Drug interaction analysis and notification system

Abstract

The present disclosure is directed to systems and methods for analyzing drug-drug and gene-drug interactions for a user and providing recommendations accordingly. The systems and methods can utilize a database comprising a list of genes are associated with a plurality of drugs based on clinical relevance of the gene to the actions of the plurality of drugs. The systems and methods can include recommending alternative drugs to users based on any identified problematic drug-drug or gene-drug interactions.

Description

438949-000216 DRUG INTERACTION ANALYSIS AND NOTIFICATION SYSTEM CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims benefit of priority under 35 U.S.C. § 119(e) of U.S.Provisional Application No.63 / 575,441, filed April 5, 2024. The disclosure of the prior application is incorporated herein by reference in its entirety. BACKGROUND

[0002] In the field of healthcare technology, the prescription of medication is a commonpractice. Medical providers, such as doctors, often prescribe medication to patients based on their symptoms, medical history, and other relevant factors. The prescription is typically recorded in an electronic medical record (EMR) system, which is a digital version of a patient's paper chart. EMRs are real-time, patient-centered records that make information available instantly and securely to authorized users.

[0003] Once a prescription is made, it is usually sent to a pharmacy benefit manager(PBM). PBMs are third-party administrators of prescription drug programs for commercial health plans, self-insured employer plans, Medicare Part D plans, the Federal Employees Health Benefits Program, and state government employee plans. They are primarily responsible for developing and maintaining the formulary, contracting with pharmacies, negotiating discounts and rebates with drug manufacturers, and processing and paying prescription drug claims.

[0004] In the process of medication prescription and dispensation, patient informationplays a pivotal role. This information can include the patient's identity, the prescribing provider, the prescribed medication, the payor, and the pharmacy. This information is often communicated via an Application Programming Interface (API), which is a set of rules and protocols for building and interacting with software applications.

[0005] A relatively recent development in the field of healthcare is the use of geneticinformation in determining the suitability of a medication for a particular patient. This practice, known as pharmacogenomics, involves the study of how genes affect a person's response to drugs. It is a relatively new field, combining pharmacology (the science of drugs) and genomics (the study of genes and their functions) to develop effective, safe medications and doses that will be tailored to a person's genetic makeup.

[0006] Pharmacogenomics has the potential to greatly improve the efficiency of drugprescription by reducing the trial-and-error approach that is often used in finding the right438949-000216 drug and dosage for a patient. However, the integration of pharmacogenomics into the process of medication prescription and dispensation involves complex data analysis and real- time communication among various parties, including the patient, the provider, the pharmacy, the payor, and the PBM.

[0007] Two of the major determinants of whether a drug will have the intendedtherapeutic effect or produce an adverse drug reaction are the patient’s genetic make-up and the potential for two concomitantly administered drugs to interact (drug-gene and drug-drug interactions, respectively). Currently, drugs are generally prescribed to patients without performing detailed genetic analyses. Further, if patients do not provide their healthcare providers with a complete and accurate list of all of the drugs that they are taking (either intentionally or unintentionally), then healthcare providers may prescribe a drug that has a negative interaction with another drug. This can cause negative health outcomes for patients and inefficiencies related to drug prescribing, generally referred to as “trial-and-error” prescribing. Therefore, there is a need in the art for a system that optimizes the mix of drugs a patient is prescribed according to genetic make-up and drug-to-drug interactions. Absent such information, one can never be assured that the drugs that they are taking are in fact completely correct for a particular patient. Some current commercially available databases have some information on drug-drug interactions and some information on the drugs themselves (e.g., major metabolite or the enzyme that forms that metabolite), but such commercial databases do not provide all of the information needed to make proper assessments regarding potential drug-drug and / or gene-drug interactions. Therefore, there is a need in the prior art for systems and methods that will fully analyze all drug-drug and gene- drug interactions in order to provide better clinical outcomes and more savings throughout the healthcare industry (whether by avoiding negative health outcomes for patients or by minimizing prescribing inefficiencies).

[0008] Pharmacogenomic testing identifies mutations or variants in genes that mayaffect whether a particular medication would be an effective treatment for the individual or whether the tested individual would suffer from side effects to the medication. Current pharmacogenetic test reports list each gene, genotype, and phenotype separately, and include a list of drugs affected by each gene. Therefore, the onus is placed on the medical provider to properly digest and interpret the myriad information in the pharmacogenetic test report to provide the best medication recommendation to the patient. Understandably, many providers find the pharmacogenetic test reports confusing and have difficulty incorporating the testing438949-000216 information into their usual practice of medicine due to (i) a general lack of expertise in interpreting pharmacogenetic data, (ii) time constraints caused by their daily patient volumes, (iii) challenges in integrating synthesizing data from multiple sections of the pharmacogenetics reports related to different genes and understanding the significance of the different sections for a particular drug, and (iv) the fact that the currently generated pharmacogenetics reports are static and, thus, have limited utility following any changes to the patient’s drug regimen. Therefore, there is a need in the prior art for systems adapted to report results and recommendations from analyzed drug-drug and gene-drug interactions in a more understandable and dynamic manner. SUMMARY

[0009] The present disclosure is directed to systems and methods for analyzing drug-drug and / or drug-gene interactions for a user and managing prescriptions if problematic drug- drug and / or drug-gene interactions are identified.

[0010] In one embodiment, there is provided a method for real-time medicationadjudication based on genetic review, wherein a pharmacy benefit manager (PBM) has received a prescription for a medication, the method comprising one of more of: receiving, from the PBM (optionally, via an API), at least one of patient information, provider information, pharmacy information, payor information, or prescription information; querying a database with the patient information to determine whether a problematic gene-drug and / or drug-drug interaction exists for the medication; sending a response to the PBM to halt adjudication of the medication if the medication is determined to be problematic; and sending a notification to at least one of the patient, provider, pharmacy, payor, and PBM, the notification indicating that the medication is problematic and, optionally, providing a list of approved replacement drugs.

[0011] In some embodiments, the notification is sent via at least one of email, text, e-fax,and phone.

[0012] In some embodiments, the list of approved replacement drugs is filtered by aprevailing formulary.

[0013] In some embodiments, the list of approved replacement drugs is geneticallycompatible with the patient.

[0014] In some embodiments, the notification includes a reason for the medication beingnot advisable.438949-000216

[0015] In some embodiments, the list of approved replacement drugs is provided for themedical provider to choose from.

[0016] In some embodiments, the patient information includes at least one of patient,provider, prescription, payor, and pharmacy.

