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A core aspect of epithelial cell function is barrier integrity. A loss of barrier integrity is a feature of a number of respiratory diseases, including asthma, allergic rhinitis, and chronic obstructive pulmonary disease. Restoration of barrier integrity is a target for respiratory disease drug discovery. Traditional methods for assessing barrier integrity have their limitations. Transepithelial electrical resistance (TEER) and dextran permeability methods can give poor in vitro assay robustness. Traditional junctional complex imaging approaches are labor-intensive and tend to be qualitative but not quantitative. To provide a robust and quantitative assessment of barrier integrity, high-content imaging of junctional complexes was combined with TEER. A scalable immunofluorescent high-content imaging technique, with automated quantification of junctional complex proteins zonula occludens-1 and occludin, was established in 3D pseudostratified primary human bronchial epithelial cells cultured at an air-liquid interface. Ionic permeability was measured using TEER on the same culture wells.The improvements to current technologies include the design of a novel 24-well holder to enable scalable in situ confocal cell imaging without Transwell membrane excision, the development of image analysis pipelines to quantify in-focus junctional complex structures in each plane of a Z stack, and the enhancement of the TEER data analysis process to enable statistical evaluation of treatment effects on barrier integrity. This novel approach was validated by demonstrating measurable changes in barrier integrity in cells grown under conditions known to perturb epithelial cell function.

The pharmaceutical industry is continuing to face high research and development (R&D) costs and low overall success rates of clinical compounds during drug development. There is an increasing demand for development and validation of healthy or disease-relevant and physiological human cellular models that can be implemented in early-stage discovery, thereby shifting attrition of future therapeutics to a point in discovery at which the costs are significantly lower. There needs to be a paradigm shift in the early drug discovery phase (which is lengthy and costly), away from simplistic cellular models that show an inability to effectively and efficiently reproduce healthy or human disease-relevant states to steer target and compound selection for safety, pharmacology, and efficacy questions. This perspective article covers the various stages of early drug discovery from target identification (ID) and validation to the hit/lead discovery phase, lead optimization, and preclinical safety. We outline key aspects that should be considered when developing, qualifying, and implementing complex in vitro models (CIVMs) during these phases, because criteria such as cell types (e.g., cell lines, primary cells, stem cells, and tissue), platform (e.g., spheroids, scaffolds or hydrogels, organoids, microphysiological systems, and bioprinting), throughput, automation, and single and multiplexing endpoints will vary. The article emphasizes the need to adequately qualify these CIVMs such that they are suitable for various applications (e.g., context of use) of drug discovery and translational research. The article ends looking to the future, in which there is an increase in combining computational modeling, artificial intelligence and machine learning (AI/ML), and CIVMs.