Optimizing nanomedicine pharmacokinetics using physiologically based pharmacokinetics modelling

药代动力学 纳米医学 基于生理学的药代动力学模型 药理学 计算机科学 医学 计算生物学 生物 纳米技术 材料科学 纳米颗粒
作者
Darren Moss,Marco Siccardi
出处
期刊:British Journal of Pharmacology [Wiley]
卷期号:171 (17): 3963-3979 被引量:103
标识
DOI:10.1111/bph.12604
摘要

The delivery of therapeutic agents is characterized by numerous challenges including poor absorption, low penetration in target tissues and non-specific dissemination in organs, leading to toxicity or poor drug exposure. Several nanomedicine strategies have emerged as an advanced approach to enhance drug delivery and improve the treatment of several diseases. Numerous processes mediate the pharmacokinetics of nanoformulations, with the absorption, distribution, metabolism and elimination (ADME) being poorly understood and often differing substantially from traditional formulations. Understanding how nanoformulation composition and physicochemical properties influence drug distribution in the human body is of central importance when developing future treatment strategies. A helpful pharmacological tool to simulate the distribution of nanoformulations is represented by physiologically based pharmacokinetics (PBPK) modelling, which integrates system data describing a population of interest with drug/nanoparticle in vitro data through a mathematical description of ADME. The application of PBPK models for nanomedicine is in its infancy and characterized by several challenges. The integration of property-distribution relationships in PBPK models may benefit nanomedicine research, giving opportunities for innovative development of nanotechnologies. PBPK modelling has the potential to improve our understanding of the mechanisms underpinning nanoformulation disposition and allow for more rapid and accurate determination of their kinetics. This review provides an overview of the current knowledge of nanomedicine distribution and the use of PBPK modelling in the characterization of nanoformulations with optimal pharmacokinetics.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
yznfly应助认真哈密瓜采纳,获得30
1秒前
yznfly应助认真哈密瓜采纳,获得30
1秒前
王志霞发布了新的文献求助10
2秒前
2秒前
3秒前
安静的雨完成签到,获得积分10
3秒前
shiyuhangsyh发布了新的文献求助10
5秒前
易酰水烊酸完成签到,获得积分10
5秒前
刘科发布了新的文献求助10
6秒前
万能图书馆应助幽默白易采纳,获得10
6秒前
HHHSean完成签到,获得积分10
6秒前
CR7应助Foldog采纳,获得20
6秒前
Yuri发布了新的文献求助10
7秒前
7秒前
8秒前
小二郎应助xmm采纳,获得10
8秒前
医者发布了新的文献求助10
8秒前
滕擎完成签到,获得积分10
8秒前
9秒前
10秒前
搜集达人应助鲜艳的手链采纳,获得10
10秒前
11秒前
昏睡的蟠桃应助LaTeXer采纳,获得100
11秒前
肉肉完成签到,获得积分20
11秒前
12秒前
小醒发布了新的文献求助10
12秒前
vvvv发布了新的文献求助10
13秒前
Zz发布了新的文献求助10
13秒前
奇异物质发布了新的文献求助10
14秒前
14秒前
柯科研完成签到,获得积分10
14秒前
大方凡灵完成签到 ,获得积分10
14秒前
14秒前
15秒前
香蕉觅云应助yang采纳,获得10
16秒前
塔菲尔完成签到 ,获得积分10
18秒前
鸭梨山大发布了新的文献求助10
19秒前
QL发布了新的文献求助10
19秒前
香蕉觅云应助奇异物质采纳,获得10
19秒前
高分求助中
The Mother of All Tableaux Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 2400
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Cognitive Neuroscience: The Biology of the Mind (Sixth Edition) 1000
Optimal Transport: A Comprehensive Introduction to Modeling, Analysis, Simulation, Applications 800
Official Methods of Analysis of AOAC INTERNATIONAL 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3958968
求助须知:如何正确求助?哪些是违规求助? 3505216
关于积分的说明 11123184
捐赠科研通 3236828
什么是DOI,文献DOI怎么找? 1788949
邀请新用户注册赠送积分活动 871455
科研通“疑难数据库(出版商)”最低求助积分说明 802794