[0017] In one embodiment, there is provided a system for real-time medicationadjudication based on genetic review, comprising one of more of: a communication module configured to receive a prescription from a medical provider via an electronic medical record and to transmit the prescription to a pharmacy benefit manager (PBM); a processing module configured to receive patient information from the PBM via an API, to query a database with the patient information to determine a genetic compatibility of the prescribed medication, and to send a response to the PBM to halt adjudication of the medication if the medication is determined to be genetically incompatible; and a notification module configured to send a notification to at least one of the patient, provider, pharmacy, payor, and PBM, the notification indicating that the medication is not advisable and providing a list of approved replacement drugs.

[0018] In some embodiments, the communication module is further configured toreceive a patient identifier code from the PBM.

[0019] In some embodiments, the patient identifier code is used by the processingmodule to query the database.

[0020] In some embodiments, the processing module is further configured to determinethe genetic compatibility of the prescribed medication by comparing the patient's genetic information with a database of known gene-drug interactions.

[0021] In some embodiments, the notification module is further configured to send thenotification via at least one of email, text, e-fax, and phone.

[0022] In some embodiments, the notification module is further configured to provide areason for the medication being not advisable in the notification.

[0023] In some embodiments, the notification module is further configured to provide alist of approved replacement drugs that are genetically compatible with the patient in the notification.

[0024] In one embodiment, there is provided a computer-implemented method for real-time medication adjudication based on genetic review, comprising one of more of: receiving a prescription from a medical provider via an electronic medical record; transmitting the prescription to a pharmacy benefit manager (PBM); receiving patient information from the438949-000216 PBM via an API; querying a database with the patient information to determine a genetic compatibility of the prescribed medication; sending a response to the PBM to halt adjudication of the medication if the medication is determined to be genetically incompatible; and sending a notification to at least one of the patient, provider, pharmacy, payor, and PBM, the notification indicating that the medication is not advisable and providing a list of approved replacement drugs.

[0025] In some embodiments, the patient information includes a genetic profile of thepatient.

[0026] In some embodiments, the genetic profile of the patient is used to determine thegenetic compatibility of the prescribed medication.

[0027] In some embodiments, the database includes information on gene-druginteractions.

[0028] In some embodiments, the response to the PBM includes a reason for haltingadjudication of the medication based on the determined gene-drug interaction.

[0029] In some embodiments, the list of approved replacement drugs is selected basedon the genetic profile of the patient and the information on gene-drug interactions in the database. BREIF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings, which are incorporated in and form a part of thespecification, illustrate the embodiments of the invention and together with the written description serve to explain the principles, characteristics, and features of the invention. In the drawings:

[0031] Figure 1 depicts a block diagram of a system for analyzing drug interactions for auser, in accordance with an embodiment of the present disclosure.

[0032] Figure 2A depicts a flow diagram of a process for analyzing drug interactions fora user, in accordance with an embodiment of the present disclosure.

[0033] Figure 2B depicts a flow diagram of a process for analyzing drug-geneinteractions and categorizing a drug accordingly, in accordance with an embodiment of the present disclosure.

[0034] Figure 3A depicts an illustrative graphical user interface (GUI) for inputtingdrugs, in accordance with an embodiment of the present disclosure.438949-000216

[0035] Figure 3B depicts an illustrative GUI for indicating drug interactions, inaccordance with an embodiment of the present disclosure.

[0036] Figure 4 depicts an illustrative internal or override table, in accordance with anembodiment.

[0037] Figure 5 depicts a diagram of a process executed by the drug interaction analysissystem for providing notifications to PBMs and other parties, in accordance with an embodiment. DETAILED DESCRIPTION

[0038] This disclosure is not limited to the particular systems, devices and methodsdescribed, as these may vary. The terminology used in the description is for the purpose of describing the particular versions or embodiments only and is not intended to limit the scope of the disclosure.

[0039] The following terms shall have, for the purposes of this application, therespective meanings set forth below. Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art. Nothing in this disclosure is to be construed as an admission that the embodiments described in this disclosure are not entitled to antedate such disclosure by virtue of prior invention. Definitions

[0040] As used herein, the singular forms “a,” “an,” and “the” include plural references,unless the context clearly dictates otherwise. Thus, for example, reference to a “pharmaceutical” is a reference to one or more pharmaceuticals and equivalents thereof known to those skilled in the art, and so forth.

[0041] As used herein, the term “about” means plus or minus 10% of the numericalvalue of the number with which it is being used. Therefore, about 50 mm means in the range of 45 mm to 55 mm.

[0042] As used herein, the term “consists of” or “consisting of” means that the device ormethod includes only the elements, steps, or ingredients specifically recited in the particular claimed embodiment or claim.

[0043] In embodiments or claims where the term “comprising” is used as the transitionphrase, such embodiments can also be envisioned with replacement of the term “comprising” with the terms “consisting of” or “consisting essentially of.”438949-000216

[0044] As used herein, terms “user,” “subject,” or “patient” can be used interchangeably.

[0045] As used herein, the terms “drug,” “medication,” or “pharmaceutical composition”refer to a composition comprising an active pharmaceutical ingredient to be delivered to a subject, for example, for therapeutic, prophylactic, diagnostic, preventative, or prognostic effect.

[0046] As used herein, the term “active pharmaceutical ingredient” or “API” refers asubstance in a pharmaceutical composition that provides a desired effect, for example, a therapeutic, prophylactic, diagnostic, preventative, or prognostic effect. In various embodiments, the active pharmaceutical ingredient can be any of a variety of substances known in the art, for example, a small molecule, a polypeptide mimetic, a biologic, an antisense RNA, a small interfering RNA (siRNA), and so on.

[0047] As used herein, “analyzing drug interactions” refers to assessing the impact of apatient’s genetics on the metabolism of a drug, i.e., analyzing how a drug is metabolized by a patient, wherein the determination is based on the genetics of the patient.

[0048] As used herein, “genetic test results” refers to results from one or more ofmolecular tests (e.g., targeted single variant tests, single gene tests, gene panels, and / or whole genome sequencing), chromosomal tests, gene expression tests, or biochemical tests for identifying genotypes and / or phenotypes of genes. In particular embodiments, the genetic test results are for genes that are relevant for drug response as described herein.

[0049] As used herein, “drug category” refers to classifications for drugs based ontherapeutic effect, mechanism of action, or other collective characteristics. Drug categories could include, for example, opioids, analgesics, beta blockers, and antipsychotics.

[0050] As used herein, “clinical relevance” refers to whether the gene directly orindirectly impacts the drug’s metabolism. Relevant genes for various types of drugs would be known by the skilled person by, for example, consulting available scientific literature, FDA labeling, and other accepted sources of drug information. In one illustrative embodiment, a mutation in a gene that enhances or reduces a particular drug’s metabolism by at least a threshold amount (e.g., 50% or greater) could be considered clinically relevant for the drug.

