Why the study?
Existing 2D hiPSC-CM models have limited structural and functional relevance to human heart muscle for screening proarrhythmic drug risk.
Does a 3D cardiac microphysiological system using hiPSC-derived heart micromuscle accurately predict the arrhythmogenic potential of drugs compared to existing 2D models?
Does a 3D cardiac microphysiological system using hiPSC-derived heart micromuscle accurately predict the arrhythmogenic potential of drugs compared to existing 2D models?
A 3D cardiac microphysiological system using hiPSC-derived cardiomyocytes successfully predicts the arrhythmogenic risk of drugs, offering a more accurate preclinical screening tool than traditional 2D models.
May reduce false-positive arrhythmogenicity signals in screening; leaves open regulatory adoption pending validation.
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 in vitro 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.
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Charwat et al. (2022) studied this question.