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Assessment of the Acute Inhalation Toxicity of Airborne Particles by Exposing Cultivated Human Lung Cells at the Air-Liquid Interface
Published on: February 23, 2020
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Emerging Technologies for In Vitro Inhalation Toxicology.
Ajay Vikram Singh1, Anthony Romeo2, Kassandra Scott2
1Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Strasse 8-10, Berlin, 10589, Germany.
Advanced Healthcare Materials
|July 22, 2021
Summary
This review explores advanced in vitro inhalation toxicity testing methods, focusing on Lungs-on-Chip (LoC) technology. It highlights bioengineering strategies and discusses future directions integrating AI for improved respiratory health assessments.
Area of Science:
- Environmental Health Sciences
- Toxicology
- Bioengineering
Background:
- Airborne viral infections and pollutant inhalation pose significant global health risks, increasing annual morbidity.
- Understanding the pulmonary health outcomes of air contaminant exposure is crucial for human health assessment.
- In vivo models have elucidated systemic effects of environmental contaminants on liver and gastrointestinal health.
Purpose of the Study:
- To provide a framework for in vitro inhalation toxicity testing.
- To introduce Lungs-on-Chip (LoC) as a novel approach for inhalation studies.
- To discuss strategies, challenges, and future directions in respiratory toxicology.
Main Methods:
- Review of bioengineering approaches and microfluidics in LoC technology.
- Analysis of different strategies for assessing inhalable substances using LoC.
- Discussion of case studies, reproducibility, and in vitro/in vivo correlations.
Main Results:
- LoC technology offers optimized bioengineering and microfluidic approaches for inhalation toxicity testing.
- Various strategies exist for assessing inhalable substances, with LoC showing promise.
- Published literature demonstrates the utility and challenges of LoC in toxicity studies.
Conclusions:
- In vitro methods, particularly LoC, are advancing respiratory toxicology assessment.
- Future directions involve integrating soft robotics, AI, and machine learning for a systems approach to toxicology.
- Addressing challenges in reproducibility and in vitro/in vivo correlation is key for future models.

