AIM: To develop a population pharmacokinetic model for melphalan in children with malignant diseases and to evaluate limited sampling strategies for melphalan. METHODS: Melphalan concentration data following a single intravenous dose were collected from 59 children with malignant diseases aged between 0.3 and 18 years. The data were split into two sets: the model development dataset (39 children, 571 concentration observations) and the model validation dataset (20 children, 277 concentration observations). Population pharmacokinetic modelling was performed with the NONMEM software. Stepwise multiple linear regression was used to develop a limited sampling model for melphalan. RESULTS: A two-compartment model was fitted to the concentration-vs.-time data. The following covariate population pharmacokinetic models were obtained: (i) Clearance (l h(-1)) = 0.34.WT - 3.17.CPT + 0.0377.GFR, where WT = weight (kg), CPT = prior carboplatin therapy (0 = no, 1 = yes), and GFR = glomerular filtration rate (ml min(-1) 1.73 m(-2)); (ii) Volume of distribution (l) = 1.12 + 0.178.WT. Interpatient variability (coefficient of variation) was 27.3% for clearance and 33.8% for volume of distribution. There was insignificant bias and imprecision between observed and model-predicted melphalan concentrations in the validation dataset. A three-sample limited sampling model was developed which adequately predicted the area under the concentration-time curve (AUC) in the development and validation datasets. CONCLUSIONS: A population pharmacokinetic model for melphalan has been developed and validated and may now be used in conjunction with pharmacodynamic data to develop safe and effective dosing guidelines in children with malignant diseases.
AIM: To develop a population pharmacokinetic model for melphalan in children with malignant diseases and to evaluate limited sampling strategies for melphalan. METHODS:Melphalan concentration data following a single intravenous dose were collected from 59 children with malignant diseases aged between 0.3 and 18 years. The data were split into two sets: the model development dataset (39 children, 571 concentration observations) and the model validation dataset (20 children, 277 concentration observations). Population pharmacokinetic modelling was performed with the NONMEM software. Stepwise multiple linear regression was used to develop a limited sampling model for melphalan. RESULTS: A two-compartment model was fitted to the concentration-vs.-time data. The following covariate population pharmacokinetic models were obtained: (i) Clearance (l h(-1)) = 0.34.WT - 3.17.CPT + 0.0377.GFR, where WT = weight (kg), CPT = prior carboplatin therapy (0 = no, 1 = yes), and GFR = glomerular filtration rate (ml min(-1) 1.73 m(-2)); (ii) Volume of distribution (l) = 1.12 + 0.178.WT. Interpatient variability (coefficient of variation) was 27.3% for clearance and 33.8% for volume of distribution. There was insignificant bias and imprecision between observed and model-predicted melphalan concentrations in the validation dataset. A three-sample limited sampling model was developed which adequately predicted the area under the concentration-time curve (AUC) in the development and validation datasets. CONCLUSIONS: A population pharmacokinetic model for melphalan has been developed and validated and may now be used in conjunction with pharmacodynamic data to develop safe and effective dosing guidelines in children with malignant diseases.
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