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Title: Population Pharmacokinetics of Topiramate in Patients with Epilepsy in Kuwait
Authors: Mandy Moien 
Supervisor: Dr. Kamal Matar
Keywords: Pharmacokinetics
Issue Date: 2018
Publisher:  Kuwait university - college of graduate studies
Abstract: Topiramate (TPM) is one of the new generation anti-epileptic medications that used for the treatment of number of epileptic seizures and the prevention of migraine. TPM is a Sulfamate derivative of fructose with hydrophilic property. The aim of the current study was to develop a population pharmacokinetic model and identify the covariates that are affecting the behavior of TPM for patients with epilepsy in Kuwait. The approach used in the current analysis to estimate the pharmacokinetic parameters was the non-parametric modeling algorithm NPAG that is implemented in Pmetrics software. Moreover, the model was validated internally through the visual predictive check (VPC) method and externally using new data set. The data in total comprised 174 blood samples from 108 patients of different age groups (2 years old and older) with epilepsy and treated with oral topiramate. Data were collected from three hospitals in Kuwait, Al-Amiri, Mubarak Al Kabeer and Ibn Sina hospital. Data were divided randomly into two groups for model development and validation. A one compartment pharmacokinetic model with first order elimination fitted the data well. The covariates that showed significant effect on the elimination rate constant (ke) were the renal function, estimated by the chronic kidney disease - epidemiology (CKD-EPI) formula, and the co-administration of carbamazepine. The mean estimated clearance (CL) of the analyzed population was 2.11 L/h, which was 50 % higher for patients that were co-administered with CBZ than the other patients. On the other hand, for the volume of distribution (V), the age and the gender were the significant covariates. The mean value of V was 48.75 L. Females had lower V than males by about 34 % while adults showed 24% more V. The internal validation of the final model using VPC showed that the final model had good predictive ability of the measured concentrations. The external validation of the final model further confirmed the good predictive performance of the model with low bias and imprecision of – 0.106 mg/L and 0.975 mg/L, respectively for the concentration population predictions.
Appears in Programs:1100 Pharmaceutical Sciences

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