METHOD AND SYSTEM FOR CALCULATION AND GRAPHICAL PRESENTATION OF DRUG-DRUG OR DRUG-BIOLOGICAL PROCESS INTERACTIONS ON A SMART PHONE, TABLET OR COMPUTER

Abstract

A method and system is provided for visualization and pictorial presentation to a user of possible interactions between a prospective drug that is being considered for prescribing to a person and that person's genotype. Genetic information of the person that can affect the manner in which a drug acts on a molecular, physiological or biological function of the body or a tissue, or a manner in which a drug is being metabolized, absorbed, excreted or otherwise eliminated from the body or a tissue by the body or tissue systems, is entered into a computerized device. The computerized device conducts a search of a drug database for drugs that have known interactions with the entered genetic information, and assigns a numeric value to each of a plurality of drugs, either in aggregate, as a class, or individually, in order to quantify the nature, strength and direction of each interaction. The computer sends the assigned numeric values to the computer's output module for their visual presentation to a user as a graph including a panel of columns, or other geometrical structures, whose geometrical characteristics correspond to the assigned numeric values of each drug, in order to facilitate the prospective drug selection by a prescriber on the basis of the totality of drug-gene and/or drug-drug interactions presented to the user as a visual graph.

Claims

1. A method of visualization and pictorial presentation to a user of possible interactions between a prospective drug that is being considered for prescribing to a person and that person's genotype, comprising: entering the person's genetic information into a computing device, wherein the entered genetic information may be a person's genetic data reflecting distinct pharmacogenetic phenotypes of cytochrome oxydase P450 (CYP) genes coding for the corresponding CYP enzymes and termed as poor, intermediate, extensive, and ultrarapid metabolizers, DNA variation data that may include single nucleotide polymorphisms (SNPs), copy number variations (CNVs), insertions/deletions (indels) or other variations appearing anywhere in the patient's DNA, DNA methylation, acetylation or any other data of up- or down-regulation of gene expression that affects the manner in which a drug acts on any molecular, physiological or biological function of the body or a tissue, or a manner in which a drug is being metabolized, absorbed, excreted or otherwise eliminated from the body or a tissue by the body or tissue systems, and whereupon the data entry causing (i) a computer to conduct a search of a drug database for drugs that have known interactions with the entered genetic information, and assign a numeric value to each of a plurality of drugs, either in aggregate, as a class, or individually, in order to quantify the nature, strength and direction of each interaction, (ii) causing the computer's processor to send the assigned numeric values to the computer's output module for their visual presentation to a user as a graph including a panel of columns, or other geometrical structures, whose geometrical characteristics corresponds to the assigned numeric values of each drug, and which can be subsequently further adjusted according to the numeric values assigned to a separately entered list of drugs that represents drugs that the patient is currently taking, which are also known to interact with the patient's genotype, in order to facilitate the prospective drug selection by a prescriber on the basis of the totality of drug-gene and drug-drug interactions presented to the user as a visual graph, reflecting the degree of the interaction on any individual prospective drug that is being considered for prescribing.

2. A method as defined in claim 1, further comprising receiving in a computerized device a list of drugs and observing effects of such drugs on genotype-dependent changes in drug biological functions.

3. A method as defined in claim 2, wherein the list of drugs includes a drug that the person is currently taking or is considering taking in the future.

4. A method as defined in claim 2, where such functions include inflammation, carcinogenesis, electric conductance, aging, neurodegeneration, growth, tissue differentiation, secretion, reproduction.

5. A method as defined in claim 4, wherein the electric conductance includes cardiac electric conductance.

6. A method as defined in claim 5, wherein the cardiac electric conductance includes the QT interval and variations thereof.

7. A method as defined in claim 1, further comprising receiving in a computerized device genetic data where such data are RNA-seq data.

8. A method as defined in claim 1, further comprising receiving in a computerized device genetic data where such data are methylome data.

9. A method as defined in claim 1, further comprising receiving in a computerized device genetic data where such data are proteomics data.

10. A method as defined in claim 1, further comprising receiving in a computerized device genetic data where such data are transcription data.

11. A method as defined in claim 1, further comprising receiving in a computerized device genetic data where such data are derived from human studies.

