Risk Assessment for Pancreatic Cancer: From Dream to Reality
Chris Sander, Ph.D., Harvard Medical School Leader, Pancreatic Cancer Collective Research Team: Computational Approaches to Identifying High-Risk Pancreatic Cancer Populations
AI may, at long last, point us toward an early-stage detection solution for pancreatic cancer. Pancreatic cancer ranks among the most aggressive cancer types, and screenings for this cancer type are limited to those with a family history or genetic risk. Pancreatic cancer patients are often asymptomatic when the cancer is in its early stages; most are diagnosed at Stage 4.
Dr. Sander, his lab, and collaborators are working to change this through a three-step project that involves 1) developing a population-wide approach to risk assessment that relies on AI to extract predictive information from enormous data sets of patients’ clinical records; 2) creating and disseminating more effective early-stage detection tests that rely on blood-based biomarkers, and 3) rolling out these tools and methodologies in early-stage detection clinics. The team is currently seeking collaborators across a number of health systems to advance all three steps.
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