Computational modeling is a powerful tool for studying complex biological processes such as "the heart." These models are used to understand mechanisms in the heart better and, for example, predict how safe a drug is. Computational models of the heart have been developed by integrating experimental and clinical data to provide more accurate results and expand the application of models. In this workshop, participants will be introduced to some key concepts of the heart's function and how this is translated into a computer model. With this knowledge, you can learn more about the heart and how it reacts to changes in heart rate and (new) medication options by simulating a heart cell yourself!
Learning outcomes
- Get an insight into computational cardiac modeling
- Become exposed to possible power and applications of cardiac modeling
- Be able to simulate a cardiac cell in various circumstances
- Know about the work done at the Computational Physiology department at Simula
- Get insight into an open-source cell and 3D cardiac electromechanics solver (SimCarDEMS).
Prerequisites
To run simulations yourself, knowledge of Python programming is required. No other previous knowledge is required, but interest in computational modeling and/or cardiac mechanisms is beneficial.
Target audience
Students and researchers with interest in computational cardiac modeling and drug development.
Required Materials
A laptop.