Pharmacokinetic drug evaluation of daclizumab for the treatment of relapsing-remitting multiple sclerosis

复发-缓解 多发性硬化 达利珠单抗 医学 药品 药代动力学 药理学 内科学 免疫学 他克莫司 移植
作者
Francesco Patti,Clara Grazia Chisari,Emanuele D’Amico,Mario Zappia
出处
期刊:Expert Opinion on Drug Metabolism & Toxicology [Taylor & Francis]
卷期号:14 (3): 341-352 被引量:1
标识
DOI:10.1080/17425255.2018.1432594
摘要

INTRODUCTION: Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system. Despite the availability of several disease-modifying therapies for relapsing MS, there is a need for highly efficacious targeted therapy with a favorable benefit-risk profile and a high level of treatment adherence. Daclizumab is a humanized monoclonal antibody directed against CD25, the α subunit of the high-affinity interleukin 2 (IL-2) receptor, that reversibly modulates IL-2 signaling. Areas covered: Daclizumab blocks the activation and expansion of autoreactive T cells that plays a role in the immune pathogenesis of MS. As its modulatory effects on the immune system, daclizumab's potential for use in MS was tested extensively showing a high efficacy in reducing relapse rate, disability progression and the number and volume of gadolinium-enhancing lesions on brain magnetic resonance imaging. Moreover, phase II and III trials showed a favorable pharmacokinetic (PK) profile with slow clearance, linear pharmacokinetics at doses above 100 mg and high subcutaneous bioavailability, not influenced by age, sex or other clinical parameters. Expert opinion: Among the new emerging drugs for MS, daclizumab also, thanks to a favorable PK profile, may represent an interesting and promising therapeutic option in the wide MS therapies armamentarium.
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
reflux发布了新的文献求助10
刚刚
搜集达人应助刘小六六六采纳,获得10
刚刚
2秒前
2秒前
orixero应助稳重的书双采纳,获得10
2秒前
公瑾孔明应助CHyaa采纳,获得10
3秒前
舒适沛珊发布了新的文献求助10
3秒前
4秒前
凝心完成签到,获得积分10
4秒前
yu完成签到,获得积分10
4秒前
cxang完成签到 ,获得积分10
6秒前
CodeCraft应助活泼小笼包采纳,获得20
6秒前
YIQI发布了新的文献求助10
6秒前
耿sir8完成签到,获得积分10
7秒前
8秒前
10秒前
ming2026应助jgg采纳,获得20
11秒前
11秒前
11秒前
HSTrigger应助mannich采纳,获得10
11秒前
HSTrigger应助mannich采纳,获得10
12秒前
HSTrigger应助mannich采纳,获得10
12秒前
HSTrigger应助mannich采纳,获得10
12秒前
祁卿完成签到,获得积分10
12秒前
HSTrigger应助mannich采纳,获得10
12秒前
HSTrigger应助mannich采纳,获得10
12秒前
HSTrigger应助mannich采纳,获得10
13秒前
HSTrigger应助mannich采纳,获得10
13秒前
v0id应助mannich采纳,获得10
13秒前
星辰大海应助mannich采纳,获得10
13秒前
13秒前
张欢馨应助莱斯够瓦瑞丝采纳,获得10
14秒前
syy应助ZC采纳,获得10
14秒前
Roach发布了新的文献求助20
14秒前
egomarine应助长春陈冠希采纳,获得10
14秒前
搜集达人应助好的采纳,获得20
14秒前
15秒前
WDW发布了新的文献求助30
16秒前
17秒前
刘洋发布了新的文献求助10
18秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 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 7583360
求助须知:如何正确求助?哪些是违规求助? 9162077
关于积分的说明 19605961
捐赠科研通 7165434
什么是DOI,文献DOI怎么找? 3266265
关于科研通互助平台的介绍 2431182
邀请新用户注册赠送积分活动 2257712