W J Sam1, M Aw, S H Quak, S M Lim, B G Charles, S Y Chan, P C Ho. 1. Department of Pharmacy, National University of Singapore, Singapore 119260, Department of Paediatrics, National University Hospital, Singapore 119074.
Abstract
AIMS: The purpose of this study was to describe the population pharmacokinetics of intravenous and oral tacrolimus (FK506) in 20 Asian paediatric patients, aged 1-14 years, following liver transplantation and to identify possible relationships between clinical covariates and population parameter estimates. METHODS: Details of drug dosage histories, sampling times and concentrations were collected retrospectively from routine therapeutic drug monitoring data accumulated for at least 4 days after surgery. Before analysis, patients were randomly allocated to either the population data set (n = 16) or a validation data set (n = 4). The population data set was comprised of 771 concentration measurements of patients admitted over the last 3 years. Population modelling using the nonlinear mixed-effects model (NONMEM) program was performed on the population data set, using a one-compartment model with first-order absorption and elimination. Population average parameter estimates of clearance (CL), volume of distribution (V) and oral bioavailability (F) were sought; a number of clinical and demographic variables were tested for their influence on these parameters. RESULTS: The final optimal population models related clearance to age, volume of distribution to body surface area and bioavailability to body weight and total bilirubin concentration. Predictive performance of this model evaluated using the validation data set, which comprised 86 concentrations, showed insignificant bias between observed and model-predicted blood tacrolimus concentrations. A final analysis performed in all 20 patients identified the following relationships: CL (l h-1) = 1.46 *[1 + 0. 339 * (AGE (years) -2.25)]; V (l) = 39.1 *[1 + 4.57 * (BSA (m2)-0. 49)]; F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] and F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] * [1.61], if the total bilirubin > or = 200 micromol l-1. The interpatient variabilities (CV%) in CL, V and F were 33.5%, 33.0% and 24.1%, respectively. The intrapatient variability (s.d.) among observed and model-predicted blood concentrations was 5.79 ng ml-1. CONCLUSIONS: In this study, the estimates of the pharmacokinetic parameters of tacrolimus agreed with those obtained from conventional pharmacokinetic studies. It also identified significant relationships in Asian paediatric liver transplant patients between the pharmacokinetics of tacrolimus and developmental characteristics of the patients.
AIMS: The purpose of this study was to describe the population pharmacokinetics of intravenous and oral tacrolimus (FK506) in 20 Asian paediatric patients, aged 1-14 years, following liver transplantation and to identify possible relationships between clinical covariates and population parameter estimates. METHODS: Details of drug dosage histories, sampling times and concentrations were collected retrospectively from routine therapeutic drug monitoring data accumulated for at least 4 days after surgery. Before analysis, patients were randomly allocated to either the population data set (n = 16) or a validation data set (n = 4). The population data set was comprised of 771 concentration measurements of patients admitted over the last 3 years. Population modelling using the nonlinear mixed-effects model (NONMEM) program was performed on the population data set, using a one-compartment model with first-order absorption and elimination. Population average parameter estimates of clearance (CL), volume of distribution (V) and oral bioavailability (F) were sought; a number of clinical and demographic variables were tested for their influence on these parameters. RESULTS: The final optimal population models related clearance to age, volume of distribution to body surface area and bioavailability to body weight and total bilirubin concentration. Predictive performance of this model evaluated using the validation data set, which comprised 86 concentrations, showed insignificant bias between observed and model-predicted blood tacrolimus concentrations. A final analysis performed in all 20 patients identified the following relationships: CL (l h-1) = 1.46 *[1 + 0. 339 * (AGE (years) -2.25)]; V (l) = 39.1 *[1 + 4.57 * (BSA (m2)-0. 49)]; F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] and F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] * [1.61], if the total bilirubin > or = 200 micromol l-1. The interpatient variabilities (CV%) in CL, V and F were 33.5%, 33.0% and 24.1%, respectively. The intrapatient variability (s.d.) among observed and model-predicted blood concentrations was 5.79 ng ml-1. CONCLUSIONS: In this study, the estimates of the pharmacokinetic parameters of tacrolimus agreed with those obtained from conventional pharmacokinetic studies. It also identified significant relationships in Asian paediatric liver transplant patients between the pharmacokinetics of tacrolimus and developmental characteristics of the patients.
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