Population Pharmacokinetics of Topiramate in Patients with Epilepsy Using Nonparametric Modeling

Abstract

Background: Topiramate (TPM) is used for the treatment of various epileptic seizures and the prevention of migraine. This study aimed to develop a population pharmacokinetic model and identify covariates that influence TPM behavior in patients with epilepsy in Kuwait. Methods: Data were collected retrospectively from 108 patients (2 years old and above) with epilepsy who were treated with oral TPM and 174 TPM blood samples from 3 hospitals in Kuwait from 2009 to 2016. Data were randomly divided into 2 groups for model development and validation. The population pharmacokinetic model was built using the nonparametric modeling algorithm (Pmetrics). The model was evaluated internally through the visual predictive check method and externally using a new data set. Results: A 1-compartment model with first-order elimination fitted the data well. Covariates showing a significant effect on the elimination rate constant were renal function and coadministration of carbamazepine (CBZ). The mean estimated clearance was 2.11 L/h; this was 50% higher for patients coadministered with CBZ. Age and sex were essential covariates for the volume of distribution (V). The visual predictive check of the final model could predict the measured concentrations. External validation further confirmed the favorable predictive performance of the model with low bias and imprecision for predicting the concentration in a particular population. Conclusions: TPM elimination was increased with CBZ coadministration and was affected by renal function. Meanwhile, age and sex were the main predictors for V. The predictive performance of the final model proved to be valid internally and externally.