Literature DB >> 30482568

Predicting critical drug concentrations and torsadogenic risk using a multiscale exposure-response simulator.

Francisco Sahli Costabal1, Jiang Yao2, Anna Sher3, Ellen Kuhl4.   

Abstract

Torsades de pointes is a serious side effect of many drugs that can trigger sudden cardiac death, even in patients with structurally normal hearts. Torsadogenic risk has traditionally been correlated with the blockage of a specific potassium channel and a prolonged recovery period in the electrocardiogram. However, the precise mechanisms by which single channel block translates into heart rhythm disorders remain incompletely understood. Here we establish a multiscale exposure-response simulator that converts block-concentration characteristics from single cell recordings into three-dimensional excitation profiles and electrocardiograms to rapidly assess torsadogenic risk. For the drug dofetilide, we characterize the QT interval and heart rate at different drug concentrations and identify the critical concentration at the onset of torsades de pointes: For dofetilide concentrations of 2x, 3x, and 4x, as multiples of the free plasma concentration Cmax = 2.1 nM, the QT interval increased by +62.0%, +71.2%, and +82.3% compared to baseline, and the heart rate changed by -21.7%, -23.3%, and +88.3%. The last number indicates that, at the critical concentration of 4x, the heart spontaneously developed an episode of a torsades-like arrhythmia. Strikingly, this critical drug concentration is higher than the concentration estimated from early afterdepolarizations in single cells and lower than in one-dimensional cable models. Our results highlight the importance of whole heart modeling and explain, at least in part, why current regulatory paradigms often fail to accurately quantify the pro-arrhythmic potential of a drug. Our exposure-response simulator could provide a more mechanistic assessment of pro-arrhythmic risk and help establish science-based guidelines to reduce rhythm disorders, design safer drugs, and accelerate drug development.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computational modeling; Early afterdepolarizations; Electrophysiology; Finite element analysis; Pharmacology; Torsades de pointes

Mesh:

Substances:

Year:  2018        PMID: 30482568      PMCID: PMC6483901          DOI: 10.1016/j.pbiomolbio.2018.10.003

Source DB:  PubMed          Journal:  Prog Biophys Mol Biol        ISSN: 0079-6107            Impact factor:   3.667


  67 in total

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Review 4.  Pharmacogenetics of Potassium Channel Blockers.

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8.  Simulation of multiple ion channel block provides improved early prediction of compounds' clinical torsadogenic risk.

Authors:  Gary R Mirams; Yi Cui; Anna Sher; Martin Fink; Jonathan Cooper; Bronagh M Heath; Nick C McMahon; David J Gavaghan; Denis Noble
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9.  Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct Features.

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Journal:  Front Pharmacol       Date:  2017-11-14       Impact factor: 5.810

10.  Evaluation of an in silico cardiac safety assay: using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge.

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