Li Zi-Wei, Peng Feng-Hua, Yan Miao, Liang Wu, Liu Xiao-Lei, Wu Yan-Qin, Lin Xiao-Bin, Tan Sheng-Lan, Wang Feng, Xu Ping, Fang Ping-Fei, Liu Yi-Ping, Xiang Da-Xiong, Zhang Bi-Kui
*Department of Pharmacy, the Second Xiangya Hospital, Central South University, Changsha; †Department of Pharmacy, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai; ‡Department of Urological Organ Transplantation, the Second Xiangya Hospital of Central South University, Changsha; §Beijing Dryas Pharma-Tech Co. Ltd, Beijing, China; and ¶Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH.
Ther Drug Monit. 2017 Aug;39(4):422-428. doi: 10.1097/FTD.0000000000000425.
Invasive fungal infection (IFI) is one of the leading causes of early death after renal transplantation. Voriconazole (VRC) is the first-line drug of IFI. Because of the large inter- and intraindividual variability in VRC plasma concentrations and the narrow therapeutic window for treating patients with IFIs, it is crucial to study the factors which could influence pharmacokinetic variability. We performed a population pharmacokinetics (PPK) study of VRC for personalized medicine.
A total of 125 trough concentrations (Cmin) from 56 patients were evaluated, retrospectively. Nonlinear mixed effect model was used to describe a PPK model that was internally validated by bootstrap method. Potential covariates included demographic characteristics, physiological and pathological data, concomitant medications, and CYP2C19 genotype.
A 1-compartment model with first-order absorption and elimination was fit to characterize the VRC pharmacokinetics in renal transplant recipients (RTRs). Aspartate aminotransferase (AST) had a significant influence on clearance (CL) while CYP2C19 genotype had a major impact on the volume of distribution (V). The parameters of CL and V were 4.76 L/h and 22.47 L, respectively. The final model was V (L) = 22.47 × [1 + 2.21 × (EM = 1)] × [1 + 4.67 × (IM = 1)] × [1 + 3.30 × (PM = 1)] × exp (0.96); CL (L/h) = 4.76 × (AST/33)^(-0.23) × exp (0.14). VRC Cmin in intermediate metabolizers was significantly higher than in extensive metabolizers.
Liver function and CYP2C19 polymorphism are major determinants of VRC pharmacokinetic variability in RTRs. Genotypes and clinical biomarkers can determine the initial scheme. Subsequently, therapeutic drug monitoring can optimize clinical efficacy and minimize toxicity. Hence, this is a feasible way to facilitate personalized medicine in RTRs. In addition, it is the first report about PPK of VRC in RTRs.
侵袭性真菌感染(IFI)是肾移植术后早期死亡的主要原因之一。伏立康唑(VRC)是IFI的一线治疗药物。由于VRC血药浓度存在较大的个体间和个体内差异,且治疗IFI患者的治疗窗较窄,因此研究影响药代动力学变异性的因素至关重要。我们开展了一项VRC群体药代动力学(PPK)研究以实现个体化治疗。
回顾性评估了56例患者的125个谷浓度(Cmin)。采用非线性混合效应模型描述PPK模型,并通过自抽样法进行内部验证。潜在的协变量包括人口统计学特征、生理和病理数据、合并用药以及CYP2C19基因型。
采用具有一级吸收和消除的一室模型来描述肾移植受者(RTRs)的VRC药代动力学特征。天冬氨酸转氨酶(AST)对清除率(CL)有显著影响,而CYP2C19基因型对分布容积(V)有重大影响。CL和V的参数分别为4.76 L/h和22.47 L。最终模型为V(L) = 22.47 × [1 + 2.21 × (EM = 1)] × [1 + 4.67 × (IM = 1)] × [1 + 3.30 × (PM = 1)] × exp(0.96);CL(L/h) = 4.76 × (AST/33)^(-0.23) × exp(0.14)。中间代谢型患者的VRC Cmin显著高于广泛代谢型患者。
肝功能和CYP2C19基因多态性是RTRs中VRC药代动力学变异性的主要决定因素。基因型和临床生物标志物可确定初始方案。随后,治疗药物监测可优化临床疗效并将毒性降至最低。因此,这是促进RTRs个体化治疗的一种可行方法。此外,这是关于RTRs中VRC的PPK的首次报道。