Transforming clinical trials: the emerging roles of large language models.

IF 1.1 Q4 PHARMACOLOGY & PHARMACY Translational and Clinical Pharmacology Pub Date : 2023-09-01 Epub Date: 2023-09-19 DOI:10.12793/tcp.2023.31.e16
Jong-Lyul Ghim, Sangzin Ahn
{"title":"Transforming clinical trials: the emerging roles of large language models.","authors":"Jong-Lyul Ghim, Sangzin Ahn","doi":"10.12793/tcp.2023.31.e16","DOIUrl":null,"url":null,"abstract":"<p><p>Clinical trials are essential for medical research, but they often face challenges in matching patients to trials and planning. Large language models (LLMs) offer a promising solution, signaling a transformative shift in the field of clinical trials. This review explores the multifaceted applications of LLMs within clinical trials, focusing on five main areas expected to be implemented in the near future: enhancing patient-trial matching, streamlining clinical trial planning, analyzing free text narratives for coding and classification, assisting in technical writing tasks, and providing cognizant consent via LLM-powered chatbots. While the application of LLMs is promising, it poses challenges such as accuracy validation and legal concerns. The convergence of LLMs with clinical trials has the potential to revolutionize the efficiency of clinical trials, paving the way for innovative methodologies and enhancing patient engagement. However, this development requires careful consideration and investment to overcome potential hurdles.</p>","PeriodicalId":23288,"journal":{"name":"Translational and Clinical Pharmacology","volume":"31 3","pages":"131-138"},"PeriodicalIF":1.1000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ab/70/tcp-31-131.PMC10551746.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational and Clinical Pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12793/tcp.2023.31.e16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/9/19 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

Abstract

Clinical trials are essential for medical research, but they often face challenges in matching patients to trials and planning. Large language models (LLMs) offer a promising solution, signaling a transformative shift in the field of clinical trials. This review explores the multifaceted applications of LLMs within clinical trials, focusing on five main areas expected to be implemented in the near future: enhancing patient-trial matching, streamlining clinical trial planning, analyzing free text narratives for coding and classification, assisting in technical writing tasks, and providing cognizant consent via LLM-powered chatbots. While the application of LLMs is promising, it poses challenges such as accuracy validation and legal concerns. The convergence of LLMs with clinical trials has the potential to revolutionize the efficiency of clinical trials, paving the way for innovative methodologies and enhancing patient engagement. However, this development requires careful consideration and investment to overcome potential hurdles.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
转变临床试验:大型语言模型的新兴作用。
临床试验对医学研究至关重要,但它们在将患者与试验和计划相匹配方面往往面临挑战。大型语言模型(LLM)提供了一个有前景的解决方案,标志着临床试验领域的变革。这篇综述探讨了LLM在临床试验中的多方面应用,重点关注了预计在不久的将来将实施的五个主要领域:增强患者试验匹配、简化临床试验规划、分析用于编码和分类的自由文本叙述、协助技术写作任务,以及通过LLM支持的聊天机器人提供认知同意。虽然LLM的应用前景广阔,但它带来了准确性验证和法律问题等挑战。LLM与临床试验的融合有可能彻底改变临床试验的效率,为创新方法和提高患者参与度铺平道路。然而,这一发展需要仔细考虑和投资,以克服潜在的障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Translational and Clinical Pharmacology
Translational and Clinical Pharmacology Medicine-Pharmacology (medical)
CiteScore
1.60
自引率
11.10%
发文量
17
期刊介绍: Translational and Clinical Pharmacology (Transl Clin Pharmacol, TCP) is the official journal of the Korean Society for Clinical Pharmacology and Therapeutics (KSCPT). TCP is an interdisciplinary journal devoted to the dissemination of knowledge relating to all aspects of translational and clinical pharmacology. The categories for publication include pharmacokinetics (PK) and drug disposition, drug metabolism, pharmacodynamics (PD), clinical trials and design issues, pharmacogenomics and pharmacogenetics, pharmacometrics, pharmacoepidemiology, pharmacovigilence, and human pharmacology. Studies involving animal models, pharmacological characterization, and clinical trials are appropriate for consideration.
期刊最新文献
Analyzing collaborations in clinical trials in Korea using association rule mining. Cardiotoxicity evaluation of two-drug fixed-dose combination therapy under CiPA: a computational study. Comparative pharmacokinetics study of two tablet formulations of delpazolid, a novel oxazolidinone class antibiotic. PMDA initiatives to enhance drug development via multi-regional clinical trials. Research on unintroduced new drugs in South Korea from 2011 to 2020: approaches to prioritization and strategy.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1