Prediction of intravenous busulfan clearance by endogenous plasma biomarkers using global pharmacometabolomics

• Published in: Metabolomics Vol. 12; no. 10; p. 1
• Main Authors: Lin, Yvonne S., Kerr, Savannah J., Randolph, Timothy, Shireman, Laura M., Senn, Tauri, McCune, Jeannine S.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.10.2016; Springer Nature B.V
• Subjects: Biochemistry; Biomedical and Life Sciences; Biomedicine; Cell Biology; Developmental Biology; Life Sciences; Molecular Medicine; Original Article; Recent advances in Pharmacometabolomics: enabling tools for precision medicine; Biomarkers; Hematopoietic cell transplantation; Busulfan; Pharmacometabolomics; Pharmacokinetics; Personalized medicine; busulfan; pharmacokinetics; pharmacometabolomics; hematopoietic cell transplantation; biomarkers; personalized medicine
• ISSN: 1573-3882; 1573-3890
• DOI: 10.1007/s11306-016-1106-6

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)-guided 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 (r 2  ≥ 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.