Jang Ji-Hun, Jeong Seung-Hyun, Lee Yong-Bok
College of Pharmacy, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea.
College of Pharmacy, Sunchon National University, 255 Jungang-ro, Suncheon-si 57922, Republic of Korea.
Pharmaceuticals (Basel). 2023 Jan 22;16(2):161. doi: 10.3390/ph16020161.
Zaltoprofen is a drug used for various pain and inflammatory diseases. Scientific and quantitative dosage regimen studies regarding its clinical application are scarce. This study aimed to discover effective covariates related to interindividual pharmacokinetic variability through population pharmacokinetic modeling for zaltoprofen and to explore dosage regimens. The bioequivalence results of healthy Korean males, biochemical analysis, and CYP2C9 genotyping information were utilized in modeling. The established model has been sufficiently verified through a bootstrap, goodness-of-fit, visual predictive check, and normalized prediction distribution error. External data sets derived from the literature were used for further model validation. The final model could be used to verify the dosage regimen through multiple exposure simulations according to the numerical change of the selected covariates. Zaltoprofen pharmacokinetics could be explained by a two-compartment with a first-order absorption model. Creatinine clearance (CrCL) and albumin were identified as effective covariates related to interindividual zaltoprofen pharmacokinetic variability, and they had positive and negative correlations with clearance (CL/F), respectively. The differences in pharmacokinetics between individuals according to CYP2C9 genetic polymorphisms (*1/*1 and *1/*3) were not significant or valid covariates. The model simulation confirmed that zaltoprofen pharmacokinetics could significantly differ as the CrCL and albumin levels changed within the normal range. Steady-state plasma exposure to zaltoprofen was significantly reduced in the group with CrCL and albumin levels of 130 mL/min and 3.5 g/dL, respectively, suggesting that dose adjustment may be necessary. This study is useful to guide precision medicine of zaltoprofen and provides scientific quantitative judgment data for its clinical applications.
扎托洛芬是一种用于治疗各种疼痛和炎症性疾病的药物。关于其临床应用的科学定量给药方案研究很少。本研究旨在通过扎托洛芬的群体药代动力学建模发现与个体间药代动力学变异性相关的有效协变量,并探索给药方案。在建模中使用了健康韩国男性的生物等效性结果、生化分析和CYP2C9基因分型信息。所建立的模型已通过自抽样法、拟合优度、可视化预测检验和标准化预测分布误差进行了充分验证。从文献中获取的外部数据集用于进一步的模型验证。最终模型可用于根据所选协变量的数值变化通过多次暴露模拟来验证给药方案。扎托洛芬的药代动力学可用具有一级吸收模型的二室模型来解释。肌酐清除率(CrCL)和白蛋白被确定为与个体间扎托洛芬药代动力学变异性相关的有效协变量,它们分别与清除率(CL/F)呈正相关和负相关。根据CYP2C9基因多态性(*1/1和1/*3)个体之间的药代动力学差异不显著或不是有效的协变量。模型模拟证实,随着CrCL和白蛋白水平在正常范围内变化,扎托洛芬的药代动力学可能会有显著差异。在CrCL和白蛋白水平分别为130 mL/min和3.5 g/dL的组中,扎托洛芬的稳态血浆暴露量显著降低,这表明可能需要调整剂量。本研究有助于指导扎托洛芬的精准医学,并为其临床应用提供科学的定量判断数据。