Coagulation-Based Customized Treatment (CPT) System

Abstract

The present invention provides a method for modeling the coagulability of a blood sample, comprising the steps of: determining the coagulability of a blood sample or preparing a blood sample with known coagulability by the direct effect of biological activity of the immune system and blood coagulation system on the coagulability; determining and attributing health status and risk factors for thrombosis and / or bleeding to the donor who provided the respective sample; determining the pharmacodynamic effect and corresponding therapeutic window of one or more drugs, including anti-inflammatory drugs, anticoagulants, on the blood sample to reduce the risk of inflammation and / or thrombosis and / or bleeding; and modeling the coagulability of the blood sample after administering the most effective treatment strategy involving drugs, including anticoagulants, to the blood sample.

Description

[Technical field]

[0001] The present invention provides a method for modeling the coagulability of a blood sample, comprising the steps of determining the coagulability of a blood sample or preparing a blood sample with a known coagulability by the direct effect of the biological activity of the immune system and blood coagulation system on coagulability; determining and attributing the health status and risk factors of thrombosis and / or bleeding to the donor who provided the respective sample; determining the pharmacodynamic effects and corresponding therapeutic windows of drugs, including anti-inflammatory drugs, anticoagulants, to reduce the risk of inflammation and / or thrombosis and / or bleeding; and modeling the coagulability of the blood sample after administration of the most effective treatment strategy involving drugs, including anticoagulants. The present invention also provides a method for providing an individualized drug treatment regimen for a patient / animal with an increased risk of pathological inflammation and / or thrombosis and / or bleeding due to undesirable activity of the immune system and / or blood coagulation system, comprising the steps of determining the coagulability of a blood sample of the patient / animal or providing a known coagulability value for the patient / animal; and providing an individualized drug treatment regimen based on the model of coagulability provided herein. This personal health status assessment and individualized treatment system utilizes coagulation as one of the primary parameters without excluding contributions from other parameters. [Background technology]

[0002] Pharmacological therapies for the treatment and / or prevention of thrombosis are some of the most frequently prescribed medicines worldwide. These medicines are called anticoagulants, which are antithrombotic drugs that prevent and / or reduce blood clotting by prolonging clotting time. These drugs are used in situations such as cardiovascular conditions, cancer, stroke, and sepsis.

[0003] Vitamin K antagonists, as an example, belong to the group of most commonly prescribed antithrombotic drugs and have been in use for more than 50 years (Zirlik and Bode 2016). Such drugs are, for example, fluindione, warfarin or coumarin. The dosage of these drugs is usually based on the PT / INR (prothrombin time / international normalized ratio) coagulation assay. The PT / INR is determined in the plasma of patients who have been given the drug for some time. This assay generalizes the dosage of vitamin K antagonists and does not provide any output regarding differences at the individual level, in vivo biochemical and physiological properties, or exact dosage requirements.

[0004] Other types of anticoagulants are direct thrombin inhibitors (DTIs), which can be administered orally (e.g., dabigatran) or via intravenous infusion / injection (e.g., argatroban, hirudin). Direct thrombin inhibitors can be small chemicals, larger peptides or peptide-like compounds that target the clotting factor thrombin with sufficient affinity and specificity. The inhibitory effect of DTIs fluctuates from day to day due to absorption, distribution, metabolism and excretion, such that drug concentrations increase and peak shortly after drug intake. Drug concentrations in plasma decrease due to drug excretion through the kidney and other routes. In addition, orally administered direct FXa inhibitors (DXaIs), such as rivaroxaban, edoxaban, apixaban, heparin or heparin-like drugs, are small chemical compounds that target the clotting factor FXa. However, the inhibitory effect of vitamin K antagonists on slowing clotting is more sustained or lasts longer than DTIs and DXaIs. Treatment is rather haphazard, since even if the prolonged coagulation process in plasma is slowed down using the prescribed drug dosage, thrombosis still occurs. Moreover, in the case of overuse of antithrombotic drugs, bleeding events increase.

[0005] Furthermore, many patients are not treated with a single anticoagulant treatment alone. Most patients are prescribed many other drug types, such as antiplatelet drugs, anti-inflammatory drugs, drug metabolizer regulators, antihypertensive drugs, cell transporter regulators, etc. All of these drug-drug interactions are common, and the net effect at each time point during the pharmacokinetics of multi-drug treatment is a black box. For example, the combination of antiplatelet and anticoagulant treatment has an increased risk of bleeding compared to single-drug treatment, while single-drug treatment increases the risk of thrombosis for certain individuals. As an example of a common antithrombotic treatment regimen, the use of an antiplatelet / anti-inflammatory drug (e.g., aspirin) in combination with an anticoagulant increases the risk of major bleeding by at least two-fold.

[0006] Thus, the problem with the prescription of anticoagulants currently used for the treatment and / or prevention of thrombosis is that anticoagulant management is empirical and extrapolated from population studies. Moreover, patients receiving commonly prescribed regimens still suffer from life-threatening thrombosis or bleeding of a mild to life-threatening nature while undergoing anticoagulation treatment.

[0007] Precision medicine is an approach for the prevention, diagnosis, treatment and monitoring of disease that includes individual differences in a patient's biology, environment and lifestyle. Patient biomarker data and diagnostic assays drive healthcare decision making by helping physicians identify appropriate treatments for patients and monitor their diseases. Moreover, biomarkers and associated diagnostics in precision medicine support pharmaceutical companies' pipelines by facilitating the design and execution of clinical trials, accelerating drug development and informing the design of early pipeline selections. A key issue is the availability of reliable biomarker diagnostics.

[0008] The immune system and blood coagulation system are closely connected with each other, and for example, the activation of chronic inflammation by autoimmunity can be observed in the activation of the blood coagulation system, so the coagulation biomarker is a novel biomarker that can indicate the state of both the immune system and the blood coagulation system.Anticoagulants can be exemplified as one of the main drug treatment typologies described in this patent, and many diseases involving the immune system and blood coagulation system can utilize such biomarkers as parameters in combination with other parameters to devise personalized health assessment, and therefore to devise personalized treatment regimens with reduced side effects such as bleeding and thrombosis in the case of single and / or combined antithrombotic treatment, and increased effectiveness of treatment.

[0009] Thus, there is a need in the art to provide patient-specific treatment options to reduce the risk of thrombosis and / or bleeding, such as in the example of antithrombotic treatments. Summary of the Invention

[0010] The present invention relates to a method for classifying a subject's risk and / or status for an inflammatory event and / or a coagulation dysregulation event, comprising: a) determining or retrieving input data, said input data comprising: i) a coagulation biomarker, wherein the coagulation biomarker is determined in a blood sample of a subject by at least two different assays; ii) Patient / animal demographic information and A process comprising: b) comparing said input data with risk and / or status reference patterns, said risk and / or status reference patterns being obtained from at least two reference subjects, at least one of said reference subjects having previously had an inflammatory and / or coagulation dysregulation event; and c) classifying said risk and / or status of said subject for an inflammatory event and / or a coagulation dysregulation event based on the comparison obtained in (b); The present invention relates to a method comprising the steps of:

[0011] The inventors have surprisingly found that the use of a novel biomarker, coagulability, to track coagulation or thrombin activity before and after anticoagulation treatment and the measurement of this biomarker offers the possibility of providing patient-specific anticoagulation and antibleeding treatments that reduce the risk of thrombosis and / or bleeding. As already shown in the previous section, this biomarker, which is an indicator of how active the immune and coagulation systems are during disease, responds to pharmaceutical treatments that have an effect on either or both systems. This patent mainly illustrates the use of anticoagulants and their pharmacodynamic effects on this biomarker. Thus, the present invention provides a personalized computational solution based on the novel biomarker by prescribing a personalized and precise dose of anticoagulant, thus improving the dosing regimen. Moreover, it has surprisingly been found that the measurement of coagulability can be easily applied to guide the personalized treatment of patients, since this diagnostic test can be adopted by automated hematology equipment.

[0012] In a further aspect, the present invention provides a method for providing an individualized anticoagulant and antibleeding treatment regimen for a patient, comprising: (a) determining the coagulation properties of a blood sample from said patient or providing a known coagulation property value for said patient; (b) providing an individualized anticoagulant and antibleeding treatment regimen based on the model of coagulation properties obtained by the method of the invention; The present invention relates to a method comprising the steps of: DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, and suitable methods and materials are described below. All publications, patent applications, patents and other references mentioned herein are incorporated by reference in their entirety. The publications and applications discussed herein are provided solely for their disclosure prior to the filing date of this application. Nothing herein should be construed as an admission that the present invention is not entitled to antedate such publications by prior invention. Additionally, the materials, methods and examples are illustrative only and are not intended to be limiting.

[0014] In case of conflict, the present specification, including definitions, will prevail. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. A single unit may fulfill the functions of several features recited in a claim. Any reference signs in the claims should not be construed as limiting the scope. As used herein, "and / or" should be understood to mean either or both alternatives.

[0015] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the subject matter of this specification belongs. As used herein, the following definitions are provided herein for the purpose of describing certain embodiments only and are not intended to limit the scope of the present invention.

[0016] Thus, the present invention relates, inter alia, to the following aspects: 1. A method for classifying a subject's risk and / or status for an inflammatory event and / or a coagulation dysregulation event, comprising: a) determining or retrieving input data, said input data comprising: i) a coagulation biomarker, wherein the coagulation biomarker is determined in a blood sample of a subject by at least two different assays; ii) Patient / animal demographic information and A process comprising: b) comparing said input data with risk and / or status reference patterns, said risk and / or status reference patterns being obtained from at least two reference subjects, at least one of said reference subjects having previously had an inflammatory and / or coagulation dysregulation event; and c) classifying said risk and / or status of said subject for an inflammatory event and / or a coagulation dysregulation event based on the comparison obtained in (b); A method comprising: 2. The method of embodiment 1, wherein said assay is a combination of a clot-based fibrinogen test and an enzyme-based fibrinogen test. 3. The method of embodiment 2, wherein said enzyme-based fibrinogen test is a clot-independent enzyme-based fibrinogen test. 4. The method of embodiment 2, wherein said clot-based fibrinogen test is selected from the group consisting of prothrombin time (PT) determination, partial thromboplastin time (PTT) determination and the Clauss test. 5. The method according to any one of aspects 2 to 4, wherein the enzyme-based fibrinogen test involves catalytic cleavage by a serine endopeptidase. 6. The method according to any one of aspects 2 to 5, wherein said enzyme-based fibrinogen test involves catalytic cleavage of fibrinogen by a snake venom serine endopeptidase, preferably by venombin A. 7. The method according to any one of aspects 2 to 6, comprising measuring the proteolytic activity of serine endopeptidase, which is inversely proportional to the fibrinogen level in said sample. 8. The method of any one of aspects 1-7, wherein said patient / animal background information comprises or consists of weight, sex, age and renal function. 9. The method of any one of aspects 1 to 8, wherein the risk and / or condition reference pattern is a machine learning model obtained by training on a dataset of reference subjects, and the step of comparing the input data with the risk and / or condition reference pattern comprises inputting the input data into the machine learning model. 10. The method according to any one of aspects 1 to 9, wherein the step of classifying the subject's risk and / or condition with respect to an inflammatory event and / or a coagulation dysregulation event is classifying the subject's risk and / or condition with respect to thrombosis and / or bleeding. 11. A method for predicting a subject's risk and / or status for an inflammatory event and / or a coagulation dysregulation event, comprising: a) i) at a first time point, classifying a subject's risk and / or status for an inflammatory event and / or a coagulation dysregulation event according to a method according to any one of aspects 1 to 10; ii) determining or retrieving coagulation biomarkers in a blood sample of said subject at a second time point, said coagulation biomarkers being determined in said blood sample of said subject by at least two different assays; determining risk and / or condition progression indicators by: b) comparing said risk and / or condition progression indicator with a predictive reference pattern, said predictive reference pattern being obtained from at least two reference subjects, at least one of said reference subjects having previously suffered an inflammatory and / or coagulation dysregulation event, and said risk and / or condition progression of said reference subjects being known; c) predicting said risk and / or condition of the subject based on the comparison obtained in (b); A method comprising: 12. The method of embodiment 11, wherein the predictive reference pattern is a machine learning model obtained by training on a dataset of reference subjects, and the step of comparing the risk and / or condition progression indicator with the predictive reference pattern comprises inputting the input data into the machine learning model. 13. A method for monitoring a subject's treatment response for inflammatory and / or coagulation dysregulation events during treatment, comprising: a) i) at a first time point, classifying a subject's risk and / or status for an inflammatory event and / or a coagulation dysregulation event according to any one of the methods of embodiments 1 to 10; ii) determining or retrieving coagulation biomarkers in a blood sample of said subject at at least one second time point, said coagulation biomarkers being determined in said blood sample of said subject by at least two different assays; iii) 1.) a time point of administration of said anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound and / or anticoagulant compound, said time point of administration being between said first time point and said second time point; preferably said time point of administration and the amount of said anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound and / or anticoagulant compound administered; 2.) a pharmacodynamic response, wherein the pharmacodynamic response is calculated based on at least the coagulation biomarker at the first time point, the coagulation biomarker at the second time point, and the time of administration, wherein the pharmacodynamic response is calculated based on at least the coagulation biomarker at the first time point, the coagulation biomarker at the second time point, the time of administration, and the amount administered; determining a treatment progress indicator by: b) comparing said treatment progress indicator with a treatment response reference pattern, said predictive reference pattern being obtained from at least two reference subjects, at least one of said reference subjects having previously been treated with an anti-inflammatory, antiplatelet, anticoagulant and / or procoagulant compound, and said treatment response of said reference subject is known; c) monitoring the subject's treatment response based on the comparison obtained in (b); A method comprising: 14. The method of embodiment 13, wherein the treatment response reference pattern is a machine learning model obtained by training on a dataset of reference subjects, and comparing the treatment progress indicator with the treatment response reference pattern comprises inputting the treatment progress indicator into the machine learning model. 15. An anti-inflammatory, antiplatelet, anticoagulant and / or procoagulant compound for use in the treatment of a subject classified as being at risk and / or in a state of an inflammatory event and / or a coagulation dysregulation event according to the method according to any one of embodiments 1 to 10 and / or predicted to develop an inflammatory event and / or a coagulation dysregulation event according to the method according to embodiment 11 or 12. 16. A method of treatment for reducing the risk of and / or improving the condition of an inflammatory event and / or a coagulation dysregulation event in a subject in need thereof, comprising: a) administering a therapeutically effective amount of a first anti-inflammatory compound, an antiplatelet compound, an anticoagulant compound and / or a procoagulant compound to a subject in need thereof during monitoring of said treatment response according to the method according to any one of embodiments 13-14; b) if the treatment response to the first anti-inflammatory, antiplatelet, anticoagulant and / or procoagulant compound is insufficient according to the method of any one of aspects 13-14, administering a second anti-inflammatory, antiplatelet, anticoagulant and / or procoagulant compound to the subject in need thereof, and if the treatment response to the first anti-inflammatory, antiplatelet, anticoagulant and / or procoagulant compound is sufficient to reduce the risk of an inflammatory event and / or a coagulation dysregulation event and / or improve the condition of an inflammatory event and / or a coagulation dysregulation event according to the method of any one of aspects 13-14 in the subject in need thereof, proceeding with treatment with the first anti-inflammatory, antiplatelet, anticoagulant and / or procoagulant compound. A method comprising: 17. The method according to any one of aspects 13 to 14, the compound for use according to aspect 15 or the method of treatment according to aspect 16, wherein said compound is a compound selected from the group consisting of vitamin K antagonists, particularly fluindione, warfarin or coumarin, direct thrombin inhibitors, particularly dabigatran, argatroban or hirudin and direct FXa inhibitors, particularly rivaroxaban, edoxaban, apixaban, heparin or heparin-like drugs. 18. The method according to any one of aspects 13-14, the compound for use according to aspect 15 or the method of treatment according to aspect 16, wherein said compound is a compound selected from the group consisting of non-steroidal anti-inflammatory drugs, corticosteroids, rapamycin, high density lipoproteins, compounds which increase HDL-cholesterol, rho-kinase inhibitors, antimalarials, acetaminophen, glucocorticoids, steroids, β-agonists, anticholinergics, xanthine derivatives, sulfasalazine, penicillamine, anti-angiogenic agents, dapsone, psoralens, anti-TNF agents, anti-IL-1 agents and statins. 19. The method according to any one of aspects 13-14, the compound for use according to aspect 15 or the method of treatment according to aspect 16, wherein said compound is a compound selected from the group consisting of irreversible cyclooxygenase inhibitors, adenosine diphosphate (ADP) receptor inhibitors, phosphodiesterase inhibitors, protease-activated receptor-1 (PAR-1) blockers, glycoprotein IIB / IIIA inhibitors, adenosine reuptake inhibitors, dipyridamole, thromboxane inhibitors and thromboxane receptor blockers. 20. The method according to any one of aspects 13 to 14, the compound for use according to aspect 15 or the method of treatment according to aspect 16, wherein said compound is a coagulation factor that promotes clotting and / or reduces bleeding, preferably a compound selected from the group consisting of FVIII concentrate, Alphanate, Humate-P, NovoSeven, Eloctate, Fibre, Prothrombin Complex, Hemlibra and Tranexamic acid. 21. A storage device comprising computer-readable program instructions for executing a method according to any one of aspects 1-14, 17-20. 22. A server comprising the storage device of aspect 21, at least one processing unit for executing the computer-readable program instructions, and a network connection for receiving the input data. 23. A system for classifying, predicting and / or monitoring treatment response, comprising: a) a measurement device comprising a container for receiving a blood sample and a reagent for determining coagulation biomarkers, said coagulation biomarkers being determined in said blood sample by at least two different assays; b) a processing device for executing the computer-readable program instructions, the processing device comprising a network connection to a storage device and / or a server of aspect 21, the server being a server according to aspect 22; c) input and / or retrievability, said input and / or retrievability enabling said server and / or said processing device to access said patient / animal background information; A system comprising:

