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[Drug repositioning to combat COVID-19 using artificial intelligence system].
Shindo, Norihisa; Toyoshiba, Hiroyoshi.
Affiliation
  • Shindo N; Life Science AI, FRONTEO, Inc.
  • Toyoshiba H; Life Science AI, FRONTEO, Inc.
Nihon Yakurigaku Zasshi ; 157(1): 41-46, 2022.
Article in Ja | MEDLINE | ID: mdl-34980812
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.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Drug Repositioning / COVID-19 Limits: Humans Language: Ja Year: 2022 Type: Article

Full text: 1 Database: MEDLINE Main subject: Drug Repositioning / COVID-19 Limits: Humans Language: Ja Year: 2022 Type: Article