Abstract Number: 179 Working Group: From Aerosol Dosimetry and Toxicology to Health
Abstract Due to the demand for further developments of predictive, robust alternative models in inhalation toxicology, a combined in vitro / ex vivo model was set up to cover both local acute toxic effects and respiratory physiological effects from inhalable powders. The in vitro and ex vivo approaches are based on an air-lifted interface (ALI) cell culture model and an isolated perfused rat lung (IPL) model including exposure to highly concentrated aerosols generated from small amounts of micronized powders. The in vitro inhalation model included a human lung alveolar epithelial cell model (A549), an optimized exposure device (P.R.I.T.® ExpoCube®), determination of cytotoxicity and dosimetry considerations. During inhalation testing with the isolated perfused lung, physiological respiratory parameters such as tidal volume, dynamic lung compliance and relative increase in lung weight were determined, offering insight into acute physiological respiratory effects. Four commercial fungicides and sodium-dodecyl sulfate (SDS) were used as test items and positive control for acute local lung toxicity. Small amounts of testing materials of less than 500 mg were needed in each model to establish complete dose-response curves. EC50-values from in vitro testing were correlated to LD50 values from acute rat inhalation in vivo testing and showed good predictivity. Similarly, exposure to the test items as well as to the positive control SDS resulted in formation of oedema and for SDS also in acute decrease of lung function parameters in the IPL model as a measure for acute respiratory toxicity. Hence, the inhalation effects from toxic fungicides could primarily be assigned to cell toxicity. In summary, the complementary in vitro / ex vivo model appeared very promising to investigate both acute local lung toxicity and respiratory physiological effects from inhalation of bulk powder material using only small amounts of material with short study times and meaningful predictivity.