IDentif.AI: Rapidly optimizing combination therapy design against severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) with digital drug development

  • Bioeng Transl Med. 2020 Dec 1;6(1):e10196. doi: 10.1002/btm2.10196.
Agata Blasiak  1  2  3 ,  Jhin Jieh Lim  4 ,  Shirley Gek Kheng Seah  5 ,  Theodore Kee  1  2  3 ,  Alexandria Remus  1  2  3 ,  De Hoe Chye  5 ,  Pui San Wong  5 ,  Lissa Hooi  4 ,  Anh T L Truong  1  2  3 ,  Nguyen Le  1  2  3 ,  Conrad E Z Chan  5 ,  Rishi Desai  6 ,  Xianting Ding  7 ,  Brendon J Hanson  5 ,  Edward Kai-Hua Chow  1  2  3  4  8 ,  Dean Ho  1  2  3  8
Affiliations
  • 1. The N.1 Institute for Health (N.1) National University of Singapore Singapore Singapore.
  • 2. The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
  • 3. Department of Biomedical Engineering, NUS Engineering National University of Singapore Singapore Singapore.
  • 4. Cancer Science Institute of Singapore National University of Singapore Singapore Singapore.
  • 5. Defence Medical and Environmental Research Institute DSO National Laboratories Singapore Singapore.
  • 6. Osmosis Baltimore Maryland USA.
  • 7. Institute for Personalized Medicine, School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China.
  • 8. Department of Pharmacology, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
PMID: 33532594 DOI: 10.1002/btm2.10196
Abstract

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to multiple drug repurposing clinical trials that have yielded largely uncertain outcomes. To overcome this challenge, we used IDentif.AI, a platform that pairs experimental validation with artificial intelligence (AI) and digital drug development to rapidly pinpoint unpredictable drug interactions and optimize infectious disease combination therapy design with clinically relevant dosages. IDentif.AI was paired with a 12-drug candidate therapy set representing over 530,000 drug combinations against the SARS-CoV-2 live virus collected from a patient sample. IDentif.AI pinpointed the optimal combination as remdesivir, ritonavir, and lopinavir, which was experimentally validated to mediate a 6.5-fold enhanced efficacy over remdesivir alone. Additionally, it showed hydroxychloroquine and azithromycin to be relatively ineffective. The study was completed within 2 weeks, with a three-order of magnitude reduction in the number of tests needed. IDentif.AI independently mirrored clinical trial outcomes to date without any data from these trials. The robustness of this digital drug development approach paired with in vitro experimentation and AI-driven optimization suggests that IDentif.AI may be clinically actionable toward current and future outbreaks.

Keywords
COVID‐19; SARS‐CoV‐2; artificial intelligence; combinatory treatment; digital medicine; drug development; drug interactions.
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