Key result
Computational modeling predicts that a high-risk antiarrhythmic drug taken at the optimal time of day may be safer regarding TdP risk than a low-risk drug taken at the least optimal time.
Why the study?
Optimal drug dosing times may improve efficacy and reduce side effects, but whether dosing time of day affects proarrhythmic risk such as Torsade de Pointes remains incompletely characterized in computational models.
Does dosing time of day impact the risk of Torsade de Pointes for antiarrhythmic drugs in a computational model?
Does dosing time of day impact the risk of Torsade de Pointes for antiarrhythmic drugs in a computational model?
Incorporating circadian clock modeling into the assessment of drug-induced TdP risk reveals that dosing time of day significantly impacts antiarrhythmic drug safety.
Answers are grounded in this paper and cite their sources.
Dosing time may modulate TdP risk beyond drug class; this model leaves open clinical translation of chronotherapy.
Circadian clocks regulate many aspects of human physiology, including cardiovascular function and drug metabolism. Administering drugs at optimal times of the day may enhance effectiveness and reduce side effects. Certain cardiac antiarrhythmic drugs have been withdrawn from the market due to unexpected proarrhythmic effects such as fatal Torsade de Pointes (TdP) ventricular tachycardia. The Comprehensive in vitro Proarrhythmia Assay (CiPA) is a recent global initiative to create guidelines for the assessment of drug-induced arrhythmias that recommends a central role for computational modeling of ion channels and in silico evaluation of compounds for TdP risk. We simulated circadian regulation of cardiac excitability and explored how dosing time of day affects TdP risk for 11 drugs previously classified into risk categories by CiPA. The model predicts that a high-risk drug taken at the most optimal time of day may actually be safer than a low-risk drug taken at the least optimal time of day. Based on these proof-of-concept results, we advocate for the incorporation of circadian clock modeling into the CiPA paradigm for assessing drug-induced TdP risk. Since cardiotoxicity is the leading cause of drug discontinuation, modeling cardiac-related chronopharmacology has significant potential to improve therapeutic outcomes.
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Wei et al. (2025) studied Drug-induced arrhythmias (Torsade de Pointes). Dosing time of day vs. Least optimal time of day was evaluated on Torsade de Pointes (TdP) risk. Computational modeling predicts that a high-risk antiarrhythmic drug taken at the optimal time of day may be safer regarding TdP risk than a low-risk drug taken at the least optimal time.
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