title: Accurately Achieving Target Busulfan Exposure in Children and Adolescents With Very Limited Sampling and the BestDose Software.
abstract: 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.
authors.affiliation: *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.
authors.forename: Michael
authors.initials: M
authors.lastname: Neely
authors.forename: Michael
authors.initials: M
authors.lastname: Philippe
authors.forename: Teresa
authors.initials: T
authors.lastname: Rushing
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Fu
authors.forename: Michael
authors.initials: M
authors.lastname: van Guilder
authors.forename: David
authors.initials: D
authors.lastname: Bayard
authors.forename: Alan
authors.initials: A
authors.lastname: Schumitzky
authors.forename: Nathalie
authors.initials: N
authors.lastname: Bleyzac
authors.forename: Sylvain
authors.initials: S
authors.lastname: Goutelle
mesh_terms: D061605:Administration, Intravenous; D000293:Adolescent; D000465:Algorithms; D018906:Antineoplastic Agents, Alkylating / Q000008:administration & dosage* / Q000493:pharmacokinetics; D019540:Area Under Curve; D001499:Bayes Theorem; D015982:Bias; D002066:Busulfan / Q000008:administration & dosage* / Q000493:pharmacokinetics; D002648:Child; D002675:Child, Preschool; D004305:Dose-Response Relationship, Drug; D006801:Humans; D007223:Infant; D008954:Models, Biological; D012984:Software; D055815:Young Adult
chemical_list: D018906:Antineoplastic Agents, Alkylating; D002066:Busulfan
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