Lamotrigine is a new antiepileptic drug with substantial interindividual variability in its pharmacokinetics and therapeutic responses. This study aimed to develop population pharmacokinetic (PPK) models of lamotrigine and its N2-glucuronide metabolites for model-informed individualized therapy. A total of 353 plasma concentrations from Chinese patients with epilepsy receiving oral lamotrigine were used to develop a population PPK model using a nonlinear mixed effects modeling method. One- and two-compartment models were applied to the nonmetabolite and metabolite model, respectively. Forward addition and backward elimination were used to establish the final model. Model validation was performed using standard goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. Finally, simulations were performed to propose lamotrigine dosages in different situations to achieve trough concentrations within the reference interval (2.5-15 mg/L). For both final population PPK models, coadministration with valproic acid (VPA) or enzyme inducer, and body weight significantly affected lamotrigine clearance. The final models for lamotrigine clearance were and for nonmetabolite and metabolite models, respectively. The precision of the PPK parameters was acceptable, and the models exhibited good predictability. Monte Carlo simulations revealed that the lamotrigine dosage administered to patients combined with an enzyme inducer must be tripled that administered with VPA to reach the target trough concentration. Variability in the pharmacokinetics of lamotrigine is large. Coadministration of VPA or an enzyme inducer and body weight are the most important factors in lamotrigine clearance in Chinese patients with epilepsy. The developed population PPK models might support further optimization of lamotrigine dosing regimens.
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