Conventional approaches to data analysis combined with standard statistical methods have been limited in their ability to identify at risk individuals. Our method integrates multiple selected measures characteristic of individual coagulation profiles and provides a unique level of resolving power with respect to differences between individuals including the potential for risk assessment of hemorrhagic and thrombotic events and monitoring of anticoagulation 
. Our method can be generalized further to take multiple measures from any type of instrument or values from standard clinical tests (i.e. PT, aPTT, etc), and repackage them into an integrated form that allows individuals to be monitored over time and directly compared to other individuals evaluated the same way.
Our method has clear advantages over currently used data presentation techniques which describe thrombin generation parameters. Typically, these values are tabulated and reported as a mean ± standard deviation or graphically with each mean ± standard deviation value presented in a bar graph or box plot. Our method is unique in that it provides a visual representation of all thrombin parameters in a single plot and captures how these parameters change over time in response to clinical events or therapies which alter an individual's haemostatic potential. Making use of three discrete populations with “abnormal” haemostasis we have demonstrated the utility of our method in visualizing changes in thrombin generation during warfarin therapy, fVIII prophylaxis for haemophilia A and pregnancy.
In the current study only one method of determining thrombin generation was used for each population but based on the extensive empirical validation of our mathematical model 
we expect that simulated and empirical thrombin generation data would be similar. Our video plot (Movie S1
) shows that the atrial fibrillation group is stably anticoagulated within 5 days of commencing warfarin therapy. These data, generated using computational methods, are consistent with the well-established role of warfarin in decreasing the production of vitamin K dependent proteins 
which results in reduced thrombin generation in vivo
, in vitro
and in silico
. Adding the protein C pathway to our mathematical model and plotting the simulated data using our video plot method, we have identified a theoretical window in which patients on warfarin may be at an increased risk of thrombosis. Our video plot based on the “Protein C model” (Movie S2
) shows that all patients have an increased thrombin generating capacity 3 days after starting warfarin therapy. After day 3, the thrombin generating capacity decreases substantially as each patient becomes stably anticoagulated. This paradoxical and theoretical increase in thrombotic risk can be explained by the relatively short half-life of protein C compared to other vitamin K dependent proteins such as prothrombin and fX 
. Since protein C levels decrease faster during warfarin therapy than prothrombin and fX, there is a window of time where the anticoagulant pathway afforded by protein C is diminished to a greater extent than that of procoagulant pathways comprising the other vitamin K dependent proteins. Interestingly, an increased thrombin generating capacity on day 3 is only marginally associated with an increased lag time. The lag time is the thrombin parameter which most closely resembles the clot time in the PT assay which is clinically used to monitor warfarin therapy. The simulated lag times are consistent with the insensitivity of the PT assay to protein C levels 
but nonetheless show a theoretical increase in thrombin generating capacity during the early stages of warfarin therapy. Therefore, modeling the kinetics of warfarin anticoagulation may be useful in identifying individuals who are most at risk of thrombosis during the early stages of warfarin therapy.
We have also illustrated the utility of our method in monitoring thrombin generating capacity among patients with severe haemophilia. Movie S3
, generated using simulated thrombin generation data, shows that the maximal rate of thrombin generation and peak thrombin decreases dramatically as fVIII decays while the lag time and total thrombin are only marginally decreased. As reviewed previously 
, the goal in prophylactic factor replacement therapy is to keep the fVIII concentration above 1% to significantly reduce the risk of bleeding. Our video (Movie S4
) shows the relative timing of reduced thrombin generating capacity in haemophilia A during prophylactic fVIII replacement therapy and illustrates very clearly the clinical benefit of theoretical fVIII products with a prolonged half-life. Since the pharmacokinetics of fVIII is not known in these patients, we fixed the fVIII concentration at 100% and allowed fVIII to decay with a half-life of 12.2 hours (). An additional potential limitation is that the effects of von Willebrand factor levels on the efficacy and half-life of fVIII replacement products is not currently part of the model. Thus, we acknowledge that this does not represent the actual dynamic thrombin generating capacity of the patients enrolled since the fVIII half-live is unlikely to be exactly 12.2 hours, but nonetheless the video demonstrates how thrombin generating capacity changes over the course of fVIII prophylaxis in patients with similar fVIII half-lives.
Finally, using our pregnant population we show that the utility of this method of data presentation is not exclusive to simulated thrombin generation parameters but can also be used to chart thrombin generating capacity using empirical parameters from thrombin generation assays. Consistent with previous reports 
, our pregnant population has an increased procoagulant tendency in early pregnancy which increases further in late pregnancy. After delivery and cessation of breast feeding (post-pregnancy) the video shows that thrombin generating capacity returns to pre-pregnancy levels. The plot also very clearly identifies subjects who contain an endogenous activator within their plasma (lag time
0 minutes). Using a previously described assay 
, it was determined that these subjects had endogenous fIXa or fXIa activity 
The marriage between simulated thrombin generation and our method allows for rapid identification of individuals with abnormal thrombin generation kinetics. In recent years, considerable effort and resources have been devoted to the development of personalized medicine, but many hurdles remain 
. Any tool which simplifies the identification of at risk individuals will likely streamline the implementation of personalized therapies, thus improving patient care and outcomes. The ways that the general population and scientific community consume and use data have changed drastically over the past few years. As recently as 5 years ago the utility of our method would have been limited to a desktop computer. Today, however, the ubiquity of the internet combined with advances in computing power make this method accessible via desktop computers as well as tablets and smartphones.