International Journal of Sustainability and Innovation in Engineering (IJSIE)
2025
DOI https://www.doi.org/10.56830/IJSIE202505
Authors
Abstract
Pharmaceutical serialization is a critical regulatory mandate aimed at ensuring product traceability, combating counterfeiting, and safeguarding patient safety.
Within the United States, compliance with FDA 21 CFR Part 11 [1] imposes stringent requirements on electronic records and signatures, positioning serialization as a pivotal compliance activity rather than a mere logistical function.
Traditional serialization approaches, often characterized by manual validations and fragmented data management, present significant challenges including increased audit risks and inefficiencies. This study addresses the evident gap in leveraging artificial intelligence (AI) within SAP Quality Management (QM) systems to enhance serialization processes and ensure robust compliance with FDA regulations.
Employing a mixed-methods methodology, the research developed an AI-enabled serialization framework integrated with SAP QM and SAP Advanced Track and Trace for Pharmaceuticals (ATTP) modules [2] within a controlled sandbox environment.
AI techniques such as predictive analytics, anomaly detection, and intelligent automation were incorporated via SAP Business Technology Platform (BTP) services to augment data integrity, automate quality checks, and facilitate comprehensive audit trail generation. Validation involved simulating FDA 21 CFR Part 11 compliance scenarios, cross-referencing system outputs with regulatory checklists, and conducting expert interviews with SAP consultants and pharmaceutical compliance officers.
Empirical findings demonstrate that AI integration significantly improves serialization accuracy by reducing manual errors by over 40%, enables real-time detection of serialization anomalies, and streamlines audit readiness by decreasing preparation time by approximately 60%. Furthermore, the synergy between SAP QM, ATTP, and AI services enhances cross-functional visibility and governance, fostering a scalable and audit-ready compliance framework.
These results suggest that AI-enabled SAP QM serialization not only fortifies regulatory adherence but also delivers operational efficiencies and risk mitigation benefits [3]. Consequently, this research contributes a novel, intelligent compliance paradigm that transforms serialization into a proactive quality intelligence system, thereby supporting pharmaceutical manufacturers in navigating complex regulatory landscapes with greater agility and confidence.
Keywords:
AI-Driven Serialization, FDA 21 CFR Part 11, Electronic Records and Signatures, Intelligent Traceability, SAP ATTP Integration, Clean-Core SAP Architecture, Predictive Quality Analytics, Pharma Manufacturing Governance, GxP Compliance Framework, Serialized Supply Chain.
Download Full Article 