The Predict-First Paradigm: How Digital Chemistry is Shaping the Future of Drug Discovery

Digital chemistry offers a modern paradigm for enabling rapid in silico testing of design ideas using highly accurate computational assays of key properties, accessible across whole project teams. This shift from design strategies based largely on experimental trial and error towards a ‘predict-first’ approach to drug discovery allows teams to dramatically expand the chemical space that can be explored and results in a highly interactive, computationally-driven design-predict-make-test-analyze cycle. Chemists are empowered to test hypotheses through predictive modeling and iteratively improve designs prior to compound synthesis. Teams can confidently explore novel, and often more complex designs while sending only the top scoring molecules for synthesis. In this talk, we will walk through the digital chemistry strategy used by Schrödinger’s therapeutics group, which has led to several successful clinical-stage drug discovery candidates. We will also introduce an upcoming expansion of the computational platform to predict toxicology risk in early stage drug discovery.