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The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation
Computational modelling is a cornerstone of Comprehensive In Vitro Proarrhythmia Assay and is re-increasingly being used in drug development. Electrophysiological effects of drug-drug interactions can be predicted in silico, e.g. with the use of in vitro cardiac ion channel data, PK profiles and hum...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5114317/ https://www.ncbi.nlm.nih.gov/pubmed/27917367 http://dx.doi.org/10.1007/s40495-016-0075-9 |
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author | Wiśniowska, Barbara Polak, Sebastian |
author_facet | Wiśniowska, Barbara Polak, Sebastian |
author_sort | Wiśniowska, Barbara |
collection | PubMed |
description | Computational modelling is a cornerstone of Comprehensive In Vitro Proarrhythmia Assay and is re-increasingly being used in drug development. Electrophysiological effects of drug-drug interactions can be predicted in silico, e.g. with the use of in vitro cardiac ion channel data, PK profiles and human ventricular cardiomyocyte models. There are, however, several approaches with different assumptions used to assess the combined effect of multiple drugs, and there is no agreed standard interaction model. The aim of this study was to assess whether the choice of the drug-drug interaction (DDI) model (Bliss independence, Loewe additivity, or simple sum) influences the results of QT interval simulation trial. The Simcyp Simulator version 12.1 (Simcyp Ltd. [part of Certara], Sheffield, UK) and Cardiac Safety Simulator 2.0 (Simcyp Ltd. [part of Certara], Sheffield, UK) were used to simulate results of 8 virtual trials mimicking clinical studies and generate individual QTc data. The combined effect of inhibitory actions of drugs which were given simultaneously was calculated with use of three different interaction models. The PD effect of DDI was assessed and the differences between mean observed and mean predicted ΔQTcB values for terfenadine interactions were not statistically significant in all but one cases. Differences between the three DDI models are not statistically significant, implying that the choice of the DDI model, in the case of lack of synergy or antagonism, is irrelevant to the average predicted effect at the clinical level. However, in some cases, it can influence the verdict on combinatorial therapy safety for individual patients. |
format | Online Article Text |
id | pubmed-5114317 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-51143172016-12-02 The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation Wiśniowska, Barbara Polak, Sebastian Curr Pharmacol Rep Pharmacometrics (H Kimko, Section Editor) Computational modelling is a cornerstone of Comprehensive In Vitro Proarrhythmia Assay and is re-increasingly being used in drug development. Electrophysiological effects of drug-drug interactions can be predicted in silico, e.g. with the use of in vitro cardiac ion channel data, PK profiles and human ventricular cardiomyocyte models. There are, however, several approaches with different assumptions used to assess the combined effect of multiple drugs, and there is no agreed standard interaction model. The aim of this study was to assess whether the choice of the drug-drug interaction (DDI) model (Bliss independence, Loewe additivity, or simple sum) influences the results of QT interval simulation trial. The Simcyp Simulator version 12.1 (Simcyp Ltd. [part of Certara], Sheffield, UK) and Cardiac Safety Simulator 2.0 (Simcyp Ltd. [part of Certara], Sheffield, UK) were used to simulate results of 8 virtual trials mimicking clinical studies and generate individual QTc data. The combined effect of inhibitory actions of drugs which were given simultaneously was calculated with use of three different interaction models. The PD effect of DDI was assessed and the differences between mean observed and mean predicted ΔQTcB values for terfenadine interactions were not statistically significant in all but one cases. Differences between the three DDI models are not statistically significant, implying that the choice of the DDI model, in the case of lack of synergy or antagonism, is irrelevant to the average predicted effect at the clinical level. However, in some cases, it can influence the verdict on combinatorial therapy safety for individual patients. Springer International Publishing 2016-10-27 2016 /pmc/articles/PMC5114317/ /pubmed/27917367 http://dx.doi.org/10.1007/s40495-016-0075-9 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Pharmacometrics (H Kimko, Section Editor) Wiśniowska, Barbara Polak, Sebastian The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation |
title | The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation |
title_full | The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation |
title_fullStr | The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation |
title_full_unstemmed | The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation |
title_short | The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation |
title_sort | role of interaction model in simulation of drug interactions and qt prolongation |
topic | Pharmacometrics (H Kimko, Section Editor) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5114317/ https://www.ncbi.nlm.nih.gov/pubmed/27917367 http://dx.doi.org/10.1007/s40495-016-0075-9 |
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