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A physiologically based pharmacokinetic model for quinoxaline‐2‐carboxylic acid in rats, extrapolation to pigs
Author(s) -
Yang X.,
Zhou Y.F.,
Yu Y.,
Zhao D.H.,
Shi W.,
Fang B.H.,
Liu Y.H.
Publication year - 2015
Publication title -
journal of veterinary pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.527
H-Index - 60
eISSN - 1365-2885
pISSN - 0140-7783
DOI - 10.1111/jvp.12143
Subject(s) - physiologically based pharmacokinetic modelling , pharmacokinetics , adipose tissue , metabolite , compartment (ship) , chemistry , pharmacology , quinoxaline , biochemistry , biology , oceanography , organic chemistry , geology
A multi‐compartment physiologically based pharmacokinetic ( PBPK ) model to describe the disposition of cyadox ( CYX ) and its metabolite quinoxaline‐2‐carboxylic acid ( QCA ) after a single oral administration was developed in rats (200 mg/kg b.w. of CYX ). Considering interspecies differences in physiology and physiochemistry, the model efficiency was validated by pharmacokinetic data set in swine. The model included six compartments that were blood, muscle, liver, kidney, adipose, and a combined compartment for the rest of tissues. The model was parameterized using rat plasma and tissue concentration data that were generated from this study. Model simulations were achieved using a commercially available software program ( ACSLX L ibero version 3.0.2.1). Results supported the validity of the model with simulated tissue concentrations within the range of the observations. The correlation coefficients of the predicted and experimentally determined values for plasma, liver, kidney, adipose, and muscles in rats were 0.98, 0.98, 0.98, 0.99, and 0.95, respectively. The rat model parameters were then extrapolated to pigs to estimate QCA disposition in tissues and validated by tissue concentration of QCA in swine. The correlation coefficients between the predicted and observed values were over 0.90. This model could provide a foundation for developing more reliable pig models once more data are available.