[0051] As used herein, “major metabolite” refers to the product predominantly producedby action of the enzyme on the drug.

[0052] As used herein, “associated with the drug” or “pharmacokinetically associatedwith the drug” refers to an enzyme that interacts with the drug or a protein that otherwise affects the response to the drug (e.g., by interacting with a receptor or membrane protein,438949-000216 such as a transporter), either directly or indirectly, to produce the major metabolite (e.g., by using the drug as a substrate) or otherwise influence the therapeutic response to the drug.

[0053] As used herein, “problematic,” particularly within the context of a problematicgene-drug interaction, refers to whether the drug’s action is affected by one or more genetic mutations of the user. This effect may be to reduce or increase the action of the drug. Increasing or reducing the action of the drug may lead to adverse effects for the patient.

[0054] As used herein, “threshold pharmacokinetic impact” refers to any factor thatreduces or enhances drug metabolism by a threshold amount (e.g., 50% or greater)

[0055] As used herein, “determining whether there is a problematic gene-druginteraction associated with the drug” refers to determining whether the genetics of the user (i.e., mutations in a gene associated with a protein which acts either directly or indirectly on the drug) impact metabolism of or response to the drug. Problematic gene-drug interactions can be calculated by, for example, examining the scientific data regarding metabolism or response to the drug and whether mutation of the protein encoded by the gene can affect the response or metabolism of the drug in a clinically relevant manner.

[0056] As used herein, “internal database” refers to a database including one or moreentries, wherein each database entry could include a variety of different information, such as the clinically relevant genes or genetic mutations for specific drugs, the degree to which the listed genes affect drug metabolism or drug response, and other gene-drug interactions.

[0057] As used herein, “external database” refers to a database including one or moreentries, wherein each database entry could include a variety of different information, such as the drug’s major metabolic pathways, the classification or category of the drug, and drug- drug interactions. A suitable external database could include, for example, the DrugBank database, which is accessible at https: / / go.drugbank.com. Drug Interaction Analysis System

[0058] The present disclosure is directed to systems and methods for analyzingmedications for a patient, including analyzing drug-drug and gene-drug interactions. Further, the described systems and methods can recommend alternative medications to the patient and / or a third party (e.g., a healthcare provider) in the event that an alternative medication could be warranted for the patient. Figure 1 illustrates a system 100 including a computer system 102 that can be accessed by a user 112 and / or a healthcare provider 114 via a network 110 (e.g., the Internet). Further, the computer system 102 could store or otherwise be438949-000216 communicatively coupled to a database 116, which can store a variety of different information associated with drug pharmacokinetics or drug-drug interactions, as described in greater detail below. In operation, the user 112 can access the computer system 102 to input data (e.g., medications that the user is taking), review pharmacogenetic analysis results and recommendations, and take other such actions. In some embodiments, the computer system 102 can further be communicatively coupled to a PBM 120 and / or a pharmacy 122, as described in greater detail below.

[0059] In one embodiment, the computer system 102 could be operated or controlled bya testing entity that is able to receive, perform, and / or order genetic testing 118 on patient- provider samples to obtain genetic data on the patient. In another embodiment, the computer system 102 could be otherwise configured to receive genetic testing 118 from an external source (e.g., via the network 110). As described in greater detail below, users’ genetic data can be utilized to analyze whether any alternative medications may provide better results or may otherwise be better suited for the user given the user’s genetic makeup. In one embodiment, the user’s genetic test results can be obtained by laboratory testing of genetic samples taken from the user (e.g., through analysis of buccal mucosal epithelial cells taken via swabbing the inside of the cheek with a specially manufactured swab). The genetic test results can be in the form of the genetic diplotype (i.e., one allele from each parent), which is then converted into a phenotype (i.e., the functional impact of the diplotype on protein function). In some embodiments, it could be beneficial to consider a user’s diplotype because each allele can be associated with a functional aspect of the protein for which it encodes. Accordingly, an individual’s diplotype could influence how he or she metabolizes a drug or how the drug otherwise affects the individual. For example, if one allele encodes a protein that exhibits normal functionality and the second allele encodes a non-functional protein, then the blended phenotype could operate as a half-functional protein. For a gene that encodes a metabolic enzyme, the example phenotype for the individual could be categorized as an “intermediate metabolizer,” for example. In one embodiment, the genetic testing 118 could include the diplotype associated with one or more tested genes. In this embodiment, the computer system 102 could be programmed to match the received diplotype from the genetic test results with a table of previously determined functionalities associated with individual alleles and, accordingly, convert the diplotype into a predicted blended phenotype for the gene. The phenotype could then be reported as the clinically relevant result for that gene. In some embodiments, the phenotype could be assigned a corresponding indicium from one or438949-000216 more indicia that represent the degree of impact on protein function for the user’s diplotype. For example, the indicia could represent severe, intermediate, or no impact. In one embodiment, the indicia for the assigned phenotypes could include a color (e.g., red, yellow, and green).

[0060] The computer system 102 can include a processor 104 and a memory 106 toexecute various process or algorithms for analyzing the drugs users are taking and / or users’ data to provide recommendations to the users accordingly. In some embodiments, the computer system 102 could include a server or a cloud-based computing system. In various embodiments, the computer system 102 could be configured to provide an interface (e.g., a GUI) that is accessed by and / or interacted with via a software application (e.g., run on a mobile device associated with the user 112) or a website. The interface could allow users to input the medications that they are taking, such as is shown in Figure 3A. Further, the interface could display various recommendations or alerts to users, such as is shown in Figure 3B.

[0061] In one embodiment, a user could manually input which drugs they are takingand / or have been prescribed. In another embodiment, the computer system 102 could be configured to obtain drugs the user is taking from the user’s electronic health records (EHR) or other external source. For example, the computer system 102 could be communicably coupled to a healthcare provider computer system and have access to the user’s EHR through either permission from the user or the user’s healthcare provider 114 (e.g., doctor). In this embodiment, the computer system 102 could be configured to automatically retrieve the list of the drugs that the user is taking and / or has been prescribed from the user’s EHR upon receipt of the appropriate permissions.

[0062] The computer system 102 can be configured to communicate with an externaldatabase 116 that provides information on drugs, such as drug-drug interactions or information on the major metabolic pathway associated with the drug (e.g., the major circulating metabolite and the metabolic enzyme responsible for its formation). The external database 116 could be accessed via a corresponding application programming interface (API), for example. The external database 116 could include the DrugBank database, for example. One issue with current drug databases, such as DrugBank, is that although they may have some information on drug-drug interactions and major metabolic pathway data for the drug (e.g., the major circulating metabolite and the metabolic enzyme responsible for its formation), the available information in such external databases 116 is not sufficient to438949-000216 determine whether any genetic mutations an individual may have (as determined from genetic testing) could affect the pharmacokinetics of a given drug. For example, although currently available drug information databases may include the metabolic enzyme associated with the major circulating metabolite associated with the drug, the pharmacokinetics of a given drug may be affected by other enzymes and / or other genetic mutations. Therefore, currently available databases are not sufficient to provide individuals with a complete, clear picture on whether a drug may be appropriate for them to use based on genetic testing.

