Convergence of Machine Learning and Translational Genomics for Prostate Cancer Precision Medicine


2020 Emerging Leader Award - Arnold J. Levine Fellow

Dr. Van Allen is developing machine-learning algorithms to analyze genomic, imaging, and clinical data from over 3000 prostate cancer patients that can be used to predict clinical outcomes, inform care decisions, and accelerate new biological discoveries. This work will create a clinical and translational discovery engine in prostate cancer that will ultimately be translated into an open source platform that can be used by both clinicians and researchers. These efforts will also lay a foundation for innovative data science efforts across cancer types. Originally from Los Angeles, Dr. Van Allen studied Symbolic Systems at Stanford University, obtained his MD from UCLA, and completed a residency in internal medicine at UCSF before completing a medical oncology fellowship at the Dana-Farber/Partners CancerCare program.

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