Application of partition coefficient methods to predict tissue:plasma affinities in common farm animals: Influence of ionisation state.

Autor: Lautz LS; Wageningen Food Safety Research, Akkermaalsbos 2, Wageningen, WB 6708, the Netherlands. Electronic address: leonie.lautz@wur.nl., Dorne JCM; European Food Safety Authority, Via Carlo Magno 1A, Parma 43126, Italy., Punt A; Wageningen Food Safety Research, Akkermaalsbos 2, Wageningen, WB 6708, the Netherlands.
Jazyk: angličtina
Zdroj: Toxicology letters [Toxicol Lett] 2024 Jul; Vol. 398, pp. 140-149. Date of Electronic Publication: 2024 Jun 24.
DOI: 10.1016/j.toxlet.2024.06.012
Abstrakt: Tissue affinities are conventionally determined from in vivo steady-state tissue and plasma or plasma-water chemical concentration data. In silico approaches were initially developed for preclinical species but standardly applied and tested in human physiologically-based kinetic (PBK) models. Recently, generic PBK models for farm animals have been made available and require partition coefficients as input parameters. In the current investigation, data for species-specific tissue compositions have been collected, and prediction of chemical distribution in various tissues of livestock species for cattle, chicken, sheep and swine have been performed. Overall, tissue composition was very similar across the four farm animal species. However, small differences were observed in moisture, fat and protein content in the various organs within each species. Such differences could be attributed to factors such as variations in age, breed, and weight of the animals and general conditions of the animal itself. With regards to the predictions of tissue:plasma partition coefficients, 80 %, 71 %, 77 % of the model predictions were within a factor 10 using the methods of Berezhkovskiy (2004), Rodgers and Rowland (2006) and Schmitt (2008). The method of Berezhkovskiy (2004) was often providing the most reliable predictions except for swine, where the method of Schmitt (2008) performed best. In addition, investigation of the impact of chemical classes on prediction performance, all methods had very similar reliability. Notwithstanding, no clear pattern regarding specific chemicals or tissues could be detected for the values predicted outside a 10-fold change in certain chemicals or specific tissues. This manuscript concludes with the need for future research, particularly focusing on lipophilicity and species differences in protein binding.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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