Predicting clinical outcomes of SARS-CoV-2 drug treatments with a high throughput human airway on chip platform

Despite the relatively common observation of therapeutic efficacy in discovery screens with immortalized cell lines, the vast majority of drug candidates do not reach clinical development. Candidates that do move forward often fail to demonstrate efficacy when progressed from animal models to humans. This dilemma highlights the need for new drug screening technologies that can parse drug candidates early in development with regard to predicted relevance for clinical use. PREDICT96-ALI is a high-throughput organ-on-chip platform incorporating human primary airway epithelial cells in a dynamic tissue microenvironment. Here we demonstrate the utility of PREDICT96-ALI as an antiviral screening tool for SARS-CoV-2, combining the high-throughput functionality of a 96-well plate format in a high containment laboratory with the relevant biology of primary human tissue. PREDICT96-ALI resolved differential efficacy in five antiviral compounds over a range of drug doses. Complementary viral genome quantification and immunofluorescence microscopy readouts achieved high repeatability between devices and replicate plates. Importantly, results from testing the three antiviral drugs currently available to patients (nirmatrelvir, molnupiravir, and remdesivir) tracked with clinical outcomes, demonstrating the value of this technology as a prognostic drug discovery tool. ### Competing Interest Statement The authors have declared no competing interest.