{"title":"药物开发和监管事务的演变:人工智能的威力。","authors":"","doi":"10.1016/j.clinthera.2024.05.012","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><p>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.</p></div><div><h3>Methods</h3><p>A narrative review was conducted to ascertain the role of AI in streamlining drug development and regulatory processes.</p></div><div><h3>Findings</h3><p>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.</p></div><div><h3>Implications</h3><p>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.</p></div>","PeriodicalId":10699,"journal":{"name":"Clinical therapeutics","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0149291824001383/pdfft?md5=06e539900ef750fac17130216c04a86d&pid=1-s2.0-S0149291824001383-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Evolution of Drug Development and Regulatory Affairs: The Demonstrated Power of Artificial Intelligence\",\"authors\":\"\",\"doi\":\"10.1016/j.clinthera.2024.05.012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><p>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.</p></div><div><h3>Methods</h3><p>A narrative review was conducted to ascertain the role of AI in streamlining drug development and regulatory processes.</p></div><div><h3>Findings</h3><p>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.</p></div><div><h3>Implications</h3><p>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.</p></div>\",\"PeriodicalId\":10699,\"journal\":{\"name\":\"Clinical therapeutics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0149291824001383/pdfft?md5=06e539900ef750fac17130216c04a86d&pid=1-s2.0-S0149291824001383-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0149291824001383\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical therapeutics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0149291824001383","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
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.
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.