# Biology models must build from proteins up to cells

Markdown copy of https://realalpha.app/s/biology-models-must-build-from-proteins-up-to-cells/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Mark Zuckerberg](https://realalpha.app/builders/mark-zuckerberg/) · Co-founder, Biohub · Launched Facebook at Harvard with his roommates in 2004, and co-founded the Chan Zuckerberg Initiative.
- Host: [Elad Gil](https://realalpha.app/people/elad-gil/) · CEO, Gil & Co · Investor in Airbnb, Stripe, Coinbase and Anthropic; co-founded Color.
- Host: [Sarah Guo](https://realalpha.app/people/sarah-guo/) · Founder, Conviction · Ex-Greylock partner; early investor in Cognition, Harvey and Mistral.
- Show: No Priors
- Episode: [“Curing All Disease by next century is too conservative" - Mark Zuckerberg](https://realalpha.app/v/u8cYwaLzN-k/), Jun 10, 2026
- Moment: 10:04 to 12:40 of the episode (3 min), playing on https://realalpha.app/s/biology-models-must-build-from-proteins-up-to-cells/; the episode from there: https://realalpha.app/v/u8cYwaLzN-k/?t=604

## Quote

> “you kind of want to build the simulations at **each level hierarchically**.”
> — [Mark Zuckerberg](https://realalpha.app/builders/mark-zuckerberg/) at [11:06](https://realalpha.app/v/u8cYwaLzN-k/?t=666) · No Priors

## Takeaways

1. Protein interactions help explain how cells work.
2. Higher-level models need to build on lower-level biology.
3. Wet-lab experiments can connect data across biological layers.

## About this segment

Mark Zuckerberg argues that cellular and system models depend on understanding lower biological layers first. Biohub pairs AI and wet-lab work to gather data that links those layers.

From ““Curing All Disease by next century is too conservative" - Mark Zuckerberg”, Jun 10, 2026. [Watch the full episode](https://realalpha.app/v/u8cYwaLzN-k/)

## Transcript

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

[10:08](https://realalpha.app/v/u8cYwaLzN-k/?t=608) You're doing cell-based stuff. You're thinking about interrogating larger scale systems in biology. How well do you think that extends from sort of the micro to the macro? You mentioned almost starting with building blocks and building up, but modeling cellular behavior is very different from modeling protein folding. The data is very different. The modeling is different. I'm just curious, like, do you think it's all similar in terms of just data and you train stuff or do you think it's actually uh there's some differences in terms of how you actually have to deal with these systems i mean there are probably some differences i mean you can probably talk more to the specifics around this but like i mean i think each layer is going to end up being somewhat qualitatively different right i mean the the but you need to be able to

[10:46](https://realalpha.app/v/u8cYwaLzN-k/?t=646) understand the protein interactions in order to be able to understand how cells work so you can't just go straight to cells in a way without understanding the protein modeling and then if you're trying to understand something like the you know the way the immune system works or a bunch of cells interact together, um, then, um, you know, it's tough to do that without first understanding cells. I mean, you might be able to, at like a very high level of abstraction, simulate a system, but if you really want to like understand how it's going to work, you kind of want to build the simulations at each level hierarchically. So that's basically the approach that we're going through, starting with the, um, the building blocks and the, and the protein. But yeah, I mean, I think that there's going to be different types of data that

[11:23](https://realalpha.app/v/u8cYwaLzN-k/?t=683) you want to collect for each, um, the modeling techniques, I think we'll see, I mean, that'll all keep on advancing across the board. But I do think that a big part of the strategy is this view that you need to build it up hierarchically. And, you know, one of the things that's unique about us in the space is we were very intentional that the AI efforts and the wet lab efforts were a single effort. And we've done a lot of work to bring them together. And the really neat thing that we can do is really try to pull and gather data that helps us connect across sort of the hierarchy. You know, you can look at transcriptomics with space within a cell and look at where it's localizing. We can look at translucent zebrafish and look at the development across different cells and when the brain develops. We have sensors that allow us to look at cell-cell

[12:15](https://realalpha.app/v/u8cYwaLzN-k/?t=735) communication in different molecules. And so we can be strategic about the types of experiments and data we want to collect that helps us bridge across these, that makes it so that there's some... connective tissue that helps drive the modeling that, you know, the modeling magic that happens. Yeah. The reason I asked the question, by the way, is I used to be a biologist. I have a PhD