Carbamazepine population pharmacokinetics in children: mixed-effect models.

The aim of the authors' study was to investigate the factors affecting carbamazepine (CBZ) clearance (CL) in children with epilepsy. The factors evaluated were total body weight (TBW), age, dose, sex, and phenobarbital (PB) and valproic acid (VA) comedication. A total of 387 steady-state serum concentration samples was analyzed. These were collected during CBZ therapy from 201 children, aged 1-14 years and weighting 9-78 kg. Population CL was calculated by using NONMEM, with a one-compartment model with first-order absorption and elimination. The absorption rate, bioavailability, and volume of distribution were set at values found in the literature. The model found best to describe the data was CL = (0.0122 TBW + 0.0467 Dose) Age0.331 (1.289 PB). The interindividual variability in CL had a variation coefficient (CV) of 11.8%, and the residual error, described by using an additive model, was 1.5 mg/l. The results show that CL increases linearly with TBW and nonlinearly with age; thus older children have a lower CL with respect to TBW than do younger ones. Likewise CL was seen to increase with the increase in the CBZ dose, suggesting a dose-dependent autoinduction of CBZ metabolism. Concomitant PB administration affected CL: however, sex and VA comedication did not affect it significantly. The final regression model for CL, was validated in a different group of 74 children. The standarized prediction error (SPE) was not significantly different from zero (SPE = 0.028), indicating that the model proposed for CL can be used to make accurate dosage recommendations. With these population estimates, CBZ doses that would be suitable for pediatric patients of different ages are proposed.

Population pharmacokinetics of caffeine in premature neonates.

OBJECTIVE: To determine population pharmacokinetic parameters of caffeine in premature neonates. METHODS: This population analysis was done using 145 serum concentration measurements gathered from 75 hospitalized patients during their routine clinical care. The data were analysed by use of NONMEM (mixed effects modeling) according to a one-compartment open model with either zero or first-order absorption and first-order elimination. The effect of a variety of developmental, demographic and clinical factors (gender, birth weight, current weight, gestational age, postnatal age, postconceptional age and concurrent treatment with phenobarbital and parenteral nutrition) on clearance and volume of distribution was investigated. Forward selection and backward elimination regression identified significant covariates. RESULTS: The final pharmacostatistical model with influential covariates were as follows: clearance (m1.h-1) = 5.81-current weight (kg) + 1.22.postnatal age (weeks), multiplied by 0.757 if gestational age < or = 28 weeks and 0.836 if the current primary source of patients' nutrition is parenteral nutrition, and volume of distribution (ml) = 911.current weight (kg). The inter-individual variability in clearance and the residual variability, expressed as coefficients of variation, were 14.8%, and 18.44%, respectively. Due to the lack of information on the data set we were unable to characterize the interindividual variability for volume of distribution. CONCLUSION: In this study, which involved on average only two serum concentrations of caffeine per patient, the use of NONMEM gave us significant and consistent information about the pharmacokinetic profile of caffeine when compared with available bibliographic information. Additionally, parenteral nutrition and low gestational age (< or = 28 weeks) may even come to be considered as risk factors, and their presence may serve as an indicator of the need for periodic monitoring of caffeine concentrations in premature infants.