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GAMP 5 Validation of AI/ML in Sterile Manufacturing

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  • Aniruddha Umeshchandra Dhole

    (Design Quality Assurance, Flex, United States of America)

Abstract

This examines the essential role of Good Automated Manufacturing Practice (GAMP) 5 in providing a formal, structured framework for validating artificial intelligence (AI) and machine learning (ML) systems within sterile pharmaceutical manufacturing facilities. AI/ML technologies offer significant potential to revolutionize sterility assurance, process optimization, and compliance monitoring, their inherent non-deterministic nature poses a critical challenge to traditional deterministic validation methods. Th research leverages the risk-based lifecycle perspective of GAMP 5, integrating it with regulatory expectations and technical best practices, to demonstrate a viable path where compliance and technological innovation can coexist. The findings underscore the necessity of robust validation practices that explicitly integrate data integrity, explainability (transparency), and continuous monitoring to ensure that AI/ML systems remain secure, auditable, and reliable in highly critical sterile manufacturing environment.

Suggested Citation

Handle: RePEc:epw:ejai00:v:5:y:2026:i:2:id:1093
DOI: 10.24018/ejai.2026.5.2.1093
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