A unified physiologically based pharmacokinetic model for low-to-high oral, subcutaneous, and intravenous dose of methotrexate in humans

Read full text
Authors: Min-Soo Kim, S.X. Wang, Paola Mian, Yves Théorêt, Julie Autmizguine, Shinya Ito, Andrea N. Edginton
Cited by: 1
References: 71

Abstract

Methotrexate (MTX) is used to treat both inflammatory conditions and cancers, administered in a wide range of oral, subcutaneous and intravenous doses. MTX's nonlinearities are well recognized in both absorption and disposition. However, no publicly available study has modeled this nonlinearity across the full dosing spectrum within a single pharmacokinetic (PK) framework in humans. The goal of this study is to develop a physiologically based pharmacokinetic (PBPK) model for MTX that encompasses the entire range of doses, while quantitatively incorporating the most up-to-date understanding of its kinetic behavior. To construct the PBPK model, MTX concentrations in plasma and liver, along with urinary excretion data, were obtained from published sources. The dataset was divided into training and evaluation subsets. Information on proteins involved in MTX kinetics was obtained from the literature. To assess model performance, the absolute average fold error (AAFE), average fold error (AFE), and the percentage of outside a three-fold deviation were calculated. The model was considered acceptable if the AAFE was below 2, the AFE ranged between 0.5 and 2, and the proportion of outliers was under 20%. For the overall training dataset, the AAFE, AFE, and percentage of outliers were 1.55, 1.07, and 4.38%, respectively. For the evaluation dataset, these values were 1.71, 1.17, and 9.68%. The model is the first public MTX PBPK model covering low to high dose and will be useful for further applications in DDIs and pediatrics.

Fields of Study & Subjects

Acute Lymphoblastic Leukemia research Rheumatoid Arthritis Research and Therapies Multiple Sclerosis Research Studies

Publication details

Journal / source
Journal of Pharmaceutical Sciences
Publisher
Elsevier BV
Volume
115
Issue
8
Pages
104348–104348
Publication date
2 June 2026
Language
EN