Heart rhythm disorders are a major health problem. The underlying mechanisms for these arrhythmias remain unknown because the technology does not exist to characterize electrical activity throughout the heart during arrhythmias and probing candidate ionic mechanisms is difficult due to the lack of specific modulators of certain currents. One approach is to study cardiac electrical activity using computer models. However, their implementation is difficult and error-prone, they are computationally demanding, and there is no method for relating model parameters to wave propagation. To address these issues, we propose to develop a software platform for exploring these models. Phase I aims are: 1) Develop a flexible environment for simulating ionic models of a cardiac cell. 2) Incorporate techniques for integration, optimization, and sensitivity analysis of ordinary differential equations into the platform. Quantities that influence wave propagation will be generated and sensitivity analysis will determine the dependence of these quantities on model parameters. 3) Test the platform on several cardiac models and by comparing simulation and experimental results. Phase II will extend the platform by including a graphical user interface and by incorporating algorithms for simulating wave propagation. The final product will be a comprehensive platform for studying models of heart function.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43HL077938-01
Application #
6819492
Study Section
Special Emphasis Panel (ZRG1-CVS-H (10))
Program Officer
Dunn, Rosalie
Project Start
2004-09-15
Project End
2005-09-30
Budget Start
2004-09-15
Budget End
2005-09-30
Support Year
1
Fiscal Year
2004
Total Cost
$99,960
Indirect Cost
Name
Gene Network Sciences, Inc.
Department
Type
DUNS #
033322194
City
Cambridge
State
MA
Country
United States
Zip Code
02141
Rand, David G; Zhou, Qinlian; Buzzard, Gregery T et al. (2008) Computationally efficient strategy for modeling the effect of ion current modifiers. IEEE Trans Biomed Eng 55:3-13