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针对特定代谢和肾脏排泄途径的虚拟中国儿科人群生理模型的开发。

Development of a Virtual Chinese Pediatric Population Physiological Model Targeting Specific Metabolism and Kidney Elimination Pathways.

作者信息

Yao Xueting, Liu Xuanlin, Tu Siqi, Li Xiaobei, Lei Zihan, Hou Zhe, Yu Zhiheng, Cui Cheng, Dong Zhongqi, Salem Farzaneh, Li Haiyan, Liu Dongyang

机构信息

Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.

School of Pharmaceutical Sciences, Tsinghua University, Beijing, China.

出版信息

Front Pharmacol. 2021 May 11;12:648697. doi: 10.3389/fphar.2021.648697. eCollection 2021.

Abstract

Physiologically based pharmacokinetic (PBPK) modeling and simulating may be a powerful tool in predicting drug behaviors in specific populations. It is a mathematical model that relates the pharmacokinetic (PK) profile of a compound with human anatomical characteristics, physiological characteristics, and biochemical parameters. Predictions using PBPK models offer a promising way to guide drug development and can be used to optimize clinical dosing regimens. However, PK data of new drugs in the pediatric population are too limited to guide clinical therapy, which may lead to frequent adverse events or insufficient efficacy for pediatric patients, particularly in neonates and infants. The objective of this study was to establish a virtual Chinese pediatric population based on the physiological parameters of Chinese children that could be utilized in PBPK models. A Chinese pediatric PBPK model was developed in Simcyp Simulator by collecting published Chinese pediatric physiological and anthropometric data to use as system parameters. This pediatric population model was then evaluated in the Chinese pediatric population by predicting the pharmacokinetic characteristics of four probe drugs: theophylline (major CYP1A2 substrate), fentanyl (major CYP3A4 substrate), vancomycin, and ceftazidime (renal-eliminated). The predicted maximum concentration (C), area under the curve of concentration-time (AUC), and clearance (CL) for theophylline (CYP1A2 metabolism pathway) and fentanyl (CYP3A4 metabolism pathway) were within two folds of the observed data. For drugs mainly eliminated by renal clearance (vancomycin and ceftazidime) in the Chinese pediatric population, the ratio of prediction to observation for major PK parameters was within a 2-fold error range. The model is a supplement to the previous Chinese population PBPK model. We anticipate the model to be a better representative of the pediatric Chinese population for drugs PK, offering greater clinical precision for medication given to the pediatric population, ultimately advancing clinical development of pediatric drugs. We can refine this model further by collecting more physiological parameters of Chinese children.

摘要

基于生理的药代动力学(PBPK)建模与模拟可能是预测特定人群药物行为的有力工具。它是一种数学模型,将化合物的药代动力学(PK)特征与人体解剖学特征、生理学特征和生化参数联系起来。使用PBPK模型进行预测为指导药物开发提供了一种有前景的方法,可用于优化临床给药方案。然而,儿科人群中新药的PK数据非常有限,无法指导临床治疗,这可能导致儿科患者频繁出现不良事件或疗效不足,尤其是新生儿和婴儿。本研究的目的是基于中国儿童的生理参数建立一个可用于PBPK模型的虚拟中国儿科人群。通过收集已发表的中国儿科生理和人体测量数据作为系统参数,在Simcyp模拟器中开发了一个中国儿科PBPK模型。然后,通过预测四种探针药物的药代动力学特征,在中国儿科人群中对该儿科人群模型进行评估:茶碱(主要CYP1A2底物)、芬太尼(主要CYP3A4底物)、万古霉素和头孢他啶(经肾消除)。茶碱(CYP A2代谢途径)和芬太尼(CYP3A4代谢途径)的预测最大浓度(C)、浓度-时间曲线下面积(AUC)和清除率(CL)在观察数据的两倍范围内。对于在中国儿科人群中主要通过肾清除消除的药物(万古霉素和头孢他啶),主要PK参数的预测值与观察值之比在2倍误差范围内。该模型是对先前中国人群PBPK模型的补充。我们预计该模型能更好地代表中国儿科人群的药物PK情况,为儿科人群给药提供更高的临床精度,最终推动儿科药物的临床开发。我们可以通过收集更多中国儿童的生理参数来进一步完善该模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8dea/8145459/f85590bc6dfa/fphar-12-648697-g001.jpg

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