id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-317628-1inxq7t5	Cuccarese, Michael F.	Functional immune mapping with deep-learning enabled phenomics applied to immunomodulatory and COVID-19 drug discovery	2020-08-14		.txt	text/plain	9573	487	43	We deploy the platform to develop phenotypic models of active SARS-CoV-2 infection and of COVID-19-associated cytokine storm, surfacing compounds with demonstrated clinical benefit and identifying several new candidates for drug repurposing. We used these capabilities to rapidly develop high-throughput-ready disease models for both SARS-CoV-2 viral infection and the resulting cytokine storm, and immediately launched large-scale drug screens that recapitulated known effective and ineffective therapies and, more importantly, identified several new potential treatments for both SARS-CoV-2 infection and COVID-19-associated cytokine storm. To define the model, we evaluated the effect of SARS-CoV-2 infection in multiple cell types, of which three resulted in robust phenoprints as compared to either mock infected or inactivated virus control populations: Calu3 (a lung adenocarcinoma line), Vero (an immortalized interferondeficient African green monkey kidney line 55 ), and primary Human Renal Cortical Epithelium (HRCE) (Fig. 5C, Fig. S6D ).	./cache/cord-317628-1inxq7t5.txt	./txt/cord-317628-1inxq7t5.txt