Use of Real-World Claims Data to Assess the Prevalence of Concomitant Medications to Inform Drug-Drug Interaction Risk in Target Patient Populations.

Abstract

A common issue in clinical drug development involves drug-drug interactions (DDI) that may lead to altered drug exposure and subsequent altered safety and efficacy of an investigational drug or concomitant medications (conmeds) in the target patient population. The drug development pipeline therefore involves DDI risk assessment of the investigational drug based on in vitro studies, in silico modeling, and clinical trials. Real-world data (RWD), particularly claims databases with reliable information on pharmacy dispensing, provide an opportunity to understand conmeds usage in the target indication in a real-world setting as one approach to assess potential DDI risk. We describe two cases of characterizing DDI-related conmeds usage with a large closed US-based claims database, IQVIA PharMetrics® Plus, and identified potential DDI risk for multiple sclerosis and hormone receptor-positive breast cancer. For example, prevalent and chronic use of statins (atorvastatin and simvastatin), which are CYP3A4 substrates, were identified among both disease cases. Further examples, limitations, and future directions are also discussed. These insights can therefore help augment decision-making during clinical drug research and development.