Modeling of Large Pharmacokinetic Data Using Nonlinear Mixed-Effects: A Paradigm Shift in Veterinary Pharmacology. A Case Study With Robenacoxib in Cats

Pelligand, L and Soubret, A and King, J N and Elliott, J and Mochel, J P (2016) Modeling of Large Pharmacokinetic Data Using Nonlinear Mixed-Effects: A Paradigm Shift in Veterinary Pharmacology. A Case Study With Robenacoxib in Cats. CPT: Pharmacometrics & Systems Pharmacology, 5 (9).

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Abstract

The objective of this study was to model the pharmacokinetics (PKs) of robenacoxib in cats using a nonlinear mixed‐effects (NLME) approach, leveraging all available information collected from cats receiving robenacoxib s.c. and/or i.v.: 47 densely sampled laboratory cats and 36 clinical cats sparsely sampled preoperatively. Data from both routes were modeled sequentially using Monolix 4.3.2. Influence of parameter correlations and available covariates (age, gender, bodyweight, and anesthesia) on population parameter estimates were evaluated by using multiple samples from the posterior distribution of the random effects. A bicompartmental disposition model with simultaneous zero and first‐order absorption best described robenacoxib PKs in blood. Clearance was 0.502 L/kg/h and the bioavailability was high (78%). The absorption constant point estimate (Ka = 0.68 h−1) was lower than beta (median, 1.08 h−1), unveiling flip‐flop kinetics. No dosing adjustment based on available covariates information is advocated. This modeling work constitutes the first application of NLME in a large feline population.