The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens

IDentif.AI-x, a clinically actionable artificial intelligence platform, was used to rapidly pinpoint and prioritize optimal combination therapies against COVID-19 by pairing a prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus and Vero E6 assay with a quadratic op...

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Published inNPJ digital medicine Vol. 5; no. 1; pp. 83 - 12
Main Authors Blasiak, Agata, Truong, Anh T. L., Remus, Alexandria, Hooi, Lissa, Seah, Shirley Gek Kheng, Wang, Peter, Chye, De Hoe, Lim, Angeline Pei Chiew, Ng, Kim Tien, Teo, Swee Teng, Tan, Yee-Joo, Allen, David Michael, Chai, Louis Yi Ann, Chng, Wee Joo, Lin, Raymond T. P., Lye, David C. B., Wong, John Eu-Li, Tan, Gek-Yen Gladys, Chan, Conrad En Zuo, Chow, Edward Kai-Hua, Ho, Dean
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 30.06.2022
Nature Publishing Group
Nature Portfolio
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Summary:IDentif.AI-x, a clinically actionable artificial intelligence platform, was used to rapidly pinpoint and prioritize optimal combination therapies against COVID-19 by pairing a prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus and Vero E6 assay with a quadratic optimization workflow. A starting pool of 12 candidate drugs developed in collaboration with a community of infectious disease clinicians was first narrowed down to a six-drug pool and then interrogated in 50 combination regimens at three dosing levels per drug, representing 729 possible combinations. IDentif.AI-x revealed EIDD-1931 to be a strong candidate upon which multiple drug combinations can be derived, and pinpointed a number of clinically actionable drug interactions, which were further reconfirmed in SARS-CoV-2 variants B.1.351 (Beta) and B.1.617.2 (Delta). IDentif.AI-x prioritized promising drug combinations for clinical translation and can be immediately adjusted and re-executed with a new pool of promising therapies in an actionable path towards rapidly optimizing combination therapy following pandemic emergence.
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ISSN:2398-6352
2398-6352
DOI:10.1038/s41746-022-00627-4