人工智能在药物发现中的未来展望。

Q1 Pharmacology, Toxicology and Pharmaceutics
Advances in pharmacology Pub Date : 2025-01-01 Epub Date: 2025-02-06 DOI:10.1016/bs.apha.2025.01.009
Mithun Bhowmick, Sourajyoti Goswami, Pratibha Bhowmick, Santanu Hait, Dipayan Rath, Sabina Yasmin
{"title":"人工智能在药物发现中的未来展望。","authors":"Mithun Bhowmick, Sourajyoti Goswami, Pratibha Bhowmick, Santanu Hait, Dipayan Rath, Sabina Yasmin","doi":"10.1016/bs.apha.2025.01.009","DOIUrl":null,"url":null,"abstract":"<p><p>Drug discovery and development is very expensive and long with an inferior success rate. It is quite inefficient and costly due to huge R&D costs and lower productivity in pharmaceutical industries, to discover effective drugs and their development. AI can revolutionize the history of drug discovery and development because it will solve all these problems. AI can identify some promising drug candidates, reduce costs, and increase precision. AI algorithms analyze large datasets, predict molecular interactions, and help optimize the design of clinical trials, making the process of drug discovery and biomedical research much more efficient. By combining cutting-edge computation with more conventional pharmaceutical strategy, AI aids in expediting the process of therapeutics development. This chapter is an investigation of the core reasons behind lower approval rates of new drugs, the potential scope of AI to improve the drug discovery and development scenario, and the practical applications in the field. This article will further explore future opportunities, key methodologies, and challenges in the implementation of AI in pharmaceutical research.</p>","PeriodicalId":7366,"journal":{"name":"Advances in pharmacology","volume":"103 ","pages":"429-449"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Future prospective of AI in drug discovery.\",\"authors\":\"Mithun Bhowmick, Sourajyoti Goswami, Pratibha Bhowmick, Santanu Hait, Dipayan Rath, Sabina Yasmin\",\"doi\":\"10.1016/bs.apha.2025.01.009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Drug discovery and development is very expensive and long with an inferior success rate. It is quite inefficient and costly due to huge R&D costs and lower productivity in pharmaceutical industries, to discover effective drugs and their development. AI can revolutionize the history of drug discovery and development because it will solve all these problems. AI can identify some promising drug candidates, reduce costs, and increase precision. AI algorithms analyze large datasets, predict molecular interactions, and help optimize the design of clinical trials, making the process of drug discovery and biomedical research much more efficient. By combining cutting-edge computation with more conventional pharmaceutical strategy, AI aids in expediting the process of therapeutics development. This chapter is an investigation of the core reasons behind lower approval rates of new drugs, the potential scope of AI to improve the drug discovery and development scenario, and the practical applications in the field. This article will further explore future opportunities, key methodologies, and challenges in the implementation of AI in pharmaceutical research.</p>\",\"PeriodicalId\":7366,\"journal\":{\"name\":\"Advances in pharmacology\",\"volume\":\"103 \",\"pages\":\"429-449\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in pharmacology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/bs.apha.2025.01.009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"Pharmacology, Toxicology and Pharmaceutics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/bs.apha.2025.01.009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 0

摘要

药物的发现和开发既昂贵又耗时,而且成功率很低。由于制药行业的研发成本巨大,生产效率较低,发现和开发有效药物的效率低下,成本高昂。人工智能可以彻底改变药物发现和开发的历史,因为它将解决所有这些问题。人工智能可以识别一些有前途的候选药物,降低成本,提高精度。人工智能算法分析大型数据集,预测分子相互作用,并帮助优化临床试验设计,使药物发现和生物医学研究过程更加高效。通过将尖端计算与更传统的药物策略相结合,人工智能有助于加快治疗方法的开发过程。本章调查了新药批准率较低背后的核心原因,人工智能改善药物发现和开发场景的潜在范围,以及该领域的实际应用。本文将进一步探讨在药物研究中实施人工智能的未来机遇、关键方法和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Future prospective of AI in drug discovery.

Drug discovery and development is very expensive and long with an inferior success rate. It is quite inefficient and costly due to huge R&D costs and lower productivity in pharmaceutical industries, to discover effective drugs and their development. AI can revolutionize the history of drug discovery and development because it will solve all these problems. AI can identify some promising drug candidates, reduce costs, and increase precision. AI algorithms analyze large datasets, predict molecular interactions, and help optimize the design of clinical trials, making the process of drug discovery and biomedical research much more efficient. By combining cutting-edge computation with more conventional pharmaceutical strategy, AI aids in expediting the process of therapeutics development. This chapter is an investigation of the core reasons behind lower approval rates of new drugs, the potential scope of AI to improve the drug discovery and development scenario, and the practical applications in the field. This article will further explore future opportunities, key methodologies, and challenges in the implementation of AI in pharmaceutical research.

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
Advances in pharmacology
Advances in pharmacology Pharmacology, Toxicology and Pharmaceutics-Pharmacology
CiteScore
9.10
自引率
0.00%
发文量
45
×
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