Prediction of Busulfan Clearance by Predose Plasma Metabolomic Profiling

Abstract

Study HighlightsWHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?; Busulfan area under the plasma concentration-time curve (AUC) is associated with various clinical outcomes, but ~ 25% of patients achieve their target AUC with current dosing methods. Although pharmacokinetic (PK)-guided busulfan dosing reaches the target AUC in the majority of patients, it is resource-intensive and timeintensive. Thus, alternative approaches to estimate busulfan clearance are needed to achieve the target AUC with the first dose.

Could Metabolomics Be the Key to Unlocking Precision Dosing in the Clinic?

“…In this issue McCune et al 1 . ask whether the metabolic products of proteins can predict busulfan clearance.…”

“…In their report on the results of a prospective study collecting samples in pre-hematopoietic stem cell transplant (HCT) recipients, McCune et al 1 find a biomarker panel associating endogenous metabolomic compounds with busulfan clearance (Figure 1). Metabolome-guided predictive performance out-did a pretransplant test dose or personalizing based on genotype.…”

“…In this issue McCune et al 1 ask whether the metabolic products of proteins can predict busulfan clearance. To understand how the authors went about this, readers may have two questions that could be considered "black box" elements in their work.…”

“…Furthermore different centers use different assays, sampling schedules, and PK parameter estimation methods, with attempts at standardization only recently being made. 6 McCune et al 1 used a prior PK model to estimate a maximum a posteriori probability of individual clearance values from a drug exhibiting two compartment kinetics with rich sampling (i.e., more samples than model parameters). The prior model employs the rather odd approach of using fat-free mass, which itself has to be predicted from a model, as a covariate.…”

“…While the dependent variable, clearance, is relatively certain then, the second question surrounds the covariates related to the metabolomic analysis. The methods presented by McCune et al 1 are somewhat uncertain with a commercial assay used to screen for 841 compounds, the identity of which were not reported, and bioinformatics undertaken with proprietary software. Nor were clear details given on how the targeted metabolomic signatures were treated as quantitative measures with the meaning of beta coefficients in Tables 2 and 3 not clearly defined.…”