Thrombus formation is one of the main issues in the development of blood-contacting medical devices. This article focuses on the modeling of one aspect of thrombosis, the coagulation cascade, which is initiated by the contact activation at the device surface and forms thrombin. Models exist representing the coagulation cascade by a series of reactions, usually solved in quiescent plasma. However, large parameter uncertainty involved in the kinetic models can affect the predictive capabilities of this approach. In addition, the large number of reactions of the kinetic models prevents their use in the simulation of complex flow configurations encountered in medical devices. In the current work, both issues are addressed to improve the applicability and fidelity of kinetic models. A sensitivity analysis is performed by two different techniques to identify the most sensitive parameters of an existing detailed kinetic model of the coagulation cascade. The results are used to select the form of a novel reduced model of the coagulation cascade which relies on eight chemical reactors only. Then, once its parameters have been calibrated thanks to the Bayesian inference, this

Thrombosis is a major concern in blood-coated medical devices. Contact activation, which is the initial part of the coagulation cascade in device-related thrombosis, is not considered in current thrombus formation models. In the present study, pro-coagulant reactions including the contact activation system are coupled with a fluid solver in order to evaluate the potential of the contact system to initiate thrombin production. The biochemical/fluid model is applied to a backward-facing step configuration, a flow configuration that frequently appears in medical devices. In contrast to the in vivo thrombosis models in which a specific thrombotic zone (injury region) is set a priori by the user to initiate the coagulation reaction, a reactive surface boundary condition is applied to the whole device wall. Simulation results show large thrombin concentration in regions related to recirculation zones without the need of an a priori knowledge of the thrombus location. The numerical results align well with the regions prone to thrombosis observed in experimental results reported in the literature. This approach could complement thrombus formation models that take into account platelet activity and thrombus growth to optimize a wide range of medical devices.

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