The Interplay of Data Governance, Integrity, and Quality in Pharmaceutical Analysis

In Pharmaceutical Technology, a new article "Data Governance, Data Integrity, and Data Quality: What’s the Connection?" was published. The paper, placed online on 06 November 2024, was written by Chris Burgess, Chairman of the ECA Analytical Quality Control Group (AQCG).

The author begins by posing the questions: "Data governance, data integrity, and data quality are all widely used terms, but what do they actually mean, and how are they connected?"

Using a structured "Lego brick" model, Burgess illustrates how data governance underpins both data integrity and quality. By adopting this approach, analysts can reinforce regulatory compliance and maintain high data quality across the entire data lifecycle. Key elements discussed include metrological integrity, standardized analytical procedures, and robust quality oversight—all essential for achieving consistency and accuracy in data reporting.

Data quality cannot be achieved in isolation but requires a structured data governance framework. This approach provides the foundation for data integrity, ensuring that all data, regardless of format, is complete, accurate, and consistent across its lifecycle. Burgess highlights several critical elements, such as metrological integrity, which ensures that instruments are "fit for intended use," and analytical procedure integrity, which validates procedures to meet specific quality standards.

Additionally, the Pharmaceutical Quality System is essential for oversight, encompassing policies, procedures, and quality documentation that support consistent data standards. Key principles, including ALCOA (Attributable, Legible, Contemporaneous, Original, Accurate) and its extensions, further emphasize the need for robust documentation and traceability to uphold data integrity.

The full article can be accessed on the PharmTech website.