12. A method as defined in claim 1, further comprising receiving in a computerized device genetic data where such data are derived from non-human studies.

13. A method as defined in claim 1, wherein the computer performing calculations and data presentation is a tablet, a smart phone, a laptop, a desktop or other computing device that has graphic output capabilities.

14. A method as defined in claim 1, wherein the user may be also a patient whose genetic and drug interaction data are being analyzed and visually represented.

15. A method as defined in claim 1, wherein the method further comprises receiving, in a computerized device a list of drugs that could include any drug that the person may be currently taking or may be considering taking in the future and observing effects of a plurality of such drugs on the graphical depiction of the drug-genotype interactions and subsequently varying and re-entering the prospective drug candidates in order to obtain a most desirable level of drug interactions as is reflected in the drug-genotype interactions graph.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0024] FIGS. 1A, 1B and 1C are a comparison of calculated metabolic rates of a drug “D” (pink columns) by CYP3A4 enzyme coded by the CYP3A4 gene that has no loss-of-function mutations (Extensive metabolizer, FIG. 1A). The Y axis represents drug metabolism inhibition, where “0” corresponds to no inhibition and “1.0” corresponds to 100% inhibition (blue column). In the absence of CYP3A4 gene loss-of-function mutations (Extensive Metabolizer phenotype) there is only a negligible (approximately 5%) inhibition of drug “D” metabolism attributed to this drug being a CYP3A4 enzyme substrate that is tying up the enzymatic reaction by its own metabolism.

[0025] FIG. 1B shows inhibition of drug “D” metabolism when there is a loss-of-function mutation in one of the two CYP3A4 alleles (Intermediate Metabolizer phenotype). Note an inhibition of drug “D” metabolism by an approximately 20% due to a reduced metabolizing capacity of the defective CYP3A4 enzyme.

[0026] FIG. 1C shows drug “D” metabolism when there is a loss-of-function mutation in one CYP3A4 allele (“Intermediate Metabolizer” phenotype) and in the presence of drug “K”, which is a potent inhibitor of CYP3A4 enzyme. Note an inhibition of drug “D” metabolism by approximately 90% due to a markedly reduced metabolizing capacity of the partially defective CYP3A4 enzyme whose function become suppressed by drug “K”.

[0027] FIGS. 2A, 2B and 2C are a visual graphical presentation of drug—genotype effects in the presence of one loss-of-function mutation in the CYP2B6 and the CYP2C9 genes (Intermediate metabolizer phenotype). Actions of two drugs that interact with these enzymes (clopidogrel and cimetidine) and one nutrient (grapefruit juice) are also taken into consideration. Note a high degree of variability in calculated prospective medication metabolic rates for all drugs that have been grouped by drug class (FIG. 2A, antipsychotic medications, FIG. 2B, antidepressant medications and FIG. 2C, anxiolytic-hypnotic medications). Since metabolic rates are known to inversely correlate with the likelihood of drug-induced side effects, selecting a prospective drug for prescribing for this particular patient can be done on the basis of the visual comparison of the column heights. Accordingly, antidepressants (FIG. 2B) that are least likely to cause side effects for this particular patient are duloxetine, trazodone and phenelzine and those that are most likely to cause side effects are fluvoxamine and paroxetine. Each column corresponds to a drug, except for the blue columns indicating the maximum CYP enzyme inhibition.

[0028] FIG. 3 is an illustration of the computer output or screen display in connection with an example of the method and system of the present disclosure for visual presentation to a user, and including a graph with a panel of columns whose geometrical characteristics correspond to the assigned numeric values of each indicated drug. The graph visually facilitates the prospective drug selection by a prescriber on the basis of the totality of drug-gene and/or drug-drug interactions presented to the user on the visual graph and reflecting the degree of the interaction on any individual prospective drug that is being considered for prescribing. In the illustrated example, the X-axis lists antipsychotic medications and the Y-axis shows a relative probability of side effects of each drug from 0 to 1. The curved arrow indicates a prospective drug (lurasidone) with the least probability of side effects for the respective patient.

