Data Integrity Takes Center Stage in Lab Quality Control Amid Rising Violations

We’re seeing a heightened awareness of data integrity violations, with both regulatory bodies and labs paying close attention. With data integrity playing a crucial role in drug safety, it has become a key focus in quality control (QC) lab operations. Staying compliant helps labs avoid setbacks from regulatory scrutiny while protecting the safety and reliability of their products.

What is Data Integrity?

Data integrity is a core part of lab operations, ensuring that all information is complete, consistent, and accurate. The data lifecycle—spanning from creation to processing, review, reporting, use, retention, and eventual destruction—demands careful oversight at each stage to uphold integrity.

Regulators expect labs to maintain strict control over processes that affect data quality. Strong systems for monitoring and verification are essential throughout the lifecycle. Any gaps, inconsistencies, or inaccuracies can lead to errors that may compromise patient safety and the results of clinical studies.
 

What is ALCOA PLUS?

ALCOA PLUS (+) is a widely used framework in industries like pharmaceuticals, biotechnology, and healthcare to protect data integrity, quality, and reliability. It plays a key role in meeting Good Manufacturing Practices (GMP) and Good Laboratory Practices (GLP) standards. ALCOA represents the core principles of data integrity, while the PLUS elements provide added layers to further strengthen data management:

ALCOA:

• Attributable – Record who performed the action and when
• Legible – Records must be readable throughout their entire lifecycle
• Contemporaneous – Data is recorded at the time of the activity
• Original – Raw data is preserved in its original format
• Accurate – Data is free of errors and reflects what was observed

PLUS:

• Complete – All data must be recorded, including any repeat tests
• Consistent – Data entries should follow a consistent format
• Enduring – Data must be maintained in a durable format
• Available – Data must be readily accessible audit, or inspection

Who are the Stakeholders?

Clinical testing and QC laboratories serve a wide range of stakeholders, including regulators, lab managers, IT managers, and quality assurance teams. While their roles may differ, they share several critical needs for smooth operations:

•  Efficiency: Streamlining processes and optimizing resources.
•  Reliability and Accuracy: Ensuring trustworthy data for decision-making.
•  Consistency: Maintaining credible results over time and across studies.
•  Timeliness: Avoiding delays that could affect patient care or product release.
•  Privacy: Protecting patient and participant data to meet ethical and regulatory standards.

Regulators are increasingly focusing on data integrity, as lapses in compliance can have serious consequences for labs and the stakeholders they serve.

Regulators Targeting Data Integrity Violations

Data integrity continues to be a critical focus for regulatory agencies, with violations having serious consequences in terms of cost and reputation. Jerry Chapman of Redica Systems, a regulatory intelligence company, analyzed 49 FDA Warning Letters from 2014-2019 and found that common data integrity issues involved original data (30%), data manipulation (25%), and system controls (14%)¹.

A more recent report highlighted that data integrity remained a significant concern for the FDA, with 61% of warning letters in 2021 citing it as a key issue². These target violations of ALCOA+ principles in various lab operations, including deletion or manipulation of data and non-contemporaneous documentation.
 

How Do You Ensure Data Integrity of Analytical Systems?

Maintaining data integrity in analytical systems comes down to a few key steps: qualifying hardware to ensure proper equipment function, securing infrastructure to prevent unauthorized access, and validating software for reliable data processing. Clear review processes, proper records retention, and regular maintenance keep data accurate and accessible, while change control manages updates to systems.

Digital solutions, in particular, simplify record retention and backups, making data more accessible when needed for audits or recovery. Prioritizing data integrity not only enhances results, but also advances scientific progress and supports patient care.

Solutions for an Automated Data Management Process

Data quality and integrity in the lab rely on proper data management, and modern labs are making this easier with digital and automated solutions. From basic lab equipment to advanced instrumentation, these tools streamline processes.

For instance, Sartorius' Cubis^® II balances fully support 21 CFR Part 11 and EU Annex 11 compliance, while the Ingenix Suite simplifies compliant fleet management for pipettes and balances across brands.

Sartorius also leads in compliance support for bioanalytical instruments, offering 21 CFR Part 11 compliant software on its legacy Octet^® Biolayer Interferometry (BLI), Incucyte^® Live-Cell Analysis, and iQue^® High-Throughput Screening Cytometry platforms. The Octet^® BLI systems also offer additional GxP features.

The recently launched Sterisart^® Universal | Gen 4 pump for contamination-free transfer of samples and media in sterility testing meets all quality and safety requirements with paperless documentation, 21 CFR Part 11 compliance, and flexible connectivity. 

Explore the resources below to see how you can move away from manual data handling and automate your data workflows.

<sub>References:
1. Redica Systems. (2021, August 31). What can regulatory data tell us about data integrity trends?
https://redica.com/what-can-regulatory-data-tell-us-about-data-integrity-trends/</sub>

_{2. European Pharmaceutical Review. (2024, March 13). FDA warning letters highlight data integrity issues.
https://www.europeanpharmaceuticalreview.com/news/219951/fda-warning-letters-highlight-data-integrity-issues/}