“Machine learning: a new approach to drug discovery”
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.
Daphne Koller is CEO and Founder of insitro, a machine-learning enabled drug discovery company. She was a Stanford CS Professor, co-founder of Coursera and Engageli, one of TIME Magazine’s 100 influential people, and a MacArthur Fellow.