[0017] Thus, in one aspect, the present invention provides a method for classifying a subject's risk and / or status for an inflammatory event and / or a coagulation dysregulation event, comprising: a) determining or retrieving input data, said input data comprising: i) coagulation biomarkers, said coagulation biomarkers being determined in a subject's blood sample by at least two different assays; and ii) patient / animal demographic information; b) comparing said input data with risk and / or status reference patterns, said risk and / or status reference patterns being obtained from at least two reference subjects, at least one of said reference subjects having previously had an inflammatory and / or coagulation dysregulation event; and c) classifying said risk and / or status of said subject for an inflammatory event and / or a coagulation dysregulation event based on the comparison obtained in (b); The present invention relates to a method comprising the steps of:

[0018] The term "subject's risk and / or condition for inflammatory events and / or coagulation dysregulation events" as used herein refers to any scale or category that indicates events that occur during dysregulation of immune system, platelet system and / or coagulation system.In some embodiments, the subject's risk and / or condition for inflammatory events and / or coagulation dysregulation events described herein is a category or scale that indicates at least one risk and / or condition selected from the group consisting of acute inflammation, chronic low-grade inflammation, cardiovascular events and bleeding.In some embodiments, the subject's risk and / or condition for inflammatory events and / or coagulation dysregulation events described herein is a category or scale that indicates at least one risk and / or condition selected from the group consisting of thrombosis, stroke, angina, myocardial infarction bleeding.In some embodiments, the thrombosis described herein is thromboembolic disease or venous thrombosis.

[0019] The term "clotting biomarker" as used herein refers to a biomarker that is determined by at least two different assays and indicates clotting.In some embodiments, at least one of the assays for determining clotting biomarkers described herein is an enzyme-based fibrinogen test, preferably the enzyme-based fibrinogen test involves catalytic cleavage by serine endopeptidase and / or catalytic cleavage of fibrinogen by snake venom serine endopeptidase, preferably by venonbin A.

[0020] The term "patient / animal background information" as used herein refers to any patient information that is not a coagulation biomarker. In some embodiments, the patient / animal background information is at least one, at least two, at least three, or at least four selected from the group consisting of medical history, vaccination status, liver function, height, BMI, infection status, treatment history, genotype, type of metabolizer, current treatment, weight, sex, age, blood pressure, and renal function. In some embodiments, the patient / animal background information is sex, age, and renal function. The term "health status" as used herein can also be understood as patient / animal background information.

[0021] The term "reference pattern" as used herein refers to a standard that is useful for classification of input data obtainable from a reference subject. Thus, a reference pattern can be at least a set of thresholds, classification functions, models or weights. In some embodiments, the reference pattern described herein is a trained machine learning model.

[0022] The term "reference subject" as used herein refers to a plurality of subjects whose parameters are known and for which they serve as a reference. In some embodiments, the reference subjects described herein include healthy subjects and subjects with disease. In some embodiments, the reference subjects described herein consist of subjects with disease. In some embodiments, the reference subjects described herein are part of a clinical study, such as a population study.

[0023] The inventors have discovered that coagulation biomarkers in combination with patient / animal background information provide an efficient method for classifying conditions and / or risks in subjects, allowing improved and individualized diagnosis, monitoring and / or treatment.

[0024] In an embodiment, the present invention relates to a method for modeling the coagulability of a blood sample, comprising the steps of: determining the coagulability of the blood sample or providing a blood sample with known coagulability, said coagulability being determined by and / or provided from at least two different assays; determining and attributing health status and risk factors for thrombosis and / or bleeding to the donor who provided the respective blood sample; determining the pharmacodynamic effect of one or more drugs and / or multiple drug administrations, said drugs and / or multiple drug administrations comprising or consisting of anti-inflammatory, antiplatelet and / or anticoagulant treatments; corresponding therapeutic windows for the blood sample to reduce risk; and modeling the coagulability of the blood sample after administering the most effective drug to said blood sample.

[0025] The term "thrombosis" as used herein refers to the formation of a blood clot inside a blood vessel, obstructing the flow of blood. Thrombosis can occur in veins (venous thrombosis) and arteries (arterial thrombosis). The term "bleeding" as used herein refers to the extravasation of blood from blood vessels in the circulatory system. Bleeding is usually stopped after a certain time by blood clotting. However, as used herein, "bleeding" relates to excessive bleeding due to blood clot formation disorders, especially due to reduced fibrinogen concentration and / or the presence of excess factors that inhibit clotting.

[0026] As used herein, the term "coagulability" relates to a quantitative (numeric) or qualitative value indicating the ability of blood to clot, preferably within a given time, preferably under specific conditions.

[0027] Blood clots are formed by fibrin, the activated and polymerized form of fibrinogen, together with platelets. Activation occurs via thrombin, a protease that forms fibrin, a fibrous, non-globular protein, from fibrinogen. The activity of the coagulation pathway can be indicated by the activity of thrombin, which is activated through the intrinsic and extrinsic pathways, with the participation of non-cellular and cellular components in the blood. This thrombin activity leaves its mark by converting fibrinogen into fibrin and fibrin-derived molecules, depending on the conditions. During this process, small soluble and insoluble polymers of various sizes and complexities are formed. These complexes and various fibrin-derived molecules or complexes are indicative of thrombin generation in vivo, and their presence in blood increases the coagulability or clotting ability of the blood, and are therefore called procoagulants. Current methods of detection of such procoagulants, including soluble fibrin, are difficult to perform and do not produce satisfactory results. Plasma with higher concentrations of such procoagulants can clot at a higher rate compared to the same plasma without such procoagulants. Thus, plasma samples taken from subjects with negligible in vivo thrombin activation or generation contain negligible procoagulant factors, an ideal condition that rarely occurs in reality. If plasma is taken from the same subject experiencing acute inflammation (e.g., endotoxin poisoning) several hours prior to sample collection, a portion of the total fibrinogen is converted into these procoagulant factors, increasing the coagulability of the plasma.

[0028] Once formed, these molecules and complexes are further processed by a proteolytic process called fibrinolysis. Fibrinolysis further processes these fibrin derivatives to generate degradation products of various completeness called fibrin degradation products (FDPs). These FDPs have different effects on fibrin polymerization or clot formation efficiency. From early to late in fibrinolysis, these FDPs generate highly to very little inhibitory effects on coagulation, respectively. Various forms of D-dimer are products of such late fibrinolysis. These factors that inhibit fibrin polymerization are called anticoagulants, and their presence in the clotting reaction can slow down the rate of clotting. As thrombin activity decreases, fibrinolytic activity becomes more pronounced.

[0029] The term "coagulability" as used herein is a measurement of these pro- and anticoagulant factors in plasma. Coagulability is based on one or more in vitro tests that can reflect the in vivo presence of these factors due to the recent or fresh activity of thrombin on fibrin(ogen). Those skilled in the art are familiar with this term, which represents both fibrin and fibrinogen of any form and size and modification. The general effect of these factors in clot-based assays (e.g., Claus or other CCT) is different degrees of acceleration (high coagulability) or deceleration (low coagulability).

[0030] Those skilled in the art know that blood clots naturally occur at wound sites to prevent leakage. However, those skilled in the art also know that clotting can occur in situations where there is no physiological need for it, potentially resulting in reduced fluidity of blood and therefore thrombosis. However, clotting can also be reduced or absent, resulting in continued bleeding in the event of rupture of a blood vessel. Thus, those skilled in the art know that the physiologically important process of blood clotting can be altered in patients / animals for better or worse.

[0031] The term "modeling coagulability" as used herein refers to a process in which the coagulability as defined above is calculated / estimated for a blood sample whose coagulability has not been determined by the use of one or more biochemical assays as defined below. The modeled coagulability can thus be used to predict the expected coagulability of a blood sample upon treatment with, for example, an anticoagulant. The modeled coagulability can thus be used to determine the optimal treatment for a patient / animal requiring anticoagulant treatment in order to reduce the risk of the above-defined effects of thrombosis and bleeding in cases where blood clots occur due to reduced or increased coagulability compared to a physiologically acceptable state.

[0032] In a first step, the method of the present invention comprises determining the coagulation properties of a blood sample or preparing a sample with known coagulation properties. The coagulation properties can be determined using a blood sample or based on a sample with known coagulation properties as defined above. As used herein, a "blood sample" can be obtained from a mammal, such as a human, but also from a horse, cow, sheep, pig, primate, dog or mouse.

[0033] It is well established that coagulation and its cardiovascular consequences, such as bleeding and thrombosis, involve the inflammatory and coagulation (including platelet) systems. Thus, the effects of drugs that affect anti-inflammatory, anticoagulant and antiplatelet compounds can be modeled as described herein.

[0034] The term "anti-inflammatory treatment" as used herein refers to a therapeutic agent for treating inflammatory disease or symptoms associated with inflammatory disease. In some embodiments, the anti-inflammatory compounds described herein are nonsteroidal anti-inflammatory drugs (NSAIDs; e.g., aspirin, ibuprofen, naproxen, methyl salicylate, diflunisal, indomethacin, sulindac, diclofenac, ketoprofen, ketorolac, carprofen, fenoprofen, mefenamic acid, piroxicam, meloxicam, methotrexate, celecoxib, valdecoxib, parecoxib, etoricoxib, and nimesulide), corticosteroids (e.g., prednisone, betamethasone, budesonide, cortisone, dexamethasone, hydrocortisone, methylprednisolone, prednisolone, tramcinolone, and fluticasone), rapamycin, high-density lipoprotein (HDL), and / or cyclosporine. The anti-inflammatory treatment is at least one compound selected from the group consisting of: compounds that increase HDL and HDL-cholesterol, rho-kinase inhibitors, antimalarials (e.g., hydroxychloroquine and chloroquine), acetaminophen, glucocorticoids, steroids, β-agonists, anticholinergics, xanthine derivatives (e.g., methylxanthines), sulfasalazine, penicillamine, antiangiogenic agents, dapsone, psoralens, anti-TNF agents, anti-IL-1 agents and statins, preferably infliximab, adalimumab, certolizumab pegol, golimumab, etanercept, curcumin, IL-1RA, canakinumab, allopurinol, colchicine, pentoxifylline and oxypurinol.In some embodiments, the anti-inflammatory treatment is a therapeutic agent for treating inflammatory disease or symptoms related thereto, and the anti-inflammatory effect is achieved by inhibiting and / or reducing the function of platelets.

[0035] The term "antiplatelet treatment" as used herein refers to a therapeutic agent that reduces or inhibits platelet aggregation. In some embodiments, the antiplatelet treatment described herein is at least one compound selected from the group consisting of irreversible cyclooxygenase inhibitors, adenosine diphosphate (ADP) receptor inhibitors, phosphodiesterase inhibitors, protease-activated receptor-1 (PAR-1) blockers, glycoprotein IIB / IIIA inhibitors, adenosine reuptake inhibitors, dipyridamole, thromboxane inhibitors and thromboxane receptor blockers. In some embodiments, the antiplatelet treatment described herein is at least one compound selected from the group consisting of terutroban, vorapaxar, cilostazol, aspirin, triflusal, cangrelor, clopidogrel, prasugrel, ticagrelor, ticlopidine, abciximab, eptifibatide and tirofiban.

[0036] The term "anticoagulant treatment" as used herein refers to any drug that includes or consists of any anticoagulant compound.In some embodiments, the anti-inflammatory compound described herein is at least one compound selected from the group consisting of vitamin K antagonists, coumarins, direct thrombin inhibitors, direct FXa inhibitors, heparin and heparin-like drugs.In some embodiments, the anti-inflammatory compound described herein is at least one compound selected from the group consisting of fluindione, warfarin, dabigatran, argatroban, hirudin, rivaroxaban, edoxaban and apixaban.

[0037] The term "pharmacodynamic effect" or "pharmacodynamic response" as described herein refers to the measurable effect of drug treatment on the coagulation system or immune and coagulation systems and the physiological consequences of such effect. Examples of such drug-induced effects can be found in Examples 5, 6, 7 and 8. In some embodiments, the "pharmacodynamic effect" or "pharmacodynamic response" is derived from the coagulation biomarker or change in the coagulation biomarker as described herein.

[0038] In one embodiment, the present invention relates to a method for modeling the coagulability of a blood sample, comprising the steps of: determining the coagulability of a blood sample or preparing a blood sample with known coagulability; determining and attributing health status and risk factors for thrombosis and / or bleeding to the donor who provided the respective sample; determining the pharmacodynamic effect of one or more anticoagulants on said blood sample and corresponding therapeutic window to mitigate the risk; and modeling the coagulability of said blood sample after administering the most effective anticoagulant to said blood sample.

[0039] One method of determining coagulability is based on the fibrinogen concentration in a blood sample. The determined fibrinogen concentration can be related to known fibrinogen concentrations to determine whether the blood sample is normocoagulable, hypercoagulable or hypocoagulable. In the present invention, one method for "determining coagulability" involves using at least two assays to determine the fibrinogen concentration and determining the difference between the results of at least two assays. In this regard, it has surprisingly been found by the inventors that the coagulability resulting from the above can serve as an indicator of health status assessment and the risk of the donor suffering from thrombosis or bleeding, depending on the hypercoagulable or hypocoagulable state, respectively. In this regard, it has surprisingly been found that for healthy donors, the resulting coagulability, preferably as the difference between the fibrinogen concentrations determined by at least two assays at different time points, can be greater than or equal to -0.5 and less than or equal to 0.5. Therefore, it has been found that in the general population, if two or more tests result in similar fibrinogen concentrations, i.e. low variance, there is a low risk of developing thrombosis or bleeding, and thus the donor is healthy with reduced activation of the immune and coagulation systems. On the other hand, if the results of at least two assays differ to such an extent that the difference in the determined fibrinogen concentrations remains much more than 0.5, the risk of developing thrombosis increases, as shown in the accompanying examples and in Figure 1. If the coagulability remains below the safe interval, the risk of bleeding occurrence increases.

