Brittany Trang, Ph.D., covers AI in health and medicine: Does it actually work? Who benefits, or might be harmed? She writes the weekly AI Prognosis newsletter. Follow her on Threads, Mastodon, and Bluesky. You can reach Brittany on Signal at btrang.01.It’s officially a trend. For the third time in nine months, a pharma company has announced that it is assembling the largest AI supercomputer in the life sciences industry. This time, it is Bristol Myers Squibb.
When the company began its partnership with NVIDIA three years ago with a smaller computing cluster, it was focusing on simpler problems with individual AI tools, like protein structure prediction. But “we actually consumed all the space we had,” said Greg Meyers, chief digital & technology officer at BMS.
Adding extra computing power is necessary for the company now that it’s “become more convinced” that computationally hungry foundation models can give the company valuable insight into how its drug candidates interact with both the body and with disease, Meyers said in an interview with STAT. He mentioned oncology and neurodegeneration as examples of areas where BMS has developed such models.
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