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IDentif.AI: Artificial Intelligence Pinpoints Remdesivir in Combination with Ritonavir and Lopinavir as an Optimal Regimen Against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)
Agata Blasiak; Jhin Jieh Lim; Shirley Gek Kheng Seah; Theodore Kee; Alexandria Remus; De Hoe Chye; Pui San Wong; Lissa Hooi; Anh T.L. Truong; Nguyen Le; Conrad E.Z. Chan; Rishi Desai; Xianting Ding; Brendon J. Hanson; Edward Kai-Hua Chow; Dean Ho.
Afiliação
  • Agata Blasiak; The N.1 Institute for Health (N.1), Institute for Digital Medicine (WisDM), and Department of Biomedical Engineering, National University of Singapore, Singapor
  • Jhin Jieh Lim; Cancer Science Institute, National University of Singapore, Singapore 117599
  • Shirley Gek Kheng Seah; Defence Medical and Environmental Research Institute, DSO National Laboratories, Singapore 117510 Singapore
  • Theodore Kee; The N.1 Institute for Health (N.1), Institute for Digital Medicine (WisDM), and Department of Biomedical Engineering, National University of Singapore, Singapor
  • Alexandria Remus; The N.1 Institute for Health (N.1), Institute for Digital Medicine (WisDM), and Department of Biomedical Engineering, National University of Singapore, Singapor
  • De Hoe Chye; Defence Medical and Environmental Research Institute, DSO National Laboratories, Singapore 117510 Singapore
  • Pui San Wong; Defence Medical and Environmental Research Institute, DSO National Laboratories, Singapore 117510 Singapore
  • Lissa Hooi; Cancer Science Institute, National University of Singapore, Singapore 117599
  • Anh T.L. Truong; The N.1 Institute for Health (N.1), Institute for Digital Medicine (WisDM), and Department of Biomedical Engineering, National University of Singapore, Singapor
  • Nguyen Le; The N.1 Institute for Health (N.1), Institute for Digital Medicine (WisDM), and Department of Biomedical Engineering, National University of Singapore, Singapor
  • Conrad E.Z. Chan; Defence Medical and Environmental Research Institute, DSO National Laboratories, Singapore 117510 Singapore
  • Rishi Desai; Osmosis (Knowledge Diffusion), Baltimore, Maryland 21224, United States
  • Xianting Ding; Institute for Personalized Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030 China
  • Brendon J. Hanson; Defence Medical and Environmental Research Institute, DSO National Laboratories, Singapore 117510 Singapore
  • Edward Kai-Hua Chow; Cancer Science Institute, National University of Singapore, Singapore 117599
  • Dean Ho; The N.1 Institute for Health (N.1), Institute for Digital Medicine (WisDM), and Department of Biomedical Engineering, National University of Singapore, Singapor
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20088104
ABSTRACT
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19) has led to the rapid initiation of urgently needed clinical trials of repurposed drug combinations and monotherapies. These regimens were primarily relying on mechanism-of-action based selection of drugs, many of which have yielded positive in vitro but largely negative clinical outcomes. To overcome this challenge, we report the use of IDentif.AI, a platform that rapidly optimizes infectious disease (ID) combination therapy design using artificial intelligence (AI). In this study, IDentif.AI was implemented on a 12-drug candidate therapy search set representing over 530,000 possible drug combinations. IDentif.AI demonstrated that the optimal combination therapy against SARS-CoV-2 was comprised of remdesivir, ritonavir, and lopinavir, which mediated a 6.5-fold improvement in efficacy over remdesivir alone. Additionally, IDentif.AI showed hydroxychloroquine and azithromycin to be relatively ineffective. The identification of a clinically actionable optimal drug combination was completed within two weeks, with a 3-order of magnitude reduction in the number of tests typically needed. IDentif.AI analysis was also able to independently confirm clinical trial outcomes to date without requiring any data from these trials. The robustness of the IDentif.AI platform suggests that it may be applicable towards rapid development of optimal drug regimens to address current and future outbreaks.
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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