Clinical and operational data is as trustworthy as the processes behind it

Most compliance failures don't start with a bad decision. They start with a spreadsheet someone "just quickly updated" without a timestamp. A lab entry corrected with white-out instead of a single strikethrough. A dataset migrated to a new system — and quietly or mistakenly changed in transit.

Data confidence isn't just a technology challenge in the life sciences and biotech industry. It's a process and culture challenge wearing a technology lab coat.

ALCOA: The principles that refuse to age

First introduced by the FDA in the 1990s, ALCOA — Attributable, Legible, Contemporaneous, Original, Accurate — remains the backbone of GxP data integrity.

But let’s take a moment to unpack GxP as a term.

GxP is shorthand terminology for a variety of Good…Practices. The “x” is just a variable, as in algebra.

The term GxP serves as a crucial umbrella for the regulatory frameworks that guarantee pharmaceutical and food products remain safe and effective.

• Good Manufacturing Practice (GMP) — governing production controls
• Good Laboratory Practice (GLP) — for non-clinical study environments
• Good Clinical Practice (GCP) — regarding human clinical trials
• Good Distribution Practice (GDP) — managing storage and logistics
• Good Documentation Practice (GDocP) — the standard for record-keeping

At its heart, this is a commitment to traceability, consistency and accountability. It ensures every phase of the lifecycle is repeatable and auditable, allowing regulators like the FDA to verify that patient safety is never left to chance.

Regulators have since expanded it to ALCOA+ (adding Complete, Consistent, Enduring and Available), but the original five tell you everything you need to know about why data fails inspection.

Each principle is deceptively simple.

• Attributable asks: Can you prove who did this, and when?
• Contemporaneous asks: Was it recorded at the time, or reconstructed later?
• Accurate asks the most uncomfortable question: Did you record what actually happened — or what you wished had happened?

When any one of these breaks down, the entire chain of evidence-based decision making becomes suspect. And, in life sciences and pharmaceuticals, where data directly connects to patient safety, "suspect" is not a recoverable position.

Governance is what makes principles stick

ALCOA tells you what good data looks like. Data Governance, or a data strategy, provides the operating model for your organization to reliably produce contextual, quality information for business decisions.

For Chief Risk Officers (CROs) and Chief Compliance Officers (CCOs) in life sciences, governance means defining data ownership clearly — not just in policy documents, but in practice. It means audit trails that are tamper-evident and routinely reviewed, not just technically present. It means training that builds judgment, not just checkbox compliance.

The companies that struggle most with FDA 483 observations and EMA findings aren't usually the ones that ignored data integrity. They're the ones that assumed good intentions were enough.

Where most organizations are leaving themselves exposed

GxP frameworks govern how data is generated and documented, but for organizations handling protected health information, HIPAA adds another critical layer. The Privacy and Security Rules require that patient data be collected only for defined, permissible purposes — a principle known as minimum necessary use — and that access be tightly controlled based on role and need. When those controls fail, the consequences extend far beyond a regulatory observation.

A reportable breach triggers a mandatory notification chain: affected individuals must be informed within 60 days of discovery, and breaches impacting 500 or more individuals in a single state require simultaneous notification to the Department of Health and Human Services and, in many cases, prominent local media. For organizations operating at the intersection of clinical research and commercial healthcare, HIPAA and GxP compliance are not parallel tracks — they are overlapping obligations. Treating them in silos is where exposure quietly accumulates.

Speedy and uneventful review with the FDA is the goal and meticulous documentation is the path. Yet several regrettable patterns repeatedly manifest in regulatory findings:

• Legacy systems running without adequate audit trail controls
• A lack of sensitivity tags on how to use data and information
• Missing classification to identify what kind of information the system contains to ensure appropriate use
• Hybrid paper-electronic environments with no clear data hierarchy and validation gaps when systems are compared, upgraded or migrated

Each of these are fixable. None of them are fixed by good intentions alone.

The standard hasn't changed. The stakes have.

Regulators are not becoming more lenient on data integrity — they're becoming more sophisticated. AI-assisted inspection tools, remote audits and cross-border data sharing agreements mean that gaps your organization managed quietly for years may be increasingly visible.

The question for CROs and CCOs today isn't whether ALCOA and data governance are a top priority. The question is whether your organization's daily habits are actually producing the data confidence your compliance program assumes. And, further, if traceability, validation and data provenance are woven into tools, tech and processes to support pristine data hygiene.

Start there. The answer is usually more honest — and more useful — than the last audit report.

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  Ben Wyman

  Ben Wyman

  Area Vice President of Sales, Healthcare & Life Science

  Collibra