{"title":"人工智能虚拟药物筛选的黄金时代到来了吗?","authors":"Kristy Carpenter, Xudong Huang","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Drug development pipeline inefficiency has called for more novel solutions and cutting-edge technologies. Artificial intelligence (AI)-based methods including different machine- and deep-learning algorithms have been employed for virtual drug screening. With the continuous refinement of algorithms, improvement of computing hardware, and increased availability of molecular datasets for drug development, it is certainly a prime time for AI-powered virtual drug screening.</p>","PeriodicalId":92024,"journal":{"name":"EC pharmacology and toxicology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133253/pdf/nihms939314.pdf","citationCount":"0","resultStr":"{\"title\":\"Is it a Prime Time for AI-powered Virtual Drug Screening?\",\"authors\":\"Kristy Carpenter, Xudong Huang\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Drug development pipeline inefficiency has called for more novel solutions and cutting-edge technologies. Artificial intelligence (AI)-based methods including different machine- and deep-learning algorithms have been employed for virtual drug screening. With the continuous refinement of algorithms, improvement of computing hardware, and increased availability of molecular datasets for drug development, it is certainly a prime time for AI-powered virtual drug screening.</p>\",\"PeriodicalId\":92024,\"journal\":{\"name\":\"EC pharmacology and toxicology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133253/pdf/nihms939314.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EC pharmacology and toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2017/11/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EC pharmacology and toxicology","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/11/27 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Is it a Prime Time for AI-powered Virtual Drug Screening?
Drug development pipeline inefficiency has called for more novel solutions and cutting-edge technologies. Artificial intelligence (AI)-based methods including different machine- and deep-learning algorithms have been employed for virtual drug screening. With the continuous refinement of algorithms, improvement of computing hardware, and increased availability of molecular datasets for drug development, it is certainly a prime time for AI-powered virtual drug screening.
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