Biohub’s Virtual Biology Initiative grows to $1.8B
DOE, NIH, Google DeepMind, Isomorphic Labs and Meta join the push for open data to build AI ‘virtual cells’
Confirmed
The takeaway
On Oct 7, 2026 Biohub (the Chan Zuckerberg science organization), the US Department of Energy and the NIH expanded the Virtual Biology Initiative to $1.8B in money, data, compute and measurement technology.
Status
- Claim
Confirmed
- Our reporting
- High confidence
- Importance
- 3 of 5
- Last verified
- 8 October 2026
Your AI and this story
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None of these four assistants can know about it. The closest, Claude Opus 5.5, stops 99 days before it.
Key facts
- Commitments: Biohub $500M (its April 2026 founding pledge: $400M measurement technology, $100M external research); DOE $500M+ over five years; NIH datasets and resources from $500M+ of prior federal investment; Google DeepMind, Isomorphic Labs and Meta $300M combined (biohub.org)
- DOE contributes exascale computing, X-ray/neutron scattering, cryo-EM and autonomous labs under the Genesis Mission; NIH coordinates datasets and standards through a ‘Bio Genesis Mission’
- Supporting organizations: Allen Institute, Broad Institute, Gladstone Institutes, Human Cell Atlas, Human Protein Atlas, Wellcome Sanger Institute, NVIDIA, Renaissance Philanthropy
- Biohub calls it the largest coordinated commitment to AI-ready biological data so far; the data are to be open
- Quotes: Alex Rives (Biohub head of science): ‘A virtual cell is one of the most important challenges for the next era of science’; Max Jaderberg (Isomorphic Labs president) on scaling past single-organization limits
- The initiative was launched in April 2026 at $500M (Biohub alone)
- The White House listed the $1.8B initiative in its Oct 8 science-summit fact sheet (see White House science summit: $2.4B in AI pledges for the Genesis Mission)
What happened
The expansion adds the US government and three AI companies to Biohub’s April 2026 program. Most of the “$1.8B” is in-kind (government data, compute, instruments) rather than new cash; the company share is $300M combined, with no per-company split published.
Why it matters
Virtual-cell models need far more standardized perturbation data than exists. Pooling federal labs, Biohub and frontier AI labs behind open data is the biggest bet yet that biology can be modelled the way AlphaFold modelled protein structure.
Sources
2 sources from 2 sites. Numbers match the chips in the text.
2 sources: 1 primary, 1 press
Primary
- Biohub: Open data for predictive AI models of biology: $1.8 billion committedbiohub.org, official
Press
Changes
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