Individualized Dosing Technique With Multiple Variables

Abstract

A method to quantify and correct for drug-drug interaction, physiologic change, diet, weight, genetic data and compliance on Warfarin dosing. The International Normalized Ratio (INR), a lab value used to follow Warfarin use, will fluctuate in an unpredictable manner due to factors other than the current Warfarin dose. The method mathematically describes these changes and eventually adjusts for these interacting factors through the use of logistic regression (LR) or multiple linear regression analysis. By anticipating changes in INR, Warfarin dosing can be adjusted resulting in patients having their INR be therapeutic range. The technique can be used in any field that requires a specific measured quantity, with variables that change and the need to correct for changes with a mathematical model.

1 .- 18 . (canceled) 
     
     
         19 . A method of determining the effect of health factors on the activity of a dose of a drug in an individual human patient in need of long-term therapy to obtain a specific laboratory test value for a medical condition and treatment thereof comprising the steps of:
 a) obtaining a test sample selected from the group consisting of blood, urine, fecal, saliva, skin, and hair, from a human patient with a medical condition;   b) detecting a specific laboratory test value for the human patient with the medical condition;   c) obtaining data of general information of the individual human patient with the medical condition comprising;
 current average daily dose of the drug in milligrams, 
 current specific laboratory test value, 
 the individual human patient's weight in kilograms, 
 the individual human patient's temperature, 
 number of episodes of fevers, 
 number of episodes of diarrhea, 
 kidney function, and 
 liver function, 
   d) obtaining data concerning ingested compounds by the individual human patient with the medical condition comprising;
 amount and type of alcohol ingested, 
 current prescription drugs, including dosage, frequency and route of intake, and 
 amount and type of food eaten, and any change in the intake of these foods, 
   e) generating and assigning a regression coefficient (β) for each data (x) in step c) and step d);
 wherein logistic function is 
   
       
         
           
             
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         and wherein variable z represents the exposure to independent variables, variable Y represents the probability of a particular outcome, and variable z is defined as: 
       
       
         
           
             
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         f) using each β n x n  from step e) to represent a predicted relationship between dose amount of the drug and a predicted specific laboratory test value in the individual human patient with the medical condition; 
         g) modifying each regression coefficient (β n ) for each data (x n ) until the mathematical model program generates an equation of a line representing the predicted relationship between the dose amount of the drug and the predicted specific laboratory test value which corresponds to the observed specific laboratory test value in the individual human patient with the medical condition; and 
         h) administering a treatment to the human patient with the medical condition, wherein the treatment is the dose amount of the drug calculated from the equation of the line representing the relationship between the dose amount of the drug and the predicted specific laboratory test value, and wherein the drug is used to treat the condition. 
       
     
     
         20 . The method of  claim 19 , wherein the long-term therapy is selected from the group consisting of: hormone replacement therapy, radiation treatment and chemotherapy. 
     
     
         21 . The method of  claim 20 , wherein the hormone replacement therapy comprises the replacement of a hormone selected from the group consisting of Melatonin (N-acetyl-5-methoxytryptamine) [MT]; Serotonin [5-HT]; Thyroxine (or tetraiodothyronine) [T4]; Triiodothyronine [T3]; levothyroxine; Epinephrine (or adrenaline) [EPI]; Norepinephrine (or noradrenaline) [NRE]; Dopamine (or prolactin inhibiting hormone) [DPM, PIH or DA]; Antimullerian hormone (or mullerian inhibiting factor or hormone) [AMH]; Adiponectin [Acrp30]; Adrenocorticotropic hormone (or corticotropin) [ACTH]; Angiotensinogen and angiotensin [AGT]; Antidiuretic hormone (or vasopres sin, arginine vasopressin) [ADH]; Atrial-natriuretic peptide (or atriopeptin) [ANP]; Calcitonin [CT]; Cholecystokinin [CCK]; Corticotropin-releasing hormone [CRH]; Erythropoietin [EPO]; Follicle-stimulating hormone [FSH]; Gastrin [GRP]; Ghrelin; Glucagon [GCG]; Gonadotropin-releasing hormone [GnRH]; Growth hormone-releasing hormone [GHRH]; Human chorionic gonadotropin [hCG]; Human placental lactogen [HPL]; Growth hormone [GH or hGH]; Inhibin; Insulin [INS]; Insulin-like growth factor (or somatomedin) [IGF]; Leptin [LEP]; Luteinizing hormone [LH]; Melanocyte stimulating hormone [MSH or a-MSH]; Orexin; Oxytocin [OXT]; Parathyroid hormone [PTH]; Prolactin [PRL]; Relaxin [RLN]; Secretin [SCT]; Somatostatin [SRIF]; Thrombopoietin [TPO]; Thyroid-stimulating hormone (or thyrotropin) [TSH]; Thyrotropin-releasing hormone [TRH]; Cortisol; Aldosterone; Testosterone; Dehydroepiandrosterone [DHEA]; Androstenedione; Dihydrotestosterone [DHT]; Estradiol [E2]; Estrone; Estriol [E3]; Progesterone; Calcitriol (1,25-dihydroxyvitamin D3); Calcidiol (25-hydroxyvitamin D3); Prostaglandins [PG]; Leukotrienes [LT]; Prostacyclin [PGI2]; Thromboxane [TXA2]; Prolactin releasing hormone [PRH]; Lipotropin [PRH]; Brain natriuretic peptide [BNP]; Neuropeptide Y [NPY]; Histamine; Endothelin; Pancreatic polypeptide; Renin; Enkephalin; natural and synthetic endocrine drugs; and natural and synthetic endocrine analogues. 
     
