The Allen Institute, the University of Washington, and Fred Hutch Cancer Center have launched AI BioDesign, a new research accelerator focusing on the development of AI models, datasets, assays, and tools to accelerate biological design for applications in human health, including precision medicine, as well as sustainability.
“For the first time, the speed of AI is beginning to match the experimental power of synthetic biology,” said David Baker, PhD, lead scientific director of AI BioDesign, director of the UW Medicine Institute for Protein Design, and investigator at the Howard Hughes Medical Institute. “That changes the question from ‘what has nature already made?’ to ‘what else is possible, and how can we test it?’ AI BioDesign can help turn that vast unknown into models that can help us solve some of humanity’s hardest problems.”
With financial support from the Fund for Science and Technology (FFST), the accelerator will bring together scientists across the three major Seattle’s institutes. The Allen Institute will provide experience in building large-scale, open-science platforms; the University of Washington will contribute expertise in synthetic biology and genome science through the Institute for Protein Design and the UW Medicine Brotman Baty Institute for Precision Medicine; while Fred Hutch Cancer Center offers depth in cellular systems, genomic, and translational medicine.
“AI BioDesign brings together the right people and the right institutions at the right time to advance biological design with AI in the loop,” said Rui M. Costa, PhD, president and CEO of the Allen Institute and professor of neuroscience at Columbia University. “The Allen Institute was built for this kind of work: big science, team science, and open science that creates resources entire fields can use. AI BioDesign combines this approach with AI models to guide which data we generate next, so experiments and models improve together in a continuous cycle of learning and testing. Ultimately, that can help us design new biological functions with greater precision.”
The accelerator’s long-term ambition is to identify underlying principles that could make biological engineering more predictable. “We want to engineer biological systems with similar reliability to mechanical, electrical, or software engineering,” said Jay Shendure, PhD, lead scientific director of AI BioDesign, scientific director of the UW Medicine Brotman Baty Institute for Precision Medicine, scientific director of the Seattle Hub for Synthetic Biology, and investigator at the Howard Hughes Medical Institute.
As researchers around the world increasingly build AI-enabled drug discovery pipelines, foundation models and virtual cells, the aim of AI BioDesign is to offer open-source, experimentally grounded resources to the scientific community. This will involve the development and combination of multiple modular models, new data generated from multiplex biological experiments, and the public release of models, datasets, assays, reagents, and benchmarks.
“For me, biology is ultimately a design challenge,” said Sanjay Srivatsan, PhD, a principal investigator at AI BioDesign and assistant professor at the Fred Hutch Cancer Center. “As part of AI BioDesign, our team plans to vastly scale up the number of genomic datasets available to researchers. We can then use AI to understand biological patterns in those datasets and use those patterns to inspire solutions to biological problems, such as designing cells that can remove cancer from the body.”