DETAILED DESCRIPTION OF EMBODIMENTS

[0029] The present disclosure is directed to a method of using a computer to conduct pharmacogenetic data analysis and present results of this analysis to an interested party (e.g., a physician, a researcher, dentist or a patient) in a visual graphic format. The method and system of the present disclosure is based on entering the patient's genetic variation, mutation, polymorphism, phenotypic, transcription or other data that are known to affect a biological function, elimination, distribution or binding to a receptor of a drug or a nutraceutical into a computer. In various embodiments of the invention the entry of these data can be done in a number of ways comprising a manual entry, a direct transfer from another computer or a server, reading of a bar code, or any other similar data entry method. In another embodiment, these data are stored locked on a memory chip or transferred from one user to another.

[0030] Upon receiving genetic data, the computer processor executes a code that causes the data to search a database of drugs and nutraceuticals whose effectiveness, side effect profile, metabolism or any other biological function may be affected by the mutation or mutations. The degree to which the biological activity of a drug or nutraceutical is affected by the mutation is assigned a numeric value reflecting the nature of the interaction between a drug or nutraceutical and the affected biological function. Information about the nature of the said interaction is derived from peer-reviewed publications indexed in such scientific publication databases as PubMed or Google Scholar, and other reputable databases that index pharmacological information. Examples of such databases could include PharmGKB (https//www.pharmgkb.org, SuperCYP (http://bioinforrmatics.charite.de/supercyp/index.php.World Guide of Pharmacogenomics etc.). The assigned numeric values may be percentage values indicative of either a loss or gain of enzymatic activity (if the gene in question codes for an enzyme) or a change in receptor binding properties (if the gene in question codes for a drug that binds to a receptor). The numeric values may be pre-entered together with the drug database into the computer. In another embodiment, the numeric values may be entered at the time the calculations are being performed, which may be particularly useful for educational and exploratory purposes.

[0031] For example, if a mutation that was entered is a partial loss of function mutation in the gene CYP2D6, reducing the metabolizing capacity of the corresponding CYP2D6 enzyme by 25%. By executing a search the computer will assign a 100% value to all drugs that are neither substates, inhibitors nor inducers of this enzyme indicating that the metabolism of these drugs was not reduced by the loss of function mutation in the CYP2D6 gene but it will assign a 75% value to all drugs that may be identified as substrates of this enzyme, indicating slower metabolism of these drugs. Drugs that are identified as inhibitors of CYP2D6 will be assigned a higher value (e.g. 50%) to reflect an additional degree of enzyme function loss. In various embodiments, the assigned values may be the same for an entire chemical class of drugs or they may be assigned to each drug individually.

[0032] In a separate embodiment of this invention, further entries of genotype data can be prevented after the initial entry of the genotype data. This may be particularly useful when the user of this method is a patient.

[0033] In a preferred embodiment, the numeric values sent by the computer's processor to the output module are converted to a multicolumn graph (or any other geometrical form such as a circle) where each column corresponds to a drug or nutraceutical and the column height corresponds to a degree to which the mutation altered each drug's biological function. Visualization of the drug-genotype interaction allows the user to make a prompt visual comparison between different drugs and select those with minimum interactions between it and the mutated gene product.

[0034] In another embodiment of this invention, a correction can be made to reflect the phenomenon of phenoconversion comprising entering a list of drugs that the patient may already be taking and using their assigned numeric values to adjust the effect of the prospective drug on a gene product. This is particularly useful when a patient is already receiving one or more medications and more prescriptions are contemplated.

[0035] In another embodiment, a user may be a patient who is taking a medication and is considering adding a nutraceutical compound or an over the counter medication. Some of these medications are substrates of the mutated enzymes competing for enzymatic capacity by defective gene products, while others may be inhibitors that may compromise the defective enzymatic activity even further, especially, if the mutation defect is of an Intermediate metabolizer type. These drugs and nutraceuticals may be entered separately by the user and the user can observe the changes in the plurality of the interactions between the prescription drugs or nutraceuticals and genetic data, and as a result become aware of potential adverse interactions or a loss of effectiveness of his or her current medications.

[0036] Since there may be thousands of drugs and nutraceutical compounds, drugs and compounds that are being outputted for visualization by the user may be grouped by their therapeutic area, comprising antidepressants, antipsychotics, antihypertensives, antiepileptics, anti-inflammatories etc.

