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The IDentif.AI 2.0 Pandemic Readiness Platform: Rapid Prioritization of Optimized COVID-19 Combination Therapy Regimens

Authors :
David M Allen
Gek-Yen Gladys Tan
Peter Wang
Alexandria Remus
Anh T. L. Truong
Yee-Joo Tan
Raymond T. P. Lin
Agata Blasiak
Edward Kai-Hua Chow
Wee Joo Chng
Kim Tien Ng
Angeline Pei Chiew Lim
Louis Yi Ann Chai
De Hoe Chye
Dean Ho
John Wong
Conrad E.Z. Chan
David C. Lye
Swee Teng Teo
Shirley Gek Kheng Seah
Lissa Hooi
Publication Year :
2021
Publisher :
Cold Spring Harbor Laboratory, 2021.

Abstract

ObjectivesWe aimed to harness IDentif.AI 2.0, a clinically actionable AI platform to rapidly pinpoint and prioritize optimal combination therapy regimens against COVID-19.MethodsA pool of starting candidate therapies was developed in collaboration with a community of infectious disease clinicians and included EIDD-1931 (metabolite of EIDD-2801), baricitinib, ebselen, selinexor, masitinib, nafamostat mesylate, telaprevir (VX-950), SN-38 (metabolite of irinotecan), imatinib mesylate, remdesivir, lopinavir, and ritonavir. Following the initial drug pool assessment, a focused, 6-drug pool was interrogated at 3 dosing levels per drug representing nearly 10,000 possible combination regimens. IDentif.AI 2.0 paired prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus (propagated, original strain, B.1.351 and B.1.617.2 variants) and Vero E6 assay with a quadratic optimization workflow.ResultsWithin 3 weeks, IDentif.AI 2.0 realized a list of combination regimens, ranked by efficacy, for clinical go/no-go regimen recommendations. IDentif.AI 2.0 revealed EIDD-1931 to be a strong candidate upon which multiple drug combinations can be derived.ConclusionsIDentif.AI 2.0 rapidly revealed promising drug combinations for clinical translation. It pinpointed dose-dependent drug synergy behavior to play a role in trial design and realizing positive treatment outcomes. IDentif.AI 2.0 represents an actionable path towards rapidly optimizing combination therapy following pandemic emergence.Graphical AbstractHighlights-When novel pathogens emerge, the immediate strategy is to repurpose drugs.-Good drugs delivered together in suboptimal combinations and doses can yield low or no efficacy, leading to misperception that the drugs are ineffective.-IDentif.AI 2.0 does not use in silico modeling or pre-existing data.-IDentif.AI 2.0 pairs optimization with prospectively acquired experimental data using a SARS-CoV-2/Vero E6 assay.-IDentif.AI 2.0 pinpoints EIDD-1931 as a foundation for optimized anti-SARS-CoV-2 combination therapies.

Details

ISSN :
21259321
Database :
OpenAIRE
Accession number :
edsair.doi...........3657e0b9e1d56a1030e8d79de9129c4c
Full Text :
https://doi.org/10.1101/2021.06.23.21259321