ICH E6 and ALCOA - data integrity in the GCP environment - QFINITY
QFINITY · RQA Quasar

ALCOA Meets ICH E6: Data Integrity, Made Practical.

In the January 2016 issue of RQA Quasar, Oliver Herrmann and Dr. Jenny Gebhardt (QFINITY) showed how data integrity can be made practical in a GCP environment - through the ALCOA principles and a process- and risk-based view of the entire data lifecycle. Written in 2016, as today's data integrity guardrails were taking shape.

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The article

Data integrity is a quality attribute of the data.

The article picks up the then-new addendum to the ICH E6 GCP guideline (draft June 2015) and turns the term data integrity into a practical definition: not as an abstract set of rules, but as a quality attribute that must be preserved throughout the entire data lifecycle - from collection at the trial site to archiving.

Data integrity arises in the process, not in the system. The system is only one of the places where it can be preserved - or lost.
Inside the article

The key points at a glance.

  • Not a new concept

    Data integrity is a quality attribute of the data - the goal is to preserve the integrity of at least the critical data across the entire lifecycle.

  • ALCOA as a verification grid

    The five ALCOA criteria (attributable, legible, contemporaneous, original, accurate), supplemented in the article by "complete" - a precursor to today's ALCOA++ framework - provide a checklist against which data can be verified.

  • Context and metadata

    A value like "160 mmHg" is only meaningful with context. Metadata - who, when, in which process - is part of the data, so the DI principles apply to both.

  • Process before system

    The horizontal view follows the data through the process: manual steps need QC checks, automated ones a form of verification or validation. Computer systems are just one of these steps.

  • Prioritize by risk

    Not all data is equal: endpoint data is essential, other data less vulnerable. A risk assessment of the data types focuses the strict DI controls where they count.

Why this matters

A decade of data integrity.

What began as a practical definition in 2016 sits at the core of regulation today - from the EU Annex 11 expectations to the ALCOA++ framework. QFINITY has not merely commented on this development but has accompanied it in practice: as a process- and risk-based view of data that aligns rigor with patient proximity and criticality. This very continuity - from the GCP data lifecycle to AI-supported validation - is the common thread running through QFINITY's publications.

The framework

Where data integrity is anchored.

The article situates data integrity within the data lifecycle of the clinical process - where data is collected, transmitted, processed, secured, and archived. The ICH E6 Addendum's risk-based approach shapes monitoring and quality management - and it must be applied just as consistently to the integrity of the data itself.

ICH E6 (GCP) ALCOA++ Data lifecycle Process- and risk-based Critical data first
The authors

Written from GCP practice.

Oliver Herrmann, Founder and CEO of QFINITY, combines computer science and GxP compliance and is active on ISPE's GAMP committees. Dr. Jenny Gebhardt brings a medical background (Ph.D. in infectiology, Master's in Clinical Trial Management) and many years of pharmacovigilance and quality management experience. The article appeared in RQA's international New Year issue - QFINITY's own publication, not a third-party article about QFINITY.

RQA Quasar No. 134 GCP & data integrity ISPE GAMP Clinical Trial Management
RQA Quasar - the members magazine of the Research Quality Association↗
Related topics

From thesis to lived practice.

Data Integrity in the GxP Environment

ALCOA++ and the data lifecycle in practice - how a robust chain of evidence takes shape.

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Validation of GCP Systems

How to validate computerized systems in the GCP environment - demonstrably and risk-based.

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Data Integrity - Key Concepts

The GAMP RDI Good Practice Guide: data integrity as a consistent concept across the lifecycle.

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Regulation of Computerized Systems

The regulatory framework where data integrity and validation converge.

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Data integrity you can demonstrate - across the entire data lifecycle.

We work with you to determine where, along your data lifecycle, the integrity of critical data is truly secured - process- and risk-based, from collection to archiving. Free initial consultation, about 30 minutes.

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