Michael Fralick

Degrees, Title/Position:
Assistant Professor, Department of Medicine, University of Toronto
Clinician Scientist, Mount Sinai Hospital
Clinician Scientist, Lenenfeld-Tanenbaum Research Institute, Sinai Health
Associate Scientist, Li Ka Shing Centre for Healthcare Analytics Research & Training, Li Ka Shing Knowledge Institute
Affiliated Faculty, Program On Regulation Therapeutics And Law, Division of Pharmacoepidemiology, Brigham and Women’s Hospital

Goal Groups/Integration Themes:
Digital Health


Michael’s main research interest is in understanding the safety and effectiveness of sodium glucose co-transporter 2 (SGLT2) inhibitors by applying pharmacoepidemiology methods and machine learning. He primarily uses data collected from routine care (e.g., ICES, insurance claims data) and his main areas of methodologic expertise are in propensity score matching and supervised machine learning (e.g., gradient boosted trees).  Michael splits his research time between GEMINI and LKS-CHART and plans to integrate pharmacoepidemiology with Machine Learning to understand the safety and effectiveness of medications for adults with diabetes and cardiovascular disease.

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