[0063] Accordingly, the system 100 described herein includes a drug interaction table109 associated with an internal database 108 that is stored on the computer system 102 or is otherwise communicably coupled to the computer system 102. The drug interaction table 109, also referred to in some instances as an “override table,” has been developed to supplement and / or override drug information in currently commercially available drug information databases. The drug interaction table 109 sets forth drug-gene interactions for drugs for which currently available external databases 116 do not provide sufficient information to identify all possible drug-gene interactions. For each drug in the drug interaction table 109, genes are associated with a drug based on clinical relevance of the gene to the actions of the drug. Clinical relevance is determined based on experimental data (usually clinical data) showing that genetic mutations affecting the function of the protein encoded by the gene have effects that impact the drug’s clinical attributes, e.g. efficacy, safety, or pharmacokinetics. In some embodiments, the drug interaction table 109 could be based on individual alleles and / or a diplotype associated with the gene or genes set forth. In one embodiment, the drug interaction table 109 is constructed in a tabular format including each drug for which the external databases 116 lack sufficient information to identify the relevant gene-drug interactions and the clinically relevant genes associated with each of the drugs. The drug interaction table 109 can further include clinically relevant metabolic genes and clinically relevant response genes. Figure 4, for example, depicts an illustrative portion of a drug interaction table 109 indicating the metabolic markers and response markers for a pair of drugs. In this example, the drugs are indicated based on their DrugBank IDs (e.g., DB00802 corresponds to alfentanil). Accordingly, the system 100 can query DrugBank or other external databases based on the particular IDs associated with those drugs from the drug interaction table 109.

[0064] In operation, the computer system 102 receives the list of one or more drugs thata user is taking (e.g., by being manually entered via an app GUI or a website GUI) and the438949-000216 user’s genetic testing results. For each drug taken by the user, the computer system 102 queries the drug interaction table 109 for the drug in question, retrieves the relevant genes from the metabolic and response gene data for the drug, checks the relevant genes against the patient’s pharmacogenetic test results, and reports any abnormalities that present a potential drug-gene interaction (e.g., a mutation present in a gene that codes for one of the clinically relevant enzymes associated with drug). If a drug is not present in the drug interaction table 109, the computer system 102 could retrieve corresponding data from an external database 116 and determine any drug-gene interactions therefrom. The report to the user could include a description of the nature of the abnormality and how that affects either drug metabolism or drug response. As new information regarding drug-gene interactions become available (e.g., new research and / or clinical data), the drug interaction table 109 can be dynamically modified to incorporate the new information. Unlike the internal database 108, current commercially available database (e.g., DrugBank) do not consider clinical relevance, but rather simply list drug attributes (e.g., drug metabolizing enzymes or drug class). These commercially available databases can be queried in a manner that assumes certain attributes have clinical relevance (i.e., clinical relevance may not be supported by experimental data) based on general principles of pharmacology (e.g., drug metabolism and dose-response relationships), but these assumptions would not be correct for all drugs. Therefore, any system that attempted to identify possible drug-gene interactions based on this commercially available information alone would be incomplete and, thus, not provide correct results in all cases. If the drug in the external database has drug attributes for which the tested pharmacogenetic genes are relevant, the relevant gene information can be reported if abnormal.

[0065] In one particular embodiment, the system 100 can be embodied as a web-basedapp that can search a commercial database of drug-drug interactions (e.g., DrugBank), identify problematic drug combinations, and display any problematic drug combinations to the physician and / or the patient user, along with extended descriptions of the problematic interaction and information on how to manage them clinically. The system 100 can further identify gene-drug interactions by comparing the patient’s medications to an internal database of specific drugs and the genes that code for proteins that impact either the biotransformation of the specific drugs (i.e., metabolic genes), transport of the specific drugs within the body, and / or the therapeutic response to the specific drug (i.e., response genes). The internal database can be established using clinical and / or research data on the various drugs.438949-000216

[0066] Any problematic drug-drug and / or drug-gene interactions identified by thesystem 100 can be indicated based on phenotypes associated with abnormal function of the encoded proteins. Further, the results can be presented to the user in a variety of different formats. For example, the results can be color-coded green, yellow, or red based on the severity of the clinical impact of the genetic mutation and / or drug-drug interaction, where green can indicate normal function, yellow can indicate an increased risk of adverse effect or decreased clinical efficacy, and red can indicate an extreme risk of adverse effect or lack of clinical efficacy. Drug Interaction Analysis Processes

[0067] One embodiment of a process 200 for analyzing users’ drug interactions is shownin Figure 2A. In one embodiment, the process 200 can be embodied as instructions stored in a memory (e.g., the memory 106) that, when executed by a processor (e.g., the processor 104), cause the computer system 102 to perform the process 200. In various embodiments, the process 200 can be embodied as software, hardware, firmware, and various combinations thereof. In various embodiments, the process 200 can be executed by and / or between a variety of different devices or systems. For example, various combinations of steps of the process 200 could be executed by the computer system 102, the network 110, and / or device (e.g., computer, laptop, or smartphone) associated with the user 112. In various embodiments, the system 100 executing the process 200 can utilize distributed processing, parallel processing, cloud processing, and / or edge computing techniques. The process 200 is described below as being executed by the system 100; accordingly, it should be understood that the functions can be individually or collectively executed by one or multiple devices or systems.

[0068] The system 100 executing the process 200 can receive 202 one or more drugsassociated with the user and receive 204 genetic information (e.g., a genetic testing results) associated with the user. In one embodiment, the user could manually input the drug(s) that he or she is taking by interacting with the computer system 102, such as by inputting the drugs in a website interface. For example, Figure 3A illustrates a GUI 300 including a drug input field 302 in which users can manually input the drugs that they are taking and / or have been prescribed. In the particular example shown in Figure 3A, the user has input two drugs 304 (propranolol and clopidogrel) that he is taking. In another embodiment, the computer system 102 could retrieve the user’s EHR (e.g., from a database associated with the patient’s438949-000216 healthcare provider) and determine the drugs that are being taken and / or have been prescribed to the user therefrom. In one embodiment, the system 100 could receive 204 the genetic information from a genetic test performed by the entity operating the computer system 102. In another embodiment, the system 100 could receive 204 the user’s genetic information from a third party or another external source.

