XML talk: Machine learning-driven small molecule screening analysis for myocardial infarction treatment

Myocardial infarction (MI) results in the loss of millions of cardiomyocytes, and the formation of a non-contractile scar, ultimately leading to heart failure. Despite more than a decade of research on cardiac regeneration, clinical study results using standard stem cell approaches have been disappointing and currently the only cure is heart transplantation. One possible solution is to identify novel small molecules that can activate the resident epicardial cells in the human heart, by promoting Epithelial-to-Mesenchymal Transition (EMT), and regenerate the infarcted heart. This talk will present the results of the drug screens we have developed using a machine learning-based image analysis protocol, which allows us to automatically calculate the percentage of EMT for each experimental image. Free Pizza will be served after the talk.