On October 7, 2026, Biohub announced an expanded Virtual Biology Initiative valued at $1.8 billion across funding, data, computing and measurement technology. Google DeepMind, Isomorphic Labs and Meta made a joint $300 million commitment. The effort aims to generate biological data and build resources for future models that could predict how cells respond to interventions.
What the partners are contributing
The $1.8 billion figure combines different kinds of resources; it is not a cash-only total. The three technology companies’ $300 million commitment is also collective, rather than a set of publicly itemized company contributions.
The U.S. Department of Energy (DOE) plans to invest more than $500 million over five years in cell research, measurement, modeling and computing for the effort. Its work is part of the Genesis Mission. The National Institutes of Health (NIH), by contrast, will coordinate existing biomedical datasets, repositories and knowledge bases, then work with Biohub to standardize suitable data for model training.
Biohub’s earlier $500 million commitment anchors the initiative. It allocated $400 million to measurement technologies and $100 million to research outside Biohub. The wider collaboration also includes scientific organizations such as the Allen Institute, Broad Institute, Gladstone Institutes, Human Cell Atlas, Human Protein Atlas and Wellcome Sanger Institute. NVIDIA is contributing computing infrastructure, software and technical expertise, while Renaissance Philanthropy is helping expand funding for biological data generation.
Why the initiative needs biological data
AI models can make predictions only from patterns they have learned. For models of biology, that means measurements of how cells respond to different interventions—not just additional computing power. The initiative aims to gather those measurements across more cell types and conditions than have been studied to date, and to make appropriate data consistent enough for researchers to use in model training.
The planned measurement work spans several scales. Biohub has described cryo-electron tomography, a technique for viewing structures inside cells at near-atomic detail; microscopy intended to image millions to billions of cells in living tissue; and tools to build and perturb biological systems at molecular, cellular, tissue and whole-organism levels. These capabilities are intended to support future research, including predictive models of cellular responses. A working universal virtual cell is a goal of that research, not an outcome of the October announcement.
Data access and reported targets
Biohub describes the initiative’s intended resource as open. Alex Rives, Biohub’s head of science, said commercial partners would have exclusive access for one year to data they help generate before public release. He said government-funded work running in parallel would not have the same restriction.
Rives also described a first large-scale dataset as a target for roughly a year later, with predictive models targeted within a five-year horizon. Those are project targets, not guaranteed delivery dates.
