Small molecule drug discovery requires identification of ligands manifesting highly potent and selective binding, while maintaining a wide variety of other ligand properties required for safety and biological efficacy. We will present how integrated deployment and collaborative use of advanced computational modeling and next-generation machine learning can enable discovery teams to rapidly achieve these goals. We will further present multiple case studies from active drug discovery projects highlighting how these technologies, rather than simply being used to evaluate ligand design ideas, can now be used to directly ideate novel ligand matter likely to advance discovery efforts.

Accelerating drug discovery through integrated deployment and collaborative use of advanced computational modeling and next-generation machine learning

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.