Charwat Verena, Charrez Bérénice, Siemons Brian A, Finsberg Henrik, Jæger Karoline H, Edwards Andrew G, Huebsch Nathaniel, Wall Samuel, Miller Evan, Tveito Aslak, Healy Kevin E
Department of Bioengineering and California Institute for Quantitative Biosciences (QB3), University of California at Berkeley, Berkeley, California 94720, United States.
Simula Research Laboratory, 0164 Oslo, Norway.
ACS Pharmacol Transl Sci. 2022 Jul 29;5(8):652-667. doi: 10.1021/acsptsci.2c00088. eCollection 2022 Aug 12.
Evaluation of arrhythmogenic drugs is required by regulatory agencies before any new compound can obtain market approval. Despite rigorous review, cardiac disorders remain the second most common cause for safety-related market withdrawal. On the other hand, false-positive preclinical findings prohibit potentially beneficial candidates from moving forward in the development pipeline. Complex models using cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CM) have been identified as a useful tool that allows for rapid and cost-efficient screening of proarrhythmic drug risk. Currently available hiPSC-CM models employ simple two-dimensional (2D) culture formats with limited structural and functional relevance to the human heart muscle. Here, we present the use of our 3D cardiac microphysiological system (MPS), composed of a hiPSC-derived heart micromuscle, as a platform for arrhythmia risk assessment. We employed two different hiPSC lines and tested seven drugs with known ion channel effects and known clinical risk: dofetilide and bepridil (high risk); amiodarone and terfenadine (intermediate risk); and nifedipine, mexiletine, and lidocaine (low risk). The cardiac MPS successfully predicted drug cardiotoxicity risks based on changes in action potential duration, beat waveform (i.e., shape), and occurrence of proarrhythmic events of healthy patient hiPSC lines in the absence of risk cofactors. We showcase examples where the cardiac MPS outperformed existing hiPSC-CM 2D models.
任何新化合物在获得市场批准之前,监管机构都要求对致心律失常药物进行评估。尽管进行了严格审查,但心脏疾病仍是与安全性相关的市场撤市的第二大常见原因。另一方面,临床前的假阳性结果阻碍了潜在有益的候选药物在研发流程中取得进展。使用源自人诱导多能干细胞的心肌细胞(hiPSC-CM)构建的复杂模型已被确定为一种有用的工具,可用于快速且经济高效地筛选致心律失常药物风险。目前可用的hiPSC-CM模型采用简单的二维(2D)培养形式,与人类心肌的结构和功能相关性有限。在此,我们展示了使用我们的三维心脏微生理系统(MPS),其由hiPSC衍生的心脏微肌肉组成,作为心律失常风险评估的平台。我们使用了两种不同的hiPSC系,并测试了七种已知具有离子通道效应和已知临床风险的药物:多非利特和苄普地尔(高风险);胺碘酮和特非那定(中度风险);以及硝苯地平、美西律和利多卡因(低风险)。在没有风险辅助因素的情况下,心脏MPS基于健康患者hiPSC系的动作电位持续时间、搏动波形(即形状)和致心律失常事件的发生情况,成功预测了药物心脏毒性风险。我们展示了心脏MPS优于现有hiPSC-CM二维模型的示例。