The National Institutes of Health (NIH) is working with the U.S. Department of Energy (DOE), Biohub, and other partners to develop the data and resources needed to build Super Intelligence (SI) models that can better predict how cells and biological systems respond to disease and potential interventions, the Bethesda, Maryland-based agency announced on October 7, 2026. Through its new Bio Genesis Mission, NIH will bring together existing biomedical datasets, national data infrastructure, and research programs to create SI-ready resources for the broader scientific community.
“By combining resources and expertise, we can accelerate the development of universal cell models with sufficient biological complexity to predict how any cell responds to an intervention,” said Nicole Kleinstreuer, Ph.D., NIH Deputy Director for Program Coordination, Planning, and Strategic Initiatives. “The return from these models could be broad and profound, resulting in substantially faster timelines for medical breakthroughs as compared with attempting to attain the same results through laboratory experiments alone.”
Building on NIH’s Data Foundation
Predictive models of biology require enormous amounts of high-quality, SI-ready data showing how cells respond to interventions across different cell types and conditions. NIH’s existing investments provide a starting point, including national biomedical repositories catalogued by its National Library of Medicine and National Center for Biotechnology Information, as well as NIH Common Fund programs already developing coordinated biological atlases, shared data standards, and SI-ready datasets.
NIH will coordinate with Biohub to help standardize appropriate datasets for model training. Training these models will require measuring how cells respond to interventions across far more cell types and conditions than have been studied so far, along with new technologies that can study cells at scales and speeds current instruments cannot capture.
Toward a Virtual Cell
“An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally. The insights that come from this could unlock a far greater understanding of disease and open up completely new paths for cures,” said Alex Rives, Head of Science at Biohub. “Because of this potential, the creation of a virtual cell is one of the most important challenges for the next era of science. It will require coordinated data generation efforts at a national and international scale, which is why these partners are coming together. We invite the worldwide scientific community to join us in this project.”
The effort aligns with the Predicting Living Systems National Science and Technology Challenge. The resulting models could ultimately help scientists explore biological questions computationally, identify promising drug targets and interventions, and prioritize the strongest ideas for laboratory and clinical testing.
About the National Institutes of Health
NIH, the nation’s medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. It is the primary federal agency conducting and supporting basic, clinical, and translational medical research, investigating the causes, treatments, and cures for both common and rare diseases.
