Personalizing therapy for atrial fibrillation: The role of stem cell and in silico disease models

Abstract

Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with substantial morbidity. There is considerable inter-patient variability in the pathologic processes that promote AF, and this variability likely has a significant genetic basis. Clinically this is reflected by the observation that anti-arrhythmic drugs and interventional procedures have highly variable efficacy, and this highlights the need for adopting a more efficacious personalized approach. We explore recent advancements in both in silico and stem cell disease models that set the stage for a personalized approach. Specifically we highlight new mechanistic insights in AF; the future role of computational models in planning personalized ablation strategies; the potential role of stem cell models as a preclinical platform for drug development; and the potential to use gene-editing technology to create patient-specific stem cell models. Finally, we introduce the concept of integrating stem cell models with computational modelling to create a novel pipeline for patient-specific drug discovery and development.