Rare disease trials face unique challenges due to small, dispersed patient populations and complex protocols. Late or fragmented RBQM implementation can leave sponsors blind to emerging risks, reducing the ability to detect data anomalies or safeguard patient safety. This summary highlights how upfront risk assessment and early RBQM integration can preempt critical issues in rare disease studies.

Why this Matters

• Small, dispersed cohorts: Any data anomaly in a limited sample can disproportionately threaten endpoint validity and trial feasibility if risks aren’t identified early.
• Complex protocols: Without early mapping of Key Risk Indicators (KRIs) and Acceptable Ranges (ARs), subtle but important trends may go unnoticed, increasing protocol deviations and safety oversight gaps.
• Resource constraints: Rare disease studies often operate with fewer sites and participants. Delayed RQBM implementation wastes scarce monitoring resources and may miss timely interventions.
• Inconsistent data standards: Varying definitions or data collection practices across sites hinder centralized analytics and anomaly detection, delaying corrective actions.
• Regulatory expectations: Guidelines emphasize Quality-by-Design and risk-based approaches. Late RBQM rollout can complicate compliance and readiness for inspections.

Incorporating RBQM from the outset, through prospective risk assessment, clear KRI/AR definitions, and centralized monitoring, optimizes resource use, maintains data integrity, and protects patient safety in rare disease trials.

The poster below, presented by Julien Nunes Goncalves, Head of Growth, and Johann Proeve, PhD, Chief Scientific Officer at Cyntegrity, describes this issue in more detail.