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Preprint in English | medRxiv | ID: ppmedrxiv-21259321

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 Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/21259321v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@f8a159org.highwire.dtl.DTLVardef@12908b7org.highwire.dtl.DTLVardef@fb6485org.highwire.dtl.DTLVardef@8493c3_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- 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.

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