[0037] A user of this invention who is a prescriber seeking to prescribe a drug to his or her patient and is looking for a drug that has the fewest side effects (or the greatest effectiveness, etc.) can visually observe the effect of genetic variations, polymorphisms, phenotypes, etc. on a drug or selected group of drugs and make immediate inferences as to the relative magnitude of the mutation's effect on each drug that is being considered for prescribing. This could be illustrated in the following example (FIGS. 1A, 1B and 1C). Elimination of an antidepressant drug “D” from an organism requires a functioning metabolic enzyme CYP3A4. A loss-of-function mutation in the corresponding CYP3A4 gene may result in an inactive or partially active CYP3A4 enzyme, which will slow the metabolism of drug “D” and increase the likelihood of side effects (so-called “Intermediate Metabolizer” gphenotype). If both strands of DNA are affected by the mutation, or if an inhibitor of the CYP3A4 enzyme is added (drug “K”) when the patient is an Intermediate metabolizer, the metabolic function of the CYP3A4 enzyme could be significantly impacted resulting in the phenoconversion to the “Poor Metabolizer” phenotype. In that case metabolism of drug “D” would be much slower than expected in the general population, and the probability of side effects would be much greater compared to only one DNA strand being affected.

[0038] In the present embodiment of the invention, the graphic output consists of multicolored columns where the column color corresponds to a specific drug and the column height corresponds to a degree that drug metabolism, side effect, effectiveness, binding to its receptor, or any other biological process involving this drug, is affected by a specific DNA mutation (or mutations) or existing medications.

[0039] The term “other biological process” refers to, in addition to drug metabolism by CYP enzymes already described in detail previously, such processes as carcinogenesis, tissue regeneration, inflammation, aging, cardiac conductance (e.g. QTc interval) or other similar processes. A user of this method and system can observe and immediately identify those drugs or supplements whose actions will be most affected or least affected by the presence of specific mutations and/or existing medications. For example, a user can immediately infer from the graph which of the antidepressant medications available for prescribing will have the least and which will have the most side effects in a patient who has a specific DNA mutation.

[0040] Another embodiment of this invention allows the user to group different classes of drugs and explore DNA mutation and existing medication effects on each class. For example, antidepressant and antipsychotic medications can be selected and viewed separately (FIGS. 2A, 2B and 2C).

[0041] In another embodiment, the invention may include an interactive feature that enables the user to further narrow and identify a prescription drug group within a prescription drug class. For example, a user may select within the antidepressant class all drugs that are not SSRIs (Selective Serotonin Reuptake Inhibitors).

[0042] In another embodiment, the user may have access to a narrative section where information by drug manufacturers or regulatory agencies pertaining to specific DNA mutations affecting a specific drug dosing may be viewed.

[0043] In one embodiment, the patient's genetic data and/or the existing medication can be entered manually, scanned from a barcode or QR code, or submitted electronically through an internet, e.g., Wi-Fi, or another wireless connection. The user is not expected to perform any laboratory experiments or obtain any data other than the data that was made available to the user. Duplicate entries or incorrect combinations of genetic data are blocked programmatically. Data processing may take place on a central server or locally on the user's mobile device or computer. If there are several users sharing one device that employs this tool, users may be required to log in in order to have calculation results available only to a specific user. In none of the embodiments, patient's personally identifiable information (e.g. name, address, date of birth) is required for the calculation and visual output, and such information is not being collected at any steps of the operation.

[0044] This invention in its various embodiments may be used by a qualified health care practitioner including an MD, DO, NP, ND, a dentist, a physician assistant or other practitioner that is a qualified prescriber of a medication or medications, or a nutritional supplement to a patient or another healthcare consumer, male or female (including a research study subject, in whole or in part, regardless of whether the subject is a human or an animal), whose DNA sequence, or presence of specific RNA transcripts, or proteins associated with a specific DNA sequence or RNA transcripts that are known to interact with medications or nutritional supplements, have been revealed, in whole or in part, to the said prescriber in order to minimize side effects and enhance effectiveness of a medication or nutritional supplement that is being prescribed or recommended.

