A physiologically based pharmacokinetic model for the prediction of the depletion of methyl-3-quinoxaline-2-carboxylic acid, the marker residue of olaquindox, in the edible tissues of pigs

• Published in: Journal of veterinary pharmacology and therapeutics Vol. 37; no. 1; pp. 66 - 82
• Main Authors: Yang, B., Huang, L. L., Fang, K., Wang, Y. L., Peng, D. P., Liu, Z. L., Yuang, Z. H.
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01-02-2014
• Subjects: Absorption; Animals; Anti-Bacterial Agents - pharmacokinetics; Dose-Response Relationship, Drug; Drug Residues; Male; Models, Biological; Monte Carlo Method; Muscle, Skeletal - metabolism; Quinoxalines - administration & dosage; Quinoxalines - blood; Quinoxalines - metabolism; Quinoxalines - pharmacokinetics; Swine - metabolism
• ISSN: 0140-7783; 1365-2885
• DOI: 10.1111/jvp.12053

To estimate the consumer exposure to olaquindox (OLA) residues in porcine edible tissues, a physiologically based pharmacokinetic (PBPK) model for methyl‐3‐quinoxaline‐2‐carboxylic acid (MQCA), the marker residue of OLA, was developed in pigs based on the assumptions of the flow‐limited distribution, hepatic metabolism, and renal excretion. The model included separate compartments corresponding to blood, muscle, liver, kidney, adipose, and an extra compartment representing the remaining carcass. Physiological parameters were determined from literatures. Plasma protein binding, partition coefficients, and renal clearance for MQCA were determined in in vitro and in vivo studies. The metabolic conversion of OLA to MQCA was assumed as a simple, one‐step process, and an apparent first‐order rate constant (k) was employed to describe this metabolic process. The PBPK model was optimized and validated with plasma and tissue data from literatures and our study. Sensitivity analysis and Monte Carlo simulation were also implemented to estimate the influence of model parameters on the goodness of fit. When compared with the observed data, the PBPK model underestimated the MQCA level in all compartments at the early time points, whereas gave excellent predictions of MQCA concentration in porcine edible tissues at later time points. The correlation coefficients between the predicted and observed values were over 0.88. The consistency between the model predictions and the real residues of OLA in pigs proved the good applicability of our model in food safety risk assessment.