Associate Professor Indiana University School of Medicine Indianapolis, Indiana
As part of a symposia focused on Clinical Pharmacology in the Era of Big Data, this presentation will describe the use of real-world, big data sources to identify and evaluate risk of novel drug-drug interactions. Using myopathy as a case example, I will describe the use of electronic health databases, such as the FDA Adverse Event Reporting System (FAERS), to identify clinically significant drug-drug interactions. Iwill further highlight a translational biomedical informatics approach that combines real-world data with mechanistic pharmacokinetic modeling to detect new clinically significant DDI signals and evaluate of their potential molecular mechanisms.
Using electronic health records, explore the risk of drug-drug interactions that produce myopathy.
Demonstrate how mechanistic pharmacokinetic modeling can support bioinformatic analyses of real-world drug interaction data.
Understand strengths and limitations of big data resources for drug drug interaction prediction.