如何将量子计算应用于临床试验设计和优化?

IF 13.9 1区 医学 Q1 PHARMACOLOGY & PHARMACY
Trends in pharmacological sciences Pub Date : 2024-10-01 Epub Date: 2024-09-23 DOI:10.1016/j.tips.2024.08.005
Hakan Doga, Aritra Bose, M Emre Sahin, Joao Bettencourt-Silva, Anh Pham, Eunyoung Kim, Alan Andress, Sudhir Saxena, Laxmi Parida, Jan Lukas Robertus, Hideaki Kawaguchi, Radwa Soliman, Daniel Blankenberg
{"title":"如何将量子计算应用于临床试验设计和优化?","authors":"Hakan Doga, Aritra Bose, M Emre Sahin, Joao Bettencourt-Silva, Anh Pham, Eunyoung Kim, Alan Andress, Sudhir Saxena, Laxmi Parida, Jan Lukas Robertus, Hideaki Kawaguchi, Radwa Soliman, Daniel Blankenberg","doi":"10.1016/j.tips.2024.08.005","DOIUrl":null,"url":null,"abstract":"<p><p>Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success due to a multitude of factors, including imperfect trial site selection, cohort recruitment challenges, lack of efficacy, absence of reliable biomarkers, etc. Each of these factors possesses a unique computational challenge, such as data management, trial simulations, statistical analyses, and trial optimization. Recent advancements in quantum computing offer a promising opportunity to overcome these hurdles. In this opinion we uniquely explore the application of quantum optimization and quantum machine learning (QML) to the design and execution of clinical trials. We examine the current capabilities and limitations of quantum computing and outline its potential to streamline clinical trials.</p>","PeriodicalId":23250,"journal":{"name":"Trends in pharmacological sciences","volume":null,"pages":null},"PeriodicalIF":13.9000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How can quantum computing be applied in clinical trial design and optimization?\",\"authors\":\"Hakan Doga, Aritra Bose, M Emre Sahin, Joao Bettencourt-Silva, Anh Pham, Eunyoung Kim, Alan Andress, Sudhir Saxena, Laxmi Parida, Jan Lukas Robertus, Hideaki Kawaguchi, Radwa Soliman, Daniel Blankenberg\",\"doi\":\"10.1016/j.tips.2024.08.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success due to a multitude of factors, including imperfect trial site selection, cohort recruitment challenges, lack of efficacy, absence of reliable biomarkers, etc. Each of these factors possesses a unique computational challenge, such as data management, trial simulations, statistical analyses, and trial optimization. Recent advancements in quantum computing offer a promising opportunity to overcome these hurdles. In this opinion we uniquely explore the application of quantum optimization and quantum machine learning (QML) to the design and execution of clinical trials. We examine the current capabilities and limitations of quantum computing and outline its potential to streamline clinical trials.</p>\",\"PeriodicalId\":23250,\"journal\":{\"name\":\"Trends in pharmacological sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":13.9000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in pharmacological sciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.tips.2024.08.005\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in pharmacological sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.tips.2024.08.005","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

摘要

临床试验是评估治疗安全性和有效性的必要手段。然而,由于试验选址不完善、队列招募困难、缺乏疗效、缺乏可靠的生物标志物等多种因素,试验时间严重推迟,成功率极低。这些因素中的每一个都带来了独特的计算挑战,如数据管理、试验模拟、统计分析和试验优化。量子计算的最新进展为克服这些障碍提供了大有可为的机会。在本报告中,我们独特地探讨了量子优化和量子机器学习(QML)在临床试验设计和执行中的应用。我们研究了量子计算目前的能力和局限性,并概述了其简化临床试验的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How can quantum computing be applied in clinical trial design and optimization?

Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success due to a multitude of factors, including imperfect trial site selection, cohort recruitment challenges, lack of efficacy, absence of reliable biomarkers, etc. Each of these factors possesses a unique computational challenge, such as data management, trial simulations, statistical analyses, and trial optimization. Recent advancements in quantum computing offer a promising opportunity to overcome these hurdles. In this opinion we uniquely explore the application of quantum optimization and quantum machine learning (QML) to the design and execution of clinical trials. We examine the current capabilities and limitations of quantum computing and outline its potential to streamline clinical trials.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
23.90
自引率
0.70%
发文量
132
审稿时长
6-12 weeks
期刊介绍: Trends in Pharmacological Sciences (TIPS) is a monthly peer-reviewed reviews journal that focuses on a wide range of topics in pharmacology, pharmacy, pharmaceutics, and toxicology. Launched in 1979, TIPS publishes concise articles discussing the latest advancements in pharmacology and therapeutics research. The journal encourages submissions that align with its core themes while also being open to articles on the biopharma regulatory landscape, science policy and regulation, and bioethics. Each issue of TIPS provides a platform for experts to share their insights and perspectives on the most exciting developments in the field. Through rigorous peer review, the journal ensures the quality and reliability of published articles. Authors are invited to contribute articles that contribute to the understanding of pharmacology and its applications in various domains. Whether it's exploring innovative drug therapies or discussing the ethical considerations of pharmaceutical research, TIPS provides a valuable resource for researchers, practitioners, and policymakers in the pharmacological sciences.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信