[0040] Coagulability values ​​may change and are therefore dynamic due to physiological processes and / or medication.Therefore, coagulability should be monitored regularly.The present invention provides a method for modeling coagulability before treatment, and therefore can reduce the empirical monitoring of coagulability before and after treatment.At the same time, the method of the present invention can provide more rapid and accurate treatment decisions, and therefore can reduce the risk of thrombosis and / or bleeding.

[0041] The method of the present invention further comprises determining and attributing a health status to the donor based on coagulation modeling reflecting the activity or activation of the immune system and blood coagulation system. Chronic activation of the immune system is known to be associated with diseases such as cancer and other non-communicable diseases, as well as infectious diseases such as HIV infection.

[0042] Furthermore, the method of the present invention includes a step of determining the pharmacodynamic effect and corresponding therapeutic window of one or more anticoagulants to reduce the risk of thrombosis and / or bleeding.The pharmacodynamic effect of one or more anticoagulants is determined to reduce the risk of thrombosis and / or bleeding.For example, reducing thrombin activation and therefore also reducing coagulation, for example from hypercoagulability to normal coagulation state, minimizes the risk of thrombosis.One example of an increased risk of bleeding in this context is the overdosing of anticoagulants, and to some extent, the overproduction of anticoagulant factors.

[0043] In the present invention, the preferred anticoagulant may be selected from the group consisting of vitamin K antagonists, particularly fluindione, warfarin or other coumarins, direct thrombin inhibitors, particularly dabigatran, argatroban or hirudin, and direct FXa inhibitors, particularly rivaroxaban, edoxaban, apixaban, heparin or heparin-like drugs. Anticoagulants are drugs used to reduce the risk of blood clots, particularly to prevent thrombosis, pulmonary embolism, stroke in individuals with atrial fibrillation, valvular heart disease and / or artificial heart valves. Anticoagulants may be administered, for example, orally, intravenously, subcutaneously, parenterally, intraarterially or locally. Preferably, anticoagulants may be administered orally or intravenously. There are different types of anticoagulants that act on different parts of the physiological process that leads to blood clot formation. In particular, a "vitamin K antagonist" is a natural or synthetic compound, its analog or derivative, that inhibits the enzyme vitamin K epoxide reductase and thus inhibits the regeneration of vitamin K, an important cofactor in the blood clotting cascade. Furthermore, a "direct thrombin inhibitor" acts as an anticoagulant by directly inhibiting the enzyme thrombin responsible for blood clotting. For example, dabigatran inhibits thrombin in the common coagulation pathway and prevents fibrin formation from fibrinogen. A "direct FXa inhibitor" directly binds to factor Xa and inhibits its action in blood clotting. However, the type of anticoagulant used in the present invention is not particularly limited.

[0044] The method of the present invention further includes modeling coagulation after administration of the most effective anticoagulant. The term "after administration" as used herein refers to the theoretical effect of the anticoagulant determined to be the most effective when administered to the patient. In the present invention, "most effective" refers to the anticoagulant or combination of anticoagulants determined to produce the most favorable physiological effect. The most favorable physiological effect may relate to a decrease or increase in coagulability, but may also include factors such as safety and / or polypharmacy. As an example, after administration of the most effective anticoagulant, if coagulability has been decreased, the patient may no longer be in a hypercoagulable state, or if coagulability has been increased, the patient may no longer be in a hypocoagulable state.

[0045] In a further embodiment the present invention relates to a method according to the invention, wherein determining the coagulation properties comprises a combination of a clot-based fibrinogen test and an enzyme-based fibrinogen test.

[0046] In one embodiment, the present invention relates to a method according to the invention, wherein the assay is a combination of a clot-based fibrinogen test and an enzyme-based fibrinogen test.

[0047] Examples of both tests are disclosed in WO 2019 / 068940. As used herein, the term "clot-based fibrinogen test" refers to the specific determination of fibrinogen activity based on the time it takes for a clot to form by evaluating the clotting process in which fibrinogen is converted to fibrin.

[0048] In the present invention, the term "clot-based fibrinogen test" includes all tests related to clotting reaction that can provide an interpolation for fibrinogen concentration. Examples of clot-based fibrinogen tests used herein include prothrombin time test (PT), partial thromboplastin time test (PTT) and Claus test (CCT). The term "enzyme-based fibrinogen test" used herein refers to a test that determines the fibrinogen concentration in blood based on competitive kinetic data by utilizing an enzyme and an artificial substrate. The "enzyme" may be selected from peptidase, protease, lipase, pectinase, amylase or isomerase. Preferably, the enzyme used in the enzyme-based fibrinogen test of the present invention is a protease. An example of an enzyme-based fibrinogen test is the true fibrinogen test (TFT), which utilizes a protease that selectively cleaves fibrinogen.

[0049] In this regard, the present invention is based at least in part on the finding that the combined use of an assay comprising a clot-based fibrinogen test and an enzyme-based fibrinogen test to determine the coagulability of a blood sample can be the basis for effectively determining coagulability.As an example, Figure 3 shows the relationship between plasma fibrinogen concentrations obtained from a clot-based fibrinogen test and an enzyme-based fibrinogen test at different time points and the derived coagulability in healthy individuals with acute inflammation.

[0050] In the present invention, the enzyme-based fibrinogen test may be a clot-independent enzyme-based fibrinogen test.

[0051] In one embodiment, the present invention relates to a method according to the invention, wherein the enzyme-based fibrinogen test is a clot-independent enzyme-based fibrinogen test.

[0052] The term "clot-independent" refers to enzyme-based fibrinogen tests that do not detect procoagulant and / or anticoagulant factors. The term "procoagulant" as used herein refers to substances in the coagulation cascade that enhance clotting efficiency. In particular, procoagulant factors are mainly soluble fibrin derivatives or intermediates from fibrinogen generated by thrombin, and some fibrin degradation products (FDPs) generated by fibrinolysis in the early stages. "Anticoagulant" refers to substances in the coagulation cascade that have the opposite effect by reducing the efficiency of clot formation. In particular, anticoagulant factors are mostly FDPs in the later stages.

[0053] It is further preferred in the present invention that the clot-based fibrinogen test is selected from the determination of the prothrombin time (PT), the determination of the partial thromboplastin time (PTT) and the Clauss test.

[0054] In particular, the PT test indirectly measures fibrinogen from the prothrombin time in seconds. Calibration is performed by calculating the prothrombin time against a series of plasma containing known fibrinogen concentration standards and plotting the optical change against the fibrinogen value. The optical change is converted to a fibrinogen value (Mackie et al., 2003).

[0055] PT is often used in combination with the aPTT (activated partial thromboplastin time) test, which can assess the amount and function of clotting factors. The term "partial thromboplastin time" or "PTT" refers to a blood test that determines how long it takes for blood to clot. These tests are used to diagnose unexplained bleeding or blood clots.

[0056] Fibrinogen in plasma can also be measured by performing the Claus test (Undas A, 2017). As used herein, the term "Claus test" or "CCT" refers to a diagnostic test of a diluted plasma sample that is subjected to clotting with a high concentration of thrombin.

[0057] In a further aspect, the invention relates to a method in which the enzyme-based fibrinogen test involves catalytic cleavage by a serine endopeptidase. The term "catalytic cleavage" as used herein refers to the change in the rate of the chemical reaction of proteolysis by the addition of a serine endopeptidase that breaks down proteins into peptides. A "serine endopeptidase" is an enzyme in which serine serves as the nucleophilic amino acid in the active site of this endopeptidase. The "active site" is the area of ​​the enzyme where a substrate molecule binds and undergoes a chemical reaction. The invention further relates to a method in which the enzyme-based fibrinogen test involves catalytic cleavage of fibrinogen by a snake venom serine endopeptidase, preferably by Benonbin A. The invention also relates to a method of the invention comprising measuring the proteolytic activity of the serine endopeptidase, which is inversely proportional to the fibrinogen concentration in said sample. Serine endopeptidase acts in a similar manner to thrombin, i.e. by activating fibrinogen and inducing the process of blood clotting. Thus, the reaction involves the conversion of fibrinogen to fibrin. In the present invention, "inversely proportional" refers to causing a decrease in one variable and an increase in another variable. The variables refer to the proteolytic activity value or fibrinogen level in the presence of serine endopeptidase.

[0058] In particular, the invention is based at least in part on the use of a clot-independent, enzyme-based fibrinogen test, in which the enzyme Benonbin A is used, which by proteolytic activity cleaves fibrinogen to form fibrin and causes the release of fibrinopeptide A. In the same reaction, Benonbin A also cleaves a synthetic substrate. Thus, the clot-independent fibrinogen test determines the concentration of fibrinogen based on substrate competition for cleavage by Benonbin A.

[0059] In one embodiment the invention relates to a method of the invention, wherein the patient / animal demographic information comprises or consists of weight, sex, age and renal function.

[0060] The inventors have found that weight, sex, age and renal function are particularly useful in complementing the information of coagulation markers and may be used in the classification, prediction, monitoring and / or treatment described herein.

[0061] In one embodiment, the invention relates to a method of the invention, wherein the risk and / or condition reference pattern is a machine learning model obtained by training on a dataset of reference subjects, and wherein comparing the input data with the risk and / or condition reference pattern comprises inputting the input data into the machine learning model.

[0062] In one embodiment the invention relates to a method according to the invention, wherein the step of classifying the subject's risk and / or condition with respect to an inflammatory event and / or a coagulation dysregulation event is classifying the subject's risk and / or condition with respect to thrombosis and / or bleeding.

[0063] The inventors have found that the methods for classification, prognosis, monitoring and / or treatment described herein are particularly useful in the context of thrombosis and / or bleeding.

[0064] In an embodiment, the present invention relates to a method for predicting a subject's risk and / or condition for an inflammatory event and / or a coagulation dysregulation event, comprising: a) determining a risk and / or condition progression indicator by: i) classifying a subject's risk and / or condition for an inflammatory event and / or a coagulation dysregulation event according to the method of the present invention during a first time point; ii) determining or retrieving coagulation biomarkers of a blood sample of said subject at a second time point, said coagulation biomarkers being determined in said blood sample of said subject by at least two different assays; b) comparing said risk and / or condition progression indicator with a predictive reference pattern obtained from at least two reference subjects, at least one of said reference subjects having previously had an inflammatory event and / or a coagulation dysregulation event, and said risk and / or condition progression of said reference subjects is known; and c) predicting said risk and / or condition of the subject based on the comparison obtained in (b).

[0065] The inventors have found that the progression of coagulation biomarkers over time, in particular coagulation biomarkers including or consisting of CCT and TFT, can be used to predict future occurrence of risk and / or condition of inflammatory and / or coagulation dysregulation events such as thrombosis and / or bleeding, by comparison of the coagulation biomarkers at at least two, at least three, at least four, at least five, or at least six time points with reference patterns from population studies.

[0066] In one embodiment, the invention relates to a method of the invention, wherein the predictive reference pattern is a machine learning model obtained by training on a dataset of reference subjects, and the step of comparing the risk and / or condition progression indicator with the predictive reference pattern comprises inputting the input data into the machine learning model.

[0067] In one embodiment, the present invention provides a method for monitoring a subject's treatment response for inflammatory and / or coagulation dysregulation events during treatment, comprising the steps of: a) i) classifying a subject's risk and / or condition for thrombosis and / or bleeding according to a method of the present invention at a first time point; and ii) determining or retrieving coagulation biomarkers of a blood sample of said subject at at least one second time point, said coagulation biomarkers being determined in said blood sample of said subject by at least two different assays; iii) 1.) a time point of administration of the anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound and / or anticoagulant compound, the time point of administration being between the first time point and the second time point; preferably the time point of administration and the amount of the anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound and / or anticoagulant compound administered; and 2.) a pharmacodynamic response, the pharmacodynamic response being calculated based on at least the coagulation biomarker at the first time point, the coagulation biomarker at the second time point and the time point of administration .... a) determining a treatment progress indicator based on the coagulation biomarkers at the first time point, the coagulation biomarkers at the second time point, and a pharmacodynamic response calculated based on the administration time point and the administered amount; b) comparing the treatment progress indicator with a treatment response reference pattern, wherein the predictive reference pattern is obtained from at least two reference subjects, at least one of which has previously been treated with an anti-inflammatory, antiplatelet, anticoagulant and / or procoagulant compound, and wherein the treatment response of the reference subject is known; and c) monitoring the treatment response of the subject based on the comparison obtained in (b).

[0068] Therefore, the method described herein is useful for monitoring treatment response.This monitoring can be used to correct treatment regime, treatment dose and / or treatment compound.Furthermore, monitoring can be used to determine drug-drug interactions and individual pharmacokinetics and pharmacodynamics.

[0069] Thus, the methods for monitoring described herein can aid in individualized treatment decisions.

[0070] In an embodiment, the present invention relates to a method of the present invention, wherein said treatment response reference pattern is a machine learning model obtained by training on a dataset of reference subjects, and wherein comparing said treatment progress indicator with the treatment response reference pattern comprises inputting said treatment progress indicator into said machine learning model.

[0071] In another aspect, the present invention relates to a method for providing an individualized anticoagulant treatment regimen for a patient, comprising: (a) determining the coagulability of a sample from said patient or providing a known coagulability value for said patient; and (b) providing an individualized anticoagulant treatment regimen based on a model of coagulability obtained by the method of the present invention. As used herein, the term "individualized anticoagulant treatment regimen" refers to a plan that specifies the dosage, schedule and / or duration of a clinical intervention that applies a set of unit doses that are administered individually to a subject, typically separated by a period of time. The term "treatment" as used herein refers to a clinical intervention in an attempt to change the natural history of the individual being treated, and can be performed for prevention or during the course of clinical pathology. The desired effects of treatment include, but are not limited to, alleviation of symptoms, attenuation of any direct or indirect pathological consequences caused by thrombosis, or prevention of at least one occurrence or recurrence of diseases such as thrombosis, cardiovascular disease, cancer, stroke or sepsis. The term "patient" as used herein refers to a mammalian subject, particularly a human subject suffering from a disease, preferably thrombosis and / or hemorrhage, who is likely to benefit from anticoagulant treatment or modified anticoagulant treatment. Individualized anticoagulant treatment includes physiological parameters and conditions, patient / patient pharmacological and clinical treatment information and biomarker information, the term biomarker refers to coagulability. Examples of physiological parameters and conditions are the age, weight and sex of the patient / patient.

[0072] In a preferred embodiment of the present invention, the patient / animal individualized anticoagulant treatment regimen is such that, if the ongoing anticoagulant treatment of said subject is not sufficient to reduce the ascribed risk factors of thrombosis and / or bleeding, the most effective anticoagulant as determined in the present invention is used for further treatment.

[0073] In a preferred embodiment of the present invention, the patient / animal personalized anticoagulant treatment regimen is such that if the ongoing anticoagulant treatment of the subject reduces the coagulability determined in the present invention below a predefined coagulability interval, the most effective anticoagulant determined in the present invention is used for further treatment.Preferably, the "predefined coagulability interval" refers to a coagulability state in which the disease-induced thrombin generation in vivo is reduced to such an extent that the risk of thrombosis and / or bleeding is minimized.Based on the coagulability modeled using the method of the present invention, and therefore based on the most effective anticoagulant treatment, the current treatment can be modified to mitigate such effects (Example 3).

