Kong Daming, Roberts Jason A, Lipman Jeffrey, Taccone Fabio Silvio, Cohen-Wolkowiez Michael, Sime Fekade B, Tsai Danny, De Cock Pieter A J G, Jaruratanasirikul Sutep, Dhaese Sofie A M, Udy Andrew A, Felton Timothy W, Michelet Robin, Thibault Céline, Koomen Jeroen V, Eleveld Douglas J, Struys Michel M R F, De Waele Jan J, Colin Pieter J
Department of Anesthesiology, University of Groningen, University Medical Center Groningen, P. O. Box 30001, 9700 RB, Groningen, The Netherlands.
University of Queensland Centre for Clinical Research, Faculty of Medicine, University of Queensland, Herston, Brisbane, QLD, Australia.
Clin Pharmacokinet. 2025 Jan;64(1):107-126. doi: 10.1007/s40262-024-01460-6. Epub 2024 Dec 25.
The pharmacokinetics (PK) of piperacillin/tazobactam (PIP/TAZ) is highly variable across different patient populations and there are controversies regarding non-linear elimination as well as the fraction unbound of PIP (f). This has led to a plethora of subgroup-specific models, increasing the risk of misusing published models when optimising dosing regimens. In this study, we aimed to develop a single model to simultaneously describe the PK of PIP/TAZ in diverse patient populations and evaluate the current dosing recommendations by predicting the PK/pharmacodynamics (PD) target attainment throughout life.
Population PK models were separately built for PIP and TAZ based on data from 13 studies in various patient populations. In the development of those single-drug models, postnatal age (PNA), postmenstrual age (PMA), total body weight (TBW), height, and serum creatinine (SCR) were tested as covariates. Subsequently, a combined population PK model was established and the correlations between the PK of PIP and TAZ were tested. Monte Carlo simulations were performed based on the final combined model to evaluate the current dosing recommendations.
The final combined model for PIP/TAZ consisted of four compartments (two for each drug), with covariates including TBW, PMA, and SCR. For a 70-kg, 35-year-old patient with SCR of 0.83 mg L, the PIP values for V, CL, V and Q were 10.4 L, 10.6 L h, 11.6 L and 15.2 L h, respectively, and the TAZ values were 10.5 L, 9.58 L h, 13.7 L and 16.8 L h, respectively. The CL for both drugs show maturation in early life, reaching 50% at 54.2 weeks PMA. With advancing age, CL of TAZ declines to 50% at 61.6 years PMA, whereas CL of PIP declines more slowly, reaching 50% at 89.1 years PMA. The f was estimated as 64.5% and non-linear elimination was not supported by our data. The simulation results indicated considerable differences in PK/PD target attainment for different patient populations under current recommended dosing regimens.
We developed a combined population PK model for PIP/TAZ across a broad range of patients covering the extremes of patient characteristics. This model can be used as a robust a priori model for Bayesian forecasting to achieve individualised dosing. The simulations indicate that adjustments based on the allometric theory as well as maturation and decline of CL of PIP may help the current dosing recommendations to provide consistent target attainment across patient populations.
哌拉西林/他唑巴坦（PIP/TAZ）在不同患者群体中的药代动力学（PK）具有高度变异性，关于其非线性消除以及PIP的游离分数（f）存在争议。这导致了大量特定亚组模型的出现，增加了在优化给药方案时误用已发表模型的风险。在本研究中，我们旨在开发一个单一模型，以同时描述PIP/TAZ在不同患者群体中的PK，并通过预测一生的PK/药效学（PD）目标达成情况来评估当前的给药建议。
基于来自13项针对不同患者群体研究的数据，分别构建PIP和TAZ的群体PK模型。在这些单药模型的开发过程中，将出生后年龄（PNA）、月经后年龄（PMA）、总体重（TBW）、身高和血清肌酐（SCR）作为协变量进行测试。随后，建立了一个联合群体PK模型，并测试了PIP和TAZ的PK之间的相关性。基于最终的联合模型进行蒙特卡洛模拟，以评估当前的给药建议。
PIP/TAZ的最终联合模型由四个房室组成（每种药物两个），协变量包括TBW、PMA和SCR。对于一名体重70kg、35岁、SCR为0.83mg/L的患者，PIP的V、CL、V和Q值分别为10.4L、10.6L/h、11.6L和15.2L/h，TAZ的值分别为10.5L、9.58L/h、13.7L和16.8L/h。两种药物的CL在生命早期均显示成熟，在PMA为54.2周时达到50%。随着年龄增长，TAZ的CL在PMA为61.6岁时降至50%，而PIP的CL下降较慢，在PMA为89.1岁时降至50%。f估计为64.5%，且我们的数据不支持非线性消除。模拟结果表明，在当前推荐给药方案下，不同患者群体的PK/PD目标达成情况存在显著差异。
我们针对涵盖患者特征极端情况的广泛患者群体开发了一个PIP/TAZ联合群体PK模型。该模型可作为一个强大的先验模型用于贝叶斯预测，以实现个体化给药。模拟表明，基于异速生长理论以及PIP的CL成熟和下降进行调整，可能有助于当前的给药建议在不同患者群体中提供一致的目标达成情况。
