Prediction of Intravenous Busulfan Clearance by Endogenous Plasma Biomarkers Using Global Pharmacometabolomics

Abstract

Introduction: High-dose busulfan (busulfan) is an integral part of the majority of hematopoietic cell transplantation conditioning regimens. Intravenous (IV) busulfan doses are personalized using pharmacokinetics (PK)-based dosing where the patient's IV busulfan clearance is calculated after the first dose and is used to personalize subsequent doses to a target plasma exposure. PK-guided dosing has improved patient outcomes and is clinically accepted but highly resource intensive.

Objective: We sought to discover endogenous plasma biomarkers predictive of IV busulfan clearance using a global pharmacometabolomics-based approach.

Methods: Using LC-QTOF, we analyzed 59 (discovery) and 88 (validation) plasma samples obtained before IV busulfan administration.

Results: In the discovery dataset, we evaluated the association of the relative abundance of 1885 ions with IV busulfan clearance and found 21 ions that were associated with IV busulfan clearance tertiles (r² ≥ 0.3). Identified compounds were deoxycholic acid and/or chenodeoxycholic acid, and linoleic acid. We used these 21 ions to develop a parsimonious seven-ion linear predictive model that accurately predicted IV busulfan clearance in 93% (discovery) and 78% (validation) of samples.

Conclusion: IV busulfan clearance was significantly correlated with the relative abundance of 21 ions, seven of which were included in a predictive model that accurately predicted IV busulfan clearance in the majority of the validation samples. These results reinforce the potential of pharmacometabolomics as a critical tool in personalized medicine, with the potential to improve the personalized dosing of drugs with a narrow therapeutic index such as busulfan.

Keywords: biomarkers; busulfan; hematopoietic cell transplantation; personalized medicine; pharmacokinetics; pharmacometabolomics.

Fig. 1

IV busulfan clearance is shown in tertiles for the discovery and validation datasets. Open circles – slow clearance tertile, “X” symbols – moderate clearance tertile, black triangles – rapid clearance tertile. Horizontal lines represent the mean clearance for that group.

Fig. 2

Linear regressions of discovery dataset ion abundance with IV busulfan clearance of the selected 21 ions with r² = 0.3 and monotonic change by IV busulfan clearance tertile. Open circles – slow clearance tertile, “X” symbols – moderate clearance tertile, black triangles – rapid clearance tertile. Each ion is identified by the mass-to-charge ratio (m/z) and retention time (RT in min).

Fig. 3

The performance of the seven-ion predictive model to estimate IV busulfan clearance in the discovery and validation datasets. The middle solid line represents the line of unity, and the outer dotted lines represent 80 and 125% of the observed IV busulfan clearance. Observed clearance is IV busulfan clearance (ml/min/kg NFM) estimated using noncompartmental analysis. Predicted clearance is IV busulfan clearance (ml/min/kg of NFM) estimated using the seven-ion predictive model. Open circles – slow clearance tertile, “X” symbols – moderate clearance tertile, black triangles – rapid clearance tertile.