June 23, 2021
Hosted by the
University of Basel
Scientific knowledge advances through iterative cycles of hypothesis and experimentation. Developing products and processes of any kind also happens in iterative cycles. For example, small molecule drugs emerge from numerous cycles of lead optimization: Medicinal chemists synthesize variants of an active molecule, their bioactivities and properties are measured, based on which a new round of syntheses is planned to match a target profile.
The challenge to fully automate, and thereby enormously accelerate such cycles has been first addressed many years ago. However, until recently, the technical hurdles were considered too high by most. With advances in the automation of chemistry, biology, and machine learning approaches, this has started to change. An increasing number of companies and institutions are taking on the challenge.
This online meeting aims to provide an overview of existing closed-loop design-make-test platforms and projects from across the world.
Welcome & Introduction
Ross King, Chalmers University & University of Cambridge
Mariano Nicolas Cruz Bournazou, DataHow & KIWI Biolab
Andy Cooper, University of Liverpool & Mobotics
Pascal Miéville, École polytechnique fédérale de Lausanne (EPFL)
Alpha Lee, University of Cambridge & iDMT
Alán Aspuru-Guzik, University of Toronto & Kebotix
Todd V. De Collo, Eli Lilly and Company, San Diego