RBQM

Ensure trial quality and patient safety at every stage

Medidata’s Risk-Based Quality Management (RBQM) in Clinical Data Studio provides a central workspace to help ensure quality at every stage of your trial. It spans proactive protocol de-risking, real-time data surveillance, and AI-driven anomaly detection. Advanced signal detection and automated protocol deviation (PD) management centralize issues into actionable workflows, giving teams cross-functional transparency from risk assessment to submission.

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Risk Planning and Documentation

·  Proactively identify critical data and processes (CtQ factors) during protocol design to minimize risk before trial execution.

·  Maintain a centralized, traceable risk register (RACT) and Integrated Quality Management Plan (IQMP) that replaces manual spreadsheets.

·  Align with ICH E6 (R3) principles by connecting initial risk assessments directly to functional monitoring strategies.

Risk Monitoring

·  Monitor study-level systemic risks and endpoint integrity using automated Quality Tolerance Limits (QTLs).

·  Track ongoing site and country performance with out-of-the-box system KRIs and drag-and-drop custom KRIs.

·  Gain parallel, real-time execution across data point, site, and study-level risk indicators.

Centralized Statistical Monitoring

·  Apply ML-powered anomaly detection to identify data propagation, digit rounding, and unnatural data distributions.

·  Automatically detect potential cross-site duplicate patients using combined demographic and geolocation insights.

·  Spot operational irregularities such as improper weekend or holiday visits across trial sites.

Tracking signals, deviations, and issues

·  Centralize protocol deviation management, signal detection, and issue tracking in a unified workspace.

·  Foster cross-functional collaboration among Risk Managers, Central Monitors, Data Managers, and CRAs.

·  Maintain transparent audit trails and action histories for complete regulatory inspection readiness.

AI-Powered Audit Trail Review & Data Surveillance

·  Rapidly analyze complex audit trail data using Generative AI, reducing manual review effort.

·  Combine real-time data flows, safety reconciliation, and third-party vendor data into single-source visualizations.

·  Accelerate data cleaning with Clean Patient Tracker, automated listings, and holistic study health views.