A high throughput microphysiological model of prosthetic valve endocarditis for investigating factors that influence bacterial adhesion under fluid shear stress.

Prosthetic heart valves are associated with almost one quarter of cases of infective endocarditis, a rare but serious condition with a staggering 25 % mortality rate. Without the endothelium of native valves, the risk of infection is exacerbated for implanted devices exposed to blood. There are currently no physiologically relevant in vitro or animal models of prosthetic valve endocarditis (PVE). Of particular importance, Staphylococcus aureus, a common agent of PVE, has demonstrated enhanced binding to blood plasma proteins (e.g., fibrinogen) and exposed matrix under fluid shear stress (FSS). An in vitro platform that mimics the multiple physiological determinants for S. aureus adhesion to prosthetic valve materials would facilitate the discovery of new treatments to minimize PVE. To this end, we developed a first-of-its-kind microphysiological model of PVE to study the effects of several key variables (endothelial cell coverage, fibrinogen deposition, surface treatments, and FSS) on S. aureus adhesion to bioprosthetic material surfaces. Our model demonstrated that viable endothelial monolayers diminished the deposition of fibrinogen and that fibrinogen was required for the subsequent adhesion of S. aureus to the bioprosthetic surface model. Next, we examined factors that affected endothelial cell coverage, such as FSS and glutaraldehyde, a common chemical treatment for bioprosthetic materials. In particular, glutaraldehyde treatment obstructed endothelialization of otherwise biocompatible collagen-coated surfaces, further enabling fibrinogen and S. aureus deposition. In future work, this model could impact multiple research areas, such as screening candidate bioprosthetic valve materials and new surface treatments to prevent PVE and further understanding host-pathogen interactions.

Predicting Clinical Outcomes of SARS-CoV-2 Drug Efficacy with a High-Throughput Human Airway Microphysiological System.

The average cost to bring a new drug from its initial discovery to a patient's bedside is estimated to surpass $2 billion and requires over a decade of research and development. There is a need for new drug screening technologies that can parse drug candidates with increased likelihood of clinical utility early in development in order to increase the cost-effectiveness of this pipeline. For example, during the COVID-19 pandemic, resources were rapidly mobilized to identify effective therapeutic treatments but many lead antiviral compounds failed to demonstrate efficacy when progressed to human trials. To address the lack of predictive preclinical drug screening tools, PREDICT96-ALI, a high-throughput (n = 96) microphysiological system (MPS)  that recapitulates primary human tracheobronchial tissue,is adapted for the evaluation of differential antiviral efficacy of native SARS-CoV-2 variants of concern. Here, PREDICT96-ALI resolves both the differential viral kinetics between variants and the efficacy of antiviral compounds over a range of drug doses. PREDICT96-ALI is able to distinguish clinically efficacious antiviral therapies like remdesivir and nirmatrelvir from promising lead compounds that do not show clinical efficacy. Importantly, results from this proof-of-concept study track with known clinical outcomes, demonstrate the feasibility of this technology as a prognostic drug discovery tool.

A High-Throughput, High-Containment Human Primary Epithelial Airway Organ-on-Chip Platform for SARS-CoV-2 Therapeutic Screening.

COVID-19 emerged as a worldwide pandemic in early 2020, and while the rapid development of safe and efficacious vaccines stands as an extraordinary achievement, the identification of effective therapeutics has been less successful. This process has been limited in part by a lack of human-relevant preclinical models compatible with therapeutic screening on the native virus, which requires a high-containment environment. Here, we report SARS-CoV-2 infection and robust viral replication in PREDICT96-ALI, a high-throughput, human primary cell-based organ-on-chip platform. We evaluate unique infection kinetic profiles across lung tissue from three human donors by immunofluorescence, RT-qPCR, and plaque assays over a 6-day infection period. Enabled by the 96 devices/plate throughput of PREDICT96-ALI, we also investigate the efficacy of Remdesivir and MPro61 in a proof-of-concept antiviral study. Both compounds exhibit an antiviral effect against SARS-CoV-2 in the platform. This demonstration of SARS-CoV-2 infection and antiviral dosing in a high-throughput organ-on-chip platform presents a critical capability for disease modeling and therapeutic screening applications in a human physiology-relevant in vitro system.