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The current pandemic has challenged many assumptions on the health of populations. In this talk, we discuss Precision Medicine as a disruptive framework which focuses on the specific characteristics and needs of the individual. Recent computational advances have enabled a dramatic escalation in the ability to capture, store, communicate and analyze large amounts of highly granular data on the health of populations and individual subjects. In the broadest sense, Precision Medicine integrates a range of human characteristics including physical phenotypes, physiological signatures, gene expression, microbial diversity, serological and imaging biomarkers, illness trajectories, environmental exposures, and individual or family preferences. Extracting knowledge from these multi-dimensional data is possible with the help of relevant biological models, advanced statistical methods and artificial intelligence. Tune in as Dr. Stevens explains how effectively leveraging these methods represents a key to defeating pandemics and creating resilience at multiple scales.

Dr. Robert David Stevens is an intensive care physician who specializes in critical surgical and neurological illnesses and injuries. Following medical studies, he completed a residency in anesthesiology and fellowships in intensive care medicine and neurocritical care. He also underwent research training in neurobiology, electrophysiology, and brain mapping. Dr Stevens is Director of Precision Medicine for Anesthesiology and Critical Care Medicine and Associate Director of the Johns Hopkins Neurocritical Care Precision Medicine Center of Excellence. The focus of his research is to enhance resilience and recovery in intensive care patients through biologically driven, individualized decision-making and therapy. To achieve this, he engages with an interdisciplinary team of engineers, neuroscientists, data scientists, systems biologists, biostatisticians and image scientists. Ongoing projects in Dr Stevens’ lab leverage statistical and machine learning algorithms to decode features captured through physiological monitoring, structural and functional imaging, genomics, and wearable sensors. The overarching goal is to enable higher levels of precision in classification, prediction and therapy.