Attributable, Legible, Contemporaneous, Original, Accurate + Complete, Consistent, Enduring, Available.
Data-integrity gap assessments across GxP systems, remediation plans, and a monitoring cadence that keeps ALCOA+ from drifting.
Data integrity means regulated data is Attributable, Legible, Contemporaneous, Original and Accurate, plus Complete, Consistent, Enduring and Available. It applies equally to paper and electronic records, at every point where data is created, changed, transferred or archived. Most findings come from shared accounts, unreviewed audit trails and uncontrolled spreadsheets.
Outcomes you can expect
- Data integrity gap report
- Remediation plan
- Monitoring cadence
Data Integrity (ALCOA+) is delivered by our validation & compliance services practice. Where it saves time, the team uses our products: GxP Copilot for validation lifecycle work and TraceDraft for clinical documentation.
Explore related capabilities: Computer System Validation (CSV), Computer Software Assurance (CSA), AI Validation Services (Annex 22), FDA 21 CFR Part 11 Compliance.
Why Data Integrity Remains the Most Cited Inspection Finding
Data integrity deficiencies have been the most frequently cited category in FDA warning letters and 483 observations for the past decade. The pattern is consistent: MHRA, FDA, WHO, and EMA inspectors consistently find that GxP data — whether in paper systems or electronic systems — is not reliably attributable, contemporaneous, and original. The root cause is almost never malicious intent. It is systematic process design that allows data to be recorded after the fact, modified without an audit trail, or attributed to the wrong person — and the absence of a data governance culture that prevents these practices from becoming normalised.
ALCOA+ is the data integrity framework that regulators use to assess GxP records. ALCOA stands for Attributable, Legible, Contemporaneous, Original, and Accurate. The + extends this to Complete, Consistent, Enduring, and Available. Every element of the framework is an inspectable requirement: inspectors will specifically check whether data entry is truly contemporaneous (or whether there is a pattern of entries clustered at shift end or batch close), whether audit trails are complete and immutable, and whether the 'original' record is preserved or has been overwritten.
- 14:32Signed: Approved for releaseQA Manager
- 11:05Changed risk of URS-015Validation lead · Supplier test evidence acceptedMedium → Low
- 10:48Edited expected result, OQ-07Validation lead · Lockout after 5 attempts, per URSv3 → v4
- 09:12Recorded result, OQ-07Tester · Evidence attachedPassed
The Data Integrity Gap Assessment: What It Covers
A data integrity gap assessment systematically evaluates each GxP system in scope against the ALCOA+ framework. The assessment methodology combines system configuration review (is the audit trail enabled? is it immutable? does it capture all GxP-critical transactions?), process observation (are operators entering data contemporaneously or reconstructing it?), and data pattern analysis (are there statistical anomalies in entry timestamps that suggest reconstruction or pre-entry?).
The most commonly identified gaps in pharmaceutical and biotech data integrity assessments are: audit trail enabled but not capturing all relevant transactions; audit trail data stored in a user-modifiable database table; paper-based systems where the recording medium can be altered without detection; computerised systems where system administrator access permits record modification without audit trail; and hybrid systems where data moves between electronic and paper without a controlled, attributable handoff. Our assessment identifies which of these gaps exist, their regulatory risk classification, and the remediation options for each.
Remediation and Ongoing Monitoring
Data integrity remediation is more complex than a single configuration fix. The technical remediation (enabling audit trails, restricting administrator access, upgrading to a version with immutable audit trail architecture) addresses the system-level gaps. But data integrity failures are also cultural — they reflect normalised practices that developed because systems and processes permitted them. Technical remediation without cultural remediation will produce a system that is technically compliant but operationally unchanged.
Our data integrity remediation programmes address both layers: technical fixes delivered through the change control system with validation evidence, and procedural training and culture-change initiatives that address the practices that generated the original gaps. The monitoring programme that follows remediation is equally important: periodic audit trail review, statistical sampling of data entry timestamps, and a formal data integrity review as part of the quality management review cycle. These monitoring activities ensure that data integrity improvements are sustained rather than reverting after the initial remediation event.
Sources
Primary documents referred to on this page, from their official publishers.
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