Abstract

The development of algorithms for reaction/route prediction, chemical space generation and affinity/property prediction is at full bloom; more and more tools are becoming accessible to Medicinal Chemists through the hands of Computational Chemists trained in ML algorithms.
But how can we accelerate the efficient implementation of these tools into Medicinal Chemistry and ultimately into drug discovery projects?
This presentation illustrates concepts for integration of ML algorithms with HT experimentation / automated DMTA. It will elucidate some of the technical questions to be solved with respect to synthesis, analytics and testing. I will outline concrete examples of ML applied within SM H2L projects and our learnings. Finally, the presentation concludes with an outlook into potential future applications for New Modalities.