Arc Institute is a nonprofit biomedical research organization based in Palo Alto, California.[
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History
Arc Institute was founded in 2021 to provide scientists with research opportunities without the need for external grant applications.
Arc Institute was launched with an initial endowment of $650 million.[ Founding donors include Ethereum creator Vitalik Buterin, Stripe co-founders Patrick Collison and John Collison, angel investor Ron Conway, Color Genomics co-founder Elad Gil, Cue co-founder Daniel Gross, Facebook and Asana co-founder Dustin Moskovitz, Open Philanthropy chair Cari Tuna, General Catalyst CEO Hemant Taneja, and Jane Street Capital executives. Silvana Konermann is the executive director, and Patrick Hsu leads the development of research teams focused on technology related to biological research. Both Konermann and Hsu lead research labs in addition to their other roles at the institute.]
The institute houses laboratories at its facility at Stanford Research Park and funds projects at partner universities.
Funding structure
Funding focuses on "high risk, high reward science,"
Arc core investigators work within the institute itself, and are given a budget to support a lab of up to 20 people and full funding for eight years of laboratory operations.
Arc innovation investigators receive $1 million over five years, while Ignite Awards grant researchers from the three partner universities $100,000 for one year.
Research
The institute brings together researchers from varied backgrounds to facilitate collaboration between biologists doing experimental research and researchers creating new technology.
In 2024, Patrick Hsu and collaborators developed a new method of genetic engineering called "bridge RNA" that simplifies the process of gene modification with increased precision to minimize disease risk.
Also in 2024, Arc researchers led by Hsu and Brian Hie released a large language model trained on biological sequence data.
In January 2025, Arc Institute announced a partnership with Nvidia to integrate biology and machine learning.
