药物开发和监管事务的演变:人工智能的威力。

IF 3.2 4区 医学 Q2 PHARMACOLOGY & PHARMACY Clinical therapeutics Pub Date : 2024-08-01 DOI:10.1016/j.clinthera.2024.05.012
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引用次数: 0

摘要

目的:人工智能(AI)是指能够模仿人类认知功能的技术,在包括药物开发在内的所有部门和行业都有重要应用。这对药物开发过程的监管有相当大的影响,因为它有望改变药物上市的方式和控制这一过程的系统。目前,关于人工智能在现实世界中应用的公开文献证据不足。因此,本综述对人工智能在药物开发及其监管过程中的应用进行了调查、整理和阐释:方法:我们进行了叙述性综述,以确定人工智能在简化药物开发和监管流程中的作用:综述结果显示,机器学习或深度学习、自然语言处理和机器人流程自动化是人工智能的热门应用。它们中的每一种都对其旨在支持的业务产生了相当大的影响。总体而言,人工智能工具促进了信息的获取,并为整个药物开发生命周期的决策提供了可管理性。不过,研究结果也表明,监管机构还需要做更多的工作,为该技术的应用提供适当的指导,这对安全性、监管流程和产品开发成本都有重要影响:人工智能已充分证明了其在药物开发中的实用性,促使人们进一步研究其在提供基本药物方面所节省的成本和时间的转化价值。
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Evolution of Drug Development and Regulatory Affairs: The Demonstrated Power of Artificial Intelligence

Purpose

Artificial intelligence (AI) refers to technology capable of mimicking human cognitive functions and has important applications across all sectors and industries, including drug development. This has considerable implications for the regulation of drug development processes, as it is expected to transform both the way drugs are brought to market and the systems through which this process is controlled. There is currently insufficient evidence in published literature of the real-world applications of AI. Therefore, this narrative review investigated, collated, and elucidated the applications of AI in drug development and its regulatory processes.

Methods

A narrative review was conducted to ascertain the role of AI in streamlining drug development and regulatory processes.

Findings

The findings of this review revealed that machine learning or deep learning, natural language processing, and robotic process automation were favored applications of AI. Each of them had considerable implications on the operations they were intended to support. Overall, the AI tools facilitated access and provided manageability of information for decision-making across the drug development lifecycle. However, the findings also indicate that additional work is required by regulatory authorities to set out appropriate guidance on applications of the technology, which has critical implications for safety, regulatory process workflow and product development costs.

Implications

AI has adequately proven its utility in drug development, prompting further investigations into the translational value of its utility based on cost and time saved for the delivery of essential drugs.

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来源期刊
Clinical therapeutics
Clinical therapeutics 医学-药学
CiteScore
6.00
自引率
3.10%
发文量
154
审稿时长
9 weeks
期刊介绍: Clinical Therapeutics provides peer-reviewed, rapid publication of recent developments in drug and other therapies as well as in diagnostics, pharmacoeconomics, health policy, treatment outcomes, and innovations in drug and biologics research. In addition Clinical Therapeutics features updates on specific topics collated by expert Topic Editors. Clinical Therapeutics is read by a large international audience of scientists and clinicians in a variety of research, academic, and clinical practice settings. Articles are indexed by all major biomedical abstracting databases.
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