Lin Yvonne S, Kerr Savannah J, Randolph Timothy, Shireman Laura M, Senn Tauri, McCune Jeannine S
Department of Pharmaceutics, University of Washington, Seattle, WA.
Fred Hutchinson Cancer Research Center, Seattle, WA.
Metabolomics. 2016 Oct;12(10). doi: 10.1007/s11306-016-1106-6. Epub 2016 Sep 15.
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.
We sought to discover endogenous plasma biomarkers predictive of IV busulfan clearance using a global pharmacometabolomics-based approach.
Using LC-QTOF, we analyzed 59 (discovery) and 88 (validation) plasma samples obtained before IV busulfan administration.
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 ≥ 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.
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.
大剂量白消安是大多数造血细胞移植预处理方案的重要组成部分。静脉注射白消安的剂量通过基于药代动力学(PK)的给药方式进行个体化设定,即先计算患者首次给药后的静脉白消安清除率,并用于将后续剂量调整至目标血浆暴露水平。PK 指导的给药方式改善了患者预后,且已被临床接受,但资源消耗极大。
我们试图采用基于全球药物代谢组学的方法,发现可预测静脉白消安清除率的内源性血浆生物标志物。
我们使用液相色谱-四极杆飞行时间质谱(LC-QTOF)分析了 59 份(发现阶段)和 88 份(验证阶段)静脉注射白消安前采集的血浆样本。
在发现数据集中,我们评估了 1885 种离子的相对丰度与静脉白消安清除率的相关性,发现 21 种离子与静脉白消安清除率三分位数相关(r≥0.3)。鉴定出的化合物为脱氧胆酸和/或鹅脱氧胆酸以及亚油酸。我们使用这 21 种离子建立了一个简洁的七离子线性预测模型,该模型在 93%(发现阶段)和 78%(验证阶段)的样本中准确预测了静脉白消安清除率。
静脉白消安清除率与 21 种离子的相对丰度显著相关,其中七种离子被纳入一个预测模型,该模型在大多数验证样本中准确预测了静脉白消安清除率。这些结果强化了药物代谢组学作为个性化医疗关键工具的潜力,有望改善白消安等治疗指数狭窄药物的个体化给药。