Biohub, DOE, NIH and Google DeepMind Back $1.8 Billion Push for Virtual Cell AI Data
Biohub said on October 7, 2026 that it, the US Department of Energy, the NIH and three AI companies are putting $1.8 billion into open biological data for AI models that predict how cells behave.
Key takeaways
- Biohub, the US Department of Energy and the National Institutes of Health announced on October 7, 2026 a $1.8 billion effort in funding, data, computation and measurement technology to build open, AI-ready biological data.
- The Department of Energy is committing more than $500 million over five years, and Google DeepMind, Isomorphic Labs and Meta are investing $300 million together, according to Biohub.
- Biohub's own $500 million dates from the Virtual Biology Initiative it launched on April 29, 2026, and NIH contributes existing datasets, so a little more than $800 million of the total is new money announced on October 7.
- Companies that fund the work get one year of exclusive access to the data they help pay for before it becomes public, Biohub head of science Alex Rives told Axios.
Biohub, the nonprofit research institute backed by Mark Zuckerberg and Priscilla Chan, announced on October 7, 2026 a $1.8 billion effort with the US Department of Energy (DOE) and the National Institutes of Health (NIH) to produce open biological data for AI models that predict how cells behave. Google DeepMind, Isomorphic Labs and Meta are investing a combined $300 million of that, Biohub said in its announcement.
The goal is a virtual cell, an AI model that can predict how a human cell reacts to a drug or a genetic change before anyone runs the experiment. AI can already model proteins, but the measurements needed to model a whole living cell mostly do not exist yet, Axios reported. That is why this bet in AI research for biology goes into lab data and instruments rather than into a new model.
What did Biohub and its partners announce?
Biohub said on October 7, 2026 that it and its partners will put $1.8 billion in funding, data, computation and new measurement technology into an open data resource for predictive AI models of biology. Biohub calls it the largest coordinated commitment to AI-ready biological data to date.
The announcement expands the Virtual Biology Initiative, a five-year program Biohub launched on April 29, 2026 with $500 million of its own: $400 million for new measurement and engineering tools and $100 million for research outside Biohub. Those tools include cryo-electron tomography, which images the inside of a cell in near-atomic detail, and microscopy that can follow millions to billions of cells in living tissue.
Reuters reported the corporate investment ahead of The Verge, The Verge noted, and The Wall Street Journal also reported the partnership on October 7.
An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally.
Who pays for what?
The DOE is committing more than $500 million over five years and Google DeepMind, Isomorphic Labs and Meta $300 million together, according to Biohub. NIH's share is not new spending: it will coordinate datasets, repositories and knowledge bases built with more than $500 million in earlier federal funding, and Biohub will standardize them for AI training.
| Partner | Contribution | What it covers |
|---|---|---|
| US Department of Energy | More than $500 million over five years | Lab measurement, modeling and computation through the Genesis Mission |
| National Institutes of Health | Datasets from more than $500 million in prior federal investment | Existing repositories and knowledge bases, standardized by Biohub |
| Google DeepMind, Isomorphic Labs, Meta | $300 million combined | Technologies and multimodal datasets for the initiative |
| Biohub | $500 million, announced April 29, 2026 | $400 million for new tools, $100 million for outside research |
| NVIDIA | No amount given | Computing infrastructure, software and technical expertise |
The DOE money runs through the Genesis Mission, a cross-agency program led by the department, and draws on exascale supercomputers, X-ray and neutron scattering, cryo-electron microscopy and autonomous labs at the national laboratories, the release says. Biohub gives one figure for the three companies together, not a split per company.
Adding up the four lines in Biohub's release gives just over $1.8 billion, but two of them were not new on October 7. Biohub's own $500 million was announced in April, and NIH's line is the value of data that federal programs have already paid for. That leaves a little more than $800 million in fresh commitments, the DOE's money plus the companies' $300 million, a calculation from the two Biohub releases rather than a figure Biohub states.
The scientific partners named on October 7 are the Allen Institute, the Broad Institute, the Gladstone Institutes, the Human Cell Atlas, the Human Protein Atlas and the Wellcome Sanger Institute.
Will the data really be open?
The data is meant to become public, but not all of it at once: companies that fund the work get one year of exclusive access to the data they help pay for before it is released, Rives told Axios and Reuters (Reuters via The Decoder). Work funded with government money will be available without that restriction, according to The Decoder.
Rives told Axios that the one year embargo gives companies a reason to take part while keeping the data an open scientific resource. Biohub's own release describes the result as "an open resource for the research community" and does not mention the one year window.
Biohub says it will build shared standards, common identifiers and a single point of access so that the partners' datasets work together. It has run community data tools before, including CELLxGENE and the CryoET Data Portal, according to the release.
We will not solve this challenge without open, experimental biological data at an unprecedented scale, showing how living cells behave and respond to changes.
When could a virtual cell model arrive?
No partner has given a date for a working virtual cell; the first dataset should be ready in about a year (Reuters via The Decoder). Within about a year of that first large dataset, researchers expect to train models, measure what they can do and learn which additional data helps most, Axios reported.
An open question is whether cell biology follows scaling laws, the pattern seen in other AI fields where models improve predictably as training data grows, according to Axios. NIH's Nicole Kleinstreuer said in the release that the partners want universal cell models that can predict how any cell responds to an intervention.
What we don't know yet
- How the $300 million splits between Google DeepMind, Isomorphic Labs and Meta, and what each company gets beyond the one year head start on data.
- Which cell types, conditions and data types the first dataset will cover, and under which license the data will be released.
- How the DOE's more than $500 million is phased over the five years.
FAQ
What is a virtual cell?
A virtual cell is an AI model that simulates a living cell well enough to predict what happens when something changes, for example when a drug is added or a gene is switched off. Researchers could then test ideas on a computer and send only the most promising ones to the lab. Biohub describes a high accuracy model of this kind as a goal, not something that exists today.
Is Mark Zuckerberg paying for this himself?
Partly, and in two ways. Biohub, founded in 2016, is the research organization backed by Zuckerberg and his wife Priscilla Chan, and it put up the founding $500 million. Meta, the company Zuckerberg runs, is one of three companies behind the separate $300 million corporate share.
Are other AI labs funding biology data?
Yes. The Decoder reports that the OpenAI Foundation is putting more than $125 million toward biological and medical datasets and that Anthropic has built its own biology lab for AI driven drug development. In dollar terms the Biohub effort is far larger than the OpenAI Foundation figure, and its money comes from government, philanthropy and three companies.
What is Isomorphic Labs?
Isomorphic Labs is an AI drug discovery startup, as The Verge describes it. Its president, Max Jaderberg, said in Biohub's announcement that the company joins the Virtual Biology Initiative as a founding member.
Sources
- International, cross-sector collaboration commits nearly $2 billion to build foundational data for AI models to predict and treat disease Biohub · biohub.org
- Biohub Launches the Virtual Biology Initiative to Galvanize a Global Effort to Create the Open Data Foundation for AI-Accelerated Biology Biohub · biohub.org
- Google invests millions in Mark Zuckerberg's efforts to create a 'virtual cell' The Verge · theverge.com
- Zuckerberg's Biohub leads a $1.8 billion push to build AI models that predict cell behavior The Decoder · the-decoder.com
- Zuckerberg teams with Google, U.S. in push to map cells Axios · axios.com
- Zuckerberg's Biohub Partners With DOE, NIH to Invest $1.8 Billion in Biological Data for AI Models The Wall Street Journal · wsj.com · paywalled, headline only
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