[0074] In one embodiment the invention relates to a method of the invention, a compound for use of the invention or a method of treatment of the invention, wherein the compound is a compound selected from the group consisting of vitamin K antagonists, particularly fluindione, warfarin or coumarin, direct thrombin inhibitors, particularly dabigatran, argatroban or hirudin and direct FXa inhibitors, particularly rivaroxaban, edoxaban, apixaban, heparin or heparin-like drugs.

[0075] In certain embodiments, the invention relates to a method of the invention, a compound for use of the invention, or a method of treatment of the invention, wherein the compound is a compound selected from the group consisting of nonsteroidal anti-inflammatory drugs, corticosteroids, rapamycin, high density lipoproteins, compounds that raise HDL-cholesterol, rho-kinase inhibitors, antimalarials, acetaminophen, glucocorticoids, steroids, beta-agonists, anticholinergics, xanthine derivatives, sulfasalazine, penicillamine, antiangiogenic agents, dapsone, psoralens, anti-TNF agents, anti-IL-1 agents, and statins.

[0076] In certain embodiments, the invention relates to a method of the invention, a compound for use of the invention, or a method of treatment of the invention, wherein the compound is a compound selected from the group consisting of an irreversible cyclooxygenase inhibitor, an adenosine diphosphate (ADP) receptor inhibitor, a phosphodiesterase inhibitor, a protease-activated receptor-1 (PAR-1) blocker, a glycoprotein IIB / IIIA inhibitor, an adenosine reuptake inhibitor, dipyridamole, a thromboxane inhibitor, and a thromboxane receptor blocker.

[0077] In one embodiment the invention relates to a method of the invention, a compound for use of the invention or a method of treatment of the invention, wherein the compound is a clotting factor that promotes clotting and / or reduces bleeding, preferably a compound selected from the group consisting of FVIII concentrate, Alphanate, Humate-P, NovoSeven, Eloctate, Fibre, Prothrombin Complex, Hemlibra and Tranexamic Acid.

[0078] In one aspect, the present invention relates to a storage device comprising computer readable program instructions for carrying out a method according to the present invention.

[0079] As used herein, the term "storage device" refers to any tangible device capable of holding and storing instructions for use by an instruction execution device.

[0080] In some embodiments, the storage device described herein is at least one selected from the group of electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof.

[0081] A non-exhaustive list of more specific examples of storage devices includes the following: portable computer diskettes, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanically encoded devices such as punch cards or ridge-in-groove structures with instructions recorded thereon, and any suitable combination of the above. Storage devices as used herein should not be construed as being ephemeral signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through wave guides or other transmission media (e.g., light pulses passing through fiber optic cables), or electrical signals transmitted over wires.

[0082] The computer readable instructions described herein may be downloaded from a computer readable storage medium into a respective computing / processing device or via a network to an external computer or external storage device.

[0083] Computer readable program instructions for carrying out operations of the present invention may be either source code or object code written in any combination of one or more programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine language instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or conventional procedural programming languages, such as object-oriented programming languages ​​such as Smalltalk, C++, and the "C" programming language or similar programming languages.

[0084] The computer readable instructions may execute entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server.

[0085] In one aspect, the present invention relates to a server comprising the storage device of the present invention, at least one processing unit for executing computer readable program instructions, and a network connection for receiving input data.

[0086] The term "network connection" as used herein refers to a communication channel of a data network. The communication channel can allow at least two computing systems to communicate data with each other. In some embodiments, the data network is selected from the group of the Internet, a local area network, a wide area network, and a wireless network. The network can include copper transmission cables, optical transmission fiber, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer-readable program instructions from the network and transfers the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device.

[0087] The server may be connected to the device for acquiring vascular images via any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (e.g., via the Internet using an Internet Service Provider). In some embodiments, electronic circuitry, including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may execute computer readable instructions by utilizing state information of the computer readable program instructions to individualize the electronic circuitry to perform aspects of the present invention.

[0088] In one embodiment, the present invention provides a system for classifying, predicting and / or monitoring treatment response, comprising: a) a measurement device comprising a container for receiving a blood sample and a reagent for determining coagulation biomarkers, said coagulation biomarkers being determined in said blood sample by at least two different assays; b) a processing device for executing computer readable program instructions, comprising a network connection to a storage device and / or server of the present invention, the server being a server according to the present invention; and c) input and / or searchability, said input and / or searchability allowing said server and / or said processing device to access patient / animal background information. The present invention relates to a system comprising:

[0089] In a further aspect, the present invention relates to a computer system having installed thereon software capable of providing an individualized anticoagulation treatment regimen based on a model of coagulation or a part thereof obtained by the method of the present invention and on the coagulation value as input data, preferably the computer system includes calculating an individualized pharmacodynamic value. As used herein, a "computer system" may take the form of a hardware aspect, a software aspect (including firmware, resident software, microcode, etc.) or an aspect combining software and hardware aspects, all of which may be generally referred to herein as a circuit, engine, module or system. Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable mediums having computer readable program code embodied thereon. The program source code may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any kind of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer via the Internet. Some of the calculations or modeling of the present invention may also be performed in the context of the Internet of Things (IoT).

[0090] The "installed software" may be executed by a computer system, and the software herein may be selected from the group consisting of NONMEM™, Certara Phoenix™ PK / PD software, DoseMe, TDMx, InsightRx, BIOiSIM, Tucuxi, and the like. As used herein, the term "input data" refers to coagulation using the method of the present invention. Thus, the term "input data" refers to coagulation information obtained from biomarker diagnostics, alone or in combination with further data such as patient background data. Example 3 describes three modules for the design of a personalized anticoagulation treatment system, where module 1 is an information system for the patient, requiring inputs obtained manually or automatically. Module 2 determines fibrinogen levels using CCT and TFT tests to generate statistical estimates for fibrinogen levels, coagulation status, thrombin and / or fibrinolytic activity. Module 3 may issue warnings regarding drug-drug interactions and provide personalized anticoagulation treatment regimens. A computer system or software may perform all or part of the method of the present invention. In general, the modules described herein refer to logical modules that may be combined with other modules or divided into sub-modules, regardless of their physical organization or storage.

[0091] Thus, the present invention is based at least in part on the surprising discovery that a computer system may be capable of providing an individualized anticoagulant treatment regimen based on a model of coagulability and coagulability values ​​as input data. The determined individualized anticoagulant treatment regimen may be output data that provides management guidance regarding precise and individualized anticoagulant dosage to reduce the risk and occurrence of thrombosis and / or bleeding.

[0092] The general methods and techniques described herein may be carried out according to conventional methods known in the art, unless otherwise specified, as well as in various general and more specific references cited and discussed throughout this specification.See, for example, WO 2019 / 068940, Mackie et al. 2002, Mackie et al. 2003, Undas A. 2017, Zirlik and Bonde 2016, Kajy and Ramappa 2009, Adeboyeje et al. 2017, Ordi-Ros et al. 2019, Harter et al. 2015, Hempenius et al. 2021, Brown et al. 2020, Hori et al. 2013, Koverech et al. 2018.

[0093] Although aspects of the present invention have been illustrated and described in detail in the drawings and the foregoing description, such illustrations and descriptions should be considered as illustrative or exemplary, and not restrictive. It will be understood that changes and modifications may be made by those skilled in the art within the scope and spirit of the following claims. In particular, the present invention encompasses further aspects having any combination of features from the different embodiments described above and below. The present invention also encompasses all further features that are individually shown in the drawings, but which may not be described in the preceding or following description. Also, single alternatives of the embodiments and single alternatives of the features described in the drawings and description may be excluded from the subject matter of other aspects of the present invention.

[0094] Throughout this specification, unless the context requires otherwise, the words "comprise", "comprises" and "comprising" are understood to mean the inclusion of a stated step or element or group of steps or elements but not to the exclusion of any other step or element or group of steps or elements.

[0095] The terms "include" and "comprise" are used synonymously. "Preferably" means one option in a set of options that does not exclude other options. "For example" means one example that is not limited to the examples mentioned. "Consisting of" means including and limited to everything that follows the word "consisting of". [Brief description of the drawings]

[0096] [Figure 1] Comparison of the determined plasma fibrinogen concentrations at different time points obtained from the CCT (squares) and TFT (triangles) tests with the derived coagulabilities (circles and solid line) in a healthy subject (A) and in a patient suffering from chronic hypercoagulability (B). The healthy subject (A) has a normal coagulability that varies between 0 and 0.3, whereas the patient (B) shows a high coagulability (hypercoagulability) that varies between 1.7 and 2.5 within that period. [Diagram 2] Example of a typical PK (pharmacokinetic) model for a new oral anticoagulant (e.g., rivaroxaban). The Y-axis represents drug concentration and the X-axis shows the time progression. The peak plasma concentration of the anticoagulant reaches a peak level immediately after ingestion of the oral anticoagulant. Each "peak" to "trough" phase is divided equally into three phases (upper, middle and lower) bounded by three brackets. [Diagram 3] Comparison of plasma fibrinogen concentrations obtained from CCT (squares) and TFT (triangles) tests at different time points with derived coagulability (circles and solid line) in healthy subjects who developed acute inflammation before day 0. Coagulability within 4 days ranges between 1.2 and -0.6. Coagulability is reduced within 2 days, implying inactivation of thrombin and high concentrations, and subsequent increased activation of fibrinolysis generating anticoagulant factors such as FDP, which interferes with the CCT test. [Figure 4]Example of a pharmacokinetic model showing the PK profile of an anticoagulant before dose adjustment (indicated by the horizontal arrow bar below the X-axis). The Y-axis represents the drug concentration and the X-axis represents the time progression. Based on the coagulation tests, the coagulation pathways are more active than normal, indicating hypercoagulability. To reduce the hypercoagulability, Module 2 calculates the required reduction and the new therapeutic range based on the pharmacodynamic (PD) model. The PD model suggests an adjustment of the therapeutic range (defined by the two dotted lines "Max" and "Min") to achieve the ideal coagulability. The new therapeutic range, which is between "Max" and "Min", is superimposed on the simulated PK profile and the newly adjusted treatment regimen is adopted at the indicated time (the vertical filled arrow indicates the start of the new regimen). [Diagram 5] Fibrin(ogen) determined via CCT and TFT in two different populations: healthy controls vs. patients with liver disease.

[0097] The following are examples of methods and compositions of the present invention. Given the above general description, it will be understood that various other embodiments may be practiced.

[0098] Aspects of the present invention are further described by the following illustrative, non-limiting examples, which provide a better understanding of the embodiments of the present invention and its many advantages. The following examples are included to demonstrate preferred embodiments of the present invention. It should be understood by those skilled in the art that the techniques disclosed in the following examples represent techniques used by the present invention to function well in the practice of the present invention, and therefore can be considered to constitute preferred modes for its practice. However, those skilled in the art should understand in light of this disclosure that many changes can be made to the specific embodiments disclosed without departing from the spirit and scope of the present invention and still obtain the same or similar results. Several documents, including patent applications, manufacturer's manuals, and scientific publications, are cited herein. The disclosures of these documents are not considered relevant to the patentability of the present invention, but are incorporated herein by reference in their entirety. More specifically, all references are incorporated by reference to the same extent as if each individual document was specifically and individually indicated to be incorporated by reference.

[0099] example Example 1 To determine the coagulability of blood, multiplex coagulability assays were performed using (a) clot-based and (b) enzyme-based fibrinogen tests. The information provided by the assays is whether the blood is normocoagulable, hypercoagulable or hypocoagulable by measuring the fibrinogen concentration in the plasma.

[0100] To estimate the coagulation kinetics, the fibrinogen concentration obtained by the clot-based assay was subtracted from the concentration obtained by the enzyme-based fibrinogen assay. Thus, coagulability is determined by subtracting the CCT (Clot-based Clauss Fibrinogen Test) value from the TFT (True Fibrinogen Test) value (coagulability = CCT - TFT). As an example, a higher value after subtracting the obtained concentrations of the test indicates a higher amount of procoagulant factors and therefore an increased thrombin activity. Thus, the greater the in vivo thrombin activation, the higher the value obtained from the coagulability test. This leads to the finding that higher values ​​are associated with increased coagulability.

[0101] a) Clot-based fibrinogen test Clot-based fibrinogen tests are described by Mackie et al. (2002). According to the present invention, any of the following tests from various tests can be performed to obtain fibrinogen levels: CCT (Clot-Based Clauss Fibrinogen Test), PT (Prothrombin Time-Derived Fibrinogen Test) or PTT (Determination of Partial Thromboplastin Time) or any other clot-based test.

[0102] Those skilled in the art know how to carry out CCT test. Thus, as an example, can use Multifibren-U from Siemens and / or HemosIL Fibrinogen-C from IL / Werfen.Furthermore, it is known that CCT test can show fibrinogen concentration higher than the actual concentration due to enhanced clotting efficiency by procoagulant factors caused by thrombin activity.

[0103] In addition to the use of an individual's plasma, essential reagents for the CCT test may be: serine proteases (e.g. thrombin), - an agent that increases the polymerization time (e.g., Gly-Pro-Arg-Pro or Gly-Pro-Arg-Pro-Ala or the like), -Heparin neutralizers (e.g., polybrene).

[0104] By way of example, another clot-based fibrinogen test that can be used within the scope of the present invention is the PT test (e.g., the PT-fibrinogen test of IL / Werfen) or the PTT test. The PT test is based on changes in light scattering or optical density, and the commercial availability and composition of the selected reagents as well as the protocol for performing the assay may be variable and adjustable.

[0105] In addition to the use of an individual's plasma, the essential reagents for a PT or PTT test may be: thromboplastin reagents (e.g. rabbit brain thromboplastin), -Heparin neutralizers (e.g., polybrene).

[0106] b) Clot-independent, enzyme-based fibrinogen test A clot-independent, enzyme-based fibrinogen test is described in WO 2019 / 068940. The fibrinogen test specifically determines the fibrinogen concentration even in the presence of natural and physiological interfering factors, which may be procoagulant and / or anticoagulant. The assay was performed using a TFT test, e.g. Pentapharm's Pefakit fibrinogen test.

[0107] In addition to using the individual's plasma, the necessary reagents may be: - serine endopeptidases (venombin A, e.g. batroxobin), - peptide substrates (e.g. Pefachrom TH Tos-Gly-Pro-Arg-pNA), polymerization inhibitors (e.g. Pefabloc FG Gly-Pro-Arg-Pro), - inhibitors of non-specific proteinase activity (e.g. Pefabloc SC AEBSF, aprotinin), - Chelating agents (e.g. EDTA).

[0108] Fibrinogen can be activated through its catalytic cleavage by the thrombin-like enzyme serine endopeptidase from snake venom. This assay determines the fibrinogen concentration in plasma samples by competitive enzyme kinetics.

[0109] Example 2 Coagulation tests can provide an indication of thrombin generation. Employing methods incorporating patient data and novel biomarkers can aid in the management of anticoagulation treatment. Three clinical studies were performed in healthy individuals and patients undergoing anticoagulation treatment.

[0110] a) Clinical Study A: Calculation of coagulability values ​​in a healthy population with reduced inflammation levels Clinical Study A was conducted in healthy individuals (n=9). Plasma samples were collected to measure coagulation and determine CRP (C-reactive protein) levels. The health status of these individuals was confirmed by obtaining low levels of CRP, which indicates reduced levels of inflammation that may indirectly correlate with activity of the coagulation pathway. However, high levels of CRP indicate acute inflammation.

[0111] CRP (C-reactive protein) assay The CRP assay utilizes antibody-antigen binding, and CRP is a common inflammation biomarker and can be measured by ELISA. During an immune response, the biomarker can induce the expression of tissue factor (TF), which can further activate the coagulation cascade. This assay can also examine the health status of an individual, as it is used in clinical research. Healthy individuals have normal coagulability ranging from -0.5 to 0.5. These low values ​​indicate low coagulation pathway activity, which correlates with reduced inflammation (Figure 1A).

