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10.1016/j.patter.2025.101346 http://scihub22266oqcxt.onion/10.1016/j.patter.2025.101346 C12546459!12546459 !41142906     free     free     free       Patterns+(N+Y) 2025 ; 6 (10 ): 101346 Nephropedia Template TP {{tp|p=41142906 |t=2025. Large language models for drug discovery and development |pdf=|usr=}}{{41142906 }} gab.com Text Large language models for drug discovery and development JO: Patterns (N Y) http://www.kidney.de/pget.php?&tw=1&pmid=41142906 #FOAvip The integration of large language models (LLMs) into the drug discovery and development field marks a significant paradigm shift, offering novel methodologies for understanding disease mechanisms, facilitating de novo drug discovery, and optimizing clinical trial processes. This review highlights the expanding role of LLMs in revolutionizing various stages of the drug development pipeline. We investigate how these advanced computational models can uncover target-disease linkage, interpret complex biomedical data, enhance drug molecule design, predict drug efficacy and safety profiles, and facilitate clinical trial processes. In this paper, we aim to provide a comprehensive overview for researchers and practitioners in computational biology, pharmacology, and AI4Science by offering insights into the potential transformative impact of LLMs on drug discovery and development. Twit Text FOAVip Large language models for drug discovery and development ????Patterns (N Y) http://www.kidney.de/pget.php?&tw=1&pmid=41142906 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=41142906 #FOAvip English Wikipedia <ref>{{Cite pmid|41142906 }}</ref> Large language models for drug discovery and development #MMPMID41142906 Zheng Y ; Koh HY ; Ju J ; Yang M ; May LT ; Webb GI ; Li L ; Pan S ; Church G Patterns (N Y) 2025[Oct]; 6 (10 ): 101346 PMID41142906 show ga The integration of large language models (LLMs) into the drug discovery and development field marks a significant paradigm shift, offering novel methodologies for understanding disease mechanisms, facilitating de novo drug discovery, and optimizing clinical trial processes. This review highlights the expanding role of LLMs in revolutionizing various stages of the drug development pipeline. We investigate how these advanced computational models can uncover target-disease linkage, interpret complex biomedical data, enhance drug molecule design, predict drug efficacy and safety profiles, and facilitate clinical trial processes. In this paper, we aim to provide a comprehensive overview for researchers and practitioners in computational biology, pharmacology, and AI4Science by offering insights into the potential transformative impact of LLMs on drug discovery and development. ?Large language models for drug discovery and development (epmc).pdf DeepDyve Pubget Overpricing