Development of a Population Pharmacokinetic Model of Busulfan in Children and Evaluation of Different Sampling Schedules for Precision Dosing

Abstract

We develop a population pharmacokinetic model to describe Busulfan pharmacokinetics in paediatric patients and investigate by simulations the impact of various sampling schedules on the calculation of AUC. Seventy-six children had 2 h infusions every 6 h. A two-compartment linear model was found to adequately describe the data. A lag-time was introduced to account for the delay of the administration of the drug through the infusion pump. The mean values of clearance, central volume of distribution, intercompartmental clearance, and peripheral volume of distribution were 10.7 L/h, 39.5 L, 4.68 L/h and 17.5 L, respectively, normalized for a Body Weight (BW) of 70 kg. BW was found to explain a portion of variability with an allometric relationship and fixed exponents of 0.75 on clearance parameters and 1 on volumes. Interindividual variability for clearance and volume of distribution was found to be 28% and 41%, respectively, and interoccasion variability for clearance was found to be 11%. Three sampling schedules were assessed by simulations for bias and imprecision to calculate AUC by a non-compartmental and a model-based method. The latter was found to be superior in all cases, while the non-compartmental was unbiased only in sampling up to 12 h corresponding to a once-daily dosing regimen.

Keywords: acute myelogenous leukemia; busulfan; hematopoietic stem cell transplantation; model-informed precision dosing; paediatric; pharmacometrics.

Figure 1

Diagnostic plots for the final PopPK model. Observed vs. population predicted plasma concentrations (A) and individual predicted plasma concentrations (B) plots (black and red lines represent the identity and cubic spline smooth lines, respectively). Conditional weighted residuals vs. population predicted plasma concentrations (C) and vs. TIME (D) (solid line y = 0, dashed lines y = 2 and y = −2). Normalized Prediction Distribution Error vs. population predicted plasma concentrations (E) and vs. Time (F).

Figure 2

pcVPC for the final model. Red lines are the 5, 50 and 95% prediction intervals. The shaded areas represent the 95% confidence interval for the estimation.

Figure 3

Bias and imprecision of the AUC calculated through the trapezoidal and the Bayesian approximation. Sampling times are as follows: Schedule 1: 2.5, 3, 4 and 6 h; Schedule 2: 2.5, 4 and 6 h; Schedule 3: 3, 6, 9 and 12 h.

Figure 4

Two representative simulated patients with 3 different approximations in the AUC calculations. Red line represents the true AUC, considering the true PK parameters obtained in the simulations; blue line represents the trapezoidal AUC, considering the simulated observations; green line represents the Bayesian AUC, considering the PK parameters obtained after the Bayesian approach.