<p><?tk 4?>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.</p>