Interpreting non-linear drug diffusion data: Utilizing Korsmeyer-Peppas model to study drug release from liposomes

脂质体 化学 药物输送 药品 色谱法 生物物理学 生物医学工程 药理学 生物化学 有机化学 医学 生物
作者
Iren Yeeling Wu,Sonali Bala,Nataša Škalko‐Basnet,Massimiliano Pio di Cagno
出处
期刊:European Journal of Pharmaceutical Sciences [Elsevier BV]
卷期号:138: 105026-105026 被引量:385
标识
DOI:10.1016/j.ejps.2019.105026
摘要

The aim of this work was to clarify the dynamics behind the influence of ionic strength on the changes in drug release from large unilamellar vesicles (LUVs). For this purpose, we have investigated the transport of two different model drugs (caffeine and hydrocortisone) formulated into liposomes through different types of barriers with different retention properties (regenerated cellulose and the newly introduced biomimetic barrier, Permeapad®). Drug release from liposomes was studied utilizing the standard Franz diffusion cells. LUV dispersions were exposed to the isotonic, hypotonic and hypertonic environment (difference of 300 mOsm/kg between the initial LUVs and the environment) and experimental data treated with both linear and non-linear (Korsmeyer-Peppas) regression models. To alter the rigidity of the liposomal membranes, cholesterol was introduced in the liposomal barriers (up to 25% w/w). Korsmeyer-Peppas model was proven to be suited to analyse experimental data throughout the experimental time frame, providing important additive information in comparison to standard linear approximation. The obtained results are highly relevant as they improve the interpretation of drug release kinetics from LUVs under osmotic stress. Moreover, the findings can be utilized in the development of liposomal formulations intended for nose-to-brain targeted drug delivery.
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
彳亍发布了新的文献求助10
1秒前
自然老师发布了新的文献求助10
1秒前
miaofajin完成签到,获得积分10
2秒前
顾矜应助burn9采纳,获得10
2秒前
2秒前
453完成签到,获得积分10
3秒前
4秒前
万能图书馆应助ttttttt采纳,获得10
5秒前
零下十五度完成签到,获得积分10
5秒前
我是老大应助沉默的金鱼采纳,获得10
6秒前
所所应助Anima采纳,获得10
6秒前
6秒前
wanchao发布了新的文献求助10
7秒前
王哈哈完成签到,获得积分10
7秒前
灵巧的以松完成签到 ,获得积分10
8秒前
英俊的铭应助何88888888采纳,获得10
9秒前
852应助有魅力的乐萱采纳,获得10
9秒前
王哈哈发布了新的文献求助10
10秒前
安装地方发布了新的文献求助10
10秒前
太阳太晒发布了新的文献求助10
11秒前
11秒前
情怀应助453采纳,获得10
12秒前
yangyang发布了新的文献求助10
12秒前
13秒前
16秒前
16秒前
16秒前
17秒前
小神仙发布了新的文献求助30
17秒前
激你肽酶发布了新的文献求助20
18秒前
peace发布了新的文献求助10
19秒前
20秒前
谨慎觅露发布了新的文献求助10
20秒前
20秒前
20秒前
21秒前
21秒前
iNk应助wj采纳,获得20
21秒前
哈哈哈发布了新的文献求助10
22秒前
22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
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7758888
求助须知:如何正确求助?哪些是违规求助? 9304675
关于积分的说明 20282383
捐赠科研通 7342810
什么是DOI,文献DOI怎么找? 3312329
关于科研通互助平台的介绍 2462936
邀请新用户注册赠送积分活动 2326319