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CCB Seminar: Transforming Drug Discovery using Digital Biology – Daphne Koller (CEO of Insitro, Adjunct Professor of CS & Pathology, Stanford University)

February 2 @ 3:00 pm - 4:00 pm

CCB Seminar: Daphne Koller (CEO of Insitro, Adjunct Prof. of CS & Pathology at Stanford)

Zoom Link: https://berkeley.zoom.us/j/99602191832

Abstract: Modern medicine has given us effective tools to treat some of the most significant and burdensome diseases. At the same time, it is becoming consistently more challenging and more expensive to develop new therapeutics. A key factor in this trend is that the drug development process involves multiple steps, each of which involves a complex and protracted experiment that often fails. We believe that, for many of these phases, it is possible to develop machine learning models to help predict the outcome of these experiments, and that those models, while inevitably imperfect, can outperform predictions based on traditional heuristics. To achieve this goal, we are bringing together high-quality data from human cohorts, while also developing cutting edge methods in high throughput biology and chemistry that can produce massive amounts of in vitro data relevant to human disease and therapeutic interventions. Those are then used to train machine learning models that make predictions about novel targets, coherent patient segments, and the clinical effect of molecules. Our ultimate goal is to develop a new approach to drug development that uses high-quality data and ML models to design novel, safe, and effective therapies that help more people, faster, and at a lower cost.

Bio: Daphne Koller is CEO and Founder of insitro, a machine-learning enabled drug discovery company. She is co-founder of Engageli and was a Computer Science Professor at Stanford, co-founder of Coursera, and Chief Computing Officer of Calico. Daphne was one of TIME Magazine’s 100 most influential people and is a MacArthur Fellow, a member of the National Academy of Engineering, and a Fellow of the American Association for Artificial Intelligence, the American Academy of Arts and Sciences, and the International Society of Computational Biology.

Details

Date:
February 2
Time:
3:00 pm - 4:00 pm