Implement a risk-based review-by-exception strategy that cuts reviewer fatigue and speeds batch release — while strengthening detection of data integrity, compliance, cybersecurity, and operational risks aligned with FDA, MHRA, EMA, and PIC/S expectations.
Includes live access & recording
In FDA and globally regulated environments, audit trail review has become one of the most resource-intensive and misunderstood compliance activities. Many organizations continue to apply manual, exhaustive review approaches that generate reviewer fatigue, slow batch release, and dilute focus on truly critical events.
This session explores how to implement a risk-based "review by exception" strategy that reduces reviewer burden while strengthening the ability to detect meaningful compliance, data integrity, cybersecurity, and operational risks. Attendees will learn how modern approaches aligned with FDA expectations, data integrity guidance, and risk-based validation principles can improve efficiency without sacrificing control.
The discussion will also address the role of AI-enabled analytics, automation, prioritizing risk, and ensuring human critical thinking remains the final guardrail for decision-making.
This webinar is intended for those involved in planning, execution and support of computer system validation activities in FDA-regulated industries, including pharmaceutical, medical device, biologics, tobacco and tobacco-related products. Functions that are applicable include research and development, manufacturing, QC testing, distribution, clinical trial management, adverse events management, and post-marketing surveillance.
Whether involved in software development, testing, implementation, validation, maintenance or use of AI-enabled solutions, you will find a wealth of knowledge to enhance your ability to use these technologies with maximum effectiveness.
Those using these systems, in particular, must understand their role as the human guardrail of AI — critically assessing outcomes, making intelligent judgment calls, and ensuring better decisions. It's not just about using AI solutions; it's about using them effectively and with full accountability for quality, compliance, and ROI.
Practical, inspection-ready strategies to transform your audit trail review program from a compliance burden into a risk intelligence function.
Reduce time spent on low-value audit trail review activities without creating compliance gaps
Focus reviewers on high-risk events and meaningful exceptions that actually indicate problems
Explore FDA, MHRA, EMA, and PIC/S expectations related to audit trails and data integrity
Identify common weaknesses that lead to reviewer overload and missed critical signals
Discover how risk-based review models improve both efficiency and detection capability simultaneously
Understand how AI and automated analytics can support smarter exception identification
Gain practical approaches implementable across manufacturing, laboratory, clinical, and quality systems
Improve inspection readiness while reducing operational burden and compliance bottlenecks
A risk-based framework that replaces reviewer fatigue with intelligent detection — across data integrity, cybersecurity, and operational risk.
Learn how to define, categorize, and rank audit trail events by risk — establishing meaningful exception thresholds that target high-risk signals while eliminating low-value manual review of routine, expected system activity.
Identify the specific event patterns that consistently precede data integrity failures — unauthorized access, backdating, disabled audit trails, metadata anomalies, suspicious sequences — and build detection rules that catch them early.
Explore how AI and advanced analytics can identify patterns, anomalies, and emerging risks across large audit trail datasets — including the limitations of AI (hallucinations, drift, bias) and why human critical thinking must remain the final control.
Build a review-by-exception program with documented rationale, SOP coverage, and effectiveness metrics that can be clearly explained and defended to FDA, EMA, MHRA, and PIC/S inspectors during site visits.
A complete review-by-exception implementation roadmap — from regulatory foundations through AI-assisted future-state monitoring.
This session benefits every professional involved in computer system validation, data integrity governance, QA oversight, and IT/digital operations in FDA-regulated environments — including vendors and consultants.
Carolyn Troiano has more than 45 years of experience in computer system validation in the pharmaceutical, medical device, biotechnology, tobacco, and other FDA-regulated industries. She is currently an independent consultant, advising companies on FDA compliance, Computer System Validation (CSV), and large-scale IT system implementation projects.
Carolyn participated in the FDA/Industry Partnership to develop 21 CFR Part 11, the FDA's Guidance for Electronic Records and Electronic Signatures. During her career she has provided training including CSV, 21 CFR Part 11, Data Integrity, and many other related compliance topics of interest to the life science industries.
Her firsthand role in developing foundational FDA electronic records regulations — combined with decades of practical CSV and audit trail review experience — makes her uniquely qualified to guide organizations through the transition from exhaustive manual review to modern, risk-based exception detection programs.
Join this focused 90-minute session on risk-based audit trail review strategy, AI-assisted exception detection, and inspection-ready data integrity governance.