[0045] In another embodiment, the invention may be used by a healthcare consumer or said consumer's next of kin to calculate the interaction effects of over the counter medications on prescription medications and nutraceuticals, including medications and nutraceuticals that the healthcare consumer is currently taking or considering taking in the future regardless of whether the genetic information is known or unknown to the consumer.

[0046] In another embodiment, this invention may be used by a health care provider or consumer who was informed of the consumer's genetic information comprising genetic mutations, polymorphisms, DNA methylation or other mechanisms of deregulation of gene expression contributing to a pathological state of a tissue or an organ, with an intent to select medications or nutritional compounds that have the opposite effect on the deregulated genes.

[0047] In its various embodiments, this invention can be installed and run as a smartphone, tablet or computer application (i.e. an “App”). In other embodiments, it can be run in a web browser on a smartphone, a tablet or a computer that is connected to the internet and can be forwarded from one user to another by sending an URL address or a QR code. It is not necessary for the user be skilled in the art of computer technology, programming or genetics in order to use this invention. Any physician, dentist, nurse practitioner or other qualified health care provider who prescribes medications or recommend nutritional supplements to his or her patients or clients, can use this invention. Students of biomedical or health sciences including research scientists, as well as health care consumers can use this invention, in order to, for example, improve their understanding of interactions between a drug and a biological substrate.

[0048] FIG. 3 presents an example of an application of the method and system to a 46 year old man exhibiting psychosis and intolerance of antipsychotic medications due to side effects. Briefly, the patient's symptoms started at age 19 and continued until the present day. He felt that someone was behind his back and he could communicate using mental telepathy. He was diagnosed with depression, schizophrenia and bipolar disorder by several practitioners and treated with depakote, prozac, cogentin, zyprexa, abilify, haldol, Benadryl, Lexapro and risperidone, but could not tolerate any of these medications due to side effects (e.g., he would become violent if taking fluoxetine).

[0049] Pharmacogenomics testing was done and revealed the following genotypes and corresponding phenotypes: CYP2B6 *1/*6 (intermediate metabolizer), CYP2C19 *1/*17 (ultrarapid metabolizer), CYP2D6 *4/*4 (poor metabolizer), CYP3A5 *3/*3 (poor metabolizer), CYP2C9, CYP3A4 both *1/*1 (normal or extensive metabolizer).

[0050] Entering this data into the computer (in the present embodiment the computer was a smartphone) and performing calculations of metabolic rates as described above, a resulting chart showed that of all antipsychotics, lurasidone (Latuda) would have the fastest metabolism and cause least side effects (curved arrow pointing to the lowest column), while other antipsychotics would likely cause significant side effects. The patient immediately started treatment with lurasidone at a dose of 40 mg a day and after 4 weeks of treatment his psychotic symptoms subsided without any significant side effects. The X-axis lists antipsychotic medications, the Y-axis shows a relative probability of side effects of each drug from 0 to 1. The curved arrow indicates a prospective drug (lurasidone) with the least probability of side effects.

[0051] The terms “tool”, “application”, “app” , “computer” as they are used here refer to executable code that anyone skilled in the art of computer or smartphone programming could compile. Terms “genetic test”, “genetic test results”, “DNA sequence variations”, “single nucleotide polymorphisms”, “SNPs”, “alleles”, “mutant alleles”, “mutations”, “mutants”, “variations”, “genetic data”, “genotype” etc., as they are used here, whether in singular or plural, refer to DNA or RNA code variations of any type that may become known to the user of this invention without performing an analysis of a DNA sample, or RNA sample or a tissue sample. The term “compounds”, “drugs”, “medications”, “nutrients”, “nutraceuticals”, “supplements”, “vitamins” etc. as they are used here refer to prescription or over the counter medications, drugs, supplements, nutrients, foods and their biologically active constituents. The term “existing medication” refers to a drug or supplement that the patient may already be taking. The term “prospective medication”, “prospective drug” refers to a drug or a supplement that is being considered to be prescribed or recommended.

[0052] As may be recognized by those or ordinary skill in the pertinent art based on the teachings herein, numerous changes and modifications may be made to the above-described and other embodiments of the present invention without departing from its scope as defined, for example, in the appended claims. Accordingly, this detailed description is to be taken in an illustrative as opposed to a limiting sense.