Finding the Rules for Successful Drug Optimization

Drug discovery is widely recognised as a process of multi-parameter optimisation, with the objective of finding compounds that meet a profile of many property criteria. These will depend on the ultimate therapeutic goal of the project and are typically chosen based on the subjective opinion of the project team. However, analysis of historical data can help to guide the determination of the most appropriate profile. In this article we describe computational approaches, described a described as rule induction, that enable an objective analysis of complex data to objectively identify multi-parameter rules that distinguish compounds likely to be successful for a project’s goal.