Real-World Data Approaches for Early Detection of Potential Safety and Effectiveness Signals for Generic Substitution: A Metoprolol Extended-Release Case Study.

Abstract

Real-world spontaneous adverse event reports and administrative health care data were utilized as one part of a multipronged approach to verify surveillance signals related to generic drug formulations. This study used metoprolol succinate extended release as a historic case example from which to develop an analytic framework. The US Food and Drug Administration Adverse Event Reporting System was utilized for disproportionality analyses and to identify outcomes of interest. Claims data were analyzed for generic uptake, proportion of prescriptions with "dispense as written" orders, time to discontinuation or switching, and relative rates of clinical events. Adverse Event Reporting System data showed that the Medical Dictionary for Regulatory Activities terms for product quality were higher for generic metoprolol cases and that a number of clinical events were increased that could be side effects of high or low variability in drug levels. Compared to amlodipine-benazepril, which also had a first-approved generic at the same time, market share data showed that metoprolol succinate had lower utilization and more prescriptions written as dispense as written. Switching and discontinuation were generally higher for metoprolol users compared to amlodipine-benazepril users. Finally, clinical event rates were generally higher for generic versus brand metoprolol but lower for the same comparison for amlodipine-benazepril users. In the claims-based analyses, the 90-day period immediately after generic entry provided stronger signal capture than using the entire study period. This analytic framework can be implemented to actively monitor new generic formulations for potential bioequivalence failures. Signals from these analyses require confirmation (eg, via pharmacometric analyses) to be informative for regulatory action.