Regulators expect data to be reliable and accurate, and ensuring data integrity is an important component of regulated industry’s responsibility to ensure the safety, efficacy, and quality of drugs.
cGMP regulations and guidance allow for flexible and risk-based strategies to prevent, detect, and monitor data integrity risks and issues.
Regarding systems, it is important to highlight that system compliance with 21 CFR Part 11 and EudraLex Annex 11 does not mean full compliance with Data Integrity current expectations, and vice versa. Nevertheless, GxP compliance cannot be achieved without securing and enforcing Data Integrity following ALCOA+ principles.
Regulated companies should implement holistic, meaningful, and effective strategies to manage their data integrity risks based upon the process understanding, knowledge of technologies, personnel, and procedures.
This white paper contains a case study which provides an alternative approach to eliminate data integrity blind spots. It can be achieved when data management risks are evaluated throughout the data life cycle along all the processes involved and not (only) by the systems (Process Data Flows vs only System GAP evaluation). The objective of this evaluation is to be more effective, complete, and useful. In this risk analysis, the data integrity is evaluated by process data flows with process data objects.