Medicine is moving from reacting to a disease to prepare personalised and precision paths to well being . The complex and multi level pathophysiological patterns of most diseases require a systemic medicine approach and are challenging current medical therapies. Computational medicine is a vibrant interdisciplinary field that could help moving from URLan-centered  to a process-oriented or systemic medicine data analysis. The resulting Computational patient may require an international interdisciplinary effort, probably of larger scientific and technological interdisciplinarity than the human genome sequencing . When deployed, it will have a profound impact on how healthcare is delivered to patients. Here we present a Computational patient model that integrates, refine and extend recent specific mechanistic or phenomenological models of cardiovascular, RAS and diabetic processes. Our aim is twofold: analyse the modularity and composability of the models-building blocks of the Computational patient and to study the dynamical properties of well-being and disease states in a broader functional context. We present results from a number of experiments among which we characterise the dynamical impact of covid-19 and T2D diabetes on cardiovascular and inflammation conditions. We tested these experiments under exercise and meals and drug regimen . We report results showing the striking importance of transient dynamical responses to acute state conditions and we provide guidelines for system design principle of the inter-relationship between modules and components for systemic medicine. Finally this initial Computational Patient can be used as a toolbox for further modifications and extensions.
Medicine is moving from a curative discipline to a preventative discipline relying on personalised and precise treatment plans . The complex and multi level pathophysiological patterns of most diseases require a systemic medicine approach and are challenging current medical therapies. On the other hand, computational medicine is a vibrant interdisciplinary field that could help move from URLan-centered approach to a process-oriented approach. The ideal computational patient would require an international interdisciplinary effort, of larger scientific and technological interdisciplinarity than the Human Genome Project . When deployed, such a patient would have a profound impact on how healthcare is delivered to patients. Here we present a computational patient model that integrates, refines and extends recent mechanistic or phenomenological models of cardiovascular, RAS and diabetic processes. Our aim is twofold: analyse the modularity and composability of the model-building blocks of the computational patient and to study the dynamical properties of well-being and disease states in a broader functional context. We present results from a number of experiments among which we characterise the dynamic impact of COVID-19 and type-2 diabetes (T2D) on cardiovascular and inflammation conditions. We tested these experiments under different exercise, meal and drug regimens . We report results showing the striking importance of transient dynamical responses to acute state conditions and we provide guidelines for system design principles for the inter-relationship between modules and components in systemic medicine. Finally this initial computational Patient can be used as a toolbox for further modifications and extensions.
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reacting to a disease to prepare personalised and precision paths to well being
a curative discipline to a preventative discipline relying on personalised and precise treatment plans
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Computational
On the other hand, computational
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moving
move
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approach
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or systemic medicine data analysis. The resulting Computational patient may
approach. The ideal computational patient would
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probably
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human genome sequencing
Human Genome Project
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it will
such a patient would
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Computational
computational
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refine and extend recent specific
refines and extends recent
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models-building
model-building
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Computational
computational
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dynamical impact of covid-19 and T2D diabetes
dynamic impact of COVID-19 and type-2 diabetes (T2D)
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exercise and meals and drug regimen
different exercise, meal and drug regimens
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principle of
principles for
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for
in
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Computational
computational