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基于生理学的药代动力学模型预测健康志愿者和肾功能损害受试者的暴露差异:头孢他啶案例研究。

Physiologically based pharmacokinetic modelling to predict exposure differences in healthy volunteers and subjects with renal impairment: Ceftazidime case study.

机构信息

Quantitative Clinical Pharmacology, Early Clinical Development, IMED Biotech Unit, AstraZeneca, Boston, Massachusetts.

Mechanistic Safety and ADME Sciences, Drug Safety and Metabolism, IMED Biotech Unit, AstraZeneca, Cambridge, UK.

出版信息

Basic Clin Pharmacol Toxicol. 2019 Aug;125(2):100-107. doi: 10.1111/bcpt.13209. Epub 2019 Mar 28.

Abstract

Ceftazidime is a widely used β-lactam antibiotic and almost entirely excreted via glomerular filtration in kidney. The objective of this analysis was to assess the ability of physiologically based pharmacokinetic (PBPK) model to predict ceftazidime exposure in healthy volunteers and subjects with renal impairment. A full PBPK model of ceftazidime was developed using physiochemical properties and clinical data. The total clearance of 115 mL/min and renal clearance of 100 mL/min were obtained from ceftazidime package insert. Healthy and chronic kidney disease (CKD) populations were applied for sampling of virtual subjects. The established PBPK model predicted mean plasma AUC were 138.5 ± 19.6, 230.7 ± 22.2, 369.3 ± 53.1 and 561.8 ± 92.4 h µg/mL in healthy, mild, moderate and severe renal impairment subjects, respectively, after administration of 1 g ceftazidime intravenous bolus dose. The predicted values were in close agreement with the weighted mean of the five reported clinical studies. The exposure was slightly under predicted in subjects with severely impaired renal function, but still within 1.5-fold range. The concentration-time profiles of ceftazidime were also well captured in healthy volunteers and subjects with renal impairment. The developed PBPK model along with systems pharmacokinetics (PK) (renal impaired populations) well predicted the ceftazidime exposure. PBPK models verified with clinical study in healthy volunteers could be potentially applied to predict PK and recommend dose adjustment for CKD patients.

摘要

头孢他啶是一种广泛使用的β-内酰胺类抗生素,几乎完全通过肾脏肾小球滤过排泄。本分析的目的是评估生理基于药代动力学(PBPK)模型预测健康志愿者和肾功能损害患者头孢他啶暴露的能力。使用头孢他啶的生理化学性质和临床数据开发了完整的 PBPK 模型。头孢他啶说明书中获得的总清除率为 115 mL/min,肾清除率为 100 mL/min。健康和慢性肾脏病(CKD)人群被应用于虚拟受试者的采样。建立的 PBPK 模型预测健康、轻度、中度和重度肾功能损害受试者分别给予 1g 头孢他啶静脉推注后,平均血浆 AUC 为 138.5±19.6、230.7±22.2、369.3±53.1 和 561.8±92.4 hμg/mL。预测值与五项报告的临床研究的加权平均值非常吻合。肾功能严重受损的受试者的暴露量略有低估,但仍在 1.5 倍范围内。健康志愿者和肾功能损害受试者的头孢他啶浓度-时间曲线也得到了很好的捕捉。开发的 PBPK 模型与系统药代动力学(PK)(肾功能损害人群)一起很好地预测了头孢他啶的暴露量。在健康志愿者中经过临床研究验证的 PBPK 模型可以潜在地应用于预测 PK 并为 CKD 患者推荐剂量调整。

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