人工智能驱动临床试验

Ankit Majie
{"title":"人工智能驱动临床试验","authors":"Ankit Majie","doi":"10.14293/S2199-1006.1.SOR-.PPSORGE.V1","DOIUrl":null,"url":null,"abstract":"The future of clinical trials is changing rapidly due to the introduction of Artificial\n Intelligence (AI) to study the clinically significant patterns and algorithms generated\n upon the input from the trial. The high failure rates in the clinical trials leads\n to inefficient drug development cycle which increases expenses of the pharmaceutical\n industry. The technique of artificial intelligence allows the decision makers to study\n the clinical trials in real life conditions which increases the accuracy of the trials.\n Thus, decreasing the burden of the pharmaceutical industry and increasing the success\n rates of the trial. Moreover, clinical trial is a much time-consuming process involving\n 10-15 years for just one drug molecule with lot of investment. The use clinical trial\n can reduce the time required for the trial and its investment reduces to one half.\n With the use of the AI powered clinical trials one drug from every 100 drugs passes\n this phase easily with genuine results which is much greater than the conventional\n procedure. Rather the use of clinical trials can help in automated documentation of\n the clinical trial data under the database of the concerned company be retrieved and\n accessed very easily. The future of AI will include generation of precision medicine\n and even prediction of drug resistance in clinical trials.","PeriodicalId":21568,"journal":{"name":"ScienceOpen Posters","volume":"64 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence Powered Clinical Trials\",\"authors\":\"Ankit Majie\",\"doi\":\"10.14293/S2199-1006.1.SOR-.PPSORGE.V1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The future of clinical trials is changing rapidly due to the introduction of Artificial\\n Intelligence (AI) to study the clinically significant patterns and algorithms generated\\n upon the input from the trial. The high failure rates in the clinical trials leads\\n to inefficient drug development cycle which increases expenses of the pharmaceutical\\n industry. The technique of artificial intelligence allows the decision makers to study\\n the clinical trials in real life conditions which increases the accuracy of the trials.\\n Thus, decreasing the burden of the pharmaceutical industry and increasing the success\\n rates of the trial. Moreover, clinical trial is a much time-consuming process involving\\n 10-15 years for just one drug molecule with lot of investment. The use clinical trial\\n can reduce the time required for the trial and its investment reduces to one half.\\n With the use of the AI powered clinical trials one drug from every 100 drugs passes\\n this phase easily with genuine results which is much greater than the conventional\\n procedure. Rather the use of clinical trials can help in automated documentation of\\n the clinical trial data under the database of the concerned company be retrieved and\\n accessed very easily. The future of AI will include generation of precision medicine\\n and even prediction of drug resistance in clinical trials.\",\"PeriodicalId\":21568,\"journal\":{\"name\":\"ScienceOpen Posters\",\"volume\":\"64 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ScienceOpen Posters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14293/S2199-1006.1.SOR-.PPSORGE.V1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ScienceOpen Posters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14293/S2199-1006.1.SOR-.PPSORGE.V1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

由于人工智能(AI)的引入,临床试验的未来正在迅速改变,以研究根据试验输入产生的临床重要模式和算法。临床试验失败率高,导致药物开发周期效率低下,增加了制药行业的费用。人工智能技术使决策者能够在现实生活条件下研究临床试验,从而提高了试验的准确性。因此,减少了制药行业的负担,提高了试验的成功率。而且,一个药物分子的临床试验耗时10-15年,投资巨大。使用临床试验可以减少试验所需的时间,其投资减少一半。通过使用人工智能驱动的临床试验,每100种药物中就有一种很容易通过这一阶段,并取得比传统程序大得多的真正效果。相反,使用临床试验可以帮助在有关公司数据库下的临床试验数据的自动文档被检索和访问非常容易。人工智能的未来将包括产生精准医学,甚至在临床试验中预测耐药性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence Powered Clinical Trials
The future of clinical trials is changing rapidly due to the introduction of Artificial Intelligence (AI) to study the clinically significant patterns and algorithms generated upon the input from the trial. The high failure rates in the clinical trials leads to inefficient drug development cycle which increases expenses of the pharmaceutical industry. The technique of artificial intelligence allows the decision makers to study the clinical trials in real life conditions which increases the accuracy of the trials. Thus, decreasing the burden of the pharmaceutical industry and increasing the success rates of the trial. Moreover, clinical trial is a much time-consuming process involving 10-15 years for just one drug molecule with lot of investment. The use clinical trial can reduce the time required for the trial and its investment reduces to one half. With the use of the AI powered clinical trials one drug from every 100 drugs passes this phase easily with genuine results which is much greater than the conventional procedure. Rather the use of clinical trials can help in automated documentation of the clinical trial data under the database of the concerned company be retrieved and accessed very easily. The future of AI will include generation of precision medicine and even prediction of drug resistance in 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
自引率
0.00%
发文量
0
×
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