Niioka Takenori, Uno Tsukasa, Yasui-Furukori Norio, Shimizu Mikiko, Sugawara Kazunobu, Tateishi Tomonori
Department of Pharmacy, Hirosaki University Hospital, Hirosaki, Japan.
Eur J Clin Pharmacol. 2006 Oct;62(10):855-61. doi: 10.1007/s00228-006-0184-1. Epub 2006 Aug 17.
The purpose of this study is to evaluate whether a simple formula using limited blood samples can predict the area under the plasma rabeprazole concentration-time curve (AUC) in co-administration with CYP inhibitors.
A randomized double-blind placebo-controlled crossover study design in three phases was conducted at intervals of 2 weeks. Twenty-one healthy Japanese volunteers, including three CYP2C19 genotype groups, took a single oral 20-mg dose of rabeprazole after three 6-day pretreatments, i.e., clarithromycin 800 mg/day, fluvoxamine 50 mg/day, and placebo. Prediction formulas of the AUC were derived from pharmacokinetics data of 21 subjects in three phases using multiple linear regression analysis. Ten blood samples were collected over 24 h to calculate AUC. Plasma concentrations of rabeprazole was measured by an HPLC-assay (l.l.q.=1 ng/ml).
The AUC was based on all the data sets (n=63). The linear regression using two points (C3 and C6) could predict AUC(0-infinity) precisely, irrespective of CYP2C19 genotypes and CYP inhibitors (AUC(0-infinity)=1.39xC3+7.17xC6+344.14, r (2)=0.825, p<0.001).
The present study demonstrated that the AUC of rabeprazole can be estimated by the simple formula using two-point concentrations. This formula can be more accurate for the prediction of AUC estimation than that reflected by CYP2C19 genotypes without any determination, even if there are significant differences for the CYP2C19 genotypes. Therefore, this prediction formula might be useful to evaluate whether CYP2C19 genotypes really reflects the curative effect of rabeprazole.
本研究旨在评估一个使用有限血样的简单公式能否预测雷贝拉唑与细胞色素P450（CYP）抑制剂合用时血浆药物浓度-时间曲线下面积（AUC）。
采用随机双盲安慰剂对照交叉研究设计，分三个阶段进行，间隔2周。21名健康日本志愿者，包括三个CYP2C19基因型组，在经过三个为期6天的预处理（即克拉霉素800mg/天、氟伏沙明50mg/天和安慰剂）后，单次口服20mg雷贝拉唑。使用多元线性回归分析，从三个阶段21名受试者的药代动力学数据中得出AUC的预测公式。在24小时内采集10份血样以计算AUC。采用高效液相色谱法测定雷贝拉唑血浆浓度（最低定量限=1ng/ml）。
AUC基于所有数据集（n=63）。使用两个时间点（C3和C6）的线性回归能够精确预测AUC(0-∞)，无论CYP2C19基因型和CYP抑制剂情况如何（AUC(0-∞)=1.39×C3+7.17×C6+344.14，r(2)=0.825，p<0.001）。
本研究表明，雷贝拉唑的AUC可通过使用两点浓度的简单公式进行估算。该公式在预测AUC估算方面比未进行任何测定的CYP2C19基因型所反映的情况更准确，即使CYP2C19基因型存在显著差异。因此，该预测公式可能有助于评估CYP2C19基因型是否真的反映雷贝拉唑的疗效。
