Key result
Computational models in hemostasis and thrombosis are progressing toward efficient virtual thrombus formation, though most currently focus on simulating individual elements rather than total responses.
Why the study?
Most computational models in hemostasis and thrombosis focus on simulating individual elements rather than the total pathophysiological response in situ.
This review highlights the progress and current applications of computational modeling in simulating hemostasis and thrombosis.
This is the authors' abstract. We don't add key points for this paper.
Computational physiology, i.e., reproduction of physiological (and, by extension, pathophysiological) processes in silico, could be considered one of the major goals in computational biology. One might use computers to simulate molecular interactions, enzyme kinetics, gene expression, or whole networks of biochemical reactions, but it is (patho)physiological meaning that is usually the meaningful goal of the research even when a single enzyme is its subject. Although exponential rise in the use of computational and mathematical models in the field of hemostasis and thrombosis began in the 1980s (first for blood coagulation, then for platelet adhesion, and finally for platelet signal transduction), the majority of their successful applications are still focused on simulating the elements of the hemostatic system rather than the total (patho)physiological response in situ. Here we discuss the state of the art, the state of the progress toward the efficient "virtual thrombus formation," and what one can already get from the existing models.
Supports development of virtual thrombus models; leaves open translation to clinical hemostasis practice pending whole-system validation.
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Nechipurenko et al. (2020) conducted a review in Hemostasis and thrombosis. In silico hemostasis modeling was evaluated. Computational models in hemostasis and thrombosis are progressing toward efficient virtual thrombus formation, though most currently focus on simulating individual elements rather than total responses.
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