Busulfan dose adjustment is routinely guided by plasma concentration monitoring using 4–9 blood samples per dose adjustment, but a pharmacometric Bayesian approach could reduce this sample burden.
The authors developed a nonparametric population model with Pmetrics. They used it to simulate optimal initial busulfan dosages, and in a blinded manner, they compared dosage adjustments using the model in the BestDose software to dosage adjustments calculated by noncompartmental estimation of area under the time–concentration curve at a national reference laboratory in a cohort of patients not included in model building.
Mean (range) age of the 53 model-building subjects was 7.8 years (0.2–19.0 years) and weight was 26.5 kg (5.6–78.0 kg), similar to nearly 120 validation subjects. There were 16.7 samples (6–26 samples) per subject to build the model. The BestDose cohort was also diverse: 10.2 years (0.25–18 years) and 46.4 kg (5.2–110.9 kg). Mean bias and imprecision of the 1-compartment model-predicted busulfan concentrations were 0.42% and 9.2%, and were similar in the validation cohorts. Initial dosages to achieve average concentrations of 600–900 ng/mL were 1.1 mg/kg (≤12 kg, 67% in the target range) and 1.0 mg/kg (>12 kg, 76% in the target range). Using all 9 concentrations after dose 1 in the Bayesian estimation of dose requirements, the mean (95% confidence interval) bias of BestDose calculations for the third dose was 0.2% (−2.4% to 2.9%, P = 0.85), compared with the standard noncompartmental method based on 9 concentrations. With 1 optimally timed concentration 15 minutes after the infusion (calculated with the authors' novel MMopt algorithm) bias was −9.2% (−16.7% to −1.5%, P = 0.02). With 2 concentrations at 15 minutes and 4 hours bias was only 1.9% (−0.3% to 4.2%, P = 0.08).
BestDose accurately calculates busulfan intravenous dosage requirements to achieve target plasma exposures in children up to 18 years of age and 110 kg using only 2 blood samples per adjustment compared with 6–9 samples for standard noncompartmental dose calculations.
*Laboratory of Applied Pharmacokinetics and Bioinformatics, Division of Pediatric Infectious Diseases, University of Southern California Children's Hospital Los Angeles;
†Institute of Pediatric Hematology and Oncology;
‡Pharmacy department, Institute of Pediatric Hematology and Oncology, Hospices Civils de Lyon;
§Laboratoire de Biométrie et Biologie Evolutive, UMR CNRS 5558, Université Lyon 1, Villeurbanne, France;
¶Pharmacy Department; and
‖Pathology and Laboratory Medicine, University of Southern California Children's Hospital Los Angeles.
Correspondence: Michael Neely, MD, 4650 Sunset Boulevard, MS#30, Los Angeles, CA 90027 (e-mail: firstname.lastname@example.org).
Supported by the National Institute of Child Health and Development (NICHD R01 HD070886) and the CHLA Clinical Trial Unit, which is part of the University of Southern California Clinical and Translational Science Institute funded by the National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (UL1TR000130).
The authors declare no conflict of interest.
Received November 08, 2015
Accepted January 04, 2016