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Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge
INTRODUCTION: Drugs that prolong the QT interval on the electrocardiogram present a major safety concern for pharmaceutical companies and regulatory agencies. Despite a range of assays performed to assess compound effects on the QT interval, QT prolongation remains a major cause of attrition during...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4142193/ https://www.ncbi.nlm.nih.gov/pubmed/23624022 http://dx.doi.org/10.1016/j.vascn.2013.04.004 |
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author | Beattie, Kylie A. Luscombe, Chris Williams, Geoff Munoz-Muriedas, Jordi Gavaghan, David J. Cui, Yi Mirams, Gary R. |
author_facet | Beattie, Kylie A. Luscombe, Chris Williams, Geoff Munoz-Muriedas, Jordi Gavaghan, David J. Cui, Yi Mirams, Gary R. |
author_sort | Beattie, Kylie A. |
collection | PubMed |
description | INTRODUCTION: Drugs that prolong the QT interval on the electrocardiogram present a major safety concern for pharmaceutical companies and regulatory agencies. Despite a range of assays performed to assess compound effects on the QT interval, QT prolongation remains a major cause of attrition during compound development. In silico assays could alleviate such problems. In this study we evaluated an in silico method of predicting the results of a rabbit left-ventricular wedge assay. METHODS: Concentration–effect data were acquired from either: the high-throughput IonWorks/FLIPR; the medium-throughput PatchXpress ion channel assays; or QSAR, a statistical IC(50) value prediction model, for hERG, fast sodium, L-type calcium and KCNQ1/minK channels. Drug block of channels was incorporated into a mathematical differential equation model of rabbit ventricular myocyte electrophysiology through modification of the maximal conductance of each channel by a factor dependent on the IC(50) value, Hill coefficient and concentration of each compound tested. Simulations were performed and agreement with experimental results, based upon input data from the different assays, was evaluated. RESULTS: The assay was found to be 78% accurate, 72% sensitive and 81% specific when predicting QT prolongation (>10%) using PatchXpress assay data (77 compounds). Similar levels of predictivity were demonstrated using IonWorks/FLIPR data (121 compounds) with 78% accuracy, 73% sensitivity and 80% specificity. QT shortening (<−10%) was predicted with 77% accuracy, 33% sensitivity and 90% specificity using PatchXpress data and 71% accuracy, 42% sensitivity and 81% specificity using IonWorks/FLIPR data. Strong quantitative agreement between simulation and experimental results was also evident. DISCUSSION: The in silico action potential assay demonstrates good predictive ability, and is suitable for very high-throughput use in early drug development. Adoption of such an assay into cardiovascular safety assessment, integrating ion channel data from routine screens to infer results of animal-based tests, could provide a cost- and time-effective cardiac safety screen. |
format | Online Article Text |
id | pubmed-4142193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
record_format | MEDLINE/PubMed |
spelling | pubmed-41421932014-08-24 Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge Beattie, Kylie A. Luscombe, Chris Williams, Geoff Munoz-Muriedas, Jordi Gavaghan, David J. Cui, Yi Mirams, Gary R. J Pharmacol Toxicol Methods Article INTRODUCTION: Drugs that prolong the QT interval on the electrocardiogram present a major safety concern for pharmaceutical companies and regulatory agencies. Despite a range of assays performed to assess compound effects on the QT interval, QT prolongation remains a major cause of attrition during compound development. In silico assays could alleviate such problems. In this study we evaluated an in silico method of predicting the results of a rabbit left-ventricular wedge assay. METHODS: Concentration–effect data were acquired from either: the high-throughput IonWorks/FLIPR; the medium-throughput PatchXpress ion channel assays; or QSAR, a statistical IC(50) value prediction model, for hERG, fast sodium, L-type calcium and KCNQ1/minK channels. Drug block of channels was incorporated into a mathematical differential equation model of rabbit ventricular myocyte electrophysiology through modification of the maximal conductance of each channel by a factor dependent on the IC(50) value, Hill coefficient and concentration of each compound tested. Simulations were performed and agreement with experimental results, based upon input data from the different assays, was evaluated. RESULTS: The assay was found to be 78% accurate, 72% sensitive and 81% specific when predicting QT prolongation (>10%) using PatchXpress assay data (77 compounds). Similar levels of predictivity were demonstrated using IonWorks/FLIPR data (121 compounds) with 78% accuracy, 73% sensitivity and 80% specificity. QT shortening (<−10%) was predicted with 77% accuracy, 33% sensitivity and 90% specificity using PatchXpress data and 71% accuracy, 42% sensitivity and 81% specificity using IonWorks/FLIPR data. Strong quantitative agreement between simulation and experimental results was also evident. DISCUSSION: The in silico action potential assay demonstrates good predictive ability, and is suitable for very high-throughput use in early drug development. Adoption of such an assay into cardiovascular safety assessment, integrating ion channel data from routine screens to infer results of animal-based tests, could provide a cost- and time-effective cardiac safety screen. 2013-04-25 2013 /pmc/articles/PMC4142193/ /pubmed/23624022 http://dx.doi.org/10.1016/j.vascn.2013.04.004 Text en © 2013 The Authors. Published by Elsevier Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original author and source are credited. |
spellingShingle | Article Beattie, Kylie A. Luscombe, Chris Williams, Geoff Munoz-Muriedas, Jordi Gavaghan, David J. Cui, Yi Mirams, Gary R. Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge |
title | Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge |
title_full | Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge |
title_fullStr | Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge |
title_full_unstemmed | Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge |
title_short | Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge |
title_sort | evaluation of an in silico cardiac safety assay: using ion channel screening data to predict qt interval changes in the rabbit ventricular wedge |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4142193/ https://www.ncbi.nlm.nih.gov/pubmed/23624022 http://dx.doi.org/10.1016/j.vascn.2013.04.004 |
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