[0069] For each of the patient’s drugs, the system 100 can identify 206 any drug-geneinteractions associated with the received 202 drug list and the received 204 genetic information. In parallel with or otherwise separately from identifying 206 drug-gene interactions, the system 100 can further identify 208 any drug-drug interactions. In one embodiment, the system 100 can identify 206 drug-drug interactions utilizing commercially available databases (e.g., DrugBank).

[0070] The system 100 can identify 206 drug-gene interactions between the received 202drug list and the received 204 genetic information for the user in a variety of different manners. In one embodiment shown in Figure 2A, the system 100 can determine 210 whether the drug is present in the internal database 108 (i.e., the drug interaction table 109). If the system 100 determines 210 that the drug is present in the internal database 108, the system 100 can determine 212 whether there any drug-gene interactions based on the pre- characterized drug-gene data in the drug interaction table 109. If the system 100 determines 210 that the drug is not present in the internal database 108, the system 100 can search 214 an external database 116 (e.g., DrugBank) for the major metabolite and the enzyme responsible for forming the major metabolite that is associated with the given drug. If a drug is not present in the internal database 108, it could be assumed that it has been determined that the information present in the external database 116 is sufficient to assess the clinical effects of pharmacogenetic data for the drug. Based on the data from the external database 116, the system 100 can identify the primary enzyme for the drug, which can in turn be utilized to determine 216 whether there any drug-gene interactions based on the user’s genetic testing information and the determined primary enzyme associated with the drug. In other words, the system 100 can determine 216 whether the user has a mutation in the gene associated with the identified primary enzyme that clinically affects the drug. In this context, a genetic mutation could clinically affect the enzyme if it deactivates the enzyme, causes the enzyme to be over functional, or causes the enzyme to be under functional. For example, the CYP2C19 codes for an enzyme that is clinically relevant to clopidogrel. Clopidogrel is a prodrug which is converted to its active form by CYP2C19. If CYP2C19 has a mutation that causes the438949-000216 enzyme to be under functional, then there will be no clinically relevant drug effect for clopidogrel. Conversely, if CYP2C19 has a mutation that causes the enzyme to be over functional, then there will be too much drug effect and the patient’s blood will be thinned too much, leading to increased risk of hemorrhage. The system 100 could determine 212, 216 whether the user has a mutation in the CYP2C19 gene or any other gene that has a clinical effect on a drug either via the precharacterized drug interaction table 109 or information obtained from an external database 116.

[0071] Accordingly, the system 100 can determine 218 whether there are anyproblematic drug-gene interactions. Different genetic mutations can have varying impacts on the pharmacokinetics of the medication; therefore, it may be desirable in some implementations to quantify or otherwise determine the degree of pharmacokinetic impact that the particular genetic mutation would have on the medication. In other words, it may be desirable to only recommended alternative medications in circumstances where the patient’s genetic mutation would have a significant or non-trivial pharmacokinetic impact on the medication. Therefore, in one embodiment, the system 100 could determine 218 whether there are any problematic drug-gene interactions based on whether the pharmacokinetics associated with the enzyme coded by the particular gene at issue would be adversely impacted with respect to the drug by at least a threshold level or degree.

[0072] In one embodiment, the system 100 can code the analyzed drug into one or morecategories depending on whether the system 100 identifies any problematic drug-gene interactions. For example, a first category could correspond to drugs for which no genetic indicators of clinical importance were identified based on the subject’s genetic data, a second category could correspond to drugs for which genetic indicators were identified that warrant caution, and a third category could correspond to drugs for which genetic indicators were identified warrant extreme caution or avoidance. To aid users in quickly identifying and assessing which of the categories the analyzed drug falls into, the categories can be associated with various indicia (e.g., color) that can be presented via a graphical user interface, such as is shown in Figures 3A and 3B.

[0073] In embodiment, the system 100 can determine 218 whether there are anyproblematic drug-gene interactions by calculating a score for the drug and comparing the calculated score to various threshold values to assess whether the particular drug or set of drugs are problematic given the subject’s genetic data. In embodiment, the drug score can include one or more separate calculations and / or components.438949-000216

[0074] In one embodiment, determining and / or calculating the drug score could includedetermining and / or calculating a metabolic component value (MCV) and a response component value (RCV). The MCV can be a calculation based on the phenotypic results for the relevant metabolic genes. The RCV can be a calculation based on the expected response or adverse effects according to the phenotypes determined from the subject’s genetic information. In one embodiment, MCV can be calculated for n genes according to the following equation: ^^ ^^^^^^ = ∑(^^^^^^^^ × ^^^^)where PCD is the phenotypic gene and I is the relativeimportance (e.g., expressed as a the particular gene. In other words, the MCV is calculated via a weighted summation the PCDs for n genes associated with the particular drug being analyzed. Notably, the relative importance (I) for the genes associated with the drug sum to one. In one embodiment, the PCD could be a value corresponding to the assigned coding for the gene (e.g., no genetic indicators of clinical importance, genetic indicators warranting caution, or genetic indicators warranting extreme caution or avoidance). For example, the PCD value for a “green” or low risk gene for the particular drug could be one, the PCD value for a “yellow” or moderate risk gene could be five, and the PCD value for a “red” or high risk gene could be ten. In other embodiments, the PCD values could be different static values, functions based on one or more variables, and so on. In one embodiment, the relevance value could be a value assigned to each value based on its pharmacological and toxicological attributes. For example, the relevance value could be based on the overall contribution of each tested gene to the total metabolism of the drug and resultant drug metabolites, the clinical relevance of the metabolic product from each tested gene (e.g., whether active metabolites are produced, whether toxic metabolites are produced, and whether the metabolites are primary to the drug response), known pharmacogenetic- related metabolic effects (e.g., obtained from the drug label), and relevant information from the scientific literature (e.g., data from in vitro studies using human hepatocytes and clinical studies).

[0075] In one embodiment, determining and / or calculating the drug score could includedetermining and / or calculating a response component value (RCV). For example, the RCV calculation can be based on the PCD obtained for a response-associated gene or PCDs for a group of response-associated genes (if more than one response gene is relevant for the drug).438949-000216 For response genes, there is no weighting of the relative importance for the individual response genes since any deleterious mutation on any relevant response gene would make the drug not efficacious. Therefore, the highest PCD value among the relevant response genes is assigned as the RCV. So, for example, if a drug has two relevant response genes with PCD values of 1 and 5, then the RCV would be 5.

