Wei Wei , Chao Song , Changxing Qi , Xin Zhang , Xiaoyi Zhang , Run Pu , Yi Ao
{"title":"Visual analysis of drug research and development based on artificial intelligence","authors":"Wei Wei , Chao Song , Changxing Qi , Xin Zhang , Xiaoyi Zhang , Run Pu , Yi Ao","doi":"10.1016/j.jhip.2024.12.002","DOIUrl":null,"url":null,"abstract":"<div><div>The iteration of artificial intelligence (AI) technology provides new opportunities for drug research and experimental development. In recent years, AI-based drug research has continuously made new progress and has garnered widespread attention. This study retrieved data from a total of 23,096 papers in AI-based drug research and development from the Web of Science up to May 14, 2024, and conducted bibliometric analysis using VOSviewer software. The results indicated that the AI-based drug research and development is a globally recognized hotspot, and the United States holds a certain authority in this field, while China ranks second in total publication output. The integration of AI technology with drug development primarily involves four stages: drug discovery, preclinical research, clinical trials, and drug manufacturing. So, AI technology has been applied throughout the entire process of drug development. AI-based virtual drug screening and structure-activity relationship analysis started early, while graph neural networks, pre-trained models (Transformer), interpretable AI technology, ChatGPT, and large language models were significantly highlighted in the last 3 years. Moreover, since 2020, AI-based drug repurposing, molecular dynamics simulation, 3D printing, and drug delivery system design have emerged as research hotspots and have been mainly applied to, particularly, on COVID-19, disease prognosis, liver cancer, lung cancer, and immunotherapy.</div></div>","PeriodicalId":100787,"journal":{"name":"Journal of Holistic Integrative Pharmacy","volume":"5 4","pages":"Pages 323-332"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Holistic Integrative Pharmacy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2707368824000657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The iteration of artificial intelligence (AI) technology provides new opportunities for drug research and experimental development. In recent years, AI-based drug research has continuously made new progress and has garnered widespread attention. This study retrieved data from a total of 23,096 papers in AI-based drug research and development from the Web of Science up to May 14, 2024, and conducted bibliometric analysis using VOSviewer software. The results indicated that the AI-based drug research and development is a globally recognized hotspot, and the United States holds a certain authority in this field, while China ranks second in total publication output. The integration of AI technology with drug development primarily involves four stages: drug discovery, preclinical research, clinical trials, and drug manufacturing. So, AI technology has been applied throughout the entire process of drug development. AI-based virtual drug screening and structure-activity relationship analysis started early, while graph neural networks, pre-trained models (Transformer), interpretable AI technology, ChatGPT, and large language models were significantly highlighted in the last 3 years. Moreover, since 2020, AI-based drug repurposing, molecular dynamics simulation, 3D printing, and drug delivery system design have emerged as research hotspots and have been mainly applied to, particularly, on COVID-19, disease prognosis, liver cancer, lung cancer, and immunotherapy.
人工智能(AI)技术的迭代为药物研究和实验开发提供了新的机遇。近年来,基于人工智能的药物研究不断取得新进展,受到广泛关注。本研究从Web of Science截至2024年5月14日的23,096篇基于人工智能的药物研发论文中检索数据,使用VOSviewer软件进行文献计量学分析。结果表明,基于人工智能的药物研发是全球公认的热点,美国在该领域拥有一定的权威,而中国在该领域的总发表量排名第二。人工智能技术与药物开发的整合主要涉及四个阶段:药物发现、临床前研究、临床试验和药物生产。因此,人工智能技术已经应用于药物开发的整个过程。基于人工智能的虚拟药物筛选和构效关系分析起步较早,而图神经网络、预训练模型(Transformer)、可解释性人工智能技术、ChatGPT和大型语言模型在最近3年得到了显著的突出。此外,自2020年以来,基于人工智能的药物再利用、分子动力学模拟、3D打印、给药系统设计等成为研究热点,主要应用于COVID-19、疾病预后、肝癌、肺癌、免疫治疗等领域。