可解释性
透明度(行为)
转化式学习
计算机科学
过程(计算)
过程管理
质量(理念)
生物制药
医药制造业
风险分析(工程)
管理科学
工程管理
人工智能
工程类
业务
计算机安全
生物技术
医学
认识论
操作系统
心理学
哲学
药理学
生物
教育学
作者
Mario Stassen,Catarina S. Leitao,Toni Manzano,Francisco Valero,Benjamin Stevens,Matt Schmucki,David Hubmayr,Ferran Mirabent Rubinat,Sandrine Dessoy,Antonio R Moreira
标识
DOI:10.5731/pdajpst.2024.012950
摘要
This review paper explores the transformative impact of Artificial Intelligence (AI) on Continued Process Verification (CPV) in the biopharmaceutical industry. Originating from the CPV of the Future project, the study investigates the challenges and opportunities associated with integrating AI into CPV, focusing on real-time data analysis and proactive process adjustments. The paper highlights the importance of aligning AI solutions with regulatory standards and offers a set of comprehensive recommendations to bridge the gap between AI's potential and its practical, compliant, and safe application in pharmaceutical manufacturing. Emphasizing transparency, interpretability, and risk management, the research contributes to establishing best practices for AI implementation, ensuring the highest quality pharmaceutical products while meeting regulatory expectations. The conclusions drawn provide valuable insights for navigating the evolving landscape of AI in pharmaceutical manufacturing. This paper serves as a guideline for implementing AI, Machine Learning and Deep Learning models to the pharma industry. Nevertheless, the specific algorithms used in the CPV of the Future are not relevant for our paper (Good Practices), since we have to generalize the process independent of the algorithm.
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