     
         22 . The method of  claim 19 , further comprising the step of obtaining the specific laboratory test value of the individual human patient during a successive visit. 
     
     
         23 . The method of  claim 19 , comprising the steps of:
 comparing the predicted specific laboratory test value with the computer using a mathematical model program selected from the group consisting of a logistic algorithm, multiple linear regression and logistic regression with the observed INR, and   modifying each regression coefficient (β n ) for each data (x n ) with the computer using a mathematical model program selected from the group consisting of a logistic algorithm, multiple linear regression and logistic regression until the mathematical model program generates a modified regression coefficient (β n ) for an equation of a line representing the relationship between the dose amount of the drug and the observed specific laboratory test value in the individual human patient.   
     
     
         24 . The method of  claim 23 , further comprising;
 using the modified regression coefficient (β n ) to generate an equation of a line representing the relationship between the dose amount of the drug and the specific laboratory test value in the individual human patient in subsequent calculations predicting INR.   
     
     
         25 . The method of  claim 19 , further comprising in step c) obtaining the data of general information of the individual human patient comprising at least one selected from the group consisting of:
 the individual human patient's genetic information concerning long-term therapy,   the individual human patient's race,   the individual human patient's age,   the individual human patient's gender,   menopausal status of an individual female,   if the individual human patient is a vegetarian,   if the individual human patient is a vegan,   occurrence and duration of travel since previous visit,   occurrences of trauma since previous visit,   number of falls since last visit,   use of an illegal drug and if yes, the type, frequency and duration of illegal drug use,   intake of dietary supplements,   intake of over the counter medications,   intake of herbal, botanical and alternative medications,   type, frequency and duration of physical exercise,   any change in altitude since previous visit,   any change in time zone since previous visit, and   any change in duration or frequency of sleep since previous visit.   
     
     
         26 . The method of  claim 25 , wherein the herbal medication is selected from the group consisting of Bromelains, Chamomile ( Matricaria recutita ), Coenzyme Q 10 , Cranberry products, Danshen, Dong quai, Echinacea ( Echinacea purpurea  and  Echinacea  spp.), Evening Primrose ( Oenothera biennis ), Feverfew ( Tanacetum parthenium ), Garlic ( Allium sativum ), Ginger ( Zingiber officinale ), Ginkgo ( Ginkgo biloba ),  Ginseng  ( Panax  spp.), Goldenseal ( Hydrastis canadensis ), Kava Kava ( Piper methysticum ), Milk Thistle ( Silybum marianum ), Saw Palmetto ( Serenoa repens ), St. John's Wort ( Hypericum perforatum ), and Valerian ( Valeriana officinalis ). 
     
     
         27 . The method of  claim 25 , wherein the over the counter drugs are selected from the group consisting of antibiotics, aspirin, aspirin-containing products, nonsteroidal anti-inflammatory drugs, ibuprofen, naproxen, oral contraceptives, streptokinase, ticlopidine, and urokinase; and medications for cancer, cholesterol, colds, allergies, depression, diabetes, digestive problems, gout, heart disease, mental illness, pain, seizures, thyroid problems and tuberculosis. 
     
     
         28 . The method of  claim 19 , wherein steps a) to d) are repeated during each visit by the individual human patient. 
     
     
         29 . The method of  claim 19 , wherein the mathematical model is logistic regression. 
     
     
         30 . The method of  claim 19 , wherein the equation of a line in step g) is a general model generated by data from multiple people. 
     
     
         31 . The method of  claim 19 , wherein the equation of a line in step g) is a model generated for the specific individual human patient. 
     
     
         32 . The method of  claim 19 , wherein the mathematical model has a variable “z,” and wherein the z is generated by a logistic regression model. 
     
     
         33 . The method of  claim 32 , wherein the z generated by the logistic regression model is averaged between a population of individual human patients to generate an averaged z and the averaged z is used as the initial z for a human patient without an individual mathematical model. 
     
     
         34 . The method of  claim 19 , wherein the data are stored in a data base for that individual human patient. 
     
     
         35 . The method of  claim 19 , wherein the data are recorded in digital form with “1” representing “yes” or “present” and “0” representing “no” or “absent”. 
     
     
         36 . The method of  claim 19 , wherein the drug is selected from the group consisting of a hormone and chemotherapy drug. 
     
     
         37 . The method of  claim 19 , wherein the prescription drugs are selected from the group consisting of antibiotics, aspirin, aspirin-containing products, nonsteroidal anti-inflammatory drugs, ibuprofen, naproxen, oral contraceptives, streptokinase, ticlopidine, and urokinase; and medications for cancer, cholesterol, colds, allergies, depression, diabetes, digestive problems, gout, heart disease, mental illness, pain, seizures, thyroid problems and tuberculosis. 
     
     
         38 . The method of  claim 19 , wherein the computer using a mathematical model program selected from the group consisting of a logistic algorithm, multiple linear regression and logistic regression is a hand-held device.