Research ArticleDrug Development

A Computational Model to Predict the Effects of Class I Anti-Arrhythmic Drugs on Ventricular Rhythms

Science Translational Medicine  31 Aug 2011:
Vol. 3, Issue 98, pp. 98ra83
DOI: 10.1126/scitranslmed.3002588

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Crowdsourcing the Heart for Drug Screening

The old way: Consult a specialist to answer your question. The new way: Consult a crowd of generalists who in the aggregate can come up with a better answer. The old way—testing drugs on single cardiac cells in vitro—has not worked well for screening out potential anti-arrhythmia agents that can occasionally block conduction in the heart or exacerbate arrhythmia, serious problems that cause sudden death in treated patients. Instead, Moreno et al. have called on the crowd by building a model of heart tissue that includes many cardiac cells and their interactions. When anti-arrhythmia drugs are “applied” to the model’s beating heart tissue—but not when they are applied to the single cardiac cells that make up the model—the drugs that cause side effects, and the concentrations at which they do so, are revealed, results that the authors were able to validate experimentally.

The model starts with the detailed kinetics of the heart’s sodium channels, first in the context of a single cell, then in two- and three-dimensional cardiac tissue. The authors compared the action of lidocaine, a class 1B anti-arrhythmic drug not known to cause conduction block, and flecainide, a prototypical class 1C drug that carries a warning from the Food and Drug Administration. In the modeled analyses of single cardiac cells, both drugs slowed excitability at concentrations that matched those used in patients, but the cells retained the ability to generate action potentials. But when the model incorporated coupled groups of cells, the behavior of the drugs diverged. Lidocaine lowered excitability without causing block, but at the higher concentrations (used clinically), flecainide caused serious conduction block when heart rates reached 160 beats per minute. Experiments in rabbit heart confirmed the results of the model. In scaled-up, 500 by 500 groups of cells, the authors’ model could also successfully predict the tendency of flecainide, but not lidocaine, to make the heart extra sensitive to heartbeats occurring too early or too late, an effect that causes even more severe arrhythmias in patients when they take anti-arrhythmia drugs. Again, experiments in rabbit hearts replicated the model’s predictions, as did simulations of anatomically accurate human hearts derived from magnetic resonance imaging images.

The ability of this sophisticated model of living cardiac tissue to replicate the clinical adverse effects of lidocaine and flecainide is promising, but it will be necessary to validate its performance with other drugs to understand how to deploy it most effectively. Ideally, such models will be useful for screening out potential arrhythmic drugs that promote conduction block or exacerbate arrhythmias. Such a view of how drugs affect the collective activity of cardiac cells should help in these situations in which the cure proves more deadly than the disease.


  • Citation: J. D. Moreno, Z. I. Zhu, P.-C. Yang, J. R. Bankston, M.-T. Jeng, C. Kang, L. Wang, J. D. Bayer, D. J. Christini, N. A. Trayanova, C. M. Ripplinger, R. S. Kass, C. E. Clancy, A Computational Model to Predict the Effects of Class I Anti-Arrhythmic Drugs on Ventricular Rhythms. Sci. Transl. Med. 3, 98ra83 (2011).