Noesion Radarnoesion.ai
Research2026-08-06

Stanford researchers led by chemical engineering assistant professor Brian Hie and graduate student Samuel King used Evo 2, an open-source generative genome model, to write complete bacteriophage genomes end-to-end from a snippet of ΦX174 DNA, which is under 6,000 base pairs. They synthesized and tested nearly 300 of the AI-designed phages against E. coli and identified 16 that performed exceptionally, with some exceeding the fitness of native ΦX174. A cocktail of the 16 phages rapidly overcame E. coli strains resistant to native ΦX174, presented as proof of concept for resistance-resistant phage therapies. The work was published in Science (doi 10.1126/science.aec2657) and reported on August 6, 2026; Evo 2 remains freely downloadable via the Arc Institute GitHub repository, with the authors addressing biosecurity concerns by arguing safety checks can be built into AI tools. Funding came from the Arc Institute, NSF, and Stanford HAI, among others.

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