Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease

Author:

Tomasevic Smiljana12,Milosevic Miljan23ORCID,Milicevic Bogdan12,Simic Vladimir23ORCID,Prodanovic Momcilo234ORCID,Mijailovich Srboljub M.45ORCID,Filipovic Nenad12ORCID

Affiliation:

1. Faculty of Engineering, University of Kragujevac, 34000 Kragujevac, Serbia

2. BioIRC Bioengineering Research and Development Center, 34000 Kragujevac, Serbia

3. Institute for Information Technologies, University of Kragujevac, 34000 Kragujevac, Serbia

4. FilamenTech, Inc., Newton, MA 02458, USA

5. BioCAT, Department of Biology, Illinois Institute of Technology, Chicago, IL 60616, USA

Abstract

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 Ca2+ 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.

Funder

European Union’s Horizon 2020 research and innovation programmes SILICOFCM

SGABU

Serbian Ministry of Education, Science, and Technological Development

Faculty of Engineering, University of Kragujevac

Publisher

MDPI AG

Subject

Pharmaceutical Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3