TY - JOUR
T1 - PBK models to predict internal and external dose levels following oral exposure of rats to imidacloprid and carbendazim
AU - Hu, Bohan
AU - van den Berg, Hans J.H.J.
AU - Rietjens, Ivonne M.C.M.
AU - van den Brink, Nico W.
PY - 2024/9
Y1 - 2024/9
N2 - Monitoring oral exposure to pesticides in wildlife is crucial for assessing environmental risks and preventing adverse effects on non-target species. Traditionally, this requires invasive tissue sampling, raising ethical, regulatory, and economic concerns. To address this gap, our study aims to develop a method for assessing external oral dose levels in rats using physiologically-based kinetic (PBK) modeling based on blood concentration levels of two pesticides, imidacloprid and carbendazim, and one of their primary metabolites. We utilized in vitro metabolic kinetic data from hepatic microsomal and S9 incubations to inform our models. These models were then evaluated by comparing their predictions with existing in vivo experimental data from the literature. Our results demonstrate that the models provide accurate predictions, presenting a novel in vitro and in silico approach for environmental exposure and risk assessment of pesticides. This methodology has the potential for application in wildlife species, advancing the frontier of knowledge in non-invasive pesticide exposure assessment.
AB - Monitoring oral exposure to pesticides in wildlife is crucial for assessing environmental risks and preventing adverse effects on non-target species. Traditionally, this requires invasive tissue sampling, raising ethical, regulatory, and economic concerns. To address this gap, our study aims to develop a method for assessing external oral dose levels in rats using physiologically-based kinetic (PBK) modeling based on blood concentration levels of two pesticides, imidacloprid and carbendazim, and one of their primary metabolites. We utilized in vitro metabolic kinetic data from hepatic microsomal and S9 incubations to inform our models. These models were then evaluated by comparing their predictions with existing in vivo experimental data from the literature. Our results demonstrate that the models provide accurate predictions, presenting a novel in vitro and in silico approach for environmental exposure and risk assessment of pesticides. This methodology has the potential for application in wildlife species, advancing the frontier of knowledge in non-invasive pesticide exposure assessment.
KW - Carbendazim
KW - Exposure assessment
KW - Imidacloprid
KW - PBK model
U2 - 10.1016/j.comtox.2024.100321
DO - 10.1016/j.comtox.2024.100321
M3 - Article
AN - SCOPUS:85197401441
SN - 2468-1113
VL - 31
JO - Computational Toxicology
JF - Computational Toxicology
M1 - 100321
ER -