, before, you know, in the 90s. And I used to come back to every five years is like, what would you need to model of the full internals of a cell so that you could do experiments on the virtual cell and what those experiment, you know, in silico and those predictions would be useful for you to save you a lot of time in the wet lab, right?

[43:09](https://realalpha.app/v/-HzgcbRXUK8/?t=2589) That would be the dream. maybe you could 100x speed up experiments by doing most of it in silico the search in silico and then you do the validation step in the wet lab that would be that's the that's the dream and so but maybe now finally so i was trying to build these components alpha fold being one that that would allow you eventually to model the full interaction a full simulation of a cell and i'd probably start with the yeast cell and partly that's what paul nurse studied because the yeast cell is like a full organism that's a single cell right so it's the kind of simplest single cell organism and so it's not just a cell it's a full organism and um and yeast is very well understood and so that would be a good candidate for a a kind of full simulated model now alpha fold is the is the solution to the

[43:58](https://realalpha.app/v/-HzgcbRXUK8/?t=2638) kind of static picture of what does a what does a protein look 3d structure protein look like a static picture of it but we know that biology all the interesting things happen with the dynamics the interactions. And that's what alpha fold three is, is the first step towards is modeling those interactions. So first of all, pair wise, you know, proteins with proteins, proteins with RNA and DNA, but then the next step after that would be modeling maybe a whole pathway, maybe like the TOR pathway that's involved in cancer or something like this. And then eventually you might be able to model, you know, a whole cell. Also, there's another complexity here that stuff in a cell happens at different timescales. Is that tricky? It's like the, you know, protein, uh folding is you know super fast yes um i don't know all the biological mechanisms but some of

[44:43](https://realalpha.app/v/-HzgcbRXUK8/?t=2683) them take a long time yeah and so is that that's a level so the levels of interaction has a different temporal scale that you have to be able to model so that would be hard so you'd probably need several simulated systems that can interact at these different temporal dynamics or at least maybe it's like a hierarchical system so um you can jump up and down the the different temporal stages so can you avoid i mean one of the challenges here is not avoid simulating for example the the quantum mechanical aspects of any of this right you want to not over model you can skip ahead to just model the really high level things that get your real Yes, so you've got to make a decision when you're modeling any natural system, what is the cutoff level of the granularity that you're going to model it to that then captures the dynamics that you're interested in. So probably for a cell, I would hope that would be the protein level, and that one wouldn't have to go down to the atomic level. So, you know, and of course, that's where alpha-fold stock kicks in. So that would be kind of the basis. And then you'd build these higher level simulations that