[0112] result As an example, in clinical study A, the measured CRP levels varied between 21 ng / mL and 300 ng / mL. These values ​​were lower than the reference level of 5,000 ng / mL. The determined coagulability values ​​(n=9) ranged from -0.3 to 0.3, indicating reduced inflammation. In contrast, plasma with CRP values ​​above 7,000 ng / mL showed a coagulability of 1.7 and was used as a control indicating increased inflammation.

[0113] This study shows that the coagulability range in healthy populations exists mainly between -0.5 and 0.5 (the extension of 0.2 is the inclusion of possible error). This coagulability range represents normal coagulability, i.e. values ​​above -0.5 and below 0.5, with low variation around "0" (zero) signifying low coagulation pathway activity and correlating with reduced inflammation (Figure 1A).

[0114] b) Clinical Study B: Calculating coagulability values ​​in a healthy population To further validate the coagulability values ​​in a healthy population, clinical study B was performed. Thus, for the clinical study, a random population of self-declared healthy individuals (n=36) and their plasma samples were included to measure coagulability values ​​and determine coagulation status (hypercoagulable, hypocoagulable, or normocoagulable).

[0115] result The determined coagulability of tested individuals in the clinical study ranged between -1.1 and 1.5. Half of the population studied (50%) had normal coagulability values ​​in the range of -0.5 to 0.5, while the other half encompassed values ​​outside the range of -0.5 and 0.5. In contrast, 28% of the population had coagulability values ​​in the range of -1.5 to -0.5, and 22% of the population had values ​​between 0.5 and 1.5.

[0116] Negative coagulability (values ​​>-1.5 and <-0.5) or hypocoagulability (representing 28% of the population) reveals fibrinolysis-induced production of fibrin degradation products (FDPs) or fibrin-derived anticoagulant factors, which inhibit clot formation. This also indicates activation of the coagulation pathway at an earlier time point. These anticoagulant factors may lose their negative effect in the coagulation process if further processed to subsequent stages.

[0117] On the other hand, positive coagulability (values ​​>0.5 and <1.5) or hypercoagulability (representing 22% of the population) indicates significantly increased procoagulant factors due to activation of the coagulation pathway. This study provides an initial reference range for a healthy population, since coagulability within an individual changes within a few hours. Therefore, coagulability tests can be performed multiple times at different time points in order to create a more accurate computational model of the individual and be able to compare this model with the population model in the database.

[0118] c) Clinical research C: Calculate coagulability values ​​for anticoagulated patients Clinical study C was initiated to investigate modern anticoagulant treatments for thrombosis and thus to evaluate the efficiency of the treatments by measuring the activity of the coagulation pathways. Plasma samples from 19 patients were tested to investigate the coagulation pathway activity using coagulation tests (CCT and TFT) and D-dimer tests. These patients were given various anticoagulants such as rivaroxaban, apixaban, edoxaban, dabigatran or argatroban, and the drug concentration was determined for each individual. The aim of the study was to investigate the activity of the coagulation pathways in relation to the determined drug concentration in plasma, both by coagulation tests and D-dimer tests.

[0119] Coagulation factor assay: D-dimer (DD) assay The D-dimer assay is an immunoassay based on antibody-antigen binding technology. D-dimer is an antigen derived from the proteolysis of fibrin. This assay is an in vitro diagnostic test that indirectly indicates activation of thrombin or the coagulation pathway. During fibrinolysis, blood clots are proteolytically degraded, resulting in the formation of fibrin-derived intermediates such as fibrin degradation products (FDPs) and D-dimers (DDs). DD concentrations can indirectly indicate in vivo thrombin activity, which can occur hours to days earlier. Various plasma components such as human anti-mouse antibodies and FDPs interfere with the D-dimer assay. Thrombosis or high in vivo thrombin activity results in high DD values. Therefore, the DD assay is mainly used to confirm whether a patient is experiencing thrombosis.

[0120] result The pharmacokinetics (PK) of anticoagulants in plasma usually shows a very rapid rise in drug concentration that reaches a peak level and therefore a peak concentration within a short period of time after ingestion of the anticoagulant. The drug concentration in plasma declines slowly from the peak (maximum) concentration to reach a trough (minimum) concentration that is very close to the lowest detectable concentration (Figure 2). The pharmacokinetic (PK) profile correlates with the drug concentration, which is classified into three levels (upper, middle, lower) by subdividing the range from the peak concentration to the trough concentration equally into three parts (Figure 2, Table 1).

[0121] The DD test can show negative and positive values, with values ​​below 500 classified as negative and values ​​above 500 classified as positive. Values ​​ranging from 501 to 1,500 are denoted as "+" and indicate a weak positive. In contrast, a moderate positive (denoted as "++") has a value between 1,501 and 2,500, and a strong positive (denoted as "+++") has a value greater than 2,501 (Table 1).

[0122] Furthermore, a correlation exists between the results of coagulation tests and DD tests, even though they detect different analytes. When treated with anticoagulants, approximately 60% of patients showed positive DD values, indicating activation of the coagulation pathway. Furthermore, a negative value of the DD test result did not indicate inactivation of the coagulation pathway, since the measurement would have yielded a negative finding if the blood collection time was not in the DD peak phase or at the appropriate time. In fact, patients with ID NOs: 11, 12, 13, 16, 18 and 19 showed coagulation pathway activation based on the coagulation test, but negative values ​​for the DD test. This is suggested to occur because D-dimers are formed at a later time point after activation of the coagulation pathway. Similar to DD, coagulation biomarkers are dynamic within individuals over different periods of time according to health status and anticoagulation treatment. In contrast to DD, coagulation can be measured at earlier time points, giving faster results. Clinical Study C was performed to evaluate the coagulation test in direct comparison with the DD test when patients were treated with anticoagulants at a single time point. This study confirmed that optimization of anticoagulant dosage is required on an individual basis to reduce the risk of ineffective treatment. Therefore, coagulation testing can be used to allow individualized monitoring and treatment adjustments, thus enabling effective treatment. [Table 1]

[0123] Based on Table 1, about 60% of all samples tested showed a coagulability above 1.5, and about 40% of these samples had a coagulability within the range of the healthy population in clinical trial B. The higher the PK profile (top), and therefore the higher the drug concentration, the greater the inhibition of the coagulation pathway. The PK profile at the bottom indicates that the drug concentration in the plasma is almost at its lowest point, which means that such a state has a lower ability to inhibit the activation of the coagulation pathway. A high coagulability value means a high activation of the coagulation pathway. As an example, the plasma samples of patients with ID NO: 3 and 4 who were given apixaban had PK profiles at the bottom, with coagulability values ​​above 1.5, and therefore the plasma was hypercoagulable compared to the plasma of the healthy population. This means that for these two patients, the coagulation pathway was activated. The high DD levels of these patients confirmed the activation of the coagulation pathway and subsequent fibrinolysis. This shows the importance of individualized drug treatment to adjust the dosage, since, as shown in the example, it is necessary to reduce the activation of the coagulation pathway, especially for these two patients.

[0124] In another example, a group of patients was given the anticoagulant rivaroxaban. Blood samples from patients with ID NOs: 15, 16, and 19 showed hypercoagulability (coagulability >1.5) in the upper and lower phase PK profiles, indicating high coagulation pathway activity. Plasma samples from patients with ID NOs: 17 and 18 were normocoagulable (see Clinical Trial A), indicating low levels of in vivo coagulation pathway activity at the time of blood collection and anticoagulation treatment regimen. Consistent observations were made in patients treated with edoxaban, dabigatran, and argatroban.

[0125] Example 3 CPT system concept A CPT (Coagulation-Based Personalized Treatment) system is an anticoagulant drug management system guided by novel coagulation biomarkers. Examples of such CPT systems are: 1. A web-based application that accepts information (including coagulation data) to be manually entered into the system and generates a list of calculated results. 2. An application installed on a computing device of any operating system such as IoT that accepts information (including coagulation data), said information may be manually entered into the system and generate a list of calculation results. 3. A system coupled with a device that can measure coagulation and other biomarkers using blood samples, such as an IoT. The data generated by the device is automatically transferred to an on-board computing system or transmitted to a computer system via a wired or wireless connection. A list of results is generated to guide physicians and medical personnel by providing individualized and optimized anticoagulation treatment regimens. A computer system having partially or completely the functionality as described in 4.3., which functionality can be transmitted to a USB stick.

[0126] Simulations and calculations using pharmacodynamic (PD) and pharmacokinetic (PK) models are required to perform health and risk assessments. Such examples of parameters and information are: 1. Biomarker information from coagulation studies and separately, information from each test, CCT and TFT, 2. Physiological parameters of the patient / animal, such as age, sex, physiological condition (e.g., blood pressure, renal function) or disease; 3. Pharmacological and clinical treatment information for anticoagulants, antiplatelet agents, anticancer agents and anti-inflammatory agents.

[0127] The CPT computer system may consist of three built-in modules. Furthermore, an example of a compartment for extending such a CPT system may be a remote device (e.g., IoT device) for the patient, which allows parameters for, for example, blood pressure data transmission or other data transfer of important parameters. The system may inform the physician about abnormal health events of the patient. Such a remote system may also have a built-in compartment to perform coagulation tests and provide test analysis of health status and risk, PD / PK models, or anticoagulation treatment regimens. The results may then be transmitted to a server.

[0128] Additionally, the CPT system built-in computational models may be created by machine learning approaches, or traditional approaches such as Bayesian-based systems and / or any statistical PK modeling program known to one of skill in the art.

[0129] Module 1 Module 1 is described as an information system for patients / animals, requiring inputs obtained manually or automatically. Thus, this module is designed to be an information inlet by automatically obtaining patient / animal information generated or recorded by other computer systems, such as the LOINC® Mapping system. Module 1 is also designed to act as a patient / animal information storage system, and this information as well as the calculations and models obtained from modules 2 and 3 are stored within this module 1. In this way, the modules work together and exchange information between the modules and the electronic medical record system. Module 1 is also designed to interact with accessed or existing electronic health / medical record systems, so that information originating from patients / animals can be securely exchanged. Another important function of module 1 is its management system of patient databases, such as scheduling appointments for visits, consultations or blood draws, etc. This allows patients to be reminded about taking medications and making appointments for doctor's visits.

[0130] Module 2 Module 2 takes information from module 1, generates modeled coagulation data by computational analysis, and generates individualized therapeutic windows by computational models. This module can simulate coagulation models based on individual coagulation information over a period of time. To generate mathematical models for health and risk assessment, individual coagulation data is statistically ranked and modeled according to population profiles. Individual basal values ​​of pharmacodynamic effects, intra-individual and inter-individual variability can be determined based on combinations (e.g., subtraction or division) of coagulation readings of at least two different coagulation assays (see Example 9).

[0131] The coagulation status indicates any activity related to the coagulation pathway and immune response, and thus can provide a health status and a risk assessment for thrombosis and bleeding. The health status and risk assessment can be calculated statistically based on population studies. Data obtained from patients / animals that can provide information on the health status include, for example: - fluctuating thrombin and fibrinolytic activity, - Coagulation status obtained from coagulation studies It could be.

[0132] Computational and statistical analysis in risk assessment studies regarding thrombosis and / or bleeding may be performed in module 2. The acquired data from module 1 may be analyzed in module 2 to investigate the health status of an individual, for example, by using information such as: - thrombin and fibrinolytic activity, - coagulation status obtained from coagulation testing, - Population studies - Determined fibrinogen levels obtained from CCT and TFT tests, -Simulation and alignment of PK and PD profiles during anticoagulant use (alone or with other drugs) Calculated plasma drug concentrations.

[0133] For example, if the patient is prescribed only one anticoagulant, module 2 can calculate whether this anticoagulant and regimen at the prescribed concentration improved the coagulant status. If the patient is prescribed multiple drugs at once, such as antiplatelet, anti-inflammatory and / or anticoagulant, module 2 may be able to recommend a stepwise reduction in hypercoagulability and adjustment of anticoagulant concentrations for the new drug prescription. Within this module, multiple dosing schemes can be generated to ensure the effectiveness of ongoing treatment. Additional coagulant data is then required to calculate the following anticoagulant dosage levels. Another example is if the patient suffers from a clotting factor deficiency (acquired or hereditary) during treatment with an anticoagulant, the system may warn the user and recommend reducing the therapeutic range or use a stepwise approach depending on the case.

[0134] result Figure 3 shows a healthy individual developing acute inflammation and elevated thrombin activity prior to day 0 that subsides prior to day 2. In contrast, fibrinolytic activity, mediated primarily by plasmin activity, is increased prior to day 2. Thus, the predominant presence of anticoagulant factors such as FDP influences the clotting process in the CCT test. Thus, one feature of Module 2 is to generate a model of in vivo fibrinolytic activity based on the coagulation data.

[0135] Module 2 calculates the plasma concentration of an anticoagulant or a series of anticoagulants predicted to achieve coagulation modulation to an acceptable level. This concentration range, containing minimum and maximum drug concentrations or other PK parameters appropriate to describe the relationship between individual drug exposure and coagulation modulation, is calculated based on mathematical and / or statistical models generated from clinical data of patients treated with anticoagulants. Within this concentration range, patients receive safe and highly effective treatment. This method is applicable to patients already receiving anticoagulant treatment. According to clinical studies, patients with ID NOs: 15, 16 and 19 taking rivaroxaban show hypercoagulability when PK is at the upper and lower levels, respectively. However, the coagulability data of patients with ID NOs: 17 and 18 show effective treatment and normal coagulability values ​​after taking the same dose of rivaroxaban. As shown in the example of FIG. 4, rivaroxaban treatment regimens and dosages can be individually adjusted for patients with ID NOs: 15, 16 and 19. After treatment adjustment is achieved in these patients (ID NOs: 15, 16 and 19), coagulation should improve, as exemplified by patients with ID NOs: 17 and 18. The same principle can be applied to patients prescribed apixaban (Table 1, ID NOs: 1-4) or any other anticoagulant.

[0136] The safety thresholds for each anticoagulant are contained in the CPT system. Module 2 retrieves the patient details stored in Module 1, analyzes interactions with other prescribed drugs, e.g. antiplatelet drugs, in terms of risk of adverse events, and recommends a stepwise approach to anticoagulant regimen adjustments. To illustrate one of the safety features, patients who only require anticoagulant treatment are recommended to receive a drug treatment concentration close to the safety threshold of this anticoagulant. The system can alert the user and recommend a lower, safer dosage in combination with other drugs, such as inflammation or anti-inflammatory regulators. Thus, the CPT system allows multiple drugs to achieve a safer and more effective treatment.

[0137] Module 3 PK modeling is a key feature of Module 3, which integrates the results of the computational and statistical analysis performed by Module 2 with suitable parameters to customize the best anticoagulant treatment regimen for an individual and to individualize the PK simulation model by providing a simulated treatment regimen. There is already a wide range of existing software to model PK and individualized dosage and treatment regimens to provide data on diseases and drugs. However, the present CPT system can convert the target treatment effect of an anticoagulant into its concentration in PK and recommend individualized drug dosage and regimens according to the parameters contained in Module 1. Another feature of Module 3 is the ability to analyze the gaps between the individualized posology and the standard generic posology. Module 3 can also calculate the risks due to these gaps, allowing the user to understand and manage possible risks. Furthermore, Module 3 can issue warnings about drug-drug interactions and generate modified simulations of individualized PK when the patient is given, for example, a P-glycoprotein inhibitor or inducer. The CPT system is able to simulate PK taking into account possible genetic variations in metabolic enzymes that affect the PK of individual anticoagulants.

