A Population Pharmacokinetics Model of Busulfan in Pediatric Patients with Thalassemia Major.

PURPOSE: This research aimed to establish a population pharmacokinetic (PPK) model for busulfan (Bu) in Chinese pediatric patients with thalassemia major. We analyzed pharmacokinetic (PK) parameter variability and explored potential covariates affecting Bu disposition using patient data. These findings are intended to support the optimization and personalization of Bu dosage regimens for children with thalassemia major.

METHODS

Concentration-time samples were collected retrospectively from 62 pediatric patients with thalassemia major. These patients had previously received intravenous Bu as a preparatory regimen for allogeneic hematopoietic stem cell transplantation (allo-HSCT). A PPK model of Bu was developed through nonlinear mixed-effects modeling. This modeling process, conducted using NONMEM software, concurrently involved data analysis and examination of the effect of covariates on Bu pharmacokinetics. For validation purposes, the resulting model was evaluated against an external dataset consisting of 20 individuals.

RESULTS

The pharmacokinetic results were optimally analyzed using a model that incorporated a onecompartment model with first-order elimination. Body surface area (BSA) was subsequently identified as the most significant factor influencing both Bu clearance (CL) and volume of distribution (V). Diagnostic evaluations, encompassing goodness-of-fit plots, normalized prediction distribution errors, and visual predictive checks, confirmed the satisfactory fit and predictability of the final PPK model. Moreover, prediction- based diagnostic indices (MDPE%, 15.75; MAPE%, 22.26; F20%, 45.71; and F30%, 58.57) from external validation showed that no significant bias was detected when comparing the model's predicted concentrations against the observed data.

CONCLUSION

The present study developed the first PPK model characterizing the pharmacokinetics of Bu specifically in children with thalassemia major. This study's final PPK model demonstrated that BSA was the key predictive covariate for CL and V.