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L. B. Ramsey, G. H. Bruun, W. Yang, L. R. Trevino, S. Vattathil, P. Scheet, C. Cheng, G. L. Rosner, K. M. Giacomini, Y. Fan, A. Sparreboom, T. S. Mikkelsen, T. J. Corydon, C. H. Pui, W. E. Evans and M. V. Relling, “Rare versus Common Variants in Pharmacogenetics: SLCO1B1 Variation and Methotrexate Disposition,” Genome Research, Vol. 22, No. 1, 2012, pp. 1-8. doi:10.1101/gr.129668.111

has been cited by the following article:

• TITLE: Population Pharmacokinetics of Methotrexate in Egyptian Children with Lymphoblastic Leukemia

  AUTHORS: Ehab Said EL Desoky, Mohamed H. Ghazal, Rajendra P. Singh, Omnia N. Abdelhamid, Hartmut Derendorf

  KEYWORDS: Methotrexate; Population Pharmacokinetics; Leukemia

  JOURNAL NAME: Pharmacology & Pharmacy, Vol.4 No.2, April 11, 2013

  ABSTRACT: Background: Individualization of high dose regimen of methotrexate (MTX) in pediatric patients with acute lymphoblastic leukemia based on pharmacokinetic (PK) parameters can help in optimization of the dose and better control of the disease. Building up of a pharmacokinetic model can help dose optimization. Objectives: A NONMEM based population (POP) PK model has been subsequently developed to evaluate the effect of demographics as covariates to address variability in pharmacokinetics of MTX. Method: Forty one patients (24 males & 17 females) with ranges of age, body weight and height of 3 - 15 years, 13 - 54 kg and 100 - 177 cm respectively and diagnosed as acute lymphoblastic leukemia (ALL) were involved in the study. MTX was administered as i.v. infusion at a dose of 2 gm/m2 over a period of two hour and its plasma concentrations were determined primarily at 24 hr post-dose to be utilized in the building-up of PK model.The initial/prior estimates of volumes of central (V1) and peripheral compartments (V2) and clearance (CL) and inter-compartmental clearance (Q2) for MTX were extracted from literature. The inter-subject variability was estimated for V1 & CL. The influence of different covariates on model performance and parameter estimates was assessed by evaluating the difference in objective function value. The final POP PK model was validated by bootstrap re-sampling procedures (1000 runs) and the 95% confidence intervals for the estimates were calculated. Results: The POP estimates for CL, V1 and V2 were 2.18 L/h, 5.74 L and 11.2 L respectively. The inter-individual variability for the CL and V1 was 23% and 30% respectively. The covariates analysis showed effect of body surface area and sex on the CL and weight on V1. Conclusions: The POP-PK model developed adequately defines the population PK of MTX in pediatric patients with lymphoblastic leukemia. The model showed effect of body surface area and sex on clearance and weight on volume of distribution of the MTX. Further studies are required on larger number of patients with enrichment of samples for MTX concentrations. The developed PK model should be also investigated in correlation with the genotyping style of different MTX transporters that may affect MTX PK parameters.