[0076] In one embodiment, the system 100 can determine 218 whether there are anyproblematic drug-gene interactions using a combination of the MCV and RCV. One example of a process for determining 218 whether there are any problematic drug-gene interactions given the subject’s genetic information and drug(s) associated with the subject (i.e., drugs currently being taken by the subject or drugs that are to be prescribed to the subject) is shown in Figure 2B. In this embodiment, the system 100 calculates 215 the MCV given the genetic information and drug(s) received 202, 204 for the subject, as described above. Further, the system 100 determines 252 whether any response and / or adverse event markers are present. The system 100 surveys the genetic information obtained by testing for pharmacogenetic mutations (i.e., the PGx test results) and matches it with the genes that are relevant for the drug for which the PCD is being determined. If no response and / or adverse event markers are present, then the system 100 assigns 254 the MCV as the score for the given genetic and / or drug information. If response and / or adverse event markers are present, then the system 100 determines 256 the RCV given the genetic information and drug(s) received 202, 204 for the subject, as described above. The system 100 compares the RCV and MCV and assigns the greater of the two values. Accordingly, the system 100 determines 258 whether the RCV is greater than the MCV. If the MCV is greater, the system 100 assigns 254 the MCV as the score for the given genetic and / or drug information. If the RCV is greater, the system 100 assigns 260 the RCV as the score for the given genetic and / or drug information. Accordingly, the system 100 categorizes 262 the drug according to the assigned 254, 260 score.

[0077] If the system 100 does determine 218 that there are problematic drug-geneinteractions for the user, the system 100 can identify 220 one or more alternative drugs to the analyzed drug. In one embodiment, the alternative drugs could be determined from the product category of the drug at issue. For example, if the drug being analyzed was a beta blocker, then the system 100 could identify 220 an alternative beta blocker for the user. As another example, if the drug being analyzed was an opioid, then the system 100 could identify 220 an alternative opioid for the user. In one embodiment, the identified 220438949-000216 alternative drug could further be analyzed to identify 206 any drug-gene interactions associated with the identified 220 alternative drug, as indicated in Figure 2. This embodiment can be beneficial because it could be desirable to check the proposed drug for any problematic gene-drug interactions so that the system 100 only proposes alternative drugs that were likewise analyzed for their gene-drug interactions. Further, the system 100 can repeat the process of identifying 206 gene-drug interactions continuously until a suitable alternative drug (i.e., a drug that does not have any problematic gene-drug interactions) that is in the same product category of the originally analyzed drug is identified.

[0078] Once the system 100 executing the process 200 has identified a suitablealternative drug, the system 100 can provide 222 the results. In one embodiment, the system 100 can provide 222 the results to the user 112. In another embodiment, the system 100 can provide 222 the results to the user’s healthcare provider 114. In yet another embodiment, the system 100 could provide 222 the results to both the user 112 and the healthcare provider 114. The results can include whether any gene-drug or drug-drug interactions were identified and / or a proposed alternative drug. In one embodiment, the system 100 could provide the patient and / or third party with data, a report, or a summary indicating the pharmacokinetic impact of the patient’s particular genetic mutation(s) on the medication(s) currently being taken by the patient. Such an embodiment could be beneficial in order to further educate patients in managing and taking an active role in their own healthcare. For example, Figure 3B illustrates a reporting GUI 310 provided by the system 100. In this example, the reporting GUI 310 includes an alert 311 indicating that problematic drug-drug and / or gene-drug interaction were identified for the user. In this example, a widget 312 of the reporting GUI 310 indicates that there is a problematic drug-drug interaction between two of the drugs being taken by the user. Further, a second widget 314 of the reporting GUI 310 further explains the identified problematic gene-drug interaction. Finally, the reporting GUI 310 lists alternative drugs 316 for each of the drugs that the user is taking for which problematic gene-drug interaction and / or drug-drug interactions were identified.

[0079] Further, the process 200 illustrated in Figure 2 can be repeated for each drug thatthe user is taking. The analyses for each of the drugs by the process 200 executed by the system 100 can be incorporated into the report provided 222 to the user.

[0080] It should further be noted that although the functions and / or steps of the process200 are depicted in a particular order or arrangement, the depicted order and / or arrangement of steps and / or functions is simply provided for illustrative purposes. Unless explicitly438949-000216 described herein to the contrary, the various steps and / or functions of the process 200 can be performed in different orders, in parallel with each other, in an interleaved manner, and so on. Drug Interaction Analysis System—Application Programmable Interface

[0081] As generally described above, a variety of different external systems (e.g., thirdparty systems) can be communicably coupled to the computer system 102 or otherwise be configured to interface with the computer system 102. In some embodiments, the external systems can be communicably coupled to the computer system 102 via an application programmable interface (API). An API is a set of protocols, routines, and tools for building software applications. Accordingly, the API defines a standard set of rules that allows external systems to communicate with the computer system 102. The API can enable external systems to exchange data with the computer system 102 in order to provide access to the drug-drug and gene-drug analyses provided by the computer system 102 (as described above) to determine drug effectiveness. The API could allow a variety of different external systems to submit queries to the computer system 102 or otherwise make use of the computer system 102 in order to instantaneously allow external systems to receive responses from the computer system 102, without the need for manual queries to be generated as typical for this field.

[0082] The API can support a variety of different endpoints, such as an API call toretrieve patient results based on a drug lookup. The API call could be structed to, for example, receive a particular drug (or set of drugs) for a subject and identifying information for the subject. In response to the call, the computer system 102 could return data indicating that the patient data was located within the internal database 108, the assigned category for the drug (i.e., whether any drug-gene and / or drug-drug interactions were identified and the severity of those interactions), and the identified drug-gene and / or drug-drug interactions. This data could then either be presented to the user (e.g., via a graphical user interface, as shown in Figures 3A and 3B) or otherwise utilized by the external system (e.g., a healthcare provider system 114) initiating the query. As generally discussed above, the genetic testing data 118 for the particular subject may have been previously received by the computer system 102 from an appropriate genetic testing facility and / or otherwise uploaded to the internal database 108.

