A minimal physiologically based pharmacokinetic model for high-dose methotrexate.

Area of Science:

• Pharmacokinetics
• Pharmacometrics
• Oncology

Background:

• High-dose methotrexate (HDMTX) is crucial for treating various cancers.
• Methotrexate pharmacokinetics exhibit significant variability, primarily influenced by renal excretion.
• Current dosing strategies based on body surface area lack precise renal function adjustment.

Purpose of the Study:

• To develop a population pharmacokinetic model for HDMTX with a physiological description of renal excretion.
• To create a basis for clinical tools that suggest model-informed dosages and support therapeutic monitoring.
• To enable individualized predictions of HDMTX pharmacokinetics.

Main Methods:

• A minimal physiologically based pharmacokinetic (PBPK) model for HDMTX was developed.
• The model incorporates individual patient characteristics (weight, height, gender, age, hematocrit, serum creatinine).
• It includes a mechanistic description of fluid compartment exchanges and individualized renal excretion.

Main Results:

• The PBPK model was identified and validated using a literature dataset of Chinese patients with primary central nervous system lymphoma.
• The proposed model demonstrated improved predictive accuracy compared to a literature pharmacokinetic model.
• The model showed no significant bias across a wide spectrum of renal function levels.

Conclusions:

• Model predictions effectively capture the intra- and inter-individual variability of HDMTX pharmacokinetics.
• Individual renal function plays a critical role in HDMTX variability.
• The developed model can serve as a foundation for clinical decision-support systems for personalized dosing and monitoring.