Strategies and Recent Advances on Improving Efficient Antitumor of Lenvatinib Based on Nanoparticle Delivery System

伦瓦提尼 纳米技术 纳米医学 药物输送 纳米颗粒 光热治疗 材料科学 药理学 癌症 医学 癌症研究 甲状腺癌 内科学
作者
Haiqing Wang,Wentao Bo,Xielin Feng,Jinliang Zhang,Ge Li,Yan Chen
出处
期刊:International Journal of Nanomedicine [Dove Medical Press]
卷期号:Volume 19: 5581-5603 被引量:3
标识
DOI:10.2147/ijn.s460844
摘要

Lenvatinib (LVN) is a potentially effective multiple-targeted receptor tyrosine kinase inhibitor approved for treating hepatocellular carcinoma, metastatic renal cell carcinoma and thyroid cancer. Nonetheless, poor pharmacokinetic properties including poor water solubility and rapid metabolic, complex tumor microenvironment, and drug resistance have impeded its satisfactory therapeutic efficacy. This article comprehensively reviews the uses of nanotechnology in LVN to improve antitumor effects. With the characteristic of high modifiability and loading capacity of the nano-drug delivery system, an active targeting approach, controllable drug release, and biomimetic strategies have been devised to deliver LVN to target tumors in sequence, compensating for the lack of passive targeting. The existing applications and advances of LVN in improving therapeutic efficacy include improving longer-term efficiency, achieving higher efficiency, combination therapy, tracking and diagnosing application and reducing toxicity. Therefore, using multiple strategies combined with photothermal, photodynamic, and immunoregulatory therapies potentially overcomes multi-drug resistance, regulates unfavorable tumor microenvironment, and yields higher synergistic antitumor effects. In brief, the nano-LVN delivery system has brought light to the war against cancer while at the same time improving the antitumor effect. More intelligent and multifunctional nanoparticles should be investigated and further converted into clinical applications in the future.

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
Jasper应助斯瑞采纳,获得10
刚刚
1秒前
机智的衣发布了新的文献求助10
1秒前
喵喵完成签到,获得积分10
1秒前
2秒前
大力的灵雁应助自信晟睿采纳,获得70
2秒前
一只呆猫er完成签到,获得积分10
2秒前
Chiyuki发布了新的文献求助10
2秒前
3秒前
酷波er应助Chaga采纳,获得10
3秒前
feizao完成签到,获得积分10
4秒前
4秒前
4秒前
传奇3应助朱良宇采纳,获得10
4秒前
平淡晓博完成签到,获得积分10
4秒前
5秒前
专一的白发布了新的文献求助10
5秒前
科研通AI6.1应助嗨害采纳,获得10
5秒前
whhh关注了科研通微信公众号
5秒前
一一一发布了新的文献求助10
6秒前
6秒前
6秒前
6秒前
CodeCraft应助平淡晓博采纳,获得10
7秒前
Percy完成签到,获得积分10
8秒前
汉堡包应助专一的白采纳,获得10
9秒前
9秒前
小恩发布了新的文献求助10
9秒前
荷西发布了新的文献求助10
9秒前
10秒前
Anlong发布了新的文献求助10
11秒前
向阳发布了新的文献求助30
11秒前
李先生完成签到 ,获得积分10
11秒前
王一会发布了新的文献求助10
11秒前
黎敏发布了新的文献求助10
12秒前
ReginaLee发布了新的文献求助10
12秒前
12秒前
14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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Rheumatoid arthritis drugs market analysis North America, Europe, Asia, Rest of world (ROW)-US, UK, Germany, France, China-size and Forecast 2024-2028 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 6366041
求助须知:如何正确求助?哪些是违规求助? 8179983
关于积分的说明 17243873
捐赠科研通 5420779
什么是DOI,文献DOI怎么找? 2868231
邀请新用户注册赠送积分活动 1845373
关于科研通互助平台的介绍 1692871