Swiss Federal Institute of Technology Zurich (ETH Zurich) Director of the Singapore-ETH Centre (SEC)
From screening to designing new molecules with machine intelligence
ETH Zurich, Department of Chemistry and Applied Biosciences, Zurich, Switzerland
Machine learning methods from the field of artificial intelligence (AI) have become indispensable tools for targeted molecular screening and design, aiming to revolutionize the drug discovery process and enable sustainable advancements. These methods find wide-ranging applications, including informed virtual compound screening, computationally optimizing combinatorial compound collections, designing focused libraries, predicting reactivity, and generating innovative molecules with specific properties "de novo." In an ideal scenario, AI learns iteratively from limited experimental data in design-make-test-analyze cycles, combining hypothesis generation through theoretical model building with the chemical synthesis and biological testing of computer-generated molecules. Throughout this presentation, we will provide examples of each application, highlight the strengths and limitations of these approaches, and explore the potential future opportunities they offer.
2.10.2023, 17:15
Innsbruck, L.EG.220, Innrain 80-82, CCB
3.10. 2023, 17:15
Linz, Hörsaal 5 , JKU campus, Altenbergerstrasse 69
5.10. 2023, 16:00
Wien, Praktikumshörsaal (Bauteil BA, 2tes Untergeschoss)