著者

進藤 軌久 豊柴 博義

出版者

公益社団法人 日本薬理学会

雑誌

日本薬理学会年会要旨集

巻号頁・発行日

vol.94, pp.1-S07-4, 2021

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<p>Although months have passed since WHO declared COVID-19 a global pandemic, only a limited number of clinically effective drugs are available, and the development of drugs to treat COVID-19 has become an urgent issue worldwide. The pace of new research on COVID-19 is extremely high and it is impossible to read every report. In order to tackle these problems, we leveraged our artificial intelligence (AI) system, Concept Encoder, to accelerate the process of drug repositioning. The Concept Encoder is a patented AI system based on natural language processing technology and by deep learning papers on COVID-19, the system identified a large group of genes implicated in COVID-19 pathogenesis. The AI system then generated a molecular linkage map for COVID-19, connecting the genes by deep learning the molecular relationship. By thoroughly reviewing the resulting map and list of the genes with rankings, we found potential key players for disease progression and existing drugs that might improve COVID-19 survival. Here, we focus on potential targets and discuss the perspective of our approach.</p>