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监管事务中的创新方法:利用人工智能和机器学习实现高效合规与决策。

Innovative Approaches in Regulatory Affairs: Leveraging Artificial Intelligence and Machine Learning for Efficient Compliance and Decision-Making.

作者信息

Ajmal C S, Yerram Sravani, Abishek V, Nizam V P Muhammed, Aglave Gayatri, Patnam Jayasri Devi, Raghuvanshi Rajeev Singh, Srivastava Saurabh

机构信息

Department of Regulatory Affairs, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, India.

Central Drugs Standard Control Organization (CDSCO), Directorate General of Health Services, Ministry of Health & Family Welfare, Government of India, New Delhi, India.

出版信息

AAPS J. 2025 Jan 7;27(1):22. doi: 10.1208/s12248-024-01006-5.

Abstract

Artificial Intelligence (AI) and AI-driven technologies are transforming industries across the board, with the pharmaceutical sector emerging as a frontrunner beneficiary. This article explores the growing impact of AI and Machine Learning (ML) within pharmaceutical Regulatory Affairs, particularly in dossier preparation, compilation, documentation, submission, review, and regulatory compliance. By automating time-intensive tasks, these technologies streamline workflows, accelerate result generation, and shorten the product approval timeline. However, despite their immense potential, AI and ML also introduce new challenges. Issues such as AI software validation, data management security and privacy, potential biases, ethical concerns, and change management requirements must be addressed. This review highlights current AI-based tools actively used by regulatory professionals such as DocShifter, Veeva Vault, RiskWatch, Freyr SubmitPro, Litera Microsystems, cortical.io etc., examines both the benefits and obstacles of integrating these advanced systems into regulatory practices. Given the rapid pace of technological innovation, the article underscores the need for proactive collaboration with regulatory bodies to manage these developments. It also stresses the importance of adapting to evolving regulatory frameworks and embracing new technologies. Although regulatory agencies like the United Sates Food and Drug Administration (USFDA), European Medicines Agency (EMA), and Medicines and Healthcare products Regulatory Agency (MHRA) are working on guidelines for AI and ML adoption, clear, standardized protocols are still in the works. While the journey ahead may be complex, the integration of AI promises to fundamentally reshape regulatory processes and accelerate the approval of safe, effective pharmaceutical products.

摘要

人工智能(AI)和由人工智能驱动的技术正在全面变革各个行业,制药行业成为主要受益者。本文探讨了人工智能和机器学习(ML)在药品监管事务中日益增长的影响,特别是在档案准备、汇编、文档编制、提交、审核和法规合规方面。通过自动化耗时的任务,这些技术简化了工作流程,加快了结果生成速度,并缩短了产品批准时间线。然而,尽管它们具有巨大潜力,人工智能和机器学习也带来了新的挑战。诸如人工智能软件验证、数据管理安全和隐私、潜在偏差、伦理问题以及变更管理要求等问题必须得到解决。本综述重点介绍了监管专业人员目前积极使用的基于人工智能的工具,如DocShifter、Veeva Vault、RiskWatch、Freyr SubmitPro、Litera Microsystems、cortical.io等,研究了将这些先进系统整合到监管实践中的好处和障碍。鉴于技术创新的快速步伐,本文强调了与监管机构积极合作以管理这些发展的必要性。它还强调了适应不断演变的监管框架和采用新技术的重要性。尽管美国食品药品监督管理局(USFDA)、欧洲药品管理局(EMA)和药品及保健品监管局(MHRA)等监管机构正在制定关于采用人工智能和机器学习的指南,但清晰、标准化的协议仍在制定中。虽然未来的道路可能很复杂,但人工智能的整合有望从根本上重塑监管流程,并加速安全、有效的药品审批。

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