Clinical Data Studio: Audit Trail Review

Every change made to clinical trial data leaves a record in the audit trail: who entered what, when, and how. Those records can reveal protocol deviations, training gaps, and even data manipulation, but today’s trials generate far more audit data than any team can review by hand. As a result, traditional audit trail review (ATR) has become a slow, after-the-fact compliance exercise where critical signals get lost in the noise.

This guide shows how Medidata Clinical Data Studio uses generative AI (GenAI) to make ATR proactive and risk-based. Teams start by pinpointing where audit data matters most. They then pull targeted data using plain-language prompts instead of programming. Built-in key risk indicators, machine-learning anomaly detection, drag-and-drop visuals, and reusable listings help surface issues such as patients completing electronic diaries outside the expected window or sites entering data after hours. Findings flow into a single dashboard and can be routed straight to the right site monitor for follow-up. Learn how Medidata can turn your overwhelming audit data into early, actionable insights that protect patient safety and data integrity.