Blanca Rodríguez

This study uses multiscale modeling to identify anti-arrhythmic strategies for cell therapy in infarcted human ventricles, showing that blocking specific currents and upregulating others reduces arrhythmias while maintaining calcium function.

This paper develops sex-specific human electromechanical models to simulate and evaluate sex differences in drug responses and ECG biomarkers, revealing ionic and anatomical mechanisms underlying these differences.

This study identifies early atrial remodelling as a driver of arrhythmia in Fabry Disease by combining ECG analysis, iPSC-derived cardiomyocytes, and in-silico modelling.

This paper introduces a GPU-based cardiac electrophysiology solver that enables fast and scalable simulations, demonstrating significant speedup and integration into a digital twin pipeline.

T-World is a computational model of human ventricular myocytes that accurately replicates physiological processes and identifies arrhythmia risks, with applications in drug response prediction.

This study calibrates and validates ventricular electromechanical models using ECG and pressure-volume biomarkers to assess their credibility for cardiac Digital Twin applications.

The paper uses in-silico trials to evaluate the efficacy of SK and K2P channel block in atrial fibrillation, finding that combined block significantly improves cardioversion success.

The paper uses human-based modeling to evaluate cell therapy in acute and chronic myocardial infarction, finding that cell heterogeneity and Purkinje system function influence arrhythmia risk.