4.5 Review

Computational modelling of biological systems: tools and visions

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ROYAL SOC
DOI: 10.1098/rsta.2000.0547

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Physiome; mathematical model; heart; ion current; in silico

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We are currently witnessing the advent of a revolutionary new tool for biomedical research. Complex biochemically, biophysically and pharmacologically detailed mathematical models of 'living cells' are being arranged in morphologically representative tissue assemblies, and, using large-scale supercomputers, utilized to produce anatomically structured models of integrated tissue and organ function. This provides biomedical sciences with a radical new tool: 'in. silico' organs, organ systems and, ultimately, organisms. In silico models will be a crucial tool for biomedical research and development in the new millennium, extracting knowledge from the vast amount of increasingly detailed data, and integrating this into a comprehensive analytical description of biological function with predictive power: the Physiome. Our review will illustrate this approach using the example of the cardiovascular system, which, along with neurophysiology, has been at, the forefront of analytical bio-mathematical modelling for many years, and which is about to deliver the first anatomico-physiological model of a whole organ. Already, electrophysiologically detailed cardiac cell models have been incorporated into mathematical descriptions of representative ventricular tissue architecture and anatomy, including the coronary vasculature. and assimilated to realistic representation of ventricular active and passive mechanical properties. This is being extended by matching atrial models and linked to an artificial torso to compute the body surface electrocardiogram as a function of sub-cellular activity during various (patho-)physiological conditions. We will illustrate the utility of in silico biological research in the context of refinement and partial replacement of in vivo and in vitro experimental work, show the potential of this approach for devising patient-specific treatment strategies, and try to forecast the impact. of this new technology on biomedical research, health-care, and related industries.

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