# Connecting Subcellular Electrophysiology to Patient Arrhythmia: A Case Study of Amiodarone

> **NIH NIH F30** · WASHINGTON UNIVERSITY · 2022 · $25,751

## Abstract

PROJECT SUMMARY
Abnormalities in cardiac rhythm, or arrhythmia, affect more than 2% of individuals and are responsible for the
majority of cases of sudden cardiac death. Understanding human cardiac electrophysiology is crucial to our
ability to prevent and treat arrhythmias. A critical obstacle to this is that cardiac rhythm involves both spatial and
temporal coordination of ion channel activity in heart muscle cells. However, while robust temporal
characterization at the single-cell level is feasible, linking this with emergent organ-level spatial manifestations
of cardiac arrhythmia is far more difficult. Despite a significant disease burden, current antiarrhythmic drug
therapies often lack therapeutic efficacy and are hampered by significant side effects. Amiodarone is a commonly
prescribed antiarrhythmic drug, with multiple clinical indications. While effective, amiodarone exhibits significant
extracardiac toxicity and affects multiple currents and ion channels, making it difficult to characterize. Further
constraining this effort is the limited availability of clinical samples of healthy human cardiac cells and tissues for
experimentation, necessitating the use of suboptimal animal model surrogates. Here, I propose a high-
throughput integrated platform of single-cell and tissue analyses in human-derived induced pluripotent stem cell
cardiomyocytes (hiPSC-CMs) to robustly characterize the electrophysiology, calcium handling, and
biomechanics of human-derived cells treated with antiarrhythmic molecules. I will use a computational model of
hiPSC-CMs to link these data. I will then complete the same analyses in isolated patient ventricular myocytes,
an innovative approach. I will then use this data to train a computational ventricular myocyte model and link these
via established methods. Here, I take a bottom-up approach to understand mechanisms of success and failure
of the most commonly prescribed antiarrhythmic drug, amiodarone. My goal is to build a framework to gain insight
into rational design of the next generation of therapeutics that are safe and effective.

## Key facts

- **NIH application ID:** 10466594
- **Project number:** 1F30HL164043-01
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Druv Bhagavan
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $25,751
- **Award type:** 1
- **Project period:** 2022-09-30 → 2023-09-01

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10466594

## Citation

> US National Institutes of Health, RePORTER application 10466594, Connecting Subcellular Electrophysiology to Patient Arrhythmia: A Case Study of Amiodarone (1F30HL164043-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10466594. Licensed CC0.

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