{"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}
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.