Generic physiologically based kinetic modelling for farm animals: Part II. Predicting tissue concentrations of chemicals in swine, cattle, and sheep

IMPORTANT : PLEASE DISREGARD VERSION 1 OF THIS UPLOAD SINCE IT INCLUDES ERRONEOUS INFORMATION. The R codes with the DOI: 10.5281/zenodo.3432796 presented here constitute generic physiologically based models for three farm animal species: cattle (Bos taurus), sheep (Ovis aries), and swine (Sus scrofa domesticus). In addition, the function “soboljansen” was used to carry out sensitivity analysis using sobol plots. The implementation of the models using case studies is described in Lautz et al., 2019. The R codes are provided for: Generic R code for PBK modelling and partition coefficient Quantitative Structure Activity Relationship (QSAR) models Physiological parameters and their inter-individual variability estimated based on the results of extensive literature searches and specific experimental data are provided in Excel under (Lautz, 2019; DOI: 10.5281/zenodo.3433224). For each species, the PBK model has been implemented for two chemicals, one antibiotic and one environmental contaminant to predict tissue concentrations, and accumulation in milk. Each generic PBK model includes: 1. A deterministic modelling method, which represents only a single animal. 2. A probabilistic modelling approach to simulate the individual differences of the physiology within a population. Sensitivity analyses can be performed to identify which parameters have the most impact on the model’s outputs. Predictions can be compared with experimental data and were accurate for the two chemicals. Our model can be used to assess the influence of physiological factors on the kinetic of chemicals and provide guidance for assessing such critical factors in animal risk assessment. For PBK modelling purposes, species and chemical specific kinetics (e.g clearance, absorption rate, etc…) should be provided by the user. The implementation of the models using case studies are described in Lautz et al., 2019 (https://doi.org/10.1016/j.toxlet.2019.10.008)NL; R code; l.lautz@science.ru.n