Population pharmacokinetics of methotrexate in paediatric patients with acute lymphoblastic leukaemia and malignant lymphoma. (4th March 2022)

• Record Type: Journal Article
• Authors: Zhan, Min; Sun, Yiqi; Zhou, Fang; Wang, Honghong; Chen, Zebin; Yan, Lianzhen; Li, Xingang
• Is Part Of: Xenobiotica. Volume 52:Number 3(2022)
• Page Start: 265
• Page End: 273
• Publication Date: 2022-03-04
• Subjects: Methotrexate -- population pharmacokinetic model -- polymorphism -- paediatric -- acute lymphoblastic leukaemia -- lymphoma; Metabolism -- Periodicals; Drugs -- Physiological effect -- Periodicals; Food additives -- Periodicals; Chemicals -- Physiological effect -- Periodicals; Biochemistry -- Periodicals; Pharmaceutical Preparations -- metabolism -- Periodicals; Metabolism -- Periodicals; 574.133
• DOI: 10.1080/00498254.2022.2069060
• Languages: English
• ISSNs: 0049-8254

Abstract

Abstract: This study aimed to identify physiological and pharmacogenomic covariates and develop a population pharmacokinetic model of high-dose methotrexate (HD-MTX) in Chinese paediatric patients with acute lymphoblastic leukaemia (ALL) and malignant lymphoma. A total of 731 MTX courses and 1658 MTX plasm concentrations from 205 paediatric patients with ALL and malignant lymphoma were analysing using a non-linear mixed-effects model technique. 47 SNPs in 16 MTX-related genes were genotyped and screened as covariates. A PPK model was established to determine the influence of covariates, such as body surface area (BSA), age, laboratory test value, and SNPs on the pharmacokinetic process of HD-MTX. Two-compartmental model with allometric scaling using BSA could nicely characterise the in vivo behaviour of HD-MTX. After accounting for body size, rs17004785 and rs4148416 were the covariates that influence MTX clearance (CL). The PPK model obtained was: CL = 9.33 * (BSA/1.73) 0.75 * e 0.13*rs17004785 * e 0.39*rs4148416 * e ηCL, Vc = 24.98 * (BSA/1.73) * e ηvc, Q = 0.18 * (BSA/1.73) 0.75 * e ηQ and Vp = 4.70 * (BSA/1.73) * e ηvp . The established model combined with the Bayesian approach could estimate individual pharmacokinetic parameters and optimise personalised HD-MTX therapy for paediatric patients with ALL and malignant lymphoma.