Physiologically Based Pharmacokinetic Modeling of Vancomycin in Critically Ill Neonates: Assessing the Impact of Pathophysiological Changes

Weiwei Shuai MSc, Jing Cao MSc, Miao Qian MMed, Zhe Tang MSc
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Abstract

Dosing vancomycin for critically ill neonates is challenging owing to substantial alterations in pharmacokinetics (PKs) caused by variability in physiology, disease, and clinical interventions. Therefore, an adequate PK model is needed to characterize these pathophysiological changes. The intent of this study was to develop a physiologically based pharmacokinetic (PBPK) model that reflects vancomycin PK and pathophysiological changes in neonates under intensive care. PK-sim software was used for PBPK modeling. An adult model (model 0) was established and verified using PK profiles from previous studies. A neonatal model (model 1) was then extrapolated from model 0 by scaling age-dependent parameters. Another neonatal model (model 2) was developed based not only on scaled age-dependent parameters but also on quantitative information on pathophysiological changes obtained via a comprehensive literature search. The predictive performances of models 1 and 2 were evaluated using a retrospectively collected dataset from neonates under intensive care (chictr.org.cn, ChiCTR1900027919), comprising 65 neonates and 92 vancomycin serum concentrations. Integrating literature-based parameter changes related to hypoalbuminemia, small-for-gestational-age, and co-medication, model 2 offered more optimized precision than model 1, as shown by a decrease in the overall mean absolute percentage error (50.6% for model 1; 37.8% for model 2). In conclusion, incorporating literature-based pathophysiological changes effectively improved PBPK modeling for critically ill neonates. Furthermore, this model allows for dosing optimization before serum concentration measurements can be obtained in clinical practice.

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重症新生儿万古霉素的生理学药代动力学模型:评估病理生理变化的影响。
由于生理、疾病和临床干预的变化导致药代动力学(PKs)发生重大改变,因此为重症新生儿服用万古霉素具有挑战性。因此,需要一个适当的 PK 模型来描述这些病理生理学变化。本研究的目的是建立一个基于生理学的药代动力学(PBPK)模型,以反映重症监护下新生儿的万古霉素 PK 和病理生理变化。PBPK 模型使用了 PK-sim 软件。利用以往研究的 PK 资料建立并验证了成人模型(模型 0)。然后,通过缩放与年龄相关的参数,从模型 0 推断出新生儿模型(模型 1)。另一个新生儿模型(模型 2)的建立不仅基于与年龄相关的比例参数,还基于通过全面文献检索获得的有关病理生理变化的定量信息。利用回顾性收集的重症监护新生儿数据集(chictr.org.cn,ChiCTR1900027919)评估了模型 1 和模型 2 的预测性能,该数据集包括 65 名新生儿和 92 个万古霉素血清浓度。模型 2 整合了与低白蛋白血症、小于妊娠年龄和联合用药相关的文献参数变化,比模型 1 提供了更高的优化精度,具体表现为总体平均绝对百分比误差的降低(模型 1 为 50.6%;模型 2 为 37.8%)。总之,纳入基于文献的病理生理学变化可有效改善重症新生儿的 PBPK 模型。此外,该模型还能在临床实践中获得血清浓度测量值之前对剂量进行优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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