Thorough QT (TQT) studies: concordance with torsadogenesis and an evolving cardiac safety testing paradigm

Clinical Characteristics of Moxifloxacin-Related Arrhythmias and Development of a Predictive Nomogram: A Case Control Study

This study aimed to analyze the incidence, clinical characteristics, and risk factors of moxifloxacin-related arrhythmias and electrocardiographic alterations in hospitalized patients using real-world data. Concurrently, a nomogram was established and validated to provide a practical tool for prediction. Retrospective automatic monitoring of inpatients using moxifloxacin was performed in a Chinese hospital from January 1, 2017, to December 31, 2021, to obtain the incidence of drug-induced arrhythmias and electrocardiographic alterations. Propensity score matching was conducted to balance confounders and analyze clinical characteristics. Based on the risk and protective factors identified through logistic regression analysis, a prediction nomogram was developed and internally validated using the Bootstrap method. Arrhythmias and electrocardiographic alterations occurred in 265 of 21,711 cases taking moxifloxacin, with an incidence of 1.2%. Independent risk factors included medication duration (odds ratio [OR] 1.211, 95% confidence interval [CI] 1.156-1.270), concomitant use of meropenem (OR 4.977, 95% CI 2.568-9.644), aspartate aminotransferase >40 U/L (OR 3.728, 95% CI 1.800-7.721), glucose >6.1 mmol/L (OR 2.377, 95% CI 1.531-3.690), and abnormally elevated level of amino-terminal brain natriuretic peptide precursor (OR 2.908, 95% CI 1.640-5.156). Concomitant use of cardioprotective drugs (OR 0.430, 95% CI 0.220-0.841) was a protective factor. The nomogram showed good differentiation and calibration, with enhanced clinical benefit. The incidence of moxifloxacin-related arrhythmias and electrocardiographic alterations is in the range of common. The nomogram proves valuable in predicting the risk in the moxifloxacin-administered population, offering significant clinical applications.

Impact of Daridorexant, a Dual Orexin Receptor Antagonist, on Cardiac Repolarization Following Bedtime Dosing: Results from a Thorough QT Study Using Concentration-QT Analysis

BACKGROUND AND OBJECTIVE

Daridorexant is a new dual orexin receptor antagonist currently in late-stage clinical development for the treatment of insomnia. This randomized, double-blind, placebo-controlled, four-period crossover study investigated the effect of daridorexant at a therapeutic and supratherapeutic dose on QT interval duration.

METHODS

Thirty-six healthy subjects received single oral doses of daridorexant (50 mg; 200 mg), moxifloxacin (400 mg; open label), and placebo. All treatments were administered at bedtime to mimic therapeutic practice. The primary analysis was based on linear mixed-effects concentration-QT modelling. Triplicate ECG data were extracted from Holter recordings at baseline and until 24 h post dosing at time points matching those for pharmacokinetic sampling. Plasma concentrations of daridorexant were determined over 24 h.

RESULTS

Assay sensitivity was demonstrated based on mean baseline- and placebo-corrected QT interval using Fridericia's formula (ΔΔQTcF) > 5 ms following moxifloxacin administration (p < 0.01). Following daridorexant administration, mean (90% confidence interval, CI) ΔΔQTcF was 1.40 ms (0.48; 2.32 ms) and 1.84 ms (-0.12; 3.79 ms) at the C_max of 747 ng/mL (50 mg dose) and 1809 ng/mL (200 mg dose), respectively, i.e., the upper bounds of the CIs were < 10 ms defined as threshold of regulatory concern. Lack of relevant QT prolongation was confirmed by secondary by-time point analysis and absence of relevant findings in the categorical outlier analysis. Daridorexant was safe and well tolerated and its pharmacokinetics were consistent with previous data.

CONCLUSION

Daridorexant does not impair cardiac repolarization evidenced by absence of relevant QT prolongation at therapeutic and supratherapeutic doses. Clinical Trials Registration ID: NCT04250506.

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC₅₀/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca²⁺-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca²⁺/late Na⁺ currents and Na⁺/Ca²⁺-exchanger, reduced Na⁺/K⁺-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na⁺ and Ca²⁺ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca²⁺-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

Quantitative Comparison of Effects of Dofetilide, Sotalol, Quinidine, and Verapamil between Human Ex vivo Trabeculae and In silico Ventricular Models Incorporating Inter-Individual Action Potential Variability

Background:In silico modeling could soon become a mainstream method of pro-arrhythmic risk assessment in drug development. However, a lack of human-specific data and appropriate modeling techniques has previously prevented quantitative comparison of drug effects between in silico models and recordings from human cardiac preparations. Here, we directly compare changes in repolarization biomarkers caused by dofetilide, dl-sotalol, quinidine, and verapamil, between in silico populations of human ventricular cell models and ex vivo human ventricular trabeculae. Methods and Results:Ex vivo recordings from human ventricular trabeculae in control conditions were used to develop populations of in silico human ventricular cell models that integrated intra- and inter-individual variability in action potential (AP) biomarker values. Models were based on the O'Hara-Rudy ventricular cardiomyocyte model, but integrated experimental AP variability through variation in underlying ionic conductances. Changes to AP duration, triangulation and early after-depolarization occurrence from application of the four drugs at multiple concentrations and pacing frequencies were compared between simulations and experiments. To assess the impact of variability in IC50 measurements, and the effects of including state-dependent drug binding dynamics, each drug simulation was repeated with two different IC50 datasets, and with both the original O'Hara-Rudy hERG model and a recently published state-dependent model of hERG and hERG block. For the selective hERG blockers dofetilide and sotalol, simulation predictions of AP prolongation and repolarization abnormality occurrence showed overall good agreement with experiments. However, for multichannel blockers quinidine and verapamil, simulations were not in agreement with experiments across all IC50 datasets and IKr block models tested. Quinidine simulations resulted in overprolonged APs and high incidence of repolarization abnormalities, which were not observed in experiments. Verapamil simulations showed substantial AP prolongation while experiments showed mild AP shortening. Conclusions: Results for dofetilide and sotalol show good agreement between experiments and simulations for selective compounds, however lack of agreement from simulations of quinidine and verapamil suggest further work is needed to understand the more complex electrophysiological effects of these multichannel blocking drugs.