Abstract

Respiratory viruses (e.g. influenza, RSV, SARS etc.) attack the proximal airway and cause a wide spectrum of diseases for which we have limited therapies. To date, a few primary human stem cell-based models of the proximal airway have been reported for drug discovery but scaling them up to a higher throughput platform remains a significant challenge. Here we present a microscale, primary human stem cell-based proximal airway model of SARS-CoV-2 infection, which is amenable to moderate-to-high throughput drug screening. The model recapitulates the heterogeneity of infection seen among different patients and with different SARS-CoV-2 variants. We applied this model to screen 2100 compounds from targeted drug libraries using an image-based quantification method. While there were heterogeneous responses across variants for host factor targeting compounds, the direct acting antivirals showed a consistent response and we characterized a new antiviral drug that is effective against both the parental strain and the Omicron variant.