Personalized in silico modeling of cardiac ion channel variants to predict drug-induced proarrhythmia risk
Abstract
Introduction: models often overlook genetic variability, limiting their ability to capture patient-specific responses. We present a computational modeling framework that integrates known genetic variants in cardiac ion channels to predict individual differences in drug-induced arrhythmogenic risk. Methods: We simulated concentration-dependent effects of amiodarone across combinations of hERG and Nav1.5 alleles in five human cardiac cell types: endocardial, epicardial, midwall, Purkinje, and atrial cells. APD90 values were evaluated across all cell types, whereas qNet was calculated in ventricular cells only to assess genotype and cell type dependent differences in electrophysiological response and torsadogenic risk. Results: Our results highlight how genetic variations and cell type context influence electrophysiological response to amiodarone, uncovering high-risk profiles otherwise masked in population-averaged models. These simulations reveal key insights with translational and regulatory relevance: genetic background meaningfully alters drug response; midmyocardial cells are disproportionately vulnerable; the same mutation can produce different effects across cell types; Purkinje cells may serve as silent proarrhythmic substrates; and celltype- specific differences in APD90 and qNet may provide additional insight beyond APD prolongation alone, and consequently improve prediction of torsades de pointes risk. Conclusion: cardiac safety. By linking genetic polymorphisms to…
Read the paper
Related studies
- Synthesis, In Vitro and In Silico Molecular Docking Studies of Novel Phthalimide–Pyrimidine Hybrid Analogues to Thalidomide as Potent Antitubercular Agents
- Exploring the inhibitory performance of expired moxifloxacin and norfloxacin on copper corrosion in saline environment
- Molecular investigation of antimicrobial peptides against Helicobacter pylori proteins using a peptide-protein docking approach
- Screening of novel narrow-spectrum benzofuroxan derivatives for the treatment of multidrug-resistant tuberculosis through in silico, in vitro, and in vivo approaches
- Synthesis, Characterization, Anticancer, Antioxidant, and In Silico Evaluation of Semicarbazides and Thiosemicarbazides
- Fast and accurate prediction of drug induced proarrhythmic risk with sex specific cardiac emulators
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.