Development and validation of high-dose methotrexate population pharmacokinetic models to inform clinical decisions on dosing

PURPOSE: High-dose methotrexate is an effective treatment for adult and pediatric patients with acute lymphoblastic leukemia, osteosarcoma, and lymphoma. However, its clearance is highly variable, and delayed clearance can lead to significant toxicity. This study aimed to identify a population pharmacokinetic model that accurately characterizes high-dose methotrexate clearance in an adult population. METHODS: We developed a new population pharmacokinetic model using a training dataset derived from a cohort of 208 adult patients who received high-dose methotrexate at Vanderbilt University Medical Center. To assess predictive performance, we evaluated both our model and several externally developed models using an independent test dataset. RESULTS: The final model was a three-compartment model incorporating body surface area as a covariate on all pharmacokinetic parameters, and serum creatinine and sex as covariates on clearance. Our newly developed model predicted with the most accuracy and precision at the first concentration measurement, taken at 24 h. Our model, along with five external models, was selected based on predictive performance for further assessment with maximum a posteriori Bayesian forecasting to compare predictions at the individual-level. The model by Hui et al. was more accurate at 48 h, while our model performed similarly at 72 h. CONCLUSION: These findings suggest an optimal strategy for therapeutic drug monitoring and dosing decisions: use our model for prediction at the 24 h mark when no prior drug levels are available, followed by Bayesian forecasting using our new model supplemented by the Taylor model.