Physiologically Based Pharmacokinetic Modeling of Oxycodone in Children to Support Pediatric Dosing Optimization

基于生理学的药代动力学模型 羟考酮 药代动力学 加药 最大值 医学 药理学 类阿片 药效学 麻醉 内科学 受体
作者
Liang Zheng,Miao Xu,Shiwei Tang,Haoxin Song,Xuehua Jiang,Ling Wang
出处
期刊:Pharmaceutical Research [Springer Science+Business Media]
卷期号:36 (12) 被引量:16
标识
DOI:10.1007/s11095-019-2708-2
摘要

Physiologically-based pharmacokinetic (PBPK) modeling offers a unique modality to predict age-specific pharmacokinetics. The objective of this study was to assess the ability of PBPK model to predict plasma exposure of oxycodone, a widely used opioid for pain management, in adults and children. A full PBPK model of oxycodone following intravenous and oral administration was developed using a ‘bottom-up’ and ‘top-down’ combined strategy. The model was then extrapolated to pediatrics through a reasonable scaling method. The adult and pediatric model was evaluated using data from 17 clinical PK studies by testing predicted/observed goodness of fit. The mean fold error for PK parameters was calculated. Finally, we used the validated PBPK model to visualize adult-children dose conversion for oxycodone. The developed PBPK model successfully predicted the oxycodone disposition in adults, wherein the predicted versus observed AUC, Cmax, and tmax were within 0.90 to 1.20-fold difference. After scaling anatomy/physiology, protein binding, and clearance, the model showed satisfactory prediction performance for pediatric populations as predicted AUC were within the 1.50-fold range of the observed values. According to the application of PBPK model, we found that different intravenous doses should be given in children of different ages compared to a standard 0.1 mg/kg in adults, while a progressive increasing dose with age growth following oral administration is recommended for children. The current example provides the opportunity for using the PBPK model to guide dose adjustment of oxycodone in the design of future pediatric clinical studies.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
刚刚
刚刚
刚刚
刚刚
刚刚
刚刚
刚刚
美满的仙人掌关注了科研通微信公众号
1秒前
mm发布了新的文献求助10
1秒前
1秒前
陈尧发布了新的文献求助10
1秒前
好好好发布了新的文献求助10
1秒前
molihuakai应助jewel9采纳,获得10
1秒前
李妍庆发布了新的文献求助10
2秒前
静秋发布了新的文献求助30
2秒前
Airy完成签到,获得积分0
2秒前
123完成签到,获得积分10
2秒前
2秒前
3秒前
斯文败类应助xuwen采纳,获得10
3秒前
since发布了新的文献求助10
3秒前
3秒前
4秒前
喜羊羊七号完成签到,获得积分10
4秒前
4秒前
阔达随阴发布了新的文献求助10
4秒前
4秒前
JamesPei应助殷勤的凡白采纳,获得10
5秒前
5秒前
molihuakai应助fragile采纳,获得10
5秒前
在水一方应助明亮的初阳采纳,获得10
5秒前
万能图书馆应助玥来玥好采纳,获得10
6秒前
潇洒的惋清应助活泼灵枫采纳,获得10
7秒前
非泽发布了新的文献求助10
7秒前
7秒前
桃子完成签到,获得积分10
7秒前
frost完成签到,获得积分10
7秒前
杜嘟嘟发布了新的文献求助10
7秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
晶种分解过程与铝酸钠溶液混合强度关系的探讨 8888
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
Leading Academic-Practice Partnerships in Nursing and Healthcare: A Paradigm for Change 800
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6422286
求助须知:如何正确求助?哪些是违规求助? 8241174
关于积分的说明 17516843
捐赠科研通 5476343
什么是DOI,文献DOI怎么找? 2892815
邀请新用户注册赠送积分活动 1869266
关于科研通互助平台的介绍 1706703