[0083] Aspects of the present invention will now be illustrated by way of example onlyand with reference to the following experimentation.438949-000216 Drug Interaction Analysis Example 1—Efavirenz

[0084] Efavirenz, sold under SUSTIVA®, is a human immunodeficiency virus type 1(HIV-1) specific, non-nucleoside, reverse transcriptase inhibitor (NNRTI). Efavirenz is metabolized by CYP3A4 / 5, CYP2B6, CYP2C9, and CYP2C19; accordingly, these genes are utilized to analyze whether any problematic interactions exist based on the subject’s genetic test results associated with these genes. In this example, an illustrative patient has the following genetic test results: 3A4 PM, 3A5 IM, 2B6 EM, 2C9 IM, 2C19 PM, where PM, IM, and EM are metabolic phenotypes. The metabolic phenotypes are determined by (i) conversion of the mutations into associated phenotypes and (ii) categorization of the two phenotypes (one from each parent), also known as the diplotype, into a composite phenotype and associated PCD via consulting a diplotype-to-phenotype conversion table. Based on the aforementioned genetic result data, the PCD for CYP3A5 is five (i.e., “yellow”), the PCD for CYP2B6 is one (i.e., “green”), the PCD for CYP2C9 is five (i.e., “yellow”), and the PCD for CYP2C19 is ten (i.e., “red”). As noted above, a relative importance is assigned by the computer system 102 to each of the various components of the MCV calculation. These weights are set forth below. Accordingly, the MCV is calculated as follows for efavirenz given the above genetic information: ^^^^^^efavirenz = (^^^^^^CYP3A5 × ^^CYP3A5 ) + (^^^^^^CYP2B6 × ^^CYP2B6)+ (^^^^^^CYP2C9 × ^^CYP2C9) + (^^^^^^CYP2C19 × ^^CYP2C19)^^^^^^efavirenz = (5 × 0.60) + (1 × 0.30) + (5 × 0.05) + (10 × 0.05) = 4.05Therefore, for this particular patient, the MCV of efavirenz is 4.05. Accordingly, the computer system 102 would assign a yellow phenotypic color designation, indicating a moderate risk associated with this drug for this patient. As described above, this categorization could be displayed to the user via a graphical user interface.

[0085] Notably, although efavirenz is metabolized by CYP3A4 and CYP3A5, CYP3A4is ignored by the computer system 102 because CYP3A4 and CYP3A5 are treated as a combined function because they act identically on the drugs they affect. Accordingly, the computer system 102 and processes described herein can utilize the best result between CYP3A4 and CYP3A5 for calculating the score for a drug. Drug Interaction Analysis Example 2—Simvastatin

[0086] Simvastatin is used to lower low-density lipoprotein (LDL-C) cholesterol in theblood. In a patient of African descent, simvastatin is metabolized by CYP3A4 / 5 and is438949-000216 associated with an adverse effect gene (SLCO1B1); accordingly, these genes are utilized to analyze whether any problematic interactions exist based on the subject’s genetic test results associated with these genes. In this example, an illustrative patient has the following genetic test results: 3A4 IM, 3A5 EM, SLCO1B1. Based on the aforementioned genetic result data, the PCD for CYP3A5 is one (i.e., “green”). As noted above, a relative importance is assigned by the computer system 102 to each of the various components of the MCV calculation. These weights are set forth below. Accordingly, the MCV is calculated as follows for simvastatin given the above genetic information: ^^^^^^simvastatin = (^^^^^^CYP3A5 × ^^CYP3A5 )^^^^^^simvastatin = (1 × 1.0) = 1.0

[0087] Once again, it should be noted that although simvastatin is metabolized by bothCYP3A4 and CYP3A5, only one of these two genes is analyzed for the reasons discussed above. Therefore, for this particular patient, the MCV of simvastatin is 1.0. However, because simvastatin additionally has an adverse event marker associated with it, the computer system 102 would additionally determine the RCV for simvastatin. In this case, an RCV of five (i.e., “yellow”) has been assigned to SLCO1B1 for this drug. Because the RCV is larger than the calculated MCV, the computer system 102 would assign the RCV as the drug score. Accordingly, the computer system 102 would assign a yellow phenotypic color designation, indicating a moderate risk associated with this drug for this patient. Drug Interaction Analysis Example 3—Desvenlafaxine

[0088] Desvenlafaxine is a selective serotonin and norepinephrine reuptake inhibitors(SNRI) that is used to treat depression. In a patient of non-African descent, simvastatin is metabolized by CYP3A4 / 5 and CYP2D6; accordingly, these genes are utilized to analyze whether any problematic interactions exist based on the subject’s genetic test results associated with these genes. In this example, an illustrative patient has the following genetic test results: 3A4 EM, 3A5 PM, and 2D6 EM. Based on the aforementioned genetic result data, the PCD for CYP3A5 is one (i.e., “green”). As noted above, a relative importance is assigned by the computer system 102 to each of the various components of the MCV calculation. These weights are set forth below. For some drugs, the computer system 102 can further apply a general metabolic relevance factor (MRF) to the MCV calculation where only a fraction of the relevant genes metabolize the drugs in vivo. For desvenlafaxine, only 5-10% of CYP genes metabolize the drug. Therefore, the computer system 102 can apply a general438949-000216 relevance factor or weight to the overall MCV calculation. Accordingly, the MCV is calculated as follows for simvastatin given the above genetic information: ^^^^^^desvenlafaxine = ^^^^^^ × [(^^^^^^CYP3A5 × ^^CYP3A5 ) + (^^^^^^CYP2D6 × ^^CYP2D6)]^^^^^^desvenlafaxine = 0.1 × [(1 × 0.9) + (1 × 0.1)] = 0.1

[0089] Once again, it should be noted that although simvastatin is metabolized by bothCYP3A4 and CYP3A5, only one of these two genes is analyzed for the reasons discussed above. Therefore, for this particular patient, the MCV of desvenlafaxine is 0.1. Accordingly, the computer system 102 would assign a green phenotypic color designation, indicating that there is little to no risk associated with this drug for this patient. Drug Interaction Notification System

[0090] In some aspects, the system for real-time medication adjudication based ongenetic review may involve several entities, including a medical provider, a pharmacy benefit manager (PBM), and a patient. The medical provider, such as a doctor or a nurse, may prescribe medication to the patient based on their symptoms, medical history, and other relevant factors. This prescription may be recorded in an electronic medical record (EMR) system, which is a digital version of a patient's paper chart. EMRs are real-time, patient- centered records that make information available instantly and securely to authorized users.

[0091] Once a prescription is made, it may be transmitted to a PBM. PBMs are third-party administrators of prescription drug programs for various health plans. They are primarily responsible for developing and maintaining the formulary, contracting with pharmacies, negotiating discounts and rebates with drug manufacturers, and processing and paying prescription drug claims. In some cases, the PBM may receive the prescription from the medical provider via an API, which is a set of rules and protocols for building and interacting with software applications.

[0092] In addition to the prescription, the PBM may also receive patient information.This information may include at least one of the following: the identity of the patient, the prescribing provider, the prescribed medication, the payor, and the pharmacy. In some cases, the PBM may also receive a patient identifier code. The patient identifier code could be associated with the PBM, the drug interaction analysis computer system 102 (FIG.1), or any other code that is able to uniquely identify the patient. This code may be used to recognize the patient and to query a database with the patient information.438949-000216

[0093] The patient, on the other hand, may be the recipient of the prescribed medication.The patient's genetic information may be used to determine the genetic compatibility of the prescribed medication. If the medication is determined to be genetically incompatible, the system may send a response to the PBM to halt adjudication of the medication. Furthermore, a notification may be sent to one or more of the patient, provider, pharmacy, payor, and PBM. This notification may indicate that the medication is not advisable and may provide a list of approved replacement drugs.

