Perspectives on Generative Chemistry — Potential and Reality

Have advances in AI and deep learning reached a threshold whereby generative chemistry methods are redefining drug design? In this webinar, our panel of experts discuss their experiences of method development, real-life application and the advances being made.

Nikolaus Stiefl, Director of Data Science at Novartis shares his experience gained whilst building a generative chemistry platform, including algorithms, backend and initial project applications. The use cases provide different insights into the pros and cons of this approach along with optimisation techniques.

Philip Cheung, Scientific Informatics Software Consultant at Collaborative Drug Discovery, explores some of the challenges faced when implementing novel machine learning models for generative chemistry – plus several interesting approaches taken to overcome them.

Matt Segall, CEO at Optibrium, discusses the challenges of applying generative chemistry methods in practice and describes how experienced chemists can guide generative methods to rigorously explore a wide range of optimisation strategies and more effectively target high-quality compounds for their projects.

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