Long Qian, Xin Lu, Parvez Haris, Jianyong Zhu, Shuo Li, Yingjie Yang
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Abstract
Clinical trials are pivotal in drug development yet fraught with uncertainties and resource-intensive demands. The application of AI models to forecast trial outcomes could mitigate failures and expedite the drug discovery process. This review discusses AI methodologies that impact clinical trial outcomes, focusing on clinical text embedding, trial multimodal learning, and prediction techniques, while addressing practical challenges and opportunities.
期刊介绍：
Drug Discovery Today delivers informed and highly current reviews for the discovery community. The magazine addresses not only the rapid scientific developments in drug discovery associated technologies but also the management, commercial and regulatory issues that increasingly play a part in how R&D is planned, structured and executed.
Features include comment by international experts, news and analysis of important developments, reviews of key scientific and strategic issues, overviews of recent progress in specific therapeutic areas and conference reports.
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