DOE's national labs will supply the computing for a $1.8 billion open-biology data effort
Biohub, NIH and the Department of Energy are building an open biological dataset for AI, with DOE putting in more than $500 million over five years. Biohub puts the total at $1.8 billion, and the supercomputers come from DOE's national labs.
Context for builders, not their beat.
DOE labs supply supercomputing, imaging and autonomous labs. DOE invests more than $500 million over five years. NIH gives datasets from more than $500 million in past federal spending. DeepMind, Isomorphic and Meta invest $300 million. Biohub commits $500 million. Researchers get open data.
- What's now possible capability DOE national laboratories Supply exascale supercomputing, X-ray and neutron scattering, cryo-EM and autonomous labs, claim 6
- What it costs cost Department of Energy Investing more than $500 million over five years in fundamental cell research, claim 2
- What's now possible capability NIH Contributes datasets built with more than $500 million in prior federal investment; Biohub standardizes them for AI, claim 3
- What it costs cost DeepMind, Isomorphic Labs, Meta Collectively investing $300 million in technologies and multi-modal datasets, claim 4
- What it costs cost Biohub Founding $500 million commitment, with $400 million for new measurement technologies, claim 5
- Who's exposed exposure Research community Gets the result as an open resource, claim 11
| Who | How | Kind | Claim |
|---|---|---|---|
| DOE national laboratories | Supply exascale supercomputing, X-ray and neutron scattering, cryo-EM and autonomous labs | capability | 6 |
| Department of Energy | Investing more than $500 million over five years in fundamental cell research | cost | 2 |
| NIH | Contributes datasets built with more than $500 million in prior federal investment; Biohub standardizes them for AI | capability | 3 |
| DeepMind, Isomorphic Labs, Meta | Collectively investing $300 million in technologies and multi-modal datasets | cost | 4 |
| Biohub | Founding $500 million commitment, with $400 million for new measurement technologies | cost | 5 |
| Research community | Gets the result as an open resource | exposure | 11 |
What happened
- NIH's contribution is datasets, repositories and knowledge bases built with more than $500 million of earlier federal spending, and Biohub will standardize them for AI training.
- Google DeepMind, Isomorphic Labs and Meta are together investing $300 million in technologies and multi-modal datasets for the Virtual Biology Initiative.
- Biohub's founding $500 million commitment anchored the initiative at its April 2026 launch, with $400 million going to new measurement technology.
Why it matters
- What it costs cost Public money covers more than half of the $1.8 billion, but DOE's five-year budget is the only new federal outlay in it.
- What's now possible capability Labs that are not funders get open training data for predictive cell models, covering more cell types and conditions than anyone has studied so far.
- Who has to decide decision Biotechs paying to generate their own cell-response data now have to weigh that spending against an open resource backed by $1.8 billion.
- What it sets up precedent DOE now has a working model for pairing national lab computing with philanthropic and corporate money under the Genesis Mission, and we'd expect it to recur in other fields.
Four stated contributions make up the $1.8 billion: more than $500 million each from DOE and NIH, $500 million from Biohub and $300 million from the three companies [14]. They are different kinds of money. NIH's share is datasets already paid for through earlier federal investment [3]. Leave it out and the commitment is about $1.3 billion [17].
On this record, the government supplies the computing and the companies pay for data. DOE's contribution runs through the Genesis Mission. It draws on exascale supercomputing, X-ray and neutron scattering, cryo-electron tomography and autonomous laboratories across the national lab system [6]. The corporate share is about a sixth of the total [16], and Biohub says it pays for technologies and multi-modal datasets [4].
The executive order behind the Genesis Mission goes further than this deal. It lists "secure cloud-based AI computing environments" beside DOE's national laboratory supercomputers as infrastructure for the mission's platform [7], and it names "pioneering American businesses" among the partners [8]. Industry's weight shows most clearly on the advisory side: Nature counted 12 technology chiefs and one academic among the President's new science advisers [10].
"Generating the data to solve predictive systems biology requires scaling past the limits of what any single organization can produce today," said Max Jaderberg, President of Isomorphic Labs [9]. In our view, the companies are buying into an open resource [11] at about a sixth of its cost because, on Jaderberg's account, none of them could generate the data alone. The releases do not say how the $300 million divides among the three companies, or whether funders get access before the open release.
What to watch
- Whether any Genesis Mission platform work runs on the secure cloud AI environments the executive order allows, and whose cloud provides them.
- Terms for the $300 million: how it splits among Google DeepMind, Isomorphic Labs and Meta, and whether funders see data before it opens.
- The first datasets released under the initiative and the date they open to outside researchers.
Claim ledger
Ranked by verification strength, evidence, and original report placement.
- [1]
On October 7, 2026, Biohub, the U.S. Department of Energy, the National Institutes of Health and new funding partners announced an expansion of an international effort, together investing $1.8 billion in funding, data, computation and new measurement technology to generate AI-ready biological data.
- [2]
DOE is investing more than $500 million over five years in fundamental cell research spanning data collection, analytics, laboratory measurement and imaging, modeling, and computation.
- [3]
NIH will coordinate the contribution of relevant datasets, repositories and knowledge bases developed through more than $500 million in prior federal investment; Biohub will work with NIH to standardize these datasets for AI model training.
- [4]
Google DeepMind, Isomorphic Labs and Meta are collectively investing $300 million in the Virtual Biology Initiative to create the technologies and multi-modal datasets needed to build predictive models of life.
- [5]
The Virtual Biology Initiative was announced in April 2026. Biohub's founding $500 million commitment anchors it: $400 million supports new measurement technologies and a further $100 million funds research outside Biohub.
- [6]
Through the Genesis Mission, DOE's contribution draws on exascale supercomputing, X-ray and neutron scattering, cryo-electron microscopy and tomography, and autonomous laboratories across the National Laboratory system.
- [7]
Executive Order 14363 directs the Secretary of Energy to establish the American Science and Security Platform, providing high-performance computing resources including DOE national laboratory supercomputers and secure cloud-based AI computing environments.
- [8]
The order says the Genesis Mission will combine the efforts of scientists, including those at national laboratories, with "pioneering American businesses", universities and existing research infrastructure.
- [9]
"Generating the data to solve predictive systems biology requires scaling past the limits of what any single organization can produce today," said Max Jaderberg, President of Isomorphic Labs.
- [10]
Trump's new science advisers include 12 technology chiefs and one academic.
- [11]
The result will be an open resource for the research community.
- [12]
The DOE, NIH and Biohub partnership delivers on the President's Executive Order Launching the Genesis Mission, drawing on resources across DOE's National Laboratory system.
- [13]
The initiative will expand cell response data to interventions across far more cell types and conditions than have yet been studied.
- [14]
The four stated contributions sum to the $1.8 billion headline.
- [15]
Federal agencies (DOE and NIH) account for more than $1 billion, about 56 percent of the $1.8 billion, and only DOE's portion is new spending.
- [16]
The three companies' $300 million is about one-sixth of the $1.8 billion.
- [17]
Excluding NIH's datasets from prior federal investment, the commitment is about $1.3 billion.
Sources & coverage · 4 publishers
The reporting this story was synthesized from, earliest first. Every link goes to the original.
- whitehouse.govNov 24Launching the Genesis Mission – The White House
- biohub.orgOct 7AI-ready biological data: $1.8 billion global commitment