Mathematical Modelling of Drug Transport and Uptake in a Realistic Model of Solid Tumour

药品 药物输送 药代动力学 药效学 细胞内 药理学 丸(消化) 细胞外 抗癌药 阿霉素 靶向给药 细胞外基质 医学 化学 癌症研究 化疗 内科学 生物化学 有机化学
作者
Wenbo Zhan,Wladyslaw Gedroyc,Xiao Yun Xu
出处
期刊:Protein and Peptide Letters [Bentham Science Publishers]
卷期号:21 (11): 1146-1156 被引量:20
标识
DOI:10.2174/0929866521666140807115629
摘要

Effective delivery of therapeutic agents to tumour cells is essential to the success of most cancer treatment therapies except for surgery. The transport of drug in solid tumours involves multiple biophysical and biochemical proc- esses which are strongly dependent on the physicochemical properties of the drug and biological properties of the tumour. Owing to the complexities involved, mathematical models are playing an increasingly important role in identifying the factors leading to inadequate drug delivery to tumours. In this study, a computational model is developed which incorpo- rates real tumour geometry reconstructed from magnetic resonance images, drug transport through the tumour vasculature and interstitium, as well as drug uptake by tumour cells. The effectiveness of anticancer therapy is evaluated based on the percentage of survival tumour cells by directly solving the pharmacodynamics equation using predicted intracellular drug concentrations. Computational simulations are performed for the delivery of doxorubicin through different administration modes and doses. Our predictions show that continuous infusion is far more effective than bolus injection in maintaining high levels of intracellular drug concentration, thereby increasing drug uptake by tumour cells. On the other hand, bolus injection leads to higher extracellular concentration in both tumour and normal tissues compared to continuous infusion, which is undesirable as high drug concentration in normal tissues may increase the risk of associated side effects. Keywords: Anticancer therapy, computational model, drug transport, MR image-based model, prostate tumour.

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
一朵小鲜花儿完成签到,获得积分10
1秒前
科研通AI2S应助孟陬二四采纳,获得10
1秒前
jenningseastera完成签到,获得积分0
1秒前
骑猪兜风完成签到 ,获得积分10
2秒前
ZZZ完成签到,获得积分10
2秒前
小小完成签到,获得积分10
4秒前
miao3718完成签到 ,获得积分10
4秒前
超级的慕山完成签到,获得积分10
4秒前
Niuniu完成签到,获得积分10
4秒前
林勇德完成签到,获得积分10
5秒前
巴乔完成签到,获得积分10
5秒前
kathy完成签到,获得积分10
6秒前
6秒前
MRshenyy完成签到,获得积分10
7秒前
积极的随阴完成签到,获得积分10
7秒前
小满完成签到,获得积分10
8秒前
猕猴桃完成签到 ,获得积分10
8秒前
9秒前
Wsh完成签到,获得积分10
9秒前
vivi完成签到 ,获得积分10
9秒前
Yanping完成签到,获得积分10
10秒前
小郭的华南虎完成签到,获得积分10
10秒前
11秒前
蓝天发布了新的文献求助10
12秒前
黄天完成签到 ,获得积分10
12秒前
laoleigang完成签到,获得积分10
12秒前
甜美香之完成签到 ,获得积分10
12秒前
123asd发布了新的文献求助10
13秒前
Yjweei完成签到,获得积分10
14秒前
斜阳完成签到 ,获得积分10
14秒前
小小怪酋长完成签到,获得积分10
14秒前
tao完成签到,获得积分10
15秒前
出水芙蓉完成签到,获得积分10
16秒前
无辜的银耳汤完成签到,获得积分10
17秒前
淡淡士晋完成签到,获得积分20
17秒前
cgliuhx完成签到,获得积分10
17秒前
sun完成签到,获得积分10
17秒前
潆星完成签到,获得积分10
18秒前
乐乐应助123asd采纳,获得10
19秒前
活泼的蘑菇完成签到 ,获得积分10
20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
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2500
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 600
Bounds for Statistical Estimation in Semiparametric Models 500
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 6498212
求助须知:如何正确求助?哪些是违规求助? 8294177
关于积分的说明 17697032
捐赠科研通 5594166
什么是DOI,文献DOI怎么找? 2917600
邀请新用户注册赠送积分活动 1894551
关于科研通互助平台的介绍 1755161