Artificial Intelligence in nanotechnology for treatment of diseases

纳米技术 医学 材料科学
作者
Soroush Heydari,Niloofar Masoumi,Erfan Esmaeeli,Seyed Mohammad Ayyoubzadeh,Fatemeh Ghorbani‐Bidkorbeh,Mahnaz Ahmadi
出处
期刊:Journal of Drug Targeting [Taylor & Francis]
卷期号:32 (10): 1247-1266 被引量:18
标识
DOI:10.1080/1061186x.2024.2393417
摘要

Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools. AI has been employed in designing, characterising and manufacturing drug delivery nanosystems, as well as in predicting treatment efficiency. AI's potential to personalise drug delivery based on individual patient factors, optimise formulation design and predict drug properties has been highlighted. By leveraging AI and large datasets, developing safe and effective DDSs can be accelerated, ultimately improving patient outcomes and advancing pharmaceutical sciences. This review article investigates the role of AI in the development of nano-DDSs, with a focus on their therapeutic applications. The use of AI in DDSs has the potential to revolutionise treatment optimisation and improve patient care.
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
zJx丶发布了新的文献求助10
刚刚
desperado完成签到 ,获得积分10
1秒前
榜一大哥的负担完成签到 ,获得积分10
1秒前
奈何人生发布了新的文献求助10
1秒前
1秒前
Yang完成签到,获得积分10
1秒前
冰冰完成签到,获得积分20
2秒前
wufel完成签到,获得积分10
2秒前
JKJ发布了新的文献求助10
2秒前
121发布了新的文献求助10
2秒前
3秒前
3秒前
4秒前
李健应助张润泽采纳,获得10
4秒前
IETPer发布了新的文献求助10
4秒前
4秒前
欣喜访旋发布了新的文献求助10
4秒前
5秒前
汉堡包应助ouyggg采纳,获得10
5秒前
冰冰发布了新的文献求助10
5秒前
背后的桐发布了新的文献求助10
6秒前
小二郎应助lzx采纳,获得10
7秒前
7秒前
7秒前
7秒前
7秒前
昏睡的蟠桃应助杨旭采纳,获得100
8秒前
Change_Jing完成签到,获得积分10
8秒前
8秒前
沉海发布了新的文献求助30
9秒前
9秒前
杭啊发布了新的文献求助10
10秒前
曾经电源完成签到,获得积分10
11秒前
hx完成签到 ,获得积分10
11秒前
CAOHOU应助满眼星辰采纳,获得10
11秒前
12秒前
24816848完成签到,获得积分10
12秒前
陈道哥完成签到 ,获得积分10
12秒前
13秒前
三七完成签到,获得积分10
13秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Handbook of Marine Craft Hydrodynamics and Motion Control, 2nd Edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
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 3987021
求助须知:如何正确求助?哪些是违规求助? 3529365
关于积分的说明 11244629
捐赠科研通 3267729
什么是DOI,文献DOI怎么找? 1803932
邀请新用户注册赠送积分活动 881223
科研通“疑难数据库(出版商)”最低求助积分说明 808635