Finding Signal in the Noise: Visualizing Big Data to Design Better Drugs

Description:
The discovery and development of new drugs has become increasingly challenging. The number of new drug candidates that encounter failure in clinical development has increased and the number of new drugs reaching the market has decreased in recent years. One factor contributing to the high attrition rate is due to unexpected behavior in the clinic, for example due to unforeseen toxicity or lack of efficacy. This has been further compounded by increasingly challenging new disease targets occupying historically “undruggable” space. The interaction between drug molecules and these undruggable targets can be difficult to predict and optimize. As a result, it is critical to understand the properties of potential drug molecules as well as their behavior towards these targets.
In parallel with these challenges, there has been a concomitant increase in the development and application of new high throughput tools for rapidly assessing and characterizing a large number of drug molecules. While this can significantly enhance the exploration of the drug molecule space, it can be also result in an overwhelming amount of data that must be carefully parsed and interpreted. While the quantity of data can be useful, it is crucial to be able to find the quality “signal in the noise” and to be able to rapidly extract meaningful conclusions from Big Data in order to better influence drug discovery and development. This presentation will focus on identifying key correlations between chemical properties obtained in high throughput approaches with meaningful study endpoints (e.g., bioperformance), resulting in improved strategies for optimizing drug molecules.

Speaker: Dennis Leung - Genentech, Inc.
Dennis Leung received his PhD in Chemistry from the University of California, Berkeley in 2006 working on supramolecular chemistry as a joint student with Prof. Bob Bergman and Ken Raymond. He then pursued a postdoctoral position at the University of California, Irvine working on designing novel polymerization catalysts before beginning his industrial career at Merck in the Pharmaceutical Sciences department. He moved to Genentech in early 2016 where he is currently a Director and Principal Scientific Manager of the Discovery Pharmaceutics and Preformulation group within the Genentech Research and Early Development organization. This is a new interdisciplinary group that supports new drug candidates in the drug discovery and early drug development phases with a focus on pharmaceutics, materials science, formulation, and drug delivery.