Test your Data Integrity with These 12 Questions
Maintaining the integrity of your data is essential when performing continuous monitoring of rooms, chambers, and storage, especially in the life science industry.
Are you taking the necessary steps to protect the integrity of your data? Data integrity compliance and maintenance are the foundation for making informed decisions, protecting valuable data, and minimizing the risk of product loss.
Data integrity expectations continue to evolve as GxP operations become increasingly digital. Proposed revisions to EU GMP Chapter 4 and Annex 11 reinforce the importance of managing data throughout its life cycle, with increased focus on risk-based data governance, audit trails, system security, and the oversight of computerized systems and external service providers.
What is Data Integrity?
The FDA describes data integrity as the completeness, consistency, and accuracy of data through its life cycle. Data integrity also encompasses the way we capture said data, how it’s transferred and stored, how we back up, archive it, or destroy it, and how it’s protected.
Continuous monitoring of environments comes with tremendous amounts of data to process, so the methods for procuring, assessing, and adequate data protection are incredibly important:
Accurate and reliable data capturing ensures that the information collected is precise, consistent, and ready for further processing.
Effective data transfer maintains data integrity as data moves across systems and interfaces. Secure and accurate transmission, supported by two-way communication between systems to verify successful data exchange, helps prevent data tampering, loss, or incomplete transfers.
Adequate data protection safeguards data from unauthorized access, including access through unauthorized equipment or systems, and ensures its integrity over time; this is vital for compliance and operational reliability.
ALCOA Principles and Data Integrity
This data we process should follow the ALCOA principles. According to these, data should always be:
Attributable: Data should always be linked to the individual that created it or modified it, to ensure accountability and traceability.
Legible: Data should be readable and understandable, to ensure accuracy when interpreted and reviewed.
Contemporaneously recorded: The data should be recorded the moment it has been generated, or immediately after, to ensure relevance.
Original or a true copy: Data should be kept in its original form, or if not possible, as a verified copy, to ensure authenticity and reliability.
Accurate: Data should accurately reflect the observed facts, free from alterations or errors, to ensure credibility.
These principles are also commonly extended through ALCOA+, which further emphasizes that data should be:
Complete: All relevant data and associated information should be retained.
Consistent: Data should be recorded and maintained in a logical and chronological manner.
Enduring: Data should remain intact and readable throughout its required retention period.
Available: Data should remain accessible for review, inspection, and audit when needed.
Together, these principles provide a useful framework for maintaining reliable data throughout its life cycle.
12 Questions to Assess Your Data Integrity Compliance
There are many challenges to overcome when ensuring data compliance. From human error to system failure, these issues can delay your audit readiness and increase the risk of asset loss.
We have created a list with 12 questions based on industry regulations. By answering them, you can evaluate your compliance with data integrity standards:
Is there an approved SOP for data review?
Are data transfer interfaces secure and tamper-proof?
Are data encryption and checksums in place to ensure data integrity during transfer?
Is there a comprehensive migration strategy for legacy data?
Are old data formats compatible or convertible to new systems?
Is there a protocol for maintaining system updates?
Does the system require unique identification for each user?
Does the system time out after a period of inactivity?
Are all data changes logged in a secure audit trail and appropriately reviewed?
Is data backup performed regularly, and can it be reliably restored when needed?
Are there protocols for user access levels and task segregation?
Is there a regular review process for SOP compliance, system readiness, and data integrity controls?
How Are Data Integrity Expectations Evolving?
Data integrity remains a key focus, and while its fundamental principles haven’t changed, the systems used to generate and manage GxP data have.
In 2025, the European Commission published proposed revisions to EU GMP Chapter 4 and Annex 11, introducing a stronger focus on risk-based data governance and the life cycle management of computerized systems.
The proposed revisions reinforce expectations around areas such as:
Computerized-system lifecycle management
Quality Risk Management
Data integrity controls
Audit trails
Electronic signatures
System security
Supplier and external service-provider oversight
These revisions were published for consultation in 2025 and should therefore be considered emerging regulatory expectations rather than current requirements until final versions enter into force.
For organizations operating GxP environments, however, they provide an important indication of how expectations around computerized systems and data governance are developing.
The Role of AI in Data Integrity
AI is adding an extra layer to the discussion around GxP data. The European Commission's proposed revision also introduced a new proposed Annex 22 on Artificial Intelligence, reflecting the growing use of AI and machine learning in pharmaceutical manufacturing.
The draft covers several areas, including intended use, model selection and training, validation and testing, data quality, performance monitoring, change control, and human oversight.
The current proposal has a defined scope and doesn’t treat all uses of AI in the same way. Organizations considering AI-supported technologies should therefore evaluate their intended use and potential impact on patient safety, product quality, and data integrity.
For data integrity teams, the underlying question remains familiar: Can you understand, control, document, and review how GxP-relevant data is being used?
Strengthen Your Data Integrity Approach
Maintaining data requires confidence in the entire chain of information, from the moment the data is generated through review, storage, retrieval, and use. A holistic strategy combined with a proactive, data-driven approach is essential for building and sustaining a compliant environment. When you integrate risk-based mapping, routine calibration, intelligent monitoring, and empowered teams, you create a strong foundation for continuous compliance, reduced variability, and long-term operational excellence.
Monitoring
