Cocrystal Prediction of Bexarotene by Graph Convolution Network and Bioavailability Improvement.

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作者： Fu,Xiao ^[1] ; Yinxiang,Cheng ^[2] ; Jian-Rong,Wang ^[3] ; Dingyan,Wang ^[2] ; Yuanyuan,Zhang ^[2] ; Kaixian,Chen ^[4] ; Xuefeng,Mei ^[2] ; Xiaomin,Luo ^[4]

作者单位： State Key Laboratory of Drug Research and Drug Discovery and Design Center, Pharmaceutical Analytical & Solid-State Chemistry Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.;School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China. ^[1] State Key Laboratory of Drug Research and Drug Discovery and Design Center, Pharmaceutical Analytical & Solid-State Chemistry Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.;University of Chinese Academy of Sciences, Beijing 100049, China. ^[2] State Key Laboratory of Drug Research and Drug Discovery and Design Center, Pharmaceutical Analytical & Solid-State Chemistry Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. ^[3] State Key Laboratory of Drug Research and Drug Discovery and Design Center, Pharmaceutical Analytical & Solid-State Chemistry Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.;School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China.;University of Chinese Academy of Sciences, Beijing 100049, China. ^[4]

关键词 GCN bexarotene bioavailability cocrystal prediction

DOI 10.3390/pharmaceutics14102198

PMID 36297633

发布时间 2024-09-29

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