Modelling the heart: insights, failures and progress

Abstract

SummaryMathematical models of the heart have developed over a period of about 40 years. Cell types in all regions of the heart have been modelled and they are now being incorporated into anatomically detailed models of the whole organ. This combination is leading to the creation of the first 'virtual organ,' which is being used in drug discovery and testing, and in simulating the action of devices, such as cardiac defibrillators. Simulation is a necessary tool of analysis in attempting to understand biological complexity. We often learn as much from the failures as from the successes of mathematical models. It is the iterative interaction between experiment and simulation that is important. Examples are given where this process has been instrumental in some of the major advances in the field.

Tachycardia as "Shadow Play"

“…In any case, all models are only partial representations of reality. One of the first questions to ask of a model therefore is what questions does it answer best" (Noble, 2002b). So, appropriate collection of cardiac models is believed to improve both diagnostics and treatment.…”

“…<…> It is however already clear that incorporation of cell models into tissue and organ models is capable of spectacular insights. <…> The potential of such simulations for teaching, drug discovery, device development, and, of course, for pure physiological insight is only beginning to be appreciated" (Noble, 2002b). Integrative physiology of the 21st century is set to become highly quantitative and, therefore, one of the most computer-intensive disciplines (Crampin et al, 2004;Noble, 2002a).…”

Bridging proteomics and systems biology: What are the roads to be traveled?

“…It defines an interval of time and frequency of data collection, which are required for capturing features of a modeled process. The shortest time scale is characteristic for chemical reactions with proteins; PTMs and protein-protein interactions occur in milliseconds to seconds [82][83][84]. An accumulation of modified proteins may take a longer time, although accumulation rates are dependent on parameters of fast reactions with single proteins.…”

“…The time frames of such processes may vary from milliseconds to hours. Examples of processes with a short lag period are electro-physiological reactions: it takes milliseconds to generate an active potential in neurons [82]. The intracellular signaling process initiated by growth factors may take from minutes to hours [3,79].…”

“…Systems biology develops tools which make possible combination of datasets generated by various techniques, such as transcriptomics, proteomics and metabolomics data [3,4,82,[110][111][112][113]. These techniques have developed tools for acquisition and presentation of data in an interchangeable format, e.g., XML-supporting MIAME, PEDRo, MAGE-ML.…”