Mechanism-driven ECG simulation framework for teaching drug-induced cardiac electrophysiology

Drug-induced cardiac arrhythmias are central to physiology and pharmacology education, yet students often struggle to connect electrophysiological mechanisms with dynamic electrocardiographic (ECG) changes. We developed a mechanism-driven ECG simulation framework to model dose-dependent waveform alterations associated with drug-induced cardiac electrophysiological disturbances and to support structured classroom implementation. The platform integrates a parameter-controlled electrophysiological engine with deterministic waveform generation to simulate progressive ECG morphology changes across drug classes and exposure levels. Computational stability and reproducibility were evaluated with agreement and validation metrics across repeated simulations within predefined physiological bounds. The system demonstrated high reproducibility and narrow confidence intervals in waveform parameter estimation. Real-time manipulation of pharmacological variables enabled visualization of QT prolongation, conduction delay, and repolarization abnormalities in a dose-responsive manner. Designed for scaffolded, hypothesis-driven classroom use, the framework promotes mechanism-based reasoning rather than memorization of static ECG patterns and provides a reproducible, educator-focused platform for teaching drug-induced cardiac arrhythmias.NEW & NOTEWORTHY This study presents a mechanism-driven ECG simulation framework specifically designed for physiology education rather than diagnostic prediction. By integrating dose-dependent waveform modeling with structured classroom implementation, the platform enables learners to link pharmacological mechanisms to dynamic ECG changes through interactive, hypothesis-driven exploration.