Attending this event?
For more information visit the symposium website: https://slas.org/events/slas-2020-european-sample-management-symposium
Monday, March 16 • 9:20am - 10:00am
Keynote Address: Molecules on Demand

Sign up or log in to save this to your schedule and see who's attending!

There is a need for fresh thinking and innovative approaches to deliver higher quality drugs at a lower cost-to-market. However, the drug design process is non-deterministic, and the molecular design-make-test cycle essentially represents an adaptive stochastic search. Identification of suitable drug candidates, and the elimination of unsuitable compounds early in the discovery process provide opportinities to achieve this goal. Already, a variety of machine learning methods from the field of ‘artificial intelligence’ (AI) have been used to generate prototypical compounds with desired druglike properties and bioactivities, and to search for solutions to various scientific and technical challenges in medicinal chemistry. There is proof-of-concept for early recognition of potential side-effects, successful drug repurposing, improved accuracy for drug property predictions, and the autonomous generation of drug candidates by machine intelligence. The combination of laboratory automation and innovative software solutions for process planning and drug design promises better drug candidates, discovered and delivered faster. We will highlight opportunities and limitations of designing "molecules on demand" using machine intelligence.

avatar for Gisbert Schneider, Ph.D.

Gisbert Schneider, Ph.D.

Professor, ETH Zurich
Gisbert Schneider is a full professor at ETH Zurich, holding the Chair for Computer-Assisted Drug Design. He is recognized as being a pioneer in the integration of machine-learning methods into practical medicinal chemistry, and for his coining the phrases ‘scaffold-hopping’ and... Read More →

Monday March 16, 2020 9:20am - 10:00am
Room Saphir