Next Generation Of Clinical Monitoring | Part 1: Detect Variability In Adverse Event Reporting

Due to the inclusion of more decentralized components, adaptive study designs, and data originating from various sources, modern clinical trials are becoming more complex. As a result, the variability in adverse event reporting can negatively impact patient safety and clinical trial data integrity.

Conventional monitoring methods—typically involving thorough site audits and monitoring activities via manual source data review (SDR) and source data verification (SDV)—are inefficient and difficult to scale across global programs. Because site data is examined separately, these methods only give a partial picture of the overall data quality and trial risk. When assessing early detection of study-level data risks, such as variability in the adverse event (AE) reporting, site-based monitoring approaches alone are also described as insufficient.

Learn how comprehensive data and risk surveillance technologies can help detect and address these issues so that study teams can ensure data veracity and quality across large datasets and supplement traditional site-based monitoring activities.