用于药物发现、开发和交付的人工智能、计算工具和机器人技术

Ayodele James Oyejide , Yemi Adekola Adekunle , Oluwatosin David Abodunrin , Ebenezer Oluwatosin Atoyebi
{"title":"用于药物发现、开发和交付的人工智能、计算工具和机器人技术","authors":"Ayodele James Oyejide ,&nbsp;Yemi Adekola Adekunle ,&nbsp;Oluwatosin David Abodunrin ,&nbsp;Ebenezer Oluwatosin Atoyebi","doi":"10.1016/j.ipha.2025.01.001","DOIUrl":null,"url":null,"abstract":"<div><div>The integration of Artificial Intelligence (AI) and robotics into the pharmaceutical sector is rapidly transforming drug discovery, development, and delivery (D-DDD) processes. Traditional drug development is often characterized by lengthy timelines, high costs, and complex challenges associated with target identification, drug efficacy, and safety profiling. AI and robotics offer transformative solutions, bringing speed, precision, and scalability to various stages of D-DDD. In this review, we analyze cutting-edge advancements in AI-driven predictive modeling, machine learning algorithms for molecular screening, and data mining techniques that enable efficient drug target identification and toxicity prediction. We also explore robotics applications that enhance automation in high-throughput screening, compound synthesis, and patient-specific drug delivery systems. Through examining the applications, limitations, and future trends of these technologies, this review provides a comprehensive outlook on the potential of AI and robotics to streamline the drug pipeline and enable personalized therapeutic strategies. Our review reveals that the convergence of AI, robotics, and big data has potential to reshape pharmaceutical research, reduce costs, and pave the way for more accessible, effective therapies. This review thus serves as a critical resource for understanding the future trajectory of intelligent, technology-driven pharmacy and its implications for advancing healthcare.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 3","pages":"Pages 207-224"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence, computational tools and robotics for drug discovery, development, and delivery\",\"authors\":\"Ayodele James Oyejide ,&nbsp;Yemi Adekola Adekunle ,&nbsp;Oluwatosin David Abodunrin ,&nbsp;Ebenezer Oluwatosin Atoyebi\",\"doi\":\"10.1016/j.ipha.2025.01.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The integration of Artificial Intelligence (AI) and robotics into the pharmaceutical sector is rapidly transforming drug discovery, development, and delivery (D-DDD) processes. Traditional drug development is often characterized by lengthy timelines, high costs, and complex challenges associated with target identification, drug efficacy, and safety profiling. AI and robotics offer transformative solutions, bringing speed, precision, and scalability to various stages of D-DDD. In this review, we analyze cutting-edge advancements in AI-driven predictive modeling, machine learning algorithms for molecular screening, and data mining techniques that enable efficient drug target identification and toxicity prediction. We also explore robotics applications that enhance automation in high-throughput screening, compound synthesis, and patient-specific drug delivery systems. Through examining the applications, limitations, and future trends of these technologies, this review provides a comprehensive outlook on the potential of AI and robotics to streamline the drug pipeline and enable personalized therapeutic strategies. Our review reveals that the convergence of AI, robotics, and big data has potential to reshape pharmaceutical research, reduce costs, and pave the way for more accessible, effective therapies. This review thus serves as a critical resource for understanding the future trajectory of intelligent, technology-driven pharmacy and its implications for advancing healthcare.</div></div>\",\"PeriodicalId\":100682,\"journal\":{\"name\":\"Intelligent Pharmacy\",\"volume\":\"3 3\",\"pages\":\"Pages 207-224\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent Pharmacy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949866X25000097\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Pharmacy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949866X25000097","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

人工智能(AI)和机器人技术与制药行业的整合正在迅速改变药物发现、开发和交付(D-DDD)流程。传统的药物开发通常具有时间长,成本高,以及与目标识别,药物功效和安全性分析相关的复杂挑战的特点。人工智能和机器人技术提供了变革性的解决方案,为D-DDD的各个阶段带来了速度、精度和可扩展性。在这篇综述中,我们分析了人工智能驱动的预测建模、用于分子筛选的机器学习算法和数据挖掘技术的前沿进展,这些技术能够有效地识别药物靶点和毒性预测。我们还探索了机器人技术在高通量筛选、化合物合成和患者特异性药物输送系统中的应用。通过研究这些技术的应用、局限性和未来趋势,本文全面展望了人工智能和机器人技术在简化药物管道和实现个性化治疗策略方面的潜力。我们的研究表明,人工智能、机器人技术和大数据的融合有可能重塑制药研究,降低成本,为更容易获得、更有效的治疗铺平道路。因此,这篇综述为理解智能、技术驱动的药房的未来发展轨迹及其对推进医疗保健的影响提供了重要资源。
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, computational tools and robotics for drug discovery, development, and delivery
The integration of Artificial Intelligence (AI) and robotics into the pharmaceutical sector is rapidly transforming drug discovery, development, and delivery (D-DDD) processes. Traditional drug development is often characterized by lengthy timelines, high costs, and complex challenges associated with target identification, drug efficacy, and safety profiling. AI and robotics offer transformative solutions, bringing speed, precision, and scalability to various stages of D-DDD. In this review, we analyze cutting-edge advancements in AI-driven predictive modeling, machine learning algorithms for molecular screening, and data mining techniques that enable efficient drug target identification and toxicity prediction. We also explore robotics applications that enhance automation in high-throughput screening, compound synthesis, and patient-specific drug delivery systems. Through examining the applications, limitations, and future trends of these technologies, this review provides a comprehensive outlook on the potential of AI and robotics to streamline the drug pipeline and enable personalized therapeutic strategies. Our review reveals that the convergence of AI, robotics, and big data has potential to reshape pharmaceutical research, reduce costs, and pave the way for more accessible, effective therapies. This review thus serves as a critical resource for understanding the future trajectory of intelligent, technology-driven pharmacy and its implications for advancing healthcare.
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:604180095
Book学术官方微信