Ensuring Data Integrity in Pharmaceutical Quality Systems: A Risk-Based Approach

Arun Ayilliath Keezhadath () and Lalitha Amarapalli ()

Journal of AI-Powered Medical Innovations (International online ISSN 3078-1930), 2024, vol. 1, issue 1, 83-104

Abstract: The integrity of data within pharmaceutical quality systems is crucial to ensuring product quality, patient safety, and regulatory compliance. This paper presents a risk-based approach to safeguarding data integrity across pharmaceutical quality systems. It discusses the regulatory frameworks, industry best practices, and the potential risks associated with data manipulation, loss, or corruption. By applying risk assessment tools, the paper outlines strategies for identifying vulnerable points in data management processes and proposes corrective actions to mitigate these risks. Furthermore, it emphasizes the importance of a robust culture of data integrity and continuous monitoring to maintain system reliability. The approach helps pharmaceutical companies comply with Good Manufacturing Practices (GMP) and other regulatory standards while ensuring the accuracy and trustworthiness of critical data.

Keywords: Data Integrity; Pharmaceutical Quality Systems; Risk-Based Approach; Regulatory Compliance; Good Manufacturing Practices (GMP); Data Management; Risk Assessment; Patient Safety; Quality Assurance (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:abu:abuabu:v:1:y:2024:i:1:p:83-104:id:39

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