Electrophysiological dependent antiarrhythmic drug response in population-based models of paroxysmal atrial fibrillation

Response to antiarrhythmic drugs varies markedly across patients with atrial fibrillation (AF), suggesting that treatment efficacy depends on the interaction between drug-specific mechanisms and patient-specific electrophysiological substrate. Here, we used population-based computational models to investigate how electrophysiological substrate and inter-individual ionic variability influence pharmacological efficacy and the underlying mechanisms.

Two populations of human atrial models were generated from distinct substrates: a reference left atrial model and a second model incorporating inward-rectifier-enhancement (IRE) through a 2-fold increase in I _K1 and I _K,ACh . Both populations were independently calibrated against the same experimental datasets from patients with paroxysmal AF (pAF), yielding pAF and IRE-pAF populations. Sustained reentrant activity was induced in two-dimensional tissue simulations and subsequently used to assess cardioversion efficacy of flecainide, vernakalant and tertiapin-Q.

Despite satisfying the same calibration criteria, IRE-pAF population exhibited a more arrhythmogenic phenotype: shorter refractoriness, higher dominant frequency (DF) and greater rotor stability. Antiarrhythmic efficacy markedly differed between substrates. Flecainide cardioversion decreased in IRE-pAF compared with pAF (34% vs 21%), whereas I _K,ACh -targeting therapies preserved or improved efficacy in IRE-pAF (vernakalant: 41% vs 44%, tertiapin-Q: 11% vs 18%). Across drugs and substrates, rotor DF strongly influenced cardioversion outcome, with higher-frequency rotors showing lower termination rates. Drug-induced DF reduction emerged as a key mechanism associated with successful cardioversion, whereas effective refractory period (ERP) prolongation alone did not consistently explain treatment efficacy. In pAF, vernakalant achieved higher cardioversion efficacy than flecainide despite a smaller increase in ERP and greater DF reduction. Ionic analyses further showed that elevated I _K,ACh favored responses to vernakalant and tertiapin-Q.

These findings demonstrate that cardioversion efficacy emerges from the interaction between electrophysiological substrate, rotor dynamics and drug-specific mechanisms. In particular, substrates differing in inward rectifier activity exhibit distinct response patterns, while DF emerges as a robust marker of pharmacological susceptibility and a potential guide for drug-mediated AF termination.

Author summary

Antiarrhythmic drugs are commonly used to restore normal rhythm in patients with paroxysmal atrial fibrillation (pAF), but their effectiveness varies substantially among individuals. The reasons underlying this variability remain incompletely understood, limiting our ability to select the most appropriate treatment for a given patient.

In this study, we used populations of computational models of human atrial tissue to investigate how differences in the underlying electrophysiological substrate influence drug response and the underlying mechanisms. We generated two pAF-like populations differing in the level of inward rectifier activity. Then, we evaluated the effects of three antiarrhythmic drugs with distinct mechanisms of action.

Our results show that, while some therapies became less effective in the inward-rectifier-enhanced substrate, others maintained or even improved their performance. We also found that rotor dominant frequency (DF) was closely linked to treatment success and that drugs producing greater DF reduction were more likely to terminate AF.

These findings highlight the importance of considering substrate-specific electrophysiology when evaluating antiarrhythmic therapies and illustrate how computational modeling can help uncover mechanisms of drug response. More broadly, our results suggest that electrophysiological markers such as DF may help identify patients more likely to benefit from specific rhythm-control strategies, supporting future personalized approaches for AF treatment.