» Articles » PMID: 28868038

Quantitative Comparison of Effects of Dofetilide, Sotalol, Quinidine, and Verapamil Between Human Trabeculae and Ventricular Models Incorporating Inter-Individual Action Potential Variability

Overview
Journal Front Physiol
Date 2017 Sep 5
PMID 28868038
Citations 28
Authors
Affiliations
Soon will be listed here.
Abstract

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 models and recordings from human cardiac preparations. Here, we directly compare changes in repolarization biomarkers caused by dofetilide, dl-sotalol, quinidine, and verapamil, between populations of human ventricular cell models and human ventricular trabeculae. recordings from human ventricular trabeculae in control conditions were used to develop populations of 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 I 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. 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.

Citing Articles

CardioGenAI: a machine learning-based framework for re-engineering drugs for reduced hERG liability.

Kyro G, Martin M, Watt E, Batista V J Cheminform. 2025; 17(1):30.

PMID: 40045386 PMC: 11881490. DOI: 10.1186/s13321-025-00976-8.


Contractility measurements for cardiotoxicity screening with ventricular myocardial slices of pigs.

Shi R, Reichardt M, Fiegle D, Kupfer L, Czajka T, Sun Z Cardiovasc Res. 2023; 119(14):2469-2481.

PMID: 37934066 PMC: 10651213. DOI: 10.1093/cvr/cvad141.


The importance of mechanical conditions in the testing of excitation abnormalities in a population of electro-mechanical models of human ventricular cardiomyocytes.

Dokuchaev A, Kursanov A, Balakina-Vikulova N, Katsnelson L, Solovyova O Front Physiol. 2023; 14:1187956.

PMID: 37362439 PMC: 10285544. DOI: 10.3389/fphys.2023.1187956.


Action potential metrics and automated data analysis pipeline for cardiotoxicity testing using optically mapped hiPSC-derived 3D cardiac microtissues.

Soepriatna A, Navarrete-Welton A, Kim T, Daley M, Bronk P, Kofron C PLoS One. 2023; 18(2):e0280406.

PMID: 36745602 PMC: 9901774. DOI: 10.1371/journal.pone.0280406.


Integrative Computational Modeling of Cardiomyocyte Calcium Handling and Cardiac Arrhythmias: Current Status and Future Challenges.

Sutanto H, Heijman J Cells. 2022; 11(7).

PMID: 35406654 PMC: 8997666. DOI: 10.3390/cells11071090.


References
1.
Li Z, Dutta S, Sheng J, Tran P, Wu W, Chang K . Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-à-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology. Circ Arrhythm Electrophysiol. 2017; 10(2):e004628. DOI: 10.1161/CIRCEP.116.004628. View

2.
Jeyaraj D, Haldar S, Wan X, McCauley M, Ripperger J, Hu K . Circadian rhythms govern cardiac repolarization and arrhythmogenesis. Nature. 2012; 483(7387):96-9. PMC: 3297978. DOI: 10.1038/nature10852. View

3.
Qi X, Yeh Y, Xiao L, Burstein B, Maguy A, Chartier D . Cellular signaling underlying atrial tachycardia remodeling of L-type calcium current. Circ Res. 2008; 103(8):845-54. DOI: 10.1161/CIRCRESAHA.108.175463. View

4.
Vargas H, Bass A, Koerner J, Matis-Mitchell S, Pugsley M, Skinner M . Evaluation of drug-induced QT interval prolongation in animal and human studies: a literature review of concordance. Br J Pharmacol. 2015; 172(16):4002-11. PMC: 4543608. DOI: 10.1111/bph.13207. View

5.
Piccini J, Whellan D, Berridge B, Finkle J, Pettit S, Stockbridge N . Current challenges in the evaluation of cardiac safety during drug development: translational medicine meets the Critical Path Initiative. Am Heart J. 2009; 158(3):317-26. DOI: 10.1016/j.ahj.2009.06.007. View