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Breathing lung-on-chip : a versatile tool for assessing respiratory toxicity across multiple therapeutic modalities

Johansson, Linnea LU ; Raggi, Giulia ; Cartwright, James ; Lindqvist, Johnny ; Froment, Laurène ; Andersson, Patrik ; Betts, Catherine ; Hornberg, Jorrit J. ; Hobi, Nina and Ollerstam, Anna , et al. (2026) In Archives of Toxicology 100(4). p.1465-1484
Abstract

Inhalation administration of therapeutics is a crucial method for treatment of respiratory diseases, offering direct access to the target organ. However, the progression of candidate drugs is frequently impacted by clinical dose level limitations due to lung histopathological findings or functional effects identified in in vivo studies. Addressing these safety concerns is crucial in advancing compounds with the right safety profile. To that end, there is a need for predictive in vitro model systems to evaluate lung toxicities, including inflammatory responses across various modalities. This study aimed to assess the predictive capability of the AlveoliX Lung-on-Chip (AXLung-on-Chip) model in determining respiratory toxicity... (More)

Inhalation administration of therapeutics is a crucial method for treatment of respiratory diseases, offering direct access to the target organ. However, the progression of candidate drugs is frequently impacted by clinical dose level limitations due to lung histopathological findings or functional effects identified in in vivo studies. Addressing these safety concerns is crucial in advancing compounds with the right safety profile. To that end, there is a need for predictive in vitro model systems to evaluate lung toxicities, including inflammatory responses across various modalities. This study aimed to assess the predictive capability of the AlveoliX Lung-on-Chip (AXLung-on-Chip) model in determining respiratory toxicity of eight inhaled substances of varying modalities. Experiments using a two-dimensional (2D) culture were conducted to assess cellular responses, optimize dose settings and study design. Differentiation between compounds with lower and higher inflammatory potential was not possible in the 2D model. In contrast however, the response following treatment in the AXLung-on-Chip model was more pronounced, and the use of multiple endpoints enabled differentiation based on their inflammatory potential. Our study also indicated a potential increased sensitivity in cytokine response following treatment when mechanical stretch was incorporated in the AXLung-on-Chip. Comparison to in vivo toxicology studies demonstrated that the AXLung-on-Chip model predicted drug-induced inflammatory responses, capturing a spectrum of lung pathologies from mild toxicity to severe inflammatory damage, and illustrates the potential of the AXLung-on-Chip to identify inhaled compound toxicity across various modalities.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
3D model, Inhalation, Lung-on-Chip, Microphysiological systems, Respiratory toxicity
in
Archives of Toxicology
volume
100
issue
4
pages
1465 - 1484
publisher
Springer Science and Business Media B.V.
external identifiers
  • pmid:41535586
  • scopus:105027884583
ISSN
0340-5761
DOI
10.1007/s00204-025-04269-9
language
English
LU publication?
yes
id
e4b1ecb5-86d5-4daf-96b2-ee61fd27edb8
date added to LUP
2026-02-25 15:55:41
date last changed
2026-07-03 14:19:15
@article{e4b1ecb5-86d5-4daf-96b2-ee61fd27edb8,
  abstract     = {{<p>Inhalation administration of therapeutics is a crucial method for treatment of respiratory diseases, offering direct access to the target organ. However, the progression of candidate drugs is frequently impacted by clinical dose level limitations due to lung histopathological findings or functional effects identified in in vivo studies. Addressing these safety concerns is crucial in advancing compounds with the right safety profile. To that end, there is a need for predictive in vitro model systems to evaluate lung toxicities, including inflammatory responses across various modalities. This study aimed to assess the predictive capability of the AlveoliX Lung-on-Chip (<sup>AX</sup>Lung-on-Chip) model in determining respiratory toxicity of eight inhaled substances of varying modalities. Experiments using a two-dimensional (2D) culture were conducted to assess cellular responses, optimize dose settings and study design. Differentiation between compounds with lower and higher inflammatory potential was not possible in the 2D model. In contrast however, the response following treatment in the <sup>AX</sup>Lung-on-Chip model was more pronounced, and the use of multiple endpoints enabled differentiation based on their inflammatory potential. Our study also indicated a potential increased sensitivity in cytokine response following treatment when mechanical stretch was incorporated in the <sup>AX</sup>Lung-on-Chip. Comparison to in vivo toxicology studies demonstrated that the <sup>AX</sup>Lung-on-Chip model predicted drug-induced inflammatory responses, capturing a spectrum of lung pathologies from mild toxicity to severe inflammatory damage, and illustrates the potential of the <sup>AX</sup>Lung-on-Chip to identify inhaled compound toxicity across various modalities.</p>}},
  author       = {{Johansson, Linnea and Raggi, Giulia and Cartwright, James and Lindqvist, Johnny and Froment, Laurène and Andersson, Patrik and Betts, Catherine and Hornberg, Jorrit J. and Hobi, Nina and Ollerstam, Anna and Fitzpatrick, Paul}},
  issn         = {{0340-5761}},
  keywords     = {{3D model; Inhalation; Lung-on-Chip; Microphysiological systems; Respiratory toxicity}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{1465--1484}},
  publisher    = {{Springer Science and Business Media B.V.}},
  series       = {{Archives of Toxicology}},
  title        = {{Breathing lung-on-chip : a versatile tool for assessing respiratory toxicity across multiple therapeutic modalities}},
  url          = {{http://dx.doi.org/10.1007/s00204-025-04269-9}},
  doi          = {{10.1007/s00204-025-04269-9}},
  volume       = {{100}},
  year         = {{2026}},
}