Anti-arrhythmic strategies for atrial fibrillation: The role of computational modeling in discovery, development, and optimization

Eleonora Grandi, Mary M. Maleckar

Research output: Contribution to journalReview article

14 Scopus citations

Abstract

Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with increased risk of cerebrovascular stroke, and with several other pathologies, including heart failure. Current therapies for AF are targeted at reducing risk of stroke (anticoagulation) and tachycardia-induced cardiomyopathy (rate or rhythm control). Rate control, typically achieved by atrioventricular nodal blocking drugs, is often insufficient to alleviate symptoms. Rhythm control approaches include antiarrhythmic drugs, electrical cardioversion, and ablation strategies. Here, we offer several examples of how computational modeling can provide a quantitative framework for integrating multiscale data to: (a) gain insight into multiscale mechanisms of AF; (b) identify and test pharmacological and electrical therapy and interventions; and (c) support clinical decisions. We review how modeling approaches have evolved and contributed to the research pipeline and preclinical development and discuss future directions and challenges in the field.

Original languageEnglish (US)
Pages (from-to)126-142
Number of pages17
JournalPharmacology and Therapeutics
Volume168
DOIs
StatePublished - Dec 1 2016

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Keywords

  • Ablation
  • Antiarrhythmic drugs
  • Atrial selectivity
  • Cardioversion
  • Simulation
  • Systems pharmacology

ASJC Scopus subject areas

  • Pharmacology
  • Pharmacology (medical)

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