[0138] result As an example, the PK model can be influenced by drug-drug interactions. Drug absorption of orally administered anticoagulants can be influenced by P-glycoprotein inducers (e.g., rifampicin) and inhibitors (e.g., verapamil), which can affect the drug PK profile. When rifampicin is co-administered with the anticoagulant dabigatran, the maximum plasma concentration of dabigatran can be reduced by about 67%, which can significantly affect the effectiveness of the anticoagulant treatment. Another example of a drug-drug interaction is the co-administration of a cytochrome P450 inhibitor with an oral anticoagulant. As the PK model is influenced by drug-drug interactions and many other parameters, Module 3 takes all of this into account and recommends drug dosage and treatment regimens, warnings and risks of drug-drug interactions, and the possibility of a stepwise approach to reduce coagulability to the target interval in order to achieve a reduction in the risk of thrombosis and / or bleeding.

[0139] Example 4: Liver disease is an interesting study model of the coagulation system due to the fact that the liver produces most of the coagulation factors, including both procoagulant and anticoagulant factors as well as other proteins involved in fibrinolysis. As liver disease progresses, the coagulation system undergoes significant changes by rebalancing these factors, and therefore typical coagulation laboratory parameters cannot provide insight into the coagulation system. These current laboratory parameters are unable to predict the thrombosis and / or bleeding risk of such patients. Thus, new diagnostic methods for such prediction are needed. This example demonstrates the use of coagulability parameters in assessing the risk of thrombosis and bleeding.

[0140] This new biomarker coagulability is composed of several key components: CCT, TFT and CCT:TFT. The diagnostic method TFT is important because it measures the true fibrinogen level in a blood sample. TFT is highly specific, so it does not measure any molecules closely similar to fibrinogen, such as fresh fibrin derivatives generated by removing fibrinopeptide Aa from fibrinogen by the action of thrombin, the so-called in vivo thrombin generation.

[0141] On the other hand, CCT gives a mixture of indications regarding the patient at the time of blood collection. These indications include the amount of fibrinogen and fibrin derivatives. These fibrin derivatives are present in the blood due to in vivo thrombin generation induced by trauma or disease. Since the initial action of thrombin on fibrinogen and its subsequent modification and degradation via the fibrinolytic system, these derivatives are present in a variety of dynamic manners, since different species are generated, developed, converted and degraded at different times. These derivatives exert different effects on the coagulation reaction on which CCT depends, either enhancing coagulation (e.g. soluble fibrin complexes), inhibiting coagulation (e.g. some FDPs) or having a neutral effect (e.g. DD). Thus, CCT is a method to measure fibrinogen and fibrin derivatives. CCT can respond to fast in vivo thrombin generation to which DD cannot respond. Moreover, the fibrin derivatives detectable by CCT have a very adequate half-life compared to the inappropriately long half-life of DD.

[0142] The overall effect of these derivatives is easily measured by determining the relationship between CCT and TFT. For simplicity, this patent mainly illustrates the relationship with simple calculations such as CCT minus TFT. When CCT has a value larger than TFT (e.g., FIG. 1B), this means that the overall effect exerted by these derivatives is enhancing the coagulation reaction, with the main derivative being, for example, soluble fibrin complex. Thus, the most important information regarding in vivo thrombin generation is incorporated in the CCT. Thus, the value of CCT indicates the health status. [Table 2]

[0143] Chronic liver disease plasma samples were collected and analyzed for factor V and DD. Samples were also measured by CCT and TFT. Factor V, a procoagulant factor, was determined to estimate liver function levels. These patients showed abnormal standard coagulation test parameters determined by standard CCT, e.g., normal fibrin (fibrinogen) levels, but prolonged PT and aPTT. Due to the fact that these patients had on average about 50% factor V compared to normal, they were in an advanced stage of liver disease. These patients had on average a TFT of about 2, statistically and significantly lower than the average of 2.8 (Figure 5). In such disease states, the risk of thrombosis and bleeding is not put in the same category as patients who do not have liver problems and do not have reduced levels of both procoagulant and anticoagulant factors. The thrombus risk in such liver patients is higher. For example, a liver disease patient, with a CCT of 4 and a TFT of 2, and therefore a coagulability (or CCT:TFT) of +2. This patient has a higher thrombotic risk than a patient without liver disease with a CCT of 5, a TFT of 3, and a CCT:TFT of +2. Thus, TFT, as exemplified here by liver disease, can provide a robust indication of how procoagulant and anticoagulant factors rebalance themselves, other than true fibrinogen levels. Algorithms that can predict risk are created either through machine learning of many clinical cases or other mathematical means.

[0144] TFT fibrinogen levels in healthy populations were distributed between 2.3 and 3.4, with a mean of 2.7 (control group in Figure 5). Only in severe liver disease populations could TFT fibrinogen fall below normal levels (liver group in Figure 5). Thus, unlike CCT, which reflects disease status and pathological in vivo thrombin generation, the TFT values ​​of any individual, either healthy or diseased, will be distributed within these two populations represented in Figure 5. This was further confirmed in a group of patients treated with anticoagulants (Table 1), whose TFT values ​​were between 1.9 and 3.2. Since TFT lacks the ability to indicate fast dynamic in vivo thrombin generation for an individual, a further example will show drug treatment effects on reversing or reducing hypercoagulability by changes in CCT values ​​alone, for clarity and simplicity. Another important point is that individuals with less than 50% liver function (ID6) are unable to produce fibrinogen above normal levels, e.g., above 4 g / L (Table 2). Thus, CCT reflects more than fibrinogen levels; CCT is an indicator of fibrin derivatives produced by in vivo thrombin generation.

[0145] The use of biomarkers of coagulation, especially CCT components, is particularly important to reveal the underlying disease state and the effect of pharmacological interventions. Since CCT can detect the generation of fibrin derivatives, the component CCT is the only biomarker component that reveals pathological in vivo thrombin generation, which is the underlying cause of hypercoagulability or hypercoagulability in many diseases. Therefore, if a clinical study is designed to measure the general trend of CCT after a pharmacological intervention known to interfere with the coagulation system, this study can demonstrate whether CCT, a dynamic component of coagulation biomarkers, can be generalized in its utility as a biomarker for monitoring the progression of diseases and drug treatments.

[0146] Example 5: Clinical studies were conducted to study the effect of anticoagulants on CCT, and clinical data were collected and analyzed to show the clinical usefulness of CCT in attenuating the coagulation system by pharmacological intervention. Several studies, conducted in accordance with medical research ethical standards, were conducted to draw conclusions about such clinical usefulness of CCT in regulating hypercoagulability or hypercoagulability caused by diseases.

[0147] First, anticoagulation studies were performed on healthy populations to show that healthy individuals have little or no fibrin derivatives and normal CCT values, and that anticoagulant treatments that lower fibrin derivatives in healthy individuals do not significantly change CCT values. In such studies, rivaroxaban studies were performed on six healthy volunteers aged 18-50 years. They met criteria for normal vital signs and clinical laboratory screening tests for infection, hematology, and coagulation, and had no abnormalities on physical examination. They were given 15 mg of rivaroxaban twice daily for 2.5 days. The dose of 15 mg twice daily was chosen because it is the highest dose approved for the initial treatment of acute venous thromboembolism (VTE). Apixaban studies were performed on another six healthy volunteers with the same health profile requirements as the rivaroxaban study. These six volunteers were given 10 mg of apixaban twice daily for 3.5 days. Blood samples were taken immediately before and 3 hours after the last dose of anticoagulant. Fibrinogen measurements were performed in duplicate.

[0148] In the rivaroxaban study, CCT changed from a mean of 2.75 (standard deviation 0.92) before rivaroxaban treatment to a mean of 2.64 (standard deviation 0.93) after treatment. The difference of -0.11 is not statistically significant. The change in CCT before and after apixaban treatment was from a mean of 2.56 (standard deviation 0.36) to a mean of 2.38 (standard deviation 0.25). The difference of -0.18 is also not statistically significant. These individuals generally had CCT values ​​around the healthy range, indicating that they generally do not have abnormal amounts of fibrin derivatives generated by pathological in vivo thrombin generation that cause hypercoagulability, for example, severe COVID-19 patients may have CCT values ​​above 6.0 and thrombosis. In other words, these volunteers were healthy and did not have hypercoagulability because of their normal CCT values. Furthermore, their CCT values ​​did not change significantly even when their coagulation system was highly inhibited. These studies clearly demonstrate that pathological in vivo thrombin generation is generally absent in healthy individuals and that high-dose pharmacological inhibition of the coagulation system in such healthy individuals results in subtle coagulability changes as revealed by CCT.

[0149] Secondly, anticoagulation studies were performed on patients with thrombosis to show that inhibition of the coagulation system is effective in patients with high fibrin derivatives or hypercoagulability, with a concomitant decrease in fibrin derivatives as revealed by CCT. This study demonstrated the efficacy of treatment through the correlation between the decrease in CCT values ​​and the improvement of physiological function.

[0150] Seventy patients with complete clinical records, diagnosed with acute cerebral infarction (ACI) and confirmed by CT or MRI were included in this study. They had to be first-time patients with ACI, the onset of the disease had to be less than 72 hours, the cause of the infarction was cardiac in origin, and they had no abnormal renal function, history of bleeding, or hemostatic abnormalities.

[0151] These 70 patients were divided into two groups, 35 in the control group and the remaining 35 in the observation group. The patients in the control group were treated with rivaroxaban (an anticoagulant), while the patients in the observation group were treated with a combination of rivaroxaban and sodium ozagrel (an antiplatelet drug). Sodium ozagrel inhibits platelet activation and aggregation through the specific inhibition of thromboxane (TX) synthase. Due to the inhibitory effect of ozagrel on platelet activation, platelets cease to be the primary lipid surface for thrombin generation.

[0152] In addition to standard treatments such as concentrated oxygen supply, all 70 patients were treated with aspirin 100 mg / tablet / day. In addition, the control and observation groups were given rivaroxaban 15 mg / tablet / day. In addition to rivaroxaban, the observation group received 80 mg of sodium ozagrel in 500 mL of glucose (5%) solution intravenously daily. All were treated for 2 weeks. Both groups have a very similar mean age and range (40-70 years).

[0153] After 2 weeks of treatment, the clinical effectiveness (neurological assessment), coagulation tests (only CCT is shown) and GCS scores of the two groups were compared. Neurological assessment was performed according to the NIH Stroke Scale (NIHSS). If the NIHSS score is reduced by more than 90%, the disability classification is grade 0 and the treatment is highly effective. If the NIHSS score is reduced to 46%-89%, the disability classification is grade 1-3 and the treatment is considered effective. If the score is less than 46%, the treatment is not effective. The neurological assessment results are summarized in Table 3. [Table 3]

[0154] Coma assessment was performed pre- and post-procedure for all subjects based on the Glasgow Coma Score (GCS) scoring system, with 15 being the highest score. Less severe coma is reflected by higher scores. Recovery based on the GCS is summarized in Table 4 along with the CCT results. [Table 4]

[0155] CCT values ​​were significantly decreased after two different treatments. The observation group had a significant decrease compared to the control group, with a P value of <0.01. The degree of decrease in CCT values ​​strongly correlates with the method of treatment. Even if either treatment method improved the patient's outcome, as exemplified by the combination of an anticoagulant (rivaroxaban) and an antiplatelet drug (ozagrel), the more the coagulation system is inhibited, the better the control of hypercoagulability and therefore the better the patient's functional recovery after stroke. The general large decrease in CCT values ​​implies a decrease in the in vivo thrombin generation process activated in the period close to before and after the stroke. As the effect of drug treatment inhibits in vivo thrombin generation, there is less generation of procoagulant fibrin derivatives and more conversion of procoagulant fibrin derivatives to anticoagulant fibrin derivatives via the fibrinolytic system. These anticoagulant fibrin derivatives exert their anticoagulant activity on all clot-based assays such as CCT, as well as other assays such as PT, aPTT and TT, as exemplified by the early FDP. Indeed, the changes in CCT values ​​are reflected in the present study, as are all these clot-based assays, which are significantly prolonged after treatment due to the anticoagulant activity of these anticoagulants. The prolongation of these clot-based assays correlated well with the type of treatment, with the observation group having a longer mean result compared to the control group (P<0.01).

[0156] The above two clinical studies, conducted in healthy volunteers and stroke patients, were conducted to show that CCT, a novel biomarker, correlates with in vivo thrombin generation and that the application of CCT to monitor coagulability changes due to hypercoagulability disorders and pharmacological interventions is valid. CCT values ​​are significantly influenced by the type and amount of fibrin derivatives generated by pathological in vivo thrombin generation, which is active in many diseases, such as cardiovascular disease, stroke, cancer, and inflammatory diseases. Coagulability, primarily reflected by CCT, is a powerful and novel biomarker with important applications in health and value-based digital healthcare.

[0157] Studies in stroke patients are consistent with published clinical studies in which combined antiplatelet and anticoagulant therapy increased the risk of bleeding due to over-suppression of the coagulation system.

[0158] Example 6: In this example, a total of 42 patients aged 35-86 years (mean age 60.5 ± 25.5) whose blood was taken to study changes in hematological parameters during VKA-anticoagulation treatment. These patients received VKA anticoagulation treatment to reduce the risk of thrombosis. These patients were recruited to study changes in VKA anticoagulant dosage and the effect of such changes on coagulation parameters, including CCT values. Patient blood samples were taken for coagulation parameter assessment before and after dosage changes. The dosage change or adjustment was maintained stable in each patient for at least one month before blood was taken and they were asked to return for further medical consultation. Based on the changes in the individuals' PT-INR (before, T0) and PT-INR (after, T1), there were essentially two groups, the "decreased" (n = 20, Table 5) and the "increased" (n = 22, Table 6) groups. To gain insight into the activity of their coagulation system, several parameters such as CCT, DD and soluble fibrin monomer (FM, an assay indicating in vivo thrombin generation) were measured. [Table 5] [Table 6] [Table 7]

[0159] The data in Table 7 show that the lower the PT-INR value, the higher the in vivo thrombin generation, as revealed by CCT, DD and FM.

[0160] Example 7: This is yet another example of how anticoagulant treatment reduces pathological in vivo thrombin generation with a concomitant reduction in fibrin derivatives detectable by CCT. This example is a highly widespread (>10%) progressive chronic disease with strong clinical manifestations of the immune and coagulation systems. Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disease that affects respiratory function with a concomitant high thrombosis risk. In this example, the study subjects were 70 patients diagnosed with COPD and who developed acute exacerbations of COPD (AECOPD). Besides standard AECOPD treatments, such as infection prophylaxis, bronchodilation, sputum removal and oxygen treatment, 32 of these AECOPD patients received no additional treatment, while the remaining 38 were treated with low molecular weight heparin calcium (LMWH, 4100 IU anti-FXa / injection, 12 hours apart, 10 days).

[0161] Treatment efficacy was evaluated based on several parameters: pulmonary function, blood gas analysis and coagulation parameters. All this information was obtained before and after LMWH anticoagulation treatment and was the same for the control group. Pulmonary function was measured in several ways, such as FEV1 (measurement of forced expiratory volume in 1 second after inhalation of a bronchodilator) and FVC (forced vital capacity, and the ratio of FEV / FVC expressed in %) as a clinical sign of respiratory capacity. Blood gas analysis was obtained by measuring the oxygen saturation (SO2), partial pressure of oxygen (PO2) and partial pressure of carbon dioxide (PCO2) of the blood. Several blood coagulation parameters were measured, they are CCT, DD, PT-INR.

[0162] As in the previous example, this study focused on the dynamic part of the coagulation biomarker CCT, which is a powerful and responsive biomarker of in vivo thrombin generation. This study included DD as a complementary indicator of thrombin activity, but it was not as specific and sensitive as CCT.

