Key result
Dofetilide increases cardiac cycle length ~18% in digital twin iPSC-CM models, signaling arrhythmogenic risk.
Absolute Event Rate: 418% vs 354%
Digital twin technology using iPSC-CMs can successfully predict drug-induced repolarization abnormalities and arrhythmia risk, offering a high-throughput tool for personalized safety pharmacology.
May advance preclinical arrhythmia risk prediction; leaves open clinical validation of iPSC-CM digital twins.
The authors demonstrate the feasibility of technological innovation for personalized medicine in the context of drug-induced arrhythmia. The authors use atomistic-scale structural models to predict rates of drug interaction with ion channels and make predictions of their effects in digital twins of induced pluripotent stem cell-derived cardiac myocytes. The authors construct a simplified multilayer, 1-dimensional ring model with sufficient path length to enable the prediction of arrhythmogenic dispersion of repolarization. Finally, the authors validate the computational pipeline prediction of drug effects with data and quantify drug-induced propensity to repolarization abnormalities in cardiac tissue. The technology is high throughput, computationally efficient, and low cost toward personalized pharmacologic prediction.
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Yang et al. (2023) studied Drug-induced arrhythmia. Dofetilide and Moxifloxacin vs. Drug-free control was evaluated on Cardiac cycle length (time from activation until full repolarization). In a digital twin model of iPSC-CMs, dofetilide increased cardiac cycle length to 418 ms compared to 354 ms in drug-free controls, indicating increased arrhythmogenic potential.
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