Events

Machine Learning-Guided Treatment Discovery and Planning

Speaker: Charlotte Bunne

Location: 60 Fifth Avenue, Room 150

Date: Monday, March 20, 2023

In recent years, massively parallel high-throughput methods have changed the course of modern drug discovery. While providing us with an unprecedented resolution into molecular processes, they require scalable and principled algorithms that integrate the most recent insights from human biology, are well aligned with the constrained nature of experiments, and incorporate the inherent structure of macromolecules and tissues. These criteria have guided my research toward mathematically grounded deep learning solutions, using notably optimal transport and geometric modeling. In this seminar, I will demonstrate how integrating these principles into the design of learning algorithms shifts our ability to predict heterogeneous patient treatment responses to the single-cell level, model combination therapies, and trace developmental differentiation processes. These novel deep learning approaches not only achieve state-of-the-art quantitative improvements over prior works but also open new frontiers in a current large-scale clinical study to predict treatment responses of unseen patients. Altogether, my work on neural optimal transport and geometric deep learning shows that innovations in the design of machine learning algorithms will be crucial for accelerating the discovery of therapeutics and proposing personalized treatment plans to patients.