Charlotte Maria Ursula Dette 1, Fatima Zahra Marok 1, Veronika Alberg 1, Christiane Dings 1, Dominik Selzer 1, Matthias Schwab 2,3,4, Barbara Faganel Kotnik 5, Vita Dolžan 6, Daniela Yildiz 7, Jörg Bittenbring 8, Marc Remke 9, Thorsten Lehr 1
1 Clinical Pharmacy, Saarland University (Saarbrücken, Deutschland), 2 Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology (Stuttgart, Germany), 3 Departments of Clinical Pharmacology, Pharmacy and Biochemistry, University of Tübingen (Tübingen, Germany), 4 Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen (Tübingen, Germany), 5 Department of Hematology and Oncology, University Children’s Hospital (Ljubljana, Slovenia), 6 Pharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana (Ljubljana, Slovenia), 7 Experimental and Clinical Pharmacology and Toxicology, Center for Molecular Signaling (PZMS), Saarland University (Homburg, Germany), 8 Saarland University Medical School, José Carreras Center for Immuno- and Gene Therapy and Internal Medicine I (Homburg, Germany), 9 Department of Pediatric Oncology & Heamatology, Saarland University (Homburg, Germany)
Background and Objectives: The antifolate agent methotrexate (MTX) is a cornerstone for chronic
inflammatory diseases and chemotherapy in adult and pediatric patients [1]. MTX shows pronounced
interpatient variability and complex pharmacokinetics driven by genetic polymorphisms, renal
function, and binding to transporters such as organic anion transporter 3 (OAT3), multidrug resistanceassociated protein 3 (MRP3), reduced folate carrier 1 (RFC1), breast cancer resistance protein (BCRP),
and organic anion-transporting polypeptide 1 (OATP1B1) [2–4]. Despite decades of clinical use, severe
toxicities, including acute kidney injury, are still observed in routine practice, and individual exposure
remains difficult to predict [5]. As a consequence, therapeutic drug monitoring (TDM) of MTX is
commonly performed 24–72 hours after dosing, with a typical target plasma concentration of 1 µmol/L
at 48 hours to avoid prolonged exposure and associated toxicities [6]. Additional age-dependent
variability in MTX and its main metabolite 7-hydroxymethotrexate (7-OH-MTX) pharmacokinetics is
found in pediatric patients, such as those treated with MTX for acute lymphoblastic leukemia (ALL),
due to developmental changes of renal function and drug transporters, making it especially challenging
to anticipate individual exposure levels. Here, physiologically based pharmacokinetic (PBPK) modeling
offers a regulatory-endorsed approach to predict pharmacokinetics, and support dose selection in
special populations [7].
By integrating individual physiology, renal function, and demographic characteristics, PBPK models can
be tailored to pediatric patients and may complement TDM by guiding dose selection and
quantitatively describing and predicting MTX pharmacokinetics at the individual level [8]. Thus, the
objectives of this project were (i) to build a PBPK model for MTX and 7-OH-MTX under p.o. and i.v.
administration, (ii) to scale the parent-metabolite model to pediatric populations, and (iii) to explore
its application for predicting individual TDM datasets from clinical routine during treatment of ALL and
other cancers.
Methods: The Open Systems Pharmacology Suite version 12.1 (www.open-systemspharmacology.org) was used with its tool PK-Sim® as an open-source PBPK modelling software [9].
Plasma concentration-time profiles of MTX and 7-OH-MTX obtained from adults and children were
digitized from published literature. The model was then scaled to pediatric populations and used to
predict mean pediatric concentration–time profiles. Based on this reference model, a digital twin was
generated and tailored to each child’s individual physiological characteristics to predict individual TDM
concentrations. The model was used to predict individual plasma concentration–time profiles for 75
children treated with MTX over four cycles, with doses ranging from 2,000 to 5,000 mg/m². The data
were obtained from retrospective TDM measurements collected between 1990 and 2004 at the
University Medical Centre Ljubljana in Slovenia. Particular emphasis was placed on the model’s ability
to predict the target concentration of 1 µmol/L at 48 hours.
Results: A whole-body PBPK model for MTX and 7-OH-MTX was developed consisting of 42 MTX and
16 7-OH-MTX plasma concentration-time profiles, covering a dosing range of 2.5 mg to 30,240 mg. The
comprehensive parent-metabolite model covers metabolism of MTX via aldehyde oxidase and
transportation via MRP3, OAT3 and RFC1, BCRP, OATP1B1 as well as intracellular retention through
binding to the pharmacodynamic target enzyme dihydrofolate reductase. Considering the entire
dataset, 53/58 predicted AUClast and 38/39 predicted Cmax values are within the 2-fold range of their
observed counterparts. Mean GMFEAUClast and GMFECmax values of 1.43 and 1.30 confirm sufficient
descriptive and predictive model performance.
The model was then fitted to pediatric populations by accounting for physiological and anatomical
differences, including age-related changes such as size, composition of tissue compartments, protein
binding and maturation of metabolization and elimination processes were scaled to children. A total
of 40 children, aged between 1 and 17 years and suffering from malignant diseases, were included in
the model and were described accurately with an overall mean GMFEAUClast of 1.52 as well as GMFECmax
of 1.47.
Conclusion: The presented parent-metabolite PBPK of MTX and 7-OH-MTX model accurately captures
plasma concentrations in adult and pediatric populations and has been used exploratively to predict
individualized TDM data during chemotherapy in children suffering from malignant diseases such as
ALL.
Funding Information
This study was funded by the European Union as part of the project “Improve Safety in Polymedication
by Managing Drug-Drug-Gene Interactions – SafepolyMed”.
References:
References
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[8] Dette, C. M. U. , Alberg, V. et al. Advancing rare disease therapeutics through digital twins: Opportunities
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[9] Lippert, J. et al. Open Systems Pharmacology Community—An Open Access, Open Source, Open Science
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Reference: PAGE 34 (2026) Abstr 11891 [www.page-meeting.org/?abstract=11891]
Poster: Drug/Disease Modelling - Absorption & PBPK