Human iPSC-based cardiac microphysiological system for drug screening applications.
Human iPSC-based cardiac microphysiological system for drug screening applications.
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DOI：
10.1038/srep08883
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发表时间：
2015-03-09
影响因子：
4.6
通讯作者：
Healy KE
中科院分区：
文献类型：
--
作者：
Mathur A;Loskill P;Shao K;Huebsch N;Hong S;Marcus SG;Marks N;Mandegar M;Conklin BR;Lee LP;Healy KE
药物发现和开发受到高失败率的阻碍，这是由于在安全性和有效性测试期间依赖非人类动物模型造成的。这种低效过程的一个根本问题是，非人类动物模型不能充分代表人类生物学。因此，迫切需要高含量的体外系统，以更好地预测药物诱导的毒性。预测心脏毒性的系统是最重要的，因为大约三分之一的基于安全的药物停药是由于心脏毒性。在这里，我们提出了一个心脏微生理系统（MPS），它具有理想的体外系统预测心脏毒性所需的属性：i)具有人类遗传背景的细胞；Ii)生理相关的组织结构（如排列的细胞）；Iii)模拟人体血管系统的可计算的灌注；iv)多种分析模式（如生物、电生理和生理）。我们的MPS能够使人类诱导多能干细胞衍生的心脏组织在数周内保持活力和功能。与细胞尺度研究相比，使用心脏MPS的药理学研究显示一半最大抑制/有效浓度值（IC50/EC50）与组织尺度参考数据更一致。我们预计mps将广泛应用于药物筛选和疾病建模。
Drug discovery and development are hampered by high failure rates attributed to the reliance on non-human animal models employed during safety and efficacy testing. A fundamental problem in this inefficient process is that non-human animal models cannot adequately represent human biology. Thus, there is an urgent need for high-content in vitro systems that can better predict drug-induced toxicity. Systems that predict cardiotoxicity are of uppermost significance, as approximately one third of safety-based pharmaceutical withdrawals are due to cardiotoxicty. Here, we present a cardiac microphysiological system (MPS) with the attributes required for an ideal in vitro system to predict cardiotoxicity: i) cells with a human genetic background; ii) physiologically relevant tissue structure (e.g. aligned cells); iii) computationally predictable perfusion mimicking human vasculature; and, iv) multiple modes of analysis (e.g. biological, electrophysiological, and physiological). Our MPS is able to keep human induced pluripotent stem cell derived cardiac tissue viable and functional over multiple weeks. Pharmacological studies using the cardiac MPS show half maximal inhibitory/effective concentration values (IC50/EC50) that are more consistent with the data on tissue scale references compared to cellular scale studies. We anticipate the widespread adoption of MPSs for drug screening and disease modeling.
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影响因子：
14
作者：
Ma, Zhen;Koo, Sangmo;Finnegan, Micaela A.;Loskill, Peter;Huebsch, Nathaniel;Marks, Natalie C.;Conklin, Bruce R.;Grigoropoulos, Costas P.;Healy, Kevin E.
通讯作者：
Healy, Kevin E.
影响因子：
2.8
作者：
Markov, Dmitry A.;Lillie, Elizabeth M.;McCawley, Lisa J.
通讯作者：
McCawley, Lisa J.
影响因子：
6.1
作者：
Grosberg A;Alford PW;McCain ML;Parker KK
通讯作者：
Parker KK
影响因子：
10.8
作者：
Brandenburger, Matthias;Wenzel, Jan;Dendorfer, Andreas
通讯作者：
Dendorfer, Andreas
影响因子：
4.1
作者：
Boudou, Thomas;Legant, Wesley R.;Chen, Christopher S.
通讯作者：
Chen, Christopher S.