Early-stage diagnosis and continuous non-invasive monitoring of coagulopathies is a challenging problem that has been exacerbated by the COVID-19 pandemic. In this context, viscoelastic characterisation of the whole blood and plasma represents an excellent diagnosis approach, incorporating implicitly several molecular factors. However, a careful interpretation of coagulation abnormalities and adaptation of the techniques to the new disease is needed. ViBRheo aims to construct a novel computational multiscale framework able to detect alterations in blood rheology during clot formations. The framework will account for variations of viscometric properties at clinically-relevant conditions, whereas incorporating large memory effects related to coagulation kinetics from the microscales. Our goal is to translate research models into clinical applications. Thus, facilitating the virtual calibration and the design of microfluidic devices to extract microstructural features of blood undergoing clotting. Additionally, ViBRheo will potentially lead to the definition of mechanistic biomarkers for early detection and easier monitoring of acute coagulopathy on COVID-19 patients. ViBRheo will count on the support of an interdisciplinary team, with broad expertise on medicine, modelling, engineering, physics, and applied mathematics. Furthermore, it will promote theoretical/experimental exchange on hemorheological results. The development of a computational tool is in line with the 2030 UN Sustainable Development Goals. It facilitates early response to unprecedented diseases with broad applicability in coagulation disorders, beyond the current COVID19-related coagulopathies.
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