[0163] Before the start of treatment, patients in the treated and untreated groups showed no significant differences in these two clinical indices, lung function and blood gas saturation (all P>0.05, Table 8). After treatment, both groups showed significant improvement in both indices (P<0.01, Table 8). Anticoagulant treatment further significantly improved the clinical recovery indices compared with untreated controls (P<0.01, Table 8). This strongly indicates the advantage of anticoagulants targeting the coagulation system in treating AECOPD. The use of anticoagulants led to changes in coagulation parameters, as summarized in Table 9. [Table 8]

[0164] The use of anticoagulant LMWH has a strong effect on the coagulation system, the effect of which is clearly seen by the biomarker CCT (Table 9). Before treatment, both groups showed no significant differences in coagulation parameters, especially CCT and DD (all P>0.05, Table 9). Before and after treatment, significant differences were found in these parameters only within the LMWH-treated group (all P<0.01, Table 9). This is in contrast to the control group, where all parameters remained statistically insignificant before and after treatment (all P>0.05, Table 9). These coagulation parameters show that a strong inhibition of the coagulation factor FXa generally inhibited the coagulation system of these 38 AECOPD patients. As in stroke (Example 5), the reduction of pathological in vivo thrombin generation by antithrombotic drugs led to a better clinical recovery of the treated patients. The effect of such inhibition leads to a reduction in in vivo thrombin generation and promotes the fibrinolytic process, which is indicated by a reduction in CCT and a reduction in the clotting rate, as indicated by an increase in PT and PT-INR. Thus, in this example, a strong correlation between CCT and pathological in vivo thrombin generation is demonstrated. The application of CCT / coagulation biomarkers in many hypercoagulability diseases is further demonstrated. Although the AECOPD standard treatment for AECOPD was effective (Table 8, control treatment), halting the activation of coagulation pathways or in vivo thrombin generation and promoting the activation of anticoagulation pathways such as fibrinolysis by supplemental treatment with LMWH or anticoagulants greatly improves clinical recovery. [Table 9]

[0165] Although the aPTT coagulation test was included in the coagulation test panel, it is of limited usefulness due to the inhibitory effect of LMWH on the aPTT assay. The aPTT results are not included in Table 9 because of the potential adverse effect it may have on the aPTT data, especially those obtained from LMWH-treated patients. Briefly, control treatments did not significantly alter the aPTT results.

[0166] This study was a comparative study between standard AECOPD treatment with and without anticoagulants, unlike the antithrombotic treatment of stroke in Example 5. Furthermore, this study with AECOPD patients was performed without antiplatelet treatment.

[0167] Comparative studies of CCT and DD levels in different populations, including healthy controls, stable COPD controls and AECOPD individuals, show that the AECOPD population, either in an active disease phase or succumbing to relapse, exhibited a significant increase in CCT, indicating activation of the immune and coagulation systems (Table 8).

[0168] These examples represent population studies, meaning that they are designed to draw conclusions about human populations generally.

[0169] Example 8: In addition to the standard use of blood clotting drugs for hemophilia patients, the use of blood clotting drugs such as clotting factors is becoming more frequent due to the increase in acquired factor deficiencies. There are also situations where patients undergoing anticoagulation treatment suffer from bleeding, and to stop the bleeding, blood clotting drugs and / or bypassing agents (BPAs) are administered. These blood clotting drugs, such as coagulants that replace specific deficient clotting factors like FVIII or drugs that increase the efficiency of blood clotting, such as Hemlibra and NovoSeven, increase the risk of thrombosis. Although the quality of life of hemophilia patients has improved with available treatments, many still suffer from bleeding and chronic diseases caused by frequent bleeding.

[0170] Over- or under-dosing of these blood clotting drugs is the main cause of treatment failure. An individualized dosing strategy of such blood clotting drugs is required to optimize the treatment. The current pseudopharmacodynamic (PD) response of all these blood clotting drugs is mainly monitored by classical coagulation tests such as PT and aPTT, which are not suitable for many current and future treatment drugs. These in vitro diagnostic tests can only provide the pharmacokinetics (PK) of the treatment agent. These in vitro diagnostic tests cannot give insights if the patient is over- or under-given the treatment agent or drugs, and these in vitro diagnostic tests are not sufficient to show the efficacy of a generic treatment. Moreover, these tests cannot give any insights on the baseline in vivo activity of thrombin. Moreover, most of these assays are performed in the absence of many other whole blood components such as cellular and intracellular components. In such conditions, the clotting reaction is artificially stimulated to check the clotting efficiency in these assays. Since blood clotting involves the whole blood and not just some fractions of blood, the assumption that such in vitro data reflects the in vivo situation does not hold. In the absence of good methods for assessing treatment efficacy, the most commonly accepted clinical endpoints are the scoring of bleeding and other adverse events.

[0171] Another issue is the variability of the pharmacokinetics (PK) of BPA treatment in different individuals: individuals given the same dose of BPA will have different PK, and therefore, due to inter-individual differences, some individuals will require more frequent BPA administration than others.

[0172] An additional problem with these treatments, including gene therapy, is that recipients frequently develop inhibitors or antibodies (either neutralizing or non-neutralizing) against these agents or drugs, affecting PK and PD differently in individuals. In the example of congenital hemophilia A (CHA), neutralizing antibodies appear in about 30% of patients, and these antibodies reduce the efficacy of factor VIII (FVIII) treatment, which remains the most representative treatment, and depending on the neutralizing activity, exogenous FVIII cannot provide full therapeutic activity along the PK concentration range. The remaining about 70% of CHA patients without neutralizing antibodies may have non-neutralizing antibodies that can greatly affect the PK and availability of FVIII during FVIII replacement therapy. Methods of immune tolerance induction (ITI) by administering high doses of FVIII and generally including other BPAs such as FVII, rFVIIa and activated prothrombin complex concentrates (aPCC) during ITI have been developed to achieve high efficacy in overcoming these inhibitors. The use of these BPAs, including Hemlibra and others, is associated with adverse events due to increased thrombotic risk, and there are no tests or tools available to monitor this treatment process and adverse effects. A definitive monitoring method is needed to know if and how severe a patient is having inhibitor problems, both before and after ITI treatment. Monitoring is needed during ITI treatment to provide individualized guidance on treatment regimens so that the risk of bleeding and thrombosis is minimized. Since inhibitor relapse is known, monitoring is still needed after ITI for long-term determination of whether the patient remains stable after treatment. Such monitoring diagnostics are lacking and not sensitive for non-neutralizing antibodies. CHA patients with only non-neutralizing inhibitors have extremely different PK due to the shorter half-life of FVIII compared to CHA patients with only a few inhibitors at a given time point. Furthermore, it is unclear whether these patients have sufficient protection near trough levels. Therefore, an innovative monitoring test system is needed in addition to the existing available tests to individually show the effectiveness of FVIII treatment along with the overall drug PK.

[0173] Because von Willebrand factor (VWF) levels vary individually and it has been demonstrated that this factor affects FVIII stability, the PK of exogenous FVIII must be determined individually in addition to the PD determination at the time of blood draw. In addition to the factors mentioned above, this factor makes it even more cumbersome to utilize FVIII for proper function. Performing many different tests and measurements for an individual CHA in addition to other hemophilia patients such as types B and C would be resource-demanding.

[0174] Last but not least, hemophilia patients also suffer from dysregulated fibrinolysis due to less thrombin-activatable fibrinolysis inhibitor (TAFI) on the fibrin clot. Therefore, individualized treatment relying on PK or therapeutic window based on PK alone is not sufficient to completely eradicate bleeding.

[0175] Since the bleeding problem in hemophilia patients is not completely overcome by these treatments of blood coagulants or BPA, collectively referred to herein as drugs, individualized dosing regimens are necessary to optimize treatment and reduce the occurrence of bleeding.In the case of bleeding, these patients treated with some of these drugs faced thrombotic complications.In order to achieve customized treatment, individuals need to have their optimized treatment methods and therapeutic ranges determined at different stages of life, so that their quality of life can be further improved and hospitalization and medical costs can be significantly reduced.

[0176] Existing methods to determine the pharmacokinetics (PK) of these blood coagulation drugs or BPAs, such as clot-based assays such as aPTT and chromogenic tests, are widely adopted. This individual PK determination is not sufficient because this information reflects only the drug concentration and cannot inform whether this drug treatment at all time points of its PK is sufficient to protect the patient from bleeding or to induce thrombosis. For example, the drug concentration at the trough concentration may have very different efficacy for different hemophilia patients. Furthermore, existing tests for FVIII inhibitors are not standardized and are not sufficient to inform about the effect of the inhibitor on the drug treatment, especially the effect of non-neutralizing inhibitors that do not interfere with the test.

[0177] Due to the insufficiency of currently available diagnostic methods, the current treatment for hemophilia is not yet optimized for all hemophilia patients. Currently, there are no biomarkers to monitor the PD effect of treatment so that hemophilia treatment can be individually optimized before breakthrough bleeding and other bleeding occurs. All of these pains and sufferings could be avoided if the extent of individually optimized therapeutic methods and specific single or mixed treatments could be measured and adjusted accordingly, without waiting until the appearance of a catastrophic event.

[0178] A solution to the above mentioned dilemma is found in the present invention, where novel biomarkers are combined with computational algorithms that are able to calculate the risk of thrombosis and bleeding in individual hemophilia patients during drug treatment, with or without determining the individual PK during different treatment methods.

[0179] The activity of the coagulation pathway can be indicated by the activity of thrombin, which is activated through the intrinsic and extrinsic pathways, with the participation of non-cellular and cellular components in the blood. This thrombin activity leaves its mark by converting fibrinogen into fibrin and fibrin-derived molecules, which can form small soluble and insoluble polymers of various sizes and complexities, depending on the conditions. These complexes and various fibrin-derived molecules or derivatives are indicators of thrombin generation in vivo and can be procoagulant and anticoagulant factors, such as soluble fibrin (see other sections for explanation). The CCT, which is part of the coagulation biomarkers, is a strong indicator of these derivatives and fibrinogen levels. Dynamic changes in the CCT reflect how the coagulation system is responding to certain inducers or treatments, e.g. drugs such as BPA. Inducers can be, for example, immunogens, pathogens, tears and injuries, and can activate both the immune and coagulation systems. Examples of these inducers are viral infections, tissue avulsion and cardiovascular diseases. By tracking and calculating the appearance and relative abundance of these fibrin derivatives to fibrinogen, predictions of the risk of thrombosis and bleeding can be calculated. This can be done during drug or ITI treatment. Based on this approach, each hemophilia patient receives customized and optimized treatment, and healthcare providers do not rely on intuition.

[0180] Hemophilia patients rely on frequent drug treatments to restore normal coagulation function. Treatment frequency usually depends on the individual's theoretical drug PK or actual measured PK. PK can range from one week to one year, depending on the type of drug. Here, an example of a drug treatment monitored with the system described in this patent is shown to briefly illustrate how this combined biomarker and computational system can provide better information and decision-making to healthcare providers and patients.

[0181] Blood samples are tested before and after drug treatment, here using a standard dose of FVIII (PK for one week) as an example. Two measurements are taken before treatment, and many measurements are distributed along the drug PK. For each time point, coagulation biomarkers are calculated. To illustrate how the present invention can solve the current problems in hemophilia treatment, three situations are presented, representing three different patients under the same treatment as above, without FVIII inhibitors (S1), with neutralizing FVIII inhibitors (S2) and with non-neutralizing FVIII inhibitors (S3). In S1, coagulation fluctuates up and down from near zero to slightly below zero before treatment. Immediately after treatment, coagulation increases and fluctuates around the same level for one and two days, then slowly fluctuates towards zero. Immediately after treatment, the coagulation system of patient S1 recovers. Due to the basal activity of the immune and coagulation systems, procoagulant fibrin derivatives are dynamically generated and degenerated, and thus coagulation fluctuates. Towards the end of PK, in the absence of extrinsic pathway activation, drug is slowly consumed or metabolized in S1 and coagulability decreases and fluctuates around 0. The change in coagulability in S1 is far from the threshold for thrombosis and bleeding.

[0182] Before S2 undergoes treatment, coagulability fluctuates around zero, similar to S1. Immediately after treatment, coagulability spikes or increases sharply due to the high immune activation-induced procoagulant fibrin derivatives and the short-term recovery of the coagulation system. Due to neutralizing antibodies, the drug is quickly ineffective, and coagulability then drops significantly due to the much higher ratio of anticoagulant factors such as FDP compared to fibrinogen. This relatively fast return of coagulability to the negative zone compared to normal is due to the low level of TAFI on the fibrin derivatives. Due to accelerated fibrinolysis, these fibrin derivatives are degraded to completion, and in the absence of extrinsic pathway activation, coagulability will return to near and below zero from day 3 (for S2) until theoretically day 7, fluctuating monotonically around and below zero. Thus, with such an invention, medical providers can easily gain insight into this treatment for S2 and can easily determine alternative treatments using, for example, Hemlibra or NovoSeven.

[0183] Cases of S3 are much milder than those of S2. Non-neutralizing antibodies shorten the PK of such treatment until day 5, but FVIII drugs can still participate in the coagulation pathway. Thus, patient S3 does not have enough FVIII in his own system from day 5 to day 7, and in the absence of extrinsic pathway activation, coagulability fluctuates monotonically around and below zero during this period.

[0184] All these cases S1-S3 assume that activation of the extrinsic pathway is negligible in the course of collective PK. In reality, this is rarely the case. Due to daily physiological and physical activities, triggers or inducers of both intrinsic and extrinsic pathways, such as infection, inflammation, tissue injury, are usually present in all people. If such inducers are present appreciably at the time of FVIII depletion, thrombin is generated in vivo via the extrinsic pathway, which leads to a situation in which most procoagulant fibrin derivatives are rapidly converted to anticoagulant fibrin derivatives. This phenomenon is reflected in the coagulability curve fluctuating further below zero, a situation that poses a higher risk of bleeding for the patient, and is shown in the example in Table 10. [Table 10]

[0185] All hemophilia patients listed in Table 10 are severe hemophilia patients. Hemophilia B is much rarer than hemophilia A, and this table is representative of the hemophilia population in terms of coagulation parameters. All cases here have normal extrinsic pathways (except case 2, due to FVII treatment), but their intrinsic pathways show dysfunction due to lack of functional FVIII and FIX (clotting factor 9). Case 4, who has hypertension, was hospitalized for bleeding problems. This single CCT data from this rare genetic disease falls below the mean TFT value of 2.7 (see Example 4). Thus, when the required coagulation factors are depleted, these patients are very likely to have coagulability curves that fluctuate below 0 or even below 0. Previous studies have shown that continuous infusion of low dose thrombin, which simulates continuous activation of the coagulation system, results in a bleeding phenotype. Therefore, this patient (Case 4) with an inefficient intrinsic pathway (FVIII level <0.1% and long APTT time), enhanced fibrinolysis and negative coagulability is at high bleeding risk. The high FDP value (16.33ug / mL; reference range 0-5ug / mL) supports the reason for the negative coagulability (1.66-2.7=-1).

[0186] Therefore, this innovative calculation method based on coagulation biomarkers provides an estimate of thrombosis and bleeding risk as well as a useful and easy monitoring of drug treatment for patients with all hemophilia types. This calculation approach, mainly based on coagulation biomarkers and supported by other measurements as listed in Table 10 (for hemophilia patients, other diseases may be different), is a novel way to evaluate thrombosis and bleeding tendency. This is certainly applicable to the antithrombotic treatments shown by the above examples and the main text, since antithrombotic drugs such as anticoagulants inhibit the coagulation pathways (e.g., FXa and FIIa), and if the inhibition is stronger and the coagulability remains more negative, this sets the conditions for a high bleeding risk.

