Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41746-022-00627-4
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dc.titleThe IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens.
dc.contributor.authorBlasiak, Agata
dc.contributor.authorTruong, Anh TL
dc.contributor.authorRemus, Alexandria
dc.contributor.authorHooi, Lissa
dc.contributor.authorSeah, Shirley Gek Kheng
dc.contributor.authorWang, Peter
dc.contributor.authorChye, De Hoe
dc.contributor.authorLim, Angeline Pei Chiew
dc.contributor.authorNg, Kim Tien
dc.contributor.authorTeo, Swee Teng
dc.contributor.authorTan, Yee-Joo
dc.contributor.authorAllen, David Michael
dc.contributor.authorChai, Louis Yi Ann
dc.contributor.authorChng, Wee Joo
dc.contributor.authorLin, Raymond TP
dc.contributor.authorLye, David CB
dc.contributor.authorWong, John Eu-Li
dc.contributor.authorTan, Gek-Yen Gladys
dc.contributor.authorChan, Conrad En Zuo
dc.contributor.authorChow, Edward Kai-Hua
dc.contributor.authorHo, Dean
dc.date.accessioned2022-07-14T04:33:36Z
dc.date.available2022-07-14T04:33:36Z
dc.date.issued2022-06-30
dc.identifier.citationBlasiak, Agata, Truong, Anh TL, 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 TP, Lye, David CB, Wong, John Eu-Li, Tan, Gek-Yen Gladys, Chan, Conrad En Zuo, Chow, Edward Kai-Hua, Ho, Dean (2022-06-30). The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens.. NPJ Digit Med 5 (1) : 83-. ScholarBank@NUS Repository. https://doi.org/10.1038/s41746-022-00627-4
dc.identifier.issn2398-6352
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/228508
dc.description.abstractIDentif.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.
dc.publisherSpringer Science and Business Media LLC
dc.sourceElements
dc.typeArticle
dc.date.updated2022-07-06T08:47:11Z
dc.contributor.departmentCANCER SCIENCE INSTITUTE OF SINGAPORE
dc.contributor.departmentCOLLEGE OF DESIGN AND ENGINEERING
dc.contributor.departmentDEAN'S OFFICE (MEDICINE)
dc.contributor.departmentMEDICINE
dc.contributor.departmentPHARMACOLOGY
dc.contributor.departmentLIFE SCIENCES INSTITUTE
dc.contributor.departmentMICROBIOLOGY AND IMMUNOLOGY
dc.contributor.departmentOFFICE OF THE SR DY PRESIDENT & PROVOST
dc.description.doi10.1038/s41746-022-00627-4
dc.description.sourcetitleNPJ Digit Med
dc.description.volume5
dc.description.issue1
dc.description.page83-
dc.published.stateUnpublished
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