Mining Adverse Event Databanks to Inform Complex Systems Pharmacology Models

Abstract

Ensuring that drugs are safe and effective is a very high priority for drug development and the US Food and Drug Administration review process. This is especially true today because of faster approval times and smaller clinical trials, especially in oncology and rare diseases. In light of these trends, systems pharmacology is seen as an essential strategy to understand and predict adverse drug events during drug development by analyzing interactions between drugs and multiple targets rather than the traditional "one-drug-one-target" approach. This talk offers an overview of the current trends and challenges of using systems pharmacology to reduce the risks of unintended adverse events and will illustrate examples of a systems approach to drug safety.