A human primary airway microphysiological system infected with SARS-CoV-2 distinguishes the treatment efficacy between nirmatrelvir and repurposed compounds fluvoxamine and amodiaquine (preprint)

The COVID-19 pandemic necessitated a rapid mobilization of resources toward the development of safe and efficacious vaccines and therapeutics. Finding effective treatments to stem the wave of infected individuals needing hospitalization and reduce the risk of adverse events was paramount. For scientists and healthcare professionals addressing this challenge, the need to rapidly identify medical countermeasures became urgent, and many compounds in clinical use for other indications were repurposed for COVID-19 clinical trials after preliminary preclinical data demonstrated antiviral activity against SARS-CoV-2. Two repurposed compounds, fluvoxamine and amodiaquine, showed efficacy in reducing SARS-CoV-2 viral loads in preclinical experiments, but ultimately failed in clinical trials, highlighting the need for improved predictive preclinical tools that can be rapidly deployed for events such as pandemic emerging infectious diseases. The PREDICT96-ALI platform is a high-throughput, high-fidelity microphysiological system (MPS) that recapitulates primary human tracheobronchial tissue and supports highly robust and reproducible viral titers of SARS-CoV-2 variants Delta and Omicron. When amodiaquine and fluvoxamine were tested in PREDICT96-ALI, neither compound demonstrated an antiviral response, consistent with clinical outcomes and in contrast with prior reports assessing the efficacy of these compounds in other human cell-based in vitro platforms. These results highlight the unique prognostic capability of the PREDICT96-ALI proximal airway MPS to assess the potential antiviral response of lead compounds.

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

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.