Biohub, Meta, Google DeepMind and the US Pool $1.8bn for AI Biology Data
The US Department of Energy and the National Institutes of Health (NIH) are investing $1.8bn to revolutionize AI-ready biology data, alongside Meta, Google DeepMind, and Isomorphic Labs, who are contributing $300M collectively. This initiative, announced on October 7, 2026, aims to create predictive models of cell behavior, accelerating scientific discovery.
Funding Breakdown
- Department of Energy: Over $500M for lab measurements, modeling, computing, and new technology, as part of the Genesis Mission science push.
- NIH: Bringing $500M in previous federal funding to standardize datasets for AI training.
- Biohub: Providing $500M for new tools to measure cells and $100M for external research.
Participation and Collaboration
Other notable institutions joining the effort include:
- The Allen Institute
- The Broad Institute
- The Gladstone Institutes
- The Wellcome Sanger Institute (UK)
- Human Cell Atlas and Human Protein Atlas consortia
- Nvidia (computing and software)
- Renaissance Philanthropy (fundraising support)
Open Data and Exclusive Access
The datasets will be publicly accessible, with commercial funders receiving one year of exclusive access to the data initially. Alex Rives, Biohub’s head of science, explained the need for incentives for commercial participation, hence the embargo period.
Future Goals
The current datasets contain hundreds of millions of cells, but accurate models require billions, and eventually trillions. The partners aim to deliver their first dataset within a year and achieve accurate predictions within five years.
Other AI labs, such as Anthropic and OpenAI Foundation, are also focusing on biology data. Rivercell, for instance, recently raised $25M to develop an AI virtual cell.