Data Integrity by Design: Building a Foundation of Data Integrity Into Digital Systems From the Ground Up

Data integrity is the bedrock for every process in the life sciences sector. Simply put, it is an expectation that companies in this industry are operating with accuracy and trust. Life sciences regulatory compliance can make or break innovation, and regulatory bodies like the U.S. Food and Drug Administration (FDA) and European Medicines Agency (EMA) have intensified their focus on ALCOA principles, including attributable, accurate, original data as a cornerstone of current good manufacturing practices (cGMP). In short, adherence isn’t just best practice; it’s required.

Implementing data integrity by design — “from the ground up” — means embedding robust validation checks, access controls, and audit trails into digital systems from their inception. This is a proactive methodology that minimizes the risks connected to data corruption. A welcome result is that it builds a foundational trust in the data used for critical decision-making and regulatory submissions.^1,2

The Role of Data Integrity in Life Sciences

Maintaining data integrity is essential in the life sciences sector to ensure that regulatory submissions accurately reflect product safety and efficacy. Regulatory agencies continue to extol the virtues of data integrity, which means life sciences companies can expect to face increasing scrutiny over their data management practices.^1,3 Issues like attribution to the user, originality of the data, and accuracy of the records can have costly, and even disastrous, consequences, like failed audits, regulatory delays, and even product recalls.

To relegate these risks to acceptable levels, companies must get serious about proactively safeguarding data integrity throughout its life cycle. How can they do this? By embedding compliance measures into system architecture. This allows life sciences organizations to reduce the risk of noncompliance and improve the reliability of their regulatory submissions — a win for all stakeholders.

But What Does “Data Integrity by Design” Mean?

Data integrity by design is a foresight-driven, action-oriented approach that integrates validation checks, access controls, and audit trails into digital systems from the outset. Those who take this path gain the near-priceless benefit of confidence — confidence that critical data are protected from corruption, manipulation, or unauthorized access because potential risks are addressed at the optimal timepoint: before they occur.¹

Systems designed with data integrity in mind help organizations simplify life sciences regulatory compliance by ensuring their data are accurate and reliable — crucial not just for successful regulatory submissions, but also for long-term operational success.²

Safeguarding Data Integrity

To maintain data integrity, life sciences companies must implement several safeguards within their digital systems. These safeguards help avoid risks, prevent data issues, and ensure that regulatory submissions meet the highest standards of accuracy.

1. Validation

Validation ensures data integrity by documenting evidence that the digital system performs as intended in a consistent and repeatable manner. Proper validation safeguards data integrity and keeps the process aligned with ALCOA principles:

• Attributable
• Legible
• Contemporaneous
• Original
• Accurate

2. Access Controls

Access controls limit who can view or enter data within a system, thus minimizing the risk of unauthorized access. These permissions help protect sensitive data by guaranteeing that only authorized personnel can make changes — changes that are tracked.³

3. Audit Trails

End-to-end, fully transparent audit trails — from equipment to batch record — make regulators happy. They provide a complete record of data modifications, tracking who made changes, when they made them, and what they altered. This high level of transparency gives organizations exactly what they need to verify data integrity and satisfy life sciences regulatory compliance requirements.²

Benefits of Proactive Data Integrity

Data integrity by design delivers important regulatory compliance benefits for life sciences companies, including:

• Reduced compliance risks — By embedding validation checks, access controls, and audit trails into their systems, life sciences companies can reduce their risk of noncompliance during audits and inspections.¹
• Enhanced reliability of submissions — Systems designed with data integrity in mind ensure that regulatory submissions are accurate and trustworthy, greatly improving the odds of timely approvals.²
• Expedited regulatory approvals — When regulatory bodies can trust that submitted data are accurate and reliable, the approval process becomes much more efficient.³

Conclusion

In this highly regulated industry, data integrity is fundamental to ensuring product safety, efficacy, and surpassing regulatory compliance. Without it, there’s simply no hope of success. Adopting a data integrity by design approach is the key to proactively safeguarding data, reducing compliance risks, and streamlining regulatory processes. And it doesn’t have to be hard.

Embedding validation, access controls, and audit trails into digital systems not only satisfies regulatory expectations but also enhances the overall reliability of data. This proactive strategy ensures that life sciences companies can build trust with regulatory bodies and accelerate the path to regulatory approvals.^1,2 And it helps you sleep at night.

Key Takeaways:

• Data integrity is crucial in life sciences, directly influencing product safety and efficacy while maintaining trust among stakeholders.
• Designing systems with built-in validation checks, access controls, and audit trails ensures robust protection against data corruption and unauthorized access.
• A proactive data integrity approach supports critical decision-making and regulatory compliance, enhancing reliability and confidence in life sciences operations.

References

1. Pharmaceutical Online. Implementing Data Quality By Design For Improved Data Integrity. Retrieved from: https://www.pharmaceuticalonline.com/doc/implementing-data-quality-by-design-for-improved-data-integrity-0001
2. Deloitte. Under the spotlight: Data Integrity in life sciences. Retrieved from: https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/deloitte-uk-data-integrity-report.pdf
3. U.S. Food and Drug Administration (FDA). Data Integrity and Compliance With CGMP Guidance for Industry. Retrieved from: https://www.fda.gov/files/drugs/published/Data-Integrity-and-Compliance-With-Current-Good-Manufacturing-Practice-Guidance-for-Industry.pdf