Development of a Complex Parent-Metabolite Joint Population Pharmacokinetic Model

Abstract

Abstract. This study aimed to develop a joint population pharmacokinetic model for an antipsychotic agent in development (S33138) and its active metabolite (S35424) produced by reversible metabolism. Because such a model leads to identifiability problems and numerical difficulties, the model building was performed using the FOCE-I and the Stochastic Approximation Expectation Maximization (SAEM) estimation algorithms in NONMEM and MONOLIX, respectively. Four different structural models were compared based on Bayesian information criteria. Models were first written as ordinary differential equations systems and then in closed form (CF) to facilitate further analyses. The impact of polymorphisms on genes coding for the CYP2C19 and CYP2D6 enzymes, respectively involved in the parent drug and the metabolite elimination were investigated using permutation Wald test. The parent drug and metabolite plasma concentrations of 101 patients were analyzed on two occasions after 4 and 8 weeks of treatment at 1, 3, 6, and 24 h following daily oral administration. All configurations led to a two compartment model with back-transformation of the metabolite into the parent drug and a first-pass effect. The elimination clearance of the metabolite through other processes than back-transformation was decreased by 35% [9-53%] in CYP2D6 poor metabolizer. Permutation tests were performed to ensure the robustness of the analysis, using SAEM and CF. In conclusion, we developed a complex joint pharmacokinetic model adequately predicting the impact of CYP2D6 polymorphisms on the parent drug and its metabolite concentrations through the back-transformation mechanism.

Modeling the Translocation and Transformation of Chemicals in the Soil‐Plant Continuum: A Dynamic Plant Uptake Module for the HYDRUS Model

“…Although obtaining comprehensive measurements of metabolites may be very difficult, such an approach strongly reduces the model flexibility due to its inability to describe the generation of metabolites usually encountered in actual conditions (Kodešová et al, 2019b). On the other hand, the use of parent-metabolites data is becoming more popular in other scientific fields, such as pharmacokinetic modeling (Bertrand et al, 2011;Stroh et al, 2013), that share some theoretical and practical similarities with the DPU models. Such joint parent-metabolites pharmacokinetics models are used to simulate transformation and interaction effects and can be used in conjunction with other numerical techniques (e.g., Dumont et al, 2013) to increase the model predictive capability.…”

Population pharmacokinetics of oxcarbazepine and its monohydroxy derivative in epileptic children

“…Comparison between monohydroxy derivative (MHD) steady-state trough concentrations obtained in therapeutic drug monitoring by Li et al[29] and predicted by different models…”

Semi‐Mechanistic Modelling and Simulation of Inhibition of Platelet Aggregation by Antiplatelet Agents

“…We assumed that the metabolites of triflusal and clopidogrel were absorbed directly from the gastrointestinal (GI) tract compartment because we did not observe a lag time in the metabolism of the parent drugs. This phenomenon is generally observed with drugs that are rapidly absorbed and metabolized in the body . Triflusal and clopidogrel were rapidly and well absorbed from the GI tract after oral administration; bioavailabilities of both drugs were ~80%.…”