Dosing Optimization of Lamotrigine in Peripregnancy Epilepsy Through PopPK Modelling and Simulation.

PURPOSE: Lamotrigine demonstrates substantial interindividual pharmacokinetic variability during pregnancy, though the underlying mechanisms remain incompletely understood. The study aimed to develop a population pharmacokinetic model of lamotrigine in Chinese epileptic patients during the peripregnancy period, in order to identify the key influencing factors and thereby assist in providing a solution for the individualized administration of lamotrigine.

METHODS

One hundred and twenty-eight perigestational epilepsy patients (293 plasma concentrations) from two Chinese hospitals between January 1, 2015 and May 31, 2024 were enrolled in the study. A nonlinear mixed-effects model was developed using Phoenix NLME™ (v8.3) with stepwise covariate selection. Model validation encompassed goodness-of-fit analysis, bootstrap analysis (n = 1000), prediction-corrected visual predictive checks, and normalized prediction distribution error evaluation. Optimal dosing regimens were derived through Monte Carlo simulations accounting for gestational/postpartum physiological changes.

RESULTS

A one - compartment model combined with an additive and proportional error model was employed to characterize the pharmacokinetics of lamotrigine. Each factor's impact on CL/F was systematically examined using a stepwise approach, resulting in the establishment of the final model: [Formula: see text]. CL/F was identified as the primary pharmacokinetic parameter, serving as the main outcome measure and foundational basis for dosing recommendations. The model demonstrated satisfactory accuracy and commendable predictability. LTG CL/F increased significantly from 5 weeks of gestation, with CL/F in stages 2, 3, and 4 being 131%, 193%, and 199% of stage 1 (<5 weeks), respectively, and declining sharply to 68% of stage 1 postpartum.

CONCLUSION

The CL/F of lamotrigine was found to be increased significantly from 5 weeks of gestation and dropped sharply postpartum. Weight, pregnancy stage, and co-administration with valproic acid were identified as significant influencing factors. The internal verification results of the model were generally satisfactory, however, prospective multicenter cohorts incorporating larger-scale external datasets are imperative to establish robust generalizability, ultimately enabling precise personalized dose optimization strategies for peripregnancy epileptic patients.