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a16z Podcast · 3 min · Nov 6, 2025

Virtual cells will combine specialized models into broader systems

Mark Zuckerberg describes building from protein and cell models toward systems such as the immune system. Biohubs would generate purpose-built datasets and combine models into increasingly general simulations.

Mark Zuckerberg

Founder & CEO, Meta

Launched Facebook at Harvard with his roommates in 2004, and co-founded the Chan Zuckerberg Initiative.

  • Erik Torenberg, Host · General partner, Andreessen Horowitz

    Helped build Product Hunt; founded On Deck, Village Global and Turpentine.

About this segment

Mark Zuckerberg describes building from protein and cell models toward systems such as the immune system. Biohubs would generate purpose-built datasets and combine models into increasingly general simulations.

From “Mark Zuckerberg & Priscilla Chan: How AI Will Cure All Disease”, Nov 6, 2025. Watch the full episode

“you have different capabilities and then over time you train them into models and it gets more and more general”
Mark Zuckerbergat 21:00 · a16z Podcast21:00

Takeaways

  1. Build models at several biological scales.
  2. Generate datasets around specific biological challenges.
  3. Combine specialized models into more general ones.

In this episode

Full episode
  1. 3:23Shared tools can tackle science NIH grants leave unfunded5:20
  2. 15:18A shared annotation tool helped create a cell atlas3:16
  3. 21:34Virtual cells could make risky experiments cheaper to test4:02
  4. 11:22Most diseases need treatment tailored to individual biology2:58
  5. 28:00A shared data-and-model loop is driving Biohub's reorganization3:59
  6. 8:50CZI takes on long-term projects with a credible path2:37
  7. 38:17Biohub is scaling compute instead of lab square footage2:17

  8. 18:33Virtual cells will combine specialized models into broader systems2:53

Up next · MoonshotsSuperintelligence may need a new kind of algorithm6:24

Transcript

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

  1. 18:40

    Yeah, I mean, we think that this is going to be one of the most important tools at this point is basically building up the kind of hierarchy from proteins to just different structures within the cell to a whole virtual immune system or different levels of hierarchy. And we think this is going to end up being a very important set of tools for people to effectively generate hypotheses for different science work.

  2. 19:09

    Even before you get to the point where you're really running full experiments in it, you can come up with some estimate of how that might run. It will be useful for some of the precision medicine type examples that Priscilla was talking about a few minutes ago. But we think that this is probably one of the most important sets of tools that you need to build. And it's not a single thing, right? So there's different angles to come at this from.

  3. 19:36

    The Cell Atlas data is helpful for understanding things on a cellular level. One of the kind of most important things that we're doing right now, how there's this great company, Evolutionary Scale, who actually had a bunch of researchers who'd formerly worked at Meta on protein folding models, is joining a biohub, and Alex Reeves, the leader of it, is actually going to... be the kind of head of the whole science program, which is actually kind of interesting when you think about it, where it's like you have AI and biology coming together, and really it's like an AI person who understands biology as running it rather than a biologist who has some understanding of AI, I think just kind of speaks a little bit to where we think the relative weight of these things is.

  4. 20:20

    But, I mean, we basically view, you know, like Priscilla was saying with the different biohubs, New York doing cellular engineering will basically make it so that you can have cells that can record different things that are going on around the body and share that data, and then you can build that into models. The Chicago Biohub being able to record inflammation and basically study that in order to kind of help understand, like, that's a different data set.

  5. 20:47

    We have the Imaging Institute, which is what we just trained our first set of models around that, which are the first, like, spatial models around understanding like the way that that kind of cells look in different states and eventually just like you have this analogy on the kind of the industry side around language models where you have different capabilities and then over time you train them into models and it gets more and more general that's kind of the idea here so we'll we'll build the biohubs around grand biological challenges the biohubs will build tools that will generate novel data sets