吞吐量
软骨
药品
高通量筛选
计算机科学
计算生物学
生物医学工程
医学
药理学
生物信息学
生物
解剖
电信
无线
作者
Nicola C. Foster,Nicole M. Hall,Alicia J. El Haj
出处
期刊:Tissue Engineering Part B-reviews
[Mary Ann Liebert]
日期:2022-04-01
卷期号:28 (2): 421-436
被引量:12
标识
DOI:10.1089/ten.teb.2020.0354
摘要
Osteoarthritis (OA) is a severely painful and debilitating disease of the joint, which brings about degradation of the articular cartilage and currently has few therapeutic solutions. Two-dimensional (2D) high-throughput screening (HTS) assays have been widely used to identify candidate drugs with therapeutic potential for the treatment of OA. A number of small molecules which improve the chondrogenic differentiation of progenitor cells for tissue engineering applications have also been discovered in this way. However, due to the failure of these models to accurately represent the native joint environment, the efficacy of these drugs has been limited in vivo. Screening systems utilizing three-dimensional (3D) models, which more closely reflect the tissue and its complex cell and molecular interactions, have also been described. However, the vast majority of these systems fail to recapitulate the complex, zonal structure of articular cartilage and its unique cell population. This review summarizes current 2D HTS techniques and addresses the question of how to use existing 3D models of tissue-engineered cartilage to create 3D drug screening platforms with improved outcomes. Currently, the use of two-dimensional (2D) screening platforms in drug discovery is common practice. However, these systems often fail to predict efficacy in vivo, as they do not accurately represent the complexity of the native three-dimensional (3D) environment. This article describes existing 2D and 3D high-throughput systems used to identify small molecules for osteoarthritis treatment or in vitro chondrogenic differentiation, and suggests ways to improve the efficacy of these systems based on the most recent research.
科研通智能强力驱动
Strongly Powered by AbleSci AI