Evangelos K. Oikonomou, MD, DPhil

Project Title: A machine learning, phenomapping strategy for adaptive predictive enrichment in randomized controlled trials

Evangelos is a clinical fellow in cardiovascular medicine and a member of the American Board of Internal Medicine (ABIM) Physician-Scientist Research Pathway at Yale School of Medicine. He obtained his medical degree from the University of Athens in Greece and subsequently completed a PhD in Medical Sciences at the University of Oxford. At Yale, Evangelos has joined the Cardiovascular Data Science (CarDS) lab (led by Rohan Khera, MD, MS). His most recent work describes a data-driven algorithm to detect personalized treatment effect signatures in randomized controlled trials. Evangelos’ CERSI project aims to test the feasibility, effectiveness, and safety of implementing this approach for the predictive enrichment of adaptive clinical trials through machine learning-guided phenomapping. This will assess a new paradigm for the design of more efficient randomized controlled trials, maximizing inference and minimizing the risk for trial participants.