Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164337
Title: The IDentif.AI-x pandemic readiness platform: rapid prioritization of optimized COVID-19 combination therapy regimens
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.
Wong, John Eu-Li
Tan, Gladys Gek-Yen
Chan, Conrad En Zuo
Chow, Edward Kai-Hua
Ho, Dean
Keywords: Science::Medicine
Issue Date: 2022
Source: Blasiak, A., Truong, A. T. L., Remus, A., Hooi, L., Seah, S. G. K., Wang, P., Chye, D. H., Lim, A. P. C., Ng, K. T., Teo, S. T., Tan, Y., Allen, D. M., Chai, L. Y. A., Chng, W. J., Lin, R. T. P., Lye, D. C., Wong, J. E., Tan, G. G., Chan, C. E. Z., ...Ho, D. (2022). The IDentif.AI-x pandemic readiness platform: rapid prioritization of optimized COVID-19 combination therapy regimens. NPJ Digital Medicine, 5(1), 83-. https://dx.doi.org/10.1038/s41746-022-00627-4
Journal: NPJ Digital Medicine 
Abstract: 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.
URI: https://hdl.handle.net/10356/164337
ISSN: 2398-6352
DOI: 10.1038/s41746-022-00627-4
Schools: Lee Kong Chian School of Medicine (LKCMedicine) 
Organisations: Yong Loo Lin School of Medicine, NUS
National Centre for Infectious Diseases
Tan Tock Seng Hospital
Rights: © The Author(s) 2022. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons. org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

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