When the FDA arrives, documentation is not enough.
Data integrity failures are not caused by dishonest people. They are caused by systems, processes, and cultures that make accurate recording harder than the alternative - and then generate documentation confirming that everything was fine.
That is the argument Data Integrity by Design makes, and sixteen chapters of regulatory analysis, enforcement case history, and practitioner-level operational guidance support it. Written for clinical research professionals who already know the regulations and need to know why compliant programs keep failing inspection, this book provides the framework for building data management programs that produce integrity as a structural outcome rather than a compliance aspiration.
What this book covers
Christopher Gent draws on deep experience in GCP regulatory frameworks to deliver a complete practitioner's reference across four areas.
The enforcement landscape: the financial, operational, and reputational cost of clinical data integrity failures, including Cetero Research, Semler Research Center, and GVK Biosciences, with analysis of what FDA warning letters, clinical holds, consent decrees, and disqualification proceedings actually require of the organizations that receive them.
The regulatory framework: ICH E6(R3) (Step 4, January 2025), 21 CFR Parts 11, 50, 56, 312, and 314, the EMA Guideline on Computerised Systems and Electronic Data in Clinical Trials (EMA/INS/GCP/112288/2023), the EU Clinical Trials Regulation, MHRA GxP Data Integrity Guidance, PIC/S PI 041-1, and the February 2026 EMA/PIC/S joint consultation - mapped to operational practice, not summarized as compliance checklists.
System and process design: data lifecycle governance, computer system validation in the CSA era, audit trail configuration and review, electronic records and signatures, decentralized trial data management, AI and machine learning systems, and cloud-hosted third-party platforms.
The human system: organizational culture, competency-based training, executive governance structures, and the leadership behaviors that determine whether a quality system finds problems or files documentation of having looked.
The book closes with a structured internal data integrity assessment framework drawn directly from the analytical methods that FDA, EMA, and MHRA investigators use, designed to surface what an inspector would find before the inspection is scheduled.
Who this book is for
Clinical data managers, regulatory affairs professionals, clinical quality leads, sponsor QA directors, CRO clinical operations teams, eClinical technology vendors, and compliance attorneys operating in FDA, EMA, MHRA, and multi-regional regulatory environments. Readers are assumed to have working knowledge of GCP. This is not an introductory text.
Data Integrity in Practice: Building, Measuring, and Sustaining Your Program, the companion implementation volume, is available separately.
