Folia Pharmacologica Japonica
Online ISSN : 1347-8397
Print ISSN : 0015-5691
ISSN-L : 0015-5691
Reviews: New Effort to New Drug Approval to Treat COVID-19; Drug Repositioning Approach
Drug repositioning to combat COVID-19 using artificial intelligence system
Norihisa ShindoHiroyoshi Toyoshiba
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JOURNAL FREE ACCESS

2022 Volume 157 Issue 1 Pages 41-46

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Abstract

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. Concept Encoder is a patented AI system based on natural language processing technology and by deeply 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 learning the molecular relationship comprehensively. 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.

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© 2022 by The Japanese Pharmacological Society
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