Abstract
Busulfan has high intra-individual variability and possible time-dependent changes in clearance, which complicates therapeutic drug monitoring (TDM), as first dose sampling may not predict the steady state concentrations. In this study, we aimed to use Bayesian pharmacokinetic parameters estimated from the first dose to predict the steady state AUC for busulfan. This observational study was conducted among pediatric patients at King Abdullah Specialist Children’s Hospital. From each patient, we collected six blood samples (2, 2.25, 2.5, 3, 4, and 6 h after the start of IV infusion of the first dose). A subset of patients were also sampled at the steady state. First, we modeled the data using only the first dose. The model was used to estimate the empirical Bayesian estimates of clearance for each individual patient, then we used the empirical Bayesian estimates of clearance to predict the AUC
0–tau
at steady state (i.e., predicted AUC
0–tau)
. Steady state AUC
0–tau
was also calculated for patients sampled at steady state using the trapezoidal method using raw time concentration data; this was considered the reference AUC
0–tau.
. Then, we compared the AUC
0–tau
predicted using the Bayesian approach with the reference AUC
0–tau
values. We calculated bias and precision to assess predictability. In total we had 33 patients sampled after first dose and at steady state. Using the Bayesian approach to predict the AUC
0–tau
, bias was −2.8% and precision was 33%. This indicates that first dose concentrations cannot accurately predict steady state busulfan concentrations; therefore, follow-up TDM may be required for optimal dosing.