Progress in Modeling Cardiac Myocyte Calcium Cycling and Investigating Arrhythmia Mechanisms: A Study Focused on the Ryanodine Receptor

SignificanceThe Ryanodine Receptor (RyR) is a central regulator of intracellular calcium (Ca2+) homeostasis in cardiomyocytes through its control of Ca2+ release from the Sarcoplasmic Reticulum (SR). Abnormal RyR activity, including excessive activation or impaired gating, is a key mechanism underlying Early Afterdepolarizations (EADs) and Delayed Afterdepolarizations (DADs), thereby increasing arrhythmia risk. The coupling between membrane electrophysiology and Ca2+ cycling in cardiomyocytes depends on spatially organized and rapidly evolving processes that are difficult to resolve experimentally. Conventional approaches, including animal models and pharmacological interventions, are constrained by high cost and limited control of experimental variables. Mathematical modeling and computer simulation of the RyR have therefore become essential tools for studying RyR regulation under physiological and pathological conditions and for elucidating arrhythmogenic mechanisms. This review provides an overview of RyR biology and modeling. It first summarizes structural features and core functional properties to establish the mechanistic basis of RyR gating and regulation. It then evaluates current and emerging modeling approaches, outlining their strengths and limitations. The review next describes the integration of RyR models into cardiomyocyte Ca2+ cycling frameworks and their application across different cardiomyocyte subtypes. It further examines arrhythmogenic mechanisms arising from RyR dysfunction and assesses drug strategies designed to stabilize RyR activity. Finally, it highlights artificial intelligence and cardiac digital twins as emerging directions for advancing RyR modeling and therapeutic development.ProgressThe growing availability of RyR structural data has enabled continued refinement of modeling strategies. Early RyR models relied primarily on phenomenological formulations that were computationally practical but limited in mechanistic detail. Markov models have become the dominant framework for simulating RyR gating behavior and enable detailed representation of Ca2+ sparks and related events through discrete state transitions. Deterministic integration of Markov models offers high computational efficiency and adaptability across different cardiomyocyte types. However, this approach neglects the stochastic nature of RyR opening and fails to reproduce random fluctuations in intracellular Ca2+ concentration, which can lead to discrepancies between simulations and physiological behavior. Stochastic Markov models capture these random processes and are therefore essential for investigating arrhythmogenic phenomena such as Ca2+ waves. Their application, however, requires extensive experimental data and substantial computational resources, which limits large-scale implementation. Recent artificial intelligence approaches, including deep neural networks that compress Markov models into single governing equations, have improved computational efficiency. Advances in structural biology have further clarified RyR conformational dynamics and subunit cooperativity during gating, particularly in relation to diastolic Ca2+ leak. These insights have motivated more detailed models that incorporate subunit interactions or molecular dynamics. Numerous RyR models have been incorporated into cardiac action potential frameworks and applied to the study of EADs and DADs. These integrated models enhance understanding of electrical disturbances caused by RyR dysfunction and provide a useful platform for drug screening and mechanistic investigation.ConclusionMultiple RyR models have been developed that successfully reproduce key physiological processes, including Ca2+ sparks, and are widely applied in studies of cardiomyocyte Ca2+ cycling. Nevertheless, several challenges remain. (1) A unified modeling framework is still lacking. No single RyR model can accurately simulate Ca2+ dynamics across the full spectrum of physiological and pathological conditions. Careful evaluation is therefore required when selecting models for intracellular Ca2+ handling. (2) Computational burden limits multiscale integration. Multiscale models are necessary to connect cellular Ca2+ dynamics with tissue-level electrical propagation by incorporating spatial heterogeneity, but their high computational cost restricts application in clinically relevant scenarios. (3) Pacemaker cell models remain underdeveloped. Current research focuses primarily on ventricular and atrial cardiomyocytes, whereas pacemaker cell models are less mature and often rely on common-pool formulations that do not represent spatial Ca2+ gradients. Future studies should prioritize the development of detailed pacemaker cell models that explicitly represent Ca2+ release unit networks and incorporate realistic RyR dynamics. Artificial intelligence and cardiac digital twins, although still at an early stage in RyR modeling, offer substantial potential to advance mechanistic research and support precision-medicine applications.ProspectsFuture RyR research will increasingly depend on integrating advances from structural biology, biophysics, and computational science. Such efforts are required to connect molecular-scale RyR conformational changes with organ-level cardiac function and to enable scalable, clinically actionable models. These models can strengthen mechanistic understanding and accelerate translational progress in precision cardiology. Artificial intelligence and cardiac digital twins provide a pathway toward multi-scale cardiac models that incorporate patient-specific electrophysiology and Ca2+ cycling. These approaches may substantially improve understanding of arrhythmia mechanisms and heart failure pathophysiology and serve as predictive platforms for the development of mechanism-based personalized antiarrhythmic therapies.