[0094] In some embodiments, the process of real-time medication adjudication based ongenetic review may begin with the receipt of a prescription from a medical provider. The medical provider, such as a doctor or a nurse, may prescribe medication to a patient based on their symptoms, medical history, and other relevant factors. This prescription may be recorded in an electronic medical record (EMR) system. EMRs are real-time, patient-centered records that make information available instantly and securely to authorized users. The prescription information may include details about the prescribed medication, dosage, frequency of use, and other relevant instructions.

[0095] Once a prescription is made, it may be transmitted to a pharmacy benefit manager(PBM). The transmission of the prescription may be facilitated by an API, which is a set of rules and protocols for building and interacting with software applications. The API may enable the electronic transfer of the prescription information from the EMR system to the PBM in a secure and efficient manner.

[0096] The PBM, in turn, may receive the prescription information and process itaccordingly. The PBM may be a third-party administrator of prescription drug programs for various health plans. They are primarily responsible for developing and maintaining the formulary, contracting with pharmacies, negotiating discounts and rebates with drug manufacturers, and processing and paying prescription drug claims.

[0097] In some cases, upon receipt of the prescription, the PBM may send a notificationto one or more parties involved in the medication prescription and dispensation process. The notification may be sent via various communication channels, such as email, text, e-fax, and phone. The notification may serve to inform the recipient about the status of the prescription, such as whether it has been received, processed, approved, or denied. The content of the notification may vary depending on the recipient. For instance, the notification sent to the patient may include information about the prescribed medication, while the notification sent to the pharmacy may include instructions for dispensing the medication.438949-000216

[0098] In some embodiments, the system may receive patient information from the PBMvia an API. The patient information may include, but is not limited to, the identity of the patient, the prescribing provider, the prescribed medication, the payor, and the pharmacy. The API, which is a set of rules and protocols for building and interacting with software applications, may facilitate the secure and efficient transfer of this patient information from the PBM to the system.

[0099] In some cases, the PBM may also send a patient identifier code along with thepatient information. This patient identifier code may be a specific code assigned to the patient, which may be used to uniquely identify the patient in the system. The patient identifier code may be either a code assigned by the PBM or a code assigned by the system. The patient identifier code may be used to recognize the patient and to query a database with the patient information.

[0100] In some embodiments, the system may include a processing module configuredto receive the patient identifier code from the PBM. Upon receipt of the patient identifier code, the processing module may use this code to query a database with the patient information. The database may include a variety of data related to the patient, such as the patient's genetic profile, medical history, and previous prescriptions. The processing module may use the patient identifier code to retrieve the relevant patient information from the database.

[0101] In some embodiments, the processing module may use the patient informationretrieved from the database to determine the genetic compatibility of the prescribed medication. This may involve comparing the patient's genetic information with a database of known gene-drug interactions. If the medication is determined to be genetically incompatible with the patient, the system may send a response to the PBM to halt adjudication of the medication. This response may be sent in real-time, allowing for immediate action to be taken to prevent the dispensation of a potentially harmful medication.

[0102] In some embodiments, the system may query a database with the patientinformation to determine a genetic compatibility of the prescribed medication. This process may involve the use of a genetic profile of the patient, which may be included in the patient information received from the PBM. The genetic profile of the patient may include various genetic markers, such as single nucleotide polymorphisms (SNPs), copy number variations (CNVs), and other genetic variations that may influence the patient's response to medications.438949-000216

[0103] In some cases, the genetic profile of the patient may be used to determine thegenetic compatibility of the prescribed medication. This may involve comparing the patient's genetic profile with information on gene-drug interactions stored in the database. Gene-drug interactions refer to the influence of genetic variations on the pharmacokinetics and pharmacodynamics of a drug. These interactions may affect the absorption, distribution, metabolism, and excretion of the drug, as well as its therapeutic and adverse effects.

[0104] The database may include comprehensive information on gene-drug interactions,which may be derived from various sources, such as scientific literature, clinical trials, and other relevant databases. The database may be regularly updated to incorporate the latest findings in the field of pharmacogenomics.

[0105] The process of determining the genetic compatibility of the prescribedmedication may be performed by a processing module in the system. The processing module may use algorithms, machine learning techniques, or other computational methods to analyze the patient's genetic profile and the information on gene-drug interactions. If the analysis reveals that the prescribed medication is genetically incompatible with the patient, the processing module may generate a response to halt the adjudication of the medication.

[0106] In some embodiments, the response generated by the processing module may besent to the PBM in real-time. This real-time communication may allow the PBM to immediately halt the adjudication of the medication, thereby preventing the dispensation of a potentially harmful medication to the patient. The real-time communication may be facilitated by an API, which may enable the secure and efficient transfer of the response from the system to the PBM.

[0107] In some cases, the system may also generate a list of approved replacement drugsthat are genetically compatible with the patient. This list may be based on the patient's genetic profile and the information on gene-drug interactions in the database. The list of approved replacement drugs may be included in the response sent to the PBM, providing an alternative solution for the patient's medication.

[0108] In some embodiments, the system may send a response to the PBM to haltadjudication of the medication if the medication is determined to be genetically incompatible. This response may be generated by the processing module after analyzing the patient's genetic profile and the information on gene-drug interactions. The response may include a reason for halting adjudication of the medication, which may be based on the determined gene-drug interaction. For instance, the response may indicate that the prescribed medication438949-000216 is likely to have reduced efficacy or increased toxicity due to a specific gene-drug interaction identified in the patient's genetic profile.

[0109] The response may be transmitted to the PBM via an API, which may facilitate thesecure and efficient transfer of the response from the system to the PBM. The API may enable real-time communication between the system and the PBM, allowing the PBM to immediately halt the adjudication of the medication upon receipt of the response. This real- time communication may be particularly beneficial in preventing the dispensation of a potentially harmful medication to the patient.

[0110] In some cases, the response sent to the PBM may also include a list of approvedreplacement drugs that are genetically compatible with the patient. This list may be generated by the processing module based on the patient's genetic profile and the information on gene- drug interactions in the database. The list of approved replacement drugs may provide alternative options for the patient's medication, which may be considered by the medical provider in prescribing a new medication for the patient. The inclusion of the list of approved replacement drugs in the response may further enhance the efficiency and accuracy of the medication prescription and dispensation process.

[0111] In some embodiments, the system may include a notification module configuredto send a