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In silico assessment on TdP risks of drug combinations under CiPA paradigm
Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines’ TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medicati...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9940090/ https://www.ncbi.nlm.nih.gov/pubmed/36807374 http://dx.doi.org/10.1038/s41598-023-29208-5 |
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author | Qauli, Ali Ikhsanul Marcellinus, Aroli Setiawan, Muhammad Aldo Zain, Andi Faiz Naufal Pinandito, Azka Muhammad Lim, Ki Moo |
author_facet | Qauli, Ali Ikhsanul Marcellinus, Aroli Setiawan, Muhammad Aldo Zain, Andi Faiz Naufal Pinandito, Azka Muhammad Lim, Ki Moo |
author_sort | Qauli, Ali Ikhsanul |
collection | PubMed |
description | Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines’ TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when limited drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models on several ion channels for various drug pairs. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as biomarker features. The drug combination maps were also used to illustrate combined medicines' TdP risk. We found that the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations. |
format | Online Article Text |
id | pubmed-9940090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99400902023-02-21 In silico assessment on TdP risks of drug combinations under CiPA paradigm Qauli, Ali Ikhsanul Marcellinus, Aroli Setiawan, Muhammad Aldo Zain, Andi Faiz Naufal Pinandito, Azka Muhammad Lim, Ki Moo Sci Rep Article Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines’ TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when limited drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models on several ion channels for various drug pairs. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as biomarker features. The drug combination maps were also used to illustrate combined medicines' TdP risk. We found that the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations. Nature Publishing Group UK 2023-02-20 /pmc/articles/PMC9940090/ /pubmed/36807374 http://dx.doi.org/10.1038/s41598-023-29208-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Qauli, Ali Ikhsanul Marcellinus, Aroli Setiawan, Muhammad Aldo Zain, Andi Faiz Naufal Pinandito, Azka Muhammad Lim, Ki Moo In silico assessment on TdP risks of drug combinations under CiPA paradigm |
title | In silico assessment on TdP risks of drug combinations under CiPA paradigm |
title_full | In silico assessment on TdP risks of drug combinations under CiPA paradigm |
title_fullStr | In silico assessment on TdP risks of drug combinations under CiPA paradigm |
title_full_unstemmed | In silico assessment on TdP risks of drug combinations under CiPA paradigm |
title_short | In silico assessment on TdP risks of drug combinations under CiPA paradigm |
title_sort | in silico assessment on tdp risks of drug combinations under cipa paradigm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9940090/ https://www.ncbi.nlm.nih.gov/pubmed/36807374 http://dx.doi.org/10.1038/s41598-023-29208-5 |
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