Can Data-Centric AI Help Us Develop Better Drugs?

Explore the potential of data-centric AI in revolutionizing drug development through this 28-minute video presentation by Snorkel AI. Delve into the challenges of modern medicine and the increasing complexity and cost of developing new therapeutics. Learn how machine learning models can be leveraged to predict outcomes of drug development experiments, potentially outperforming traditional heuristics. Discover the integration of high-quality data from human cohorts with cutting-edge methods in high-throughput biology and chemistry to produce massive amounts of relevant in vitro data. Understand how these data are used to train ML models for predicting novel targets, identifying coherent patient segments, and forecasting clinical effects of molecules. Gain insights into a new approach to drug development that aims to design novel, safe, and effective therapies more efficiently, helping more people at a lower cost. This talk bridges the gap between digital biology, drug discovery, and machine learning in medicine, offering a glimpse into the future of pharmaceutical research and development.