Biohub, DOE, NIH, Google DeepMind, Isomorphic Labs, and Meta committed $1.8 billion to expand open AI-ready biological data. DOE will invest over $500 million in lab measurement, modeling, and computation. NIH will coordinate existing datasets and repositories aligned to the initiative. Biohub will standardize these datasets for AI model training. Google DeepMind, Isomorphic Labs, and Meta are investing $300 million in new technologies and datasets. The initiative aims to enable predictive models of life for disease prevention and treatment. The Virtual Biology Initiative was announced in April 2026. Biohub’s founding $500 million commitment anchors the work. The effort includes scaling measurement technologies like cryo-electron tomography and microscopy. Leading institutions like the Allen Institute and Broad Institute are supporting the initiative. NVIDIA will provide accelerated computing infrastructure and expertise. The goal is to create a unified, open data resource for the global research community.
What changed
AI-ready biological data generation was fragmented and smaller in scale.
What it unlocks
Building and training predictive AI models of biology at unprecedented scale.
- $1.8 billion total commitment
- $500M from DOE over five years
- $500M in prior NIH investment
- $300M from Google DeepMind, Isomorphic Labs, Meta
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