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

IF 5 3区 医学 Q1 PHARMACOLOGY & PHARMACY AAPS Journal Pub Date : 2025-01-07 DOI:10.1208/s12248-024-01006-5
C S Ajmal, Sravani Yerram, V Abishek, V P Muhammed Nizam, Gayatri Aglave, Jayasri Devi Patnam, Rajeev Singh Raghuvanshi, Saurabh Srivastava
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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.

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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和决策。
人工智能(AI)和人工智能驱动的技术正在全面改变各行业,制药行业正成为首当其冲的受益者。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、编写、文档、提交、审查和法规遵从方面。通过自动化时间密集型任务,这些技术简化了工作流程,加速了结果生成,缩短了产品批准时间。然而,尽管具有巨大的潜力,人工智能和机器学习也带来了新的挑战。人工智能软件验证、数据管理安全和隐私、潜在偏见、道德问题和变更管理要求等问题必须得到解决。本文重点介绍了目前监管专业人员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。报告还强调了适应不断变化的监管框架和采用新技术的重要性。尽管美国食品和药物管理局(USFDA)、欧洲药品管理局(EMA)和药品和保健产品监管局(MHRA)等监管机构正在制定人工智能和机器学习应用的指导方针,但明确的标准化协议仍在制定中。尽管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、有效药品的批准。
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来源期刊
AAPS Journal
AAPS Journal 医学-药学
CiteScore
7.80
自引率
4.40%
发文量
109
审稿时长
1 months
期刊介绍: The AAPS Journal, an official journal of the American Association of Pharmaceutical Scientists (AAPS), publishes novel and significant findings in the various areas of pharmaceutical sciences impacting human and veterinary therapeutics, including: · Drug Design and Discovery · Pharmaceutical Biotechnology · Biopharmaceutics, Formulation, and Drug Delivery · Metabolism and Transport · Pharmacokinetics, Pharmacodynamics, and Pharmacometrics · Translational Research · Clinical Evaluations and Therapeutic Outcomes · Regulatory Science We invite submissions under the following article types: · Original Research Articles · Reviews and Mini-reviews · White Papers, Commentaries, and Editorials · Meeting Reports · Brief/Technical Reports and Rapid Communications · Regulatory Notes · Tutorials · Protocols in the Pharmaceutical Sciences In addition, The AAPS Journal publishes themes, organized by guest editors, which are focused on particular areas of current interest to our field.
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