A multiformalism and multiresolution modelling environment: application to the cardiovascular system and its...

Area of Science:

• Computational Biology
• Systems Biology
• Physiological Modeling

Background:

• Modeling and simulation are crucial for systemic analysis of living systems.
• Emerging disciplines like systems biology rely heavily on these methodologies.
• Efficient integration of diverse models across scales and resolutions is a key challenge.

Purpose of the Study:

• To present a multiformalism modeling and simulation environment (M2SL) that facilitates model integration.
• To address the challenge of integrating heterogeneous models in systems biology and physiological research.

Main Methods:

• Developed M2SL, a multiformalism modeling and simulation environment.
• Represented models as coupled, atomic components with heterogeneous properties.
• Employed a co-simulation approach to solve hybrid systems.
• Implemented Guyton's cardiovascular regulation model and a pulsatile ventricular model.

Main Results:

• Demonstrated the integration of diverse models within M2SL.
• Successfully simulated physiological conditions using different coupling methods.
• Showcased the benefits of the M2SL environment for multi-resolution modeling.

Conclusions:

• M2SL effectively eases the integration of multiformalism models for complex biological systems.
• The environment supports multi-resolution approaches, enhancing physiological simulations.
• Co-simulation is a viable method for solving hybrid systems in physiological modeling.