[0187] Example 9: Most current biomarkers are characterized by intra-individual quantitative variability, making comparisons between different individuals difficult. For example, biomarker A found in person A is a biomarker of the immune system. Biomarker A is found to be quantitatively different within a day or week, while person A is completely healthy and normal. However, for person B, who has a chronic disease with immune system involvement, biomarker A is found to be present in a wide quantitative range at different times. Person B may or may not have the same level of biomarker A as person A. Due to the wide variability in amounts, biomarkers are usually classified in a binary manner, e.g., true / false, healthy / disease, etc.

[0188] With this mathematical approach to data quantification, a lot of information about the immune system is lost. A completely healthy and normal person A may have some slight immune activity, but this information is lost because the quantitative changes are still within the cutoff values ​​that define health / disease. Furthermore, there is no way to determine the basal levels of biomarker A for persons A and B, which are likely to be extremely different from each other. Without basal values, it is impossible to measure or define the biological meaning of the variation in values ​​for persons A and B. The general practice is to obtain as many people as possible that represent the condition of person A and measure their biomarker A levels. By obtaining a statistically meaningful average, this value is assumed to be the basal value for everyone and even the basal value for person B. This is not a correct assumption and cannot be used to estimate the activity of the immune system in all individuals.

[0189] A mathematical approach to circumvent such problems in biomedical research is found in this example. There are at least two ways to overcome the problems with existing biomarkers. The main goal here is to obtain information about the coagulation and / or immune system, mainly about when and to what extent the coagulation and / or immune system is active and inactive. These two methods correspond to two different ways to indicate the activity of the system. When the coagulation system is activated, the key enzyme that is being produced is thrombin. Thrombin converts fibrinogen into fibrin derivatives that are involved in the formation of fibrin clots. Thrombin also activates many cells, including many immune cells, endothelial cells, platelets, etc. Also, when the immune system is activated, immune cells and platelets activate the coagulation pathway and more thrombin is produced. CCT is a quantitative expression of fibrinogen and fibrin derivatives, while TFT is a quantitative expression of fibrinogen only. The first method is the subtraction of CCT with TFT, and this resulting value (coagulability) is a quantitative expression of fibrin derivatives that can be of procoagulant and anticoagulant nature. If most fibrin derivatives are procoagulant, this implies recent thrombin generation, and most fresh procoagulant fibrin derivatives have not been fibrinolytically processed. After a few hours, most of these fibrin derivatives will become anticoagulant and neutral in a short time if thrombin is not further produced or maintained. When multiple coagulabilities are available for one individual and plotted against time, it is a simple visualization of the immune and coagulation systems over time.

[0190] The second method is CCT / TFT-1. This value represents the ratio of fibrin derivative to fibrinogen. These two exemplary calculations solve the problems of basal values, intra-individual variability and inter-individual variability in translating biomarkers into clinical and biological meaning.

[0191] Coagulation biomarkers can be combined with other existing markers (and other clinical classifications included or input in module 1, e.g., heart disease or hypertension or diabetes) to provide much improved performance in diagnosis, prognosis and monitoring. These parameters can be combined to enhance machine learning or AI.

[0192] The numerical representation of the coagulation biomarkers obtained from these two exemplary arithmetic calculations is a strong indicator of in vivo thrombin generation and fibrinolysis. In other words, the higher the value of the coagulation biomarker, the more in vivo thrombin is generated. Usually, thrombin is generated in vivo transiently when either physical injury or immune activation is present. However, in certain conditions such as obesity, diabetes, etc., thrombin is generated chronically, which is reflected in long-term measurements of coagulation. The higher the value and the longer the value remains high, the worse the health status. The assessment of health status and risk of thrombosis is based on statistical models reflecting the appropriate population. As an example, if the activity of in vivo thrombin generation is chronically etiologically high in an individual, the algorithm matches this data to an appropriate representative population with known risk of thrombosis. The health status is reflected and scored according to how far this individual is from the risk of thrombosis and the amplitude and frequency of coagulation (Figures 1 and 3). The activation and process of fibrinolysis is reflected in the coagulability data and is an important parameter to be modeled in the risk of thrombosis. The more active fibrinolysis is initiated after an increase in coagulability, the lower the risk of thrombosis. An example of the calculation of the bleeding risk is given in Example 8.

[0193] The present invention further relates to the following aspects. 1. A method for modeling the coagulation properties of a blood sample, comprising: (a) determining the coagulation properties of a blood sample or preparing a blood sample with known coagulation properties; (b) determining and attributing health status and risk factors for thrombosis and / or bleeding to the donor who provided each sample; (c) determining the pharmacodynamic effects and corresponding therapeutic window of a multi-drug administration containing one or more anticoagulants and / or anticoagulant treatments on said blood sample to mitigate the risk determined in step (b); (d) modeling the coagulability of the blood sample after administering to the blood sample the most effective anticoagulant determined in step (c); A method comprising: 2. The method of embodiment 1, wherein the step of determining the coagulation properties comprises a combination of a clot-based fibrinogen test and an enzyme-based fibrinogen test. 3. The method of embodiment 2, wherein said enzyme-based fibrinogen test is a clot-independent enzyme-based fibrinogen test. 4. The method of embodiment 2, wherein said clot-based fibrinogen test is selected from the group consisting of prothrombin time (PT) determination, partial thromboplastin time (PTT) determination and the Clauss test. 5. The method according to any one of aspects 2 to 4, wherein the enzyme-based fibrinogen test involves catalytic cleavage by a serine endopeptidase. 6. The method according to any one of aspects 2 to 5, wherein said enzyme-based fibrinogen test involves catalytic cleavage of fibrinogen by a snake venom serine endopeptidase, preferably by venombin A. 7. The method according to any one of aspects 2 to 6, comprising measuring the proteolytic activity of serine endopeptidase, which is inversely proportional to the fibrinogen level in said sample. 8. A method for providing an individualized anticoagulation treatment regimen for a patient, comprising: (a) determining the coagulation properties of a blood sample from said patient or providing a known coagulation property value for said patient; (b) providing an individualized anticoagulant treatment regimen based on the model of coagulation properties obtained by the method of embodiment 1; A method comprising: 9. The method of embodiment 8, wherein the most effective anticoagulant of embodiment 1 is used for further treatment if ongoing anticoagulant treatment of said patient is not sufficient to reduce the ascribed risk factors for thrombosis and / or bleeding. 10. The method of embodiment 8, wherein if ongoing anticoagulant treatment of said patient reduces the coagulability modeled in embodiment 1 below a pre-defined threshold, then the most effective anticoagulant of embodiment 1 is used for further treatment. 11. The method according to any one of aspects 1 to 10, wherein said anticoagulant is selected from the group consisting of vitamin K antagonists, particularly fluindione, warfarin or coumarin, direct thrombin inhibitors, particularly dabigatran, argatroban or hirudin, and direct FXa inhibitors, particularly rivaroxaban, edoxaban, apixaban, heparin or heparin-like drugs. 12. A computer system or software capable of providing an individualized anticoagulant treatment regimen based on a model of coagulability obtained by the method of embodiment 1 and coagulability values ​​as input data, said computer system providing a health status, risk assessment and / or individualized anticoagulant treatment regimen. Reference materials JPEG2024524281000011.jpg182163 JPEG2024524281000012.jpg190163

Claims

1. A method for classifying the risk and / or status of a subject for an inflammatory event and / or a coagulation dysregulation event, comprising: a) determining or retrieving input data, said input data comprising: i) a coagulation biomarker, said coagulation biomarker being determined in a blood sample of the subject by at least two different assays; and ii) patient / animal background information; b) comparing said input data with a risk and / or status reference pattern, said risk and / or status reference pattern being obtained from at least two reference subjects, at least one of said reference subjects having had an inflammatory event and / or a coagulation dysregulation event previously; and c) classifying the risk and / or status of the subject for the inflammatory event and / or the coagulation dysregulation event based on the comparison obtained in b). A method as claimed in claim 1, further comprising: A method as claimed in claim 1, further comprising:

2. The method according to claim 1, wherein said assays are a combination of a clot-based fibrinogen test and an enzyme-based fibrinogen test.

3. The method according to claim 2, wherein said enzyme-based fibrinogen test is a clot-independent, enzyme-based fibrinogen test.

4. The method according to claim 2, wherein said clot-based fibrinogen test is selected from determination of prothrombin time (PT), determination of partial thromboplastin time (PTT), and the Clauss test.

5. The method according to claim 2, wherein said enzyme-based fibrinogen test involves catalytic cleavage by a serine endopeptidase.

6. The method according to claim 2, wherein said enzyme-based fibrinogen test involves catalytic cleavage of fibrinogen by a snake venom serine endopeptidase, preferably by batroxobin A.

7. The method according to claim 2, further comprising measuring the proteolytic activity of a serine endopeptidase inversely proportional to the level of fibrinogen in said sample.

8. The method according to claim 1, wherein said patient / animal background information includes or consists of weight, gender, age, and renal function.

9. The risk and / or state reference pattern is a machine learning model obtained by training on a reference target data set, and the step of comparing the input data with the risk and / or state reference pattern includes inputting the input data into the machine learning model, according to the method of claim 1.

10. The step of classifying the risk and / or state of the subject for the inflammatory event and / or coagulation dysregulation event is classifying the risk and / or state of the subject for thrombosis and / or bleeding, according to the method of claim 1.

11. A method for predicting the risk and / or state of a subject for an inflammatory event and / or a coagulation dysregulation event, comprising: a) i) At a first time point, classifying the risk and / or state of the subject for an inflammatory event and / or a coagulation dysregulation event according to the method of claim 1; ii) At a second time point, determining or retrieving a coagulability biomarker of the blood sample of the subject, wherein the coagulability biomarker is determined in the blood sample of the subject by at least two different assays; by which a risk and / or state progression index is determined; b) Comparing the risk and / or state progression index with a prediction reference pattern, wherein the prediction reference pattern is obtained from at least two reference subjects, at least one of the reference subjects having had an inflammatory event and / or a coagulation dysregulation event before, and the risk and / or state progression of the reference subject being known; c) Predicting the risk and / or state of the subject based on the comparison obtained in (b). A method comprising the steps of.

12. The prediction reference pattern is a machine learning model obtained by training on a reference target data set, and the step of comparing the risk and / or state progression index with the prediction reference pattern includes inputting the input data into the machine learning model, according to the method of claim 11.

13. A method for monitoring the treatment response of a subject for an inflammatory event and / or a coagulation dysregulation event during treatment, comprising: a) i) At a first time point, classifying the risk and / or state of the subject for an inflammatory event and / or a coagulation dysregulation event according to the method of claim 1; ii) at least one second time point, determining or searching for a coagulability biomarker of the blood sample of the subject, wherein the coagulability biomarker is determined in the blood sample of the subject by at least two different assays; iii) 1.) an administration time point of an anti-inflammatory compound, an antiplatelet compound, an anticoagulant compound and / or a coagulation-promoting compound and / or an anticoagulant compound, wherein the administration time point is between the first time point and the second time point; preferably, the administration time point and the administered amount of the anti-inflammatory compound, the antiplatelet compound, the anticoagulant compound and / or the coagulation-promoting compound and / or the anticoagulant compound; 2.) a pharmacodynamic response, wherein the pharmacodynamic response is calculated based on at least the coagulability biomarker at the first time point, the coagulability biomarker at the second time point and the administration time point, and the pharmacodynamic response is calculated based on at least the coagulability biomarker at the first time point, the coagulability biomarker at the second time point, the administration time point and the administered amount; determining a treatment progress index by; b) comparing the treatment progress index with a treatment response reference pattern, wherein the prediction reference pattern is obtained from at least two reference subjects, and at least one of the reference subjects has previously received treatment with an anti-inflammatory compound, an antiplatelet compound, an anticoagulant compound and / or a coagulation-promoting compound, and the treatment response of the reference subject is known; c) monitoring the treatment response of the subject based on the comparison obtained in (b) A method comprising.

14. The method according to claim 13, wherein the treatment response reference pattern is a machine learning model obtained by training on a dataset of reference subjects, and comparing the treatment progress index with the treatment response reference pattern comprises inputting the treatment progress index into the machine learning model.

15. A pharmaceutical composition comprising an anti-inflammatory compound, an antiplatelet compound, an anticoagulant compound and / or a procoagulant compound for reducing the risk and / or improving the condition of an inflammatory event and / or a coagulation dysregulation event in a subject classified as having a risk and / or condition of an inflammatory event and / or a coagulation dysregulation event according to the method according to any one of claims 1 to 10 and / or predicted to develop a risk and / or condition of an inflammatory event and / or a coagulation dysregulation event according to the method according to claim 11 or 12.

16. A pharmaceutical composition comprising a second anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound for use in combination with a first anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound to reduce the risk of an inflammatory event and / or a coagulation dysregulation event and / or to improve the condition of an inflammatory event and / or a coagulation dysregulation event in a subject in need thereof, comprising: a) administering the first anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound to a subject in need thereof under monitoring of the treatment response according to the method according to any one of claims 13 to 14; b) If the treatment response to the first anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound is insufficient according to the method according to any one of claims 13 to 14, the second anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound is administered to a subject in need thereof, and the treatment response to the first anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound is such that it is necessary to reduce the risk of inflammatory events and / or coagulation dysregulation events and / or improve the condition of inflammatory events and / or coagulation dysregulation events. In the subject in question, if it is sufficient to reduce the risk of inflammatory events and / or coagulation dysregulation events and / or improve the condition of inflammatory events and / or coagulation dysregulation events according to the method according to any one of claims 13 to 14, treatment with the first anti-inflammatory compound, antiplatelet compound, anticoagulant compound and / or procoagulant compound is continued, a pharmaceutical composition.

17. The pharmaceutical composition according to claim 15, wherein the compound is selected from the group consisting of vitamin K antagonists, in particular fluindione, warfarin or coumarin, direct thrombin inhibitors, in particular dabigatran, argatroban or hirudin and direct FXa inhibitors, in particular rivaroxaban, edoxaban, apixaban, heparin or heparin-like drugs.

18. The pharmaceutical composition according to claim 15, wherein the compound is selected from the group consisting of non-steroidal anti-inflammatory drugs, corticosteroids, rapamycin, compounds that increase high-density lipoprotein, HDL-cholesterol, rho-kinase inhibitors, antimalarial agents, acetaminophen, glucocorticoids, steroids, β-agonists, anticholinergics, xanthine derivatives, sulfasalazine, penicillamine, anti-angiogenic agents, dapsone, psoralen, anti-TNF agents, anti-IL-1 agents and statins.

19. The pharmaceutical composition according to claim 15, wherein the compound is a compound selected from the group consisting of an irreversible cyclooxygenase inhibitor, an adenosine diphosphate (ADP) receptor inhibitor, a phosphodiesterase inhibitor, a protease-activated receptor-1 (PAR-1) blocker, a glycoprotein IIb / IIIa inhibitor, an adenosine reuptake inhibitor, dipyridamole, a thromboxane inhibitor, and a thromboxane receptor blocker.

20. The pharmaceutical composition according to claim 15, wherein the compound is a coagulation factor that promotes coagulation and / or reduces bleeding, preferably a compound selected from the group consisting of FVIII concentrate, Alphanate, Humate-P, Novoseven, Irocotide, Fiba, prothrombin complex, Hemlibra, and tranexamic acid.

21. A storage device comprising computer-readable program instructions for performing the method according to any one of claims 1 to 14.

22. A server comprising the storage device according to claim 21, at least one processing device for executing the computer-readable program instructions, and a network connection for receiving the input data.

23. A system for classifying, predicting, and / or monitoring treatment responses, comprising: a) A measuring device comprising a container for receiving a blood sample and a reagent for determining a coagulation biomarker, wherein the coagulation biomarker is determined in the blood sample by at least two different assays; b) A processing device for executing the computer-readable program instructions, comprising a network connection to the storage device and / or server according to claim 21; c) An input and / or searchability that enables the server and / or the processing device to access the patient / animal patient background information. A system.

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