Risk-based quality management (RBQM) encourages clinical research teams to actively identify and assess risks that could impact study success, underscoring a thoughtful, proactive approach to compliance along the study lifecycle. Risk-based data management (RBDM) focuses on modern, adaptive, and intelligent analytics, identifying real-time “outliers,” such as training deficiencies or fraud, and enabling prompt corrective action.

This session will define the RBQM model and its value in protecting data quality and participant safety. It’ll demonstrate how RBQM, within the broader framework of RBDM, flags systemic data issues that traditional approaches might overlook, ensuring comprehensive risk management in clinical research.