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Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease

Cardiomyopathy is associated with structural and functional abnormalities of the ventricular myocardium and can be classified in two major groups: hypertrophic (HCM) and dilated (DCM) cardiomyopathy. Computational modeling and drug design approaches can speed up the drug discovery and significantly...

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Autores principales: Tomasevic, Smiljana, Milosevic, Miljan, Milicevic, Bogdan, Simic, Vladimir, Prodanovic, Momcilo, Mijailovich, Srboljub M., Filipovic, Nenad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058954/
https://www.ncbi.nlm.nih.gov/pubmed/36986654
http://dx.doi.org/10.3390/pharmaceutics15030793
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author Tomasevic, Smiljana
Milosevic, Miljan
Milicevic, Bogdan
Simic, Vladimir
Prodanovic, Momcilo
Mijailovich, Srboljub M.
Filipovic, Nenad
author_facet Tomasevic, Smiljana
Milosevic, Miljan
Milicevic, Bogdan
Simic, Vladimir
Prodanovic, Momcilo
Mijailovich, Srboljub M.
Filipovic, Nenad
author_sort Tomasevic, Smiljana
collection PubMed
description Cardiomyopathy is associated with structural and functional abnormalities of the ventricular myocardium and can be classified in two major groups: hypertrophic (HCM) and dilated (DCM) cardiomyopathy. Computational modeling and drug design approaches can speed up the drug discovery and significantly reduce expenses aiming to improve the treatment of cardiomyopathy. In the SILICOFCM project, a multiscale platform is developed using coupled macro- and microsimulation through finite element (FE) modeling of fluid–structure interactions (FSI) and molecular drug interactions with the cardiac cells. FSI was used for modeling the left ventricle (LV) with a nonlinear material model of the heart wall. Simulations of the drugs’ influence on the electro-mechanics LV coupling were separated in two scenarios, defined by the principal action of specific drugs. We examined the effects of Disopyramide and Dygoxin which modulate Ca(2+) transients (first scenario), and Mavacamten and 2-deoxy adenosine triphosphate (dATP) which affect changes of kinetic parameters (second scenario). Changes of pressures, displacements, and velocity distributions, as well as pressure–volume (P-V) loops in the LV models of HCM and DCM patients were presented. Additionally, the results obtained from the SILICOFCM Risk Stratification Tool and PAK software for high-risk HCM patients closely followed the clinical observations. This approach can give much more information on risk prediction of cardiac disease to specific patients and better insight into estimated effects of drug therapy, leading to improved patient monitoring and treatment.
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spelling pubmed-100589542023-03-30 Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease Tomasevic, Smiljana Milosevic, Miljan Milicevic, Bogdan Simic, Vladimir Prodanovic, Momcilo Mijailovich, Srboljub M. Filipovic, Nenad Pharmaceutics Article Cardiomyopathy is associated with structural and functional abnormalities of the ventricular myocardium and can be classified in two major groups: hypertrophic (HCM) and dilated (DCM) cardiomyopathy. Computational modeling and drug design approaches can speed up the drug discovery and significantly reduce expenses aiming to improve the treatment of cardiomyopathy. In the SILICOFCM project, a multiscale platform is developed using coupled macro- and microsimulation through finite element (FE) modeling of fluid–structure interactions (FSI) and molecular drug interactions with the cardiac cells. FSI was used for modeling the left ventricle (LV) with a nonlinear material model of the heart wall. Simulations of the drugs’ influence on the electro-mechanics LV coupling were separated in two scenarios, defined by the principal action of specific drugs. We examined the effects of Disopyramide and Dygoxin which modulate Ca(2+) transients (first scenario), and Mavacamten and 2-deoxy adenosine triphosphate (dATP) which affect changes of kinetic parameters (second scenario). Changes of pressures, displacements, and velocity distributions, as well as pressure–volume (P-V) loops in the LV models of HCM and DCM patients were presented. Additionally, the results obtained from the SILICOFCM Risk Stratification Tool and PAK software for high-risk HCM patients closely followed the clinical observations. This approach can give much more information on risk prediction of cardiac disease to specific patients and better insight into estimated effects of drug therapy, leading to improved patient monitoring and treatment. MDPI 2023-02-28 /pmc/articles/PMC10058954/ /pubmed/36986654 http://dx.doi.org/10.3390/pharmaceutics15030793 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tomasevic, Smiljana
Milosevic, Miljan
Milicevic, Bogdan
Simic, Vladimir
Prodanovic, Momcilo
Mijailovich, Srboljub M.
Filipovic, Nenad
Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease
title Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease
title_full Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease
title_fullStr Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease
title_full_unstemmed Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease
title_short Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease
title_sort computational modeling on drugs effects for left ventricle in cardiomyopathy disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058954/
https://www.ncbi.nlm.nih.gov/pubmed/36986654
http://dx.doi.org/10.3390/pharmaceutics15030793
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