Background: Blood coagulation is a complex network of biochemical reactions, which is peculiar in that it is time- and space-dependent, and has to function in the presence of rapid flow. Recent experimental reports suggest that flow plays a significant role in its regulation. The objective of this study was to use systems biology techniques to investigate this regulation and to identify mechanisms creating a flow-dependent switch in the coagulation onset. Results: Using a detailed mechanism-driven model of tissue factor (TF)-initiated thrombus formation in a two-dimensional channel we demonstrate that blood flow can regulate clotting onset in the model in a threshold-like manner, in agreement with existing experimental evidence. Sensitivity analysis reveals that this is achieved due to a combination of the positive feedback of TF-bound factor VII activation by activated factor X (Xa) and effective removal of factor Xa by flow from the activating patch depriving the feedback of "ignition". The level of this trigger (i.e. coagulation sensitivity to flow) is controlled by the activity of tissue factor pathway inhibitor. Conclusions: This mechanism explains the difference between red and white thrombi observed in vivo at different shear rates. It can be speculated that this is a special switch protecting vascular system from uncontrolled formation and spreading of active coagulation factors in vessels with rapidly flowing blood.

Recombinant factor VIIa (rFVIIa) is used for treatment of hemophilia patients with inhibitors, as well for off-label treatment of severe bleeding in trauma and surgery. Effective bleeding control requires supraphysiological doses of rFVIIa, posing both high expense and uncertain thrombotic risk. Two major competing theories offer different explanations for the supraphysiological rFVIIa dosing requirement: (1) the need to overcome competition between FVIIa and FVII zymogen for tissue factor (TF) binding, and (2) a high-dose–requiring phospholipid-related pathway of FVIIa action. In the present study, we found experimental conditions in which both mechanisms contribute simultaneously and independently to rFVIIa-driven thrombin generation in FVII-deficient human plasma. From mathematical simulations of our model of FX activation, which were confirmed by thrombin-generation experiments, we conclude that the action of rFVIIa at pharmacologic doses is dominated by the TF-dependent pathway with a minor contribution from a phospholipid-dependent mechanism. We established a dose-response curve for rFVIIa that is useful to explain dosing strategies. In the present study, we present a pathway to reconcile the 2 major mechanisms of rFVIIa action, a necessary step to understanding future dose optimization and evaluation of new rFVIIa analogs currently under development.

Blood coagulation is a complex biochemical network that plays critical roles in haemostasis (a physiological process that stops bleeding on injury) and thrombosis (pathological vessel occlusion). Both up- and down-regulation of coagulation remain a major challenge for modern medicine, with the ultimate goal to correct haemostasis without causing thrombosis and vice versa. Mathematical/computational modelling is potentially an important tool for understanding blood coagulation disorders and their treatment. It can save a huge amount of time and resources, and provide a valuable alternative or supplement when clinical studies are limited, or not ethical, or technically impossible. This article reviews contemporary state of the art in the modelling of blood coagulation for practical purposes: to reveal the molecular basis of a disease, to understand mechanisms of drug action, to predict pharmacodynamics and drug–drug interactions, to suggest potential drug targets or to improve quality of diagnostics. Different model types and designs used for this are discussed. Functional mechanisms of procoagulant bypassing agents and investigations of coagulation inhibitors were the two particularly popular applications of computational modelling that gave non-trivial results. Yet, like any other tool, modelling has its limitations, mainly determined by insufficient knowledge of the system, uncertainty and unreliability of complex models. We show how to some extent this can be overcome and discuss what can be expected from the mathematical modelling of coagulation in not-so-far future.

Fibrinolysis is a cascade of proteolytic reactions occurring in blood and soft tissues, which functions to disintegrate fibrin clots when they are no more needed. In order to elucidate its regulation in space and time, fibrinolysis was investigated using an in vitro reaction-diffusion experimental model of blood clot formation and dissolution. Clotting was activated by a surface with immobilized tissue factor in a thin layer of recalcified blood plasma supplemented with tissue plasminogen activator (TPA), urokinase plasminogen activator or streptokinase. Formation and dissolution of fibrin clot was monitored by videomicroscopy. Computer systems biology model of clot formation and lysis was developed for data analysis and experimental planning. Fibrin clot front propagated in space from tissue factor, followed by a front of clot dissolution propagating from the same source. Velocity of lysis front propagation linearly depended on the velocity clotting front propagation (correlation r² = 0.91). Computer model revealed that fibrin formation was indeed the rate-limiting step in the fibrinolysis front propagation. The phenomenon of two fronts which switched the state of blood plasma from liquid to solid and then back to liquid did not depend on the fibrinolysis activator. Interestingly, TPA at high concentrations began to increase lysis onset time and to decrease lysis propagation velocity, presumably due to plasminogen depletion. Spatially non-uniform lysis occurred simultaneously with clot formation and detached the clot from the procoagulant surface. These patterns of spatial fibrinolysis provide insights into its regulation and might explain clinical phenomena associated with thrombolytic therapy.