The first machine learning-based tool that can predict immune checkpoint inhibitor (ICI) response using routine clinical data such as complete blood counts and metabolic profiles has been developed. The SCORPIO model was validated using data from 9,745 patients across 21 cancer types treated with ICIs from Memorial Sloan Kettering Cancer Center (MSKCC), Mount Sinai Health System (MSHS), and 10 global Phase III clinical trials.
The paper appeared in Nature Medicine and the lead author is Seong-Keun Yoo, PhD, a postdoctoral fellow at the Icahn School of Medicine at Mount Sinai. Diego Chowell, PhD, assistant professor of immunology and immunotherapy, oncological sciences, and artificial intelligence and human health, Icahn School of Medicine at Mount…