Biological and Pharmaceutical Bulletin
Online ISSN : 1347-5215
Print ISSN : 0918-6158
ISSN-L : 0918-6158
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A Nonlinear Mixed Effects Modelling Analysis of Topiramate Pharmacokinetics in Patients with Epilepsy
Tomaž VovkMihajlo B. JakovljevićMojca Kerec KosSlobodan M. JankovićAleš MrharIztok Grabnar
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2010 Volume 33 Issue 7 Pages 1176-1182

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Abstract

Topiramate pharmacokinetics is influenced by individual factors such as patient age, renal function and co-treatment. The aim of this study was to develop a population pharmacokinetic model of topiramate to assist dosage adjustments in individual patients. Steady-state topiramate plasma concentrations in patients with epilepsy were determined by HPLC using fluorescent labelling. Demographic, biochemical data and dosing history including concomitant drug therapy were collected from patients' charts. Nonlinear mixed effects modelling was used to fit a one-compartment pharmacokinetic model. The influence of patient weight and gender, body surface area, age, creatinine clearance, serum transaminases, topiramate daily dose and co-treatment with carbamazepine, valproic acid, benzodiazepines, and risperidone on topiramate pharmacokinetics was evaluated. Additionally, the relationship between topiramate plasma concentration and clinical response was investigated. Volume of distribution of topiramate was 0.518 l/kg. For a typical patient oral clearance was estimated at 1.47 l/h, with interindividual variability of 39.2%. Clearance was 70% higher in patients co-treated with carbamazepine and was found to increase with patient age. Somnolence was the most frequently observed adverse event. Incidence of headache was associated with topiramate plasma concentration. Somnolence, ataxia, tremor, speech disorders and fatigue were associated with adjunctive therapy with carbamazepine, valproic acid, benzodiazepines, risperidone, and clozapine. No association of topiramate plasma concentration with frequency of seizures or patient quality of life was observed. The developed model can be used for Bayesian estimation of pharmacokinetic parameters based on sparse plasma samples and for selection of optimum dosing in routine patient care.

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© 2010 The Pharmaceutical Society of Japan
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