Sign in

Abstract

The development of alternative in vitro methods for assessing acute inhalation toxicity is a critical step toward reducing animal testing and aligns with the principles of the 3Rs (replacement, reduction, and refinement). In this study, we developed and optimized a neutral red uptake (NRU) assay using human lung adenocarcinoma cells (A549) as a predictive model (A549-NRU) for acute inhalation toxicity. To improve assay efficiency and robustness, we introduced two key modifications: the incubation time was reduced to 15 minutes to enable rapid and high-throughput screening, and for chemicals reactive with polystyrene 6-well glass plates were used to prevent chemical-induced degradation and ensure assay consistency. LC50 values were determined for 49 chemicals and compared with reported LC50 values from 4-hour rat inhalation studies. A significant positive correlation was observed between A549-NRU-derived LC50 values and in vivo LC50 values for water-soluble compounds and chemicals containing aldehyde, ketone, alcohol, ether, and epoxide functional groups, suggesting that in vivo LC50 values may be predictable using the A549-NRU assay. Additionally, A549-NRU LC50 values showed significant negative correlations with molecular weight and octanol-water partition coefficients, indicating that chemicals with higher values tended to be less cytotoxic in vitro. Importantly, the A549-NRU assay demonstrated stronger correlation with in vivo LC50 values than the conventional NRU assay using mouse 3T3 fibroblast cells. These findings support the use of the A549-NRU assay to estimate starting doses for in vivo studies, and potentially as an in vitro alternative for predicting acute inhalation toxicity. Impact statementThe optimized A549-NRU assay demonstrates predictive potential for inhalation toxicity while reducing reliance on animal testing. This model serves as a human-relevant alternative for estimating starting doses for in vivo inhalation toxicity studies.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
1
FWCI
1.19
Field percentile
top 18%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISUrbančič '26Inesta-Vaqu '22Tian '25Camilleri '24Chen '20Gutierrez '23
60% semantic matchPharmacology & Toxicology
Iztok Urbančič, Tilen Koklič, Hana Kokot+19 more·bioRxiv·May 17, 2026