Human-in-the-Loop AI Use in Ongoing Process Verification in the Pharmaceutical Industry
The pharmaceutical industry’s pursuit of enhanced product quality, regulatory compliance, and operational efficiency has catalyzed the integration of Artificial Intelligence (AI) into Ongoing Process Verification (OPV) frameworks. This comprehensive review examines the synergistic application of Hum...
| Autores: | , , , , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2025 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositório: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/225266 |
| Acesso em linha: | https://hdl.handle.net/2445/225266 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Intel·ligència artificial Sistemes classificadors (Intel·ligència artificial) Indústria farmacèutica Artificial intelligence Learning classifier systems Pharmaceutical industry |
| Resumo: | The pharmaceutical industry’s pursuit of enhanced product quality, regulatory compliance, and operational efficiency has catalyzed the integration of Artificial Intelligence (AI) into Ongoing Process Verification (OPV) frameworks. This comprehensive review examines the synergistic application of Human-in-the-Loop (HITL) AI systems within OPV, contextualized by the evolving regulatory landscape, particularly the newly introduced Annex 22 of the European Union Good Manufacturing Practices (EU-GMP). The review delineates the sector’s strategic shift from traditional validation models toward dynamic, data-driven approaches that leverage AI for real-time monitoring, predictive analytics, and proactive process control. Central to this transformation is the HITL paradigm, which ensures that human expertise remains embedded in critical decision-making loops, thereby safeguarding patient safety, product quality, data integrity, and ethical responsibility. Annex 22 explicitly mandates deterministic behavior, traceability, and explainability for AI models used in GMP-critical applications, excluding adaptive and probabilistic systems from such contexts. The document also reinforces the necessity of multidisciplinary governance, rigorous validation protocols, and risk-based oversight throughout the AI lifecycle. This paper synthesizes current industry practices, regulatory expectations, and technological capabilities, offering a structured framework for compliant AI deployment in OPV. By aligning AI implementation with Annex 22 principles and existing GMP frameworks (e.g., Annex 11 and ICH Q9), the pharmaceutical sector can harness AI’s transformative potential while maintaining robust regulatory compliance. The review concludes with actionable recommendations for integrating HITL AI into OPV strategies, fostering a resilient, transparent, ethical, and future-ready manufacturing ecosystem. |
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