Multi-parameter optimization (MPO) is increasingly used in drug discovery to prioritize compounds against a profile of properties required for success. But, how do we know what profile to use? The property criteria will depend on the ultimate objective of the project and are typically based on the subjective opinion of the project team. In this presentation we will describe computational approaches, described as rule induction, that guide this process by analysing historical data. These identify objective multi-parameter rules that distinguish successful compounds for a chosen goal, e.g. efficacy, pharmacokinetics or safety. The resulting rules are interpretable and modifiable, allowing experts to understand and adjust them based on their knowledge of the underlying biology and chemistry. Furthermore, the importance of each criterion can be identified, allowing the most critical data to be prioritized in order to make effective compound selection decisions.

Finding multi-parameter rules for successful optimization

245th National Meeting (2013)

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