A novel in vitro high-content imaging assay for the prediction of drug-induced lung toxicity.

Autor: Fitzpatrick, Paul A., Johansson, Julia, Maglennon, Gareth, Wallace, Ian, Hendrickx, Ramon, Stamou, Marianna, Balogh Sivars, Kinga, Busch, Susann, Johansson, Linnea, Van Zuydam, Natalie, Patten, Kelley, Åberg, Per M., Ollerstam, Anna, Hornberg, Jorrit J.
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Zdroj: Archives of Toxicology; Sep2024, Vol. 98 Issue 9, p2985-2998, 14p
Abstrakt: The development of inhaled drugs for respiratory diseases is frequently impacted by lung pathology in non-clinical safety studies. To enable design of novel candidate drugs with the right safety profile, predictive in vitro lung toxicity assays are required that can be applied during drug discovery for early hazard identification and mitigation. Here, we describe a novel high-content imaging-based screening assay that allows for quantification of the tight junction protein occludin in A549 cells, as a model for lung epithelial barrier integrity. We assessed a set of compounds with a known lung safety profile, defined by clinical safety or non-clinical in vivo toxicology data, and were able to correctly identify 9 of 10 compounds with a respiratory safety risk and 9 of 9 compounds without a respiratory safety risk (90% sensitivity, 100% specificity). The assay was sensitive at relevant compound concentrations to influence medicinal chemistry optimization programs and, with an accessible cell model in a 96-well plate format, short protocol and application of automated imaging analysis algorithms, this assay can be readily integrated in routine discovery safety screening to identify and mitigate respiratory toxicity early during drug discovery. Interestingly, when we applied physiologically-based pharmacokinetic (PBPK) modelling to predict epithelial lining fluid exposures of the respiratory tract after inhalation, we found a robust correlation between in vitro occludin assay data and lung pathology in vivo, suggesting the assay can inform translational risk assessment for inhaled small molecules. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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