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成人心肌细胞中变力性药物的多参数机械机理分析。

Multiparametric Mechanistic Profiling of Inotropic Drugs in Adult Human Primary Cardiomyocytes.

机构信息

AnaBios Corporation, San Diego, CA, 92109, USA.

Arena Pharmaceuticals, San Diego, CA, 92121, USA.

出版信息

Sci Rep. 2020 May 6;10(1):7692. doi: 10.1038/s41598-020-64657-2.

Abstract

Effects of non-cardiac drugs on cardiac contractility can lead to serious adverse events. Furthermore, programs aimed at treating heart failure have had limited success and this therapeutic area remains a major unmet medical need. The challenges in assessing drug effect on cardiac contractility point to the fundamental translational value of the current preclinical models. Therefore, we sought to develop an adult human primary cardiomyocyte contractility model that has the potential to provide a predictive preclinical approach for simultaneously predicting drug-induced inotropic effect (sarcomere shortening) and generating multi-parameter data to profile different mechanisms of action based on cluster analysis of a set of 12 contractility parameters. We report that 17 positive and 9 negative inotropes covering diverse mechanisms of action exerted concentration-dependent increases and decreases in sarcomere shortening, respectively. Interestingly, the multiparametric readout allowed for the differentiation of inotropes operating via distinct mechanisms. Hierarchical clustering of contractility transient parameters, coupled with principal component analysis, enabled the classification of subsets of both positive as well as negative inotropes, in a mechanism-related mode. Thus, human cardiomyocyte contractility model could accurately facilitate informed mechanistic-based decision making, risk management and discovery of molecules with the most desirable pharmacological profile for the correction of heart failure.

摘要

非心脏药物对心肌收缩力的影响可能导致严重的不良事件。此外,旨在治疗心力衰竭的方案收效甚微,这一治疗领域仍然存在重大的未满足的医疗需求。评估药物对心肌收缩力影响的挑战凸显了当前临床前模型的基本转化价值。因此,我们试图开发一种成人原代心肌细胞收缩力模型,该模型有可能提供一种预测性的临床前方法,同时预测药物的变力作用(肌节缩短),并根据 12 个收缩力参数集的聚类分析生成多参数数据,以分析不同的作用机制。我们报告说,17 种阳性变力药和 9 种阴性变力药分别通过不同的作用机制,表现出浓度依赖性的肌节缩短增加和减少。有趣的是,多参数读数允许区分通过不同机制作用的变力药。收缩力瞬变参数的层次聚类,加上主成分分析,能够以相关机制的方式对阳性和阴性变力药的亚组进行分类。因此,人心肌细胞收缩力模型可以准确地促进基于机制的决策、风险管理和具有最理想药理学特征的分子的发现,以纠正心力衰竭。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0a6/7203129/5ec633c46a3f/41598_2020_64657_Fig1_HTML.jpg

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