AI tool predicts responses to cancer therapy using information from each cell of the tumor
Sanju Sinha, Ph.D., along with Eytan Ruppin, M.D., Ph.D., and Alejandro Schaffer, Ph.D., at the National Cancer Institute, described a first-of-its-kind computational tool to systematically predict patient response to cancer drugs at single-cell resolution.
Dubbed PERsonalized Single-Cell Expression-Based Planning for Treatments in Oncology, or PERCEPTION, the new artificial intelligence–based approach dives deeper into the utility of transcriptomics—the study of transcription factors, the messenger RNA molecules expressed by genes that carry and convert DNA information into action.
“Our goal is to create a clinical tool that can predict the treatment response of individual cancer patients in a systematic, data-driven manner. We hope these findings spur more data and more such studies, sooner rather than later,” says Sinha.
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