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Updated: Jun 27, 2026

Cytotoxic Efficacy of Photodynamic Therapy in Osteosarcoma Cells In Vitro
Published on: March 18, 2014
Population pharmacokinetics of high-dose methotrexate after intravenous administration in pediatric patients with
Helena Colom1, Rosa Farré, Dolors Soy
1Department of Biopharmaceutics and Pharmacokinetics, School of Pharmacy, University of Barcelona, Spain. helena.colom@ub.edu
Abstract:
The goal of this study was to establish the population pharmacokinetics (PK) of high-dose methotrexate (HD-MTX) treatment in children with osteosarcoma and to explore the influence of patient covariates and between-occasion variability on drug disposition. Patient covariates and concentration-time data were collected. PK data analysis from 209 HD-MTX cycles from 14 patients was performed using the population approach (NONMEM V). Internal and external validations were performed to confirm the model. PK of methotrexate was best described by a 2-compartment open PK model with first-order elimination from the central compartment. Between-subject variability (BSV) was included in total plasma clearance (CL) and in central compartment distribution volume (V1) [coefficient of variation (CV) 11.9% and 8.9%, respectively]. The CV of BSV in the residual error was 25.5%. Between-occasion variability was only retained for CL (CV 8.2%). RE consisted of a proportional error of 41.6%. Age and body weight in CL and body weight in V1 were identified as the appropriate covariates. The final estimates of total CL and V1 were given by the equations CL = 88.5.(AGE/15) + 27.4 x (WGT/50) L/d and V1 = 11.0 + 5.6 x (WGT/50) L, respectively. Internal validation results showed that the 95% confidence interval covered all the observed MTX concentrations. Mean bias and precision of the individual predicted concentrations, calculated in a validation dataset, resulted in -1.36% and 19.71%, respectively. A population PK model was developed for HD-MTX in children with osteosarcoma. Validation studies confirmed the suitability of the model for further dose individualization by means of a Bayesian approach.
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