Validating the Arrhythmogenic Potential of High-, Intermediate-, and Low-Risk Drugs in a Human-Induced Pluripotent Stem Cell-Derived Cardiac Microphysiological System.

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.

Heart Muscle Microphysiological System for Cardiac Liability Prediction of Repurposed COVID-19 Therapeutics.

Despite global efforts, it took 7 months between the proclamation of global SARS-CoV-2 pandemic and the first FDA-approved treatment for COVID-19. During this timeframe, clinicians focused their efforts on repurposing drugs, such as hydroxychloroquine (HCQ) or azithromycin (AZM) to treat hospitalized COVID-19 patients. While clinical trials are time-consuming, the exponential increase in hospitalizations compelled the FDA to grant an emergency use authorization for HCQ and AZM as treatment for COVID-19, although there was limited evidence of their combined efficacy and safety. The authorization was revoked 4 months later, giving rise to controversial political and scientific debates illustrating important challenges such as premature authorization of potentially ineffective or unsafe therapeutics, while diverting resources from screening of effective drugs. Here we report on a preclinical drug screening platform, a cardiac microphysiological system (MPS), to rapidly identify clinically relevant cardiac liabilities associated with HCQ and AZM. The cardiac MPS is a microfabricated fluidic system in which cardiomyocytes derived from human induced pluripotent stem cells self-arrange into a uniaxially beating tissue. The drug response was measured using outputs that correlate with clinical measurements such as action potential duration (proxy for clinical QT interval) and drug-biomarker pairing. The cardiac MPS predicted clinical arrhythmias associated with QT prolongation and rhythm instabilities in tissues treated with HCQ. We found no change in QT interval upon acute exposure to AZM, while still observing a significant increase in arrhythmic events. These results suggest that this MPS can not only predict arrhythmias, but it can also identify arrhythmias even when QT prolongation is absent. When exposed to HCQ and AZM polytherapy, this MPS faithfully reflected clinical findings, in that the combination of drugs synergistically increased QT interval when compared to single drug exposure, while not worsening the overall frequency of arrhythmic events. The high content cardiac MPS can rapidly evaluate the cardiac safety of potential therapeutics, ultimately accelerating patients' access to safe and effective treatments.

New Molecular Scaffolds for Fluorescent Voltage Indicators.

The ability to non-invasively monitor membrane potential dynamics in excitable cells like neurons and cardiomyocytes promises to revolutionize our understanding of the physiology and pathology of the brain and heart. Here, we report the design, synthesis, and application of a new class of fluorescent voltage indicators that make use of a fluorene-based molecular wire as a voltage-sensing domain to provide fast and sensitive measurements of membrane potential in both mammalian neurons and human-derived cardiomyocytes. We show that the best of the new probes, fluorene VoltageFluor 2 (fVF 2), readily reports on action potentials in mammalian neurons, detects perturbations to the cardiac action potential waveform in human induced pluripotent stem cell-derived cardiomyocytes, shows a substantial decrease in phototoxicity compared to existing molecular wire-based indicators, and can monitor cardiac action potentials for extended periods of time. Together, our results demonstrate the generalizability of a molecular wire approach to voltage sensing and highlight the utility of fVF 2 for interrogating membrane potential dynamics.

Quantitatively characterizing drug-induced arrhythmic contractile motions of human stem cell-derived cardiomyocytes.

Quantification of abnormal contractile motions of cardiac tissue has been a noteworthy challenge and significant limitation in assessing and classifying the drug-induced arrhythmias (i.e., Torsades de pointes). To overcome these challenges, researchers have taken advantage of computational image processing tools to measure contractile motion from cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs). However, the amplitude and frequency analysis of contractile motion waveforms does not produce sufficient information to objectively classify the degree of variations between two or more sets of cardiac contractile motions. In this paper, we generated contractile motion data from beating hiPSC-CMs using motion tracking software based on optical flow analysis, and then implemented a computational algorithm, phase space reconstruction (PSR), to derive parameters (embedding, regularity, and fractal dimensions) to further characterize the dynamic nature of the cardiac contractile motions. Application of drugs known to cause cardiac arrhythmia induced significant changes to these resultant dimensional parameters calculated from PSR analysis. Integrating this new computational algorithm with the existing analytical toolbox of cardiac contractile motions will allow us to expand current assessments of cardiac tissue physiology into an automated, high-throughput, and quantifiable manner which will allow more objective assessments of drug-induced proarrhythmias.