Biohub leads $1.8 billion AI push to predict cell behavior

The effort builds on Biohub's earlier pledge of $500 million in April for its five-year Virtual Biology Initiative, with the new $1.8 billion expanding the scope to include data, lab equipment, and compute. The US Department of Energy is investing over $500 million in lab measurements and compute over five years, while the National Institutes of Health are coordinating datasets built with more than $500 million in prior federal funding. Biohub's role includes standardizing those datasets for AI training.

Other AI companies are pursuing biology projects as well. Anthropic has built its own biology lab for AI-driven drug development, and the OpenAI Foundation is putting more than $125 million toward biological and medical datasets. The commercial funders in Biohub's effort are granted one year of exclusive access to the data they paid for before it becomes public, a condition that may influence how quickly academic and other researchers can use the results.

The outcome hinges on whether standardizing government-funded datasets leads to models that can reliably predict cell behavior, which the body frames as a way to speed up drug development. That is an inference from the stated goal rather than a demonstrated result. For now, the first dataset expected in about a year will be an early signal of whether the combined funding translates into usable training data, and how the one-year exclusivity window shapes who gets to build on it.