Systems biology of coagulation

Abstract

Accurate computer simulation of blood function can inform drug target selection, patient-specific dosing, clinical trial design, biomedical device design, as well as the scoring of patient-specific disease risk and severity. These large-scale simulations rely on hundreds of independently measured physical parameters and kinetic rate constants. However, the models can be validated against large-scale, patient-specific laboratory measurements. By validation with high-dimensional data, modeling becomes a powerful tool to predict clinically complex scenarios. Currently, it is possible to accurately predict the clotting rate of plasma or blood in a tube as it is activated with a dose of tissue factor, even as numerous coagulation factors are altered by exogenous attenuation or potentiation. Similarly, the dynamics of platelet activation, as indicated by calcium mobilization or inside-out signaling, can now be numerically simulated with accuracy in cases where platelets are exposed to combinations of agonists. Multiscale models have emerged to combine platelet function and coagulation kinetics into complete physics-based descriptions of thrombosis under flow. Blood flow controls platelet fluxes, delivery and removal of coagulation factors, adhesive bonding, and von Willebrand factor conformation. The field of blood systems biology has now reached a stage that anticipates the inclusion of contact, complement, and fibrinolytic pathways along with models of neutrophil and endothelial activation. Along with '-omics' data sets, such advanced models seek to predict the multifactorial range of healthy responses and diverse bleeding and clotting scenarios, ultimately to understand and improve patient outcomes.

Keywords: computer; convection; platelet; simulation; thrombin; thrombosis.

Fig. 1. Systems Biology model of thrombin production in the presence of thrombin-dependent activation of platelets

The Hockin-Mann topology (unshaded, [ref. 2]) was extended (shaded blue) to include contact activation, platelet activation which reduces protein dissociation rates from complexes, thrombin-mediated cleavage of fibrinogen and fluorogenic detector, and other reactions (A) (from [7]). The Platelet-Plasma model (dotted lines) and Hockin-Mann model (solid lines) were compared to diverse conditions where the initiation time was measured by fluorogenic assay in blood treated with increasing concentrations of TF (B), prothrombinase components (Xa and Va) (C), and intrinsic pathway components (IXa, XIa) or high doses of recombinant VIIa (D).

Fig. 2. Multiscale models of thrombosis and inner clot dynamics

(A) Combinatorial measurements of intracellular calcium in platelets exposed to pairs of activators of GPVI, TP, P2Y1, P2Y12, and IP receptors, allowed training of a platelet activation multiscale model (B) for platelets arriving on collagen (red bar), mobilizing intracellular calcium (platelet greyscale), and releasing ADP (orange to blue colour scale) (from [22]). (C) Platelet mass and velocity field (arrows) after 30 sec perfusion at wall shear rate of 1500 s^-1 over 15 fmol/cm² of TF (from [27] used with permission). (D) Platelet accumulation at a site of laser injury with concomitant production of thrombin and fibrin (from [29]) where thrombin was detected with a thrombin sensitive fluorogenic peptide-antibody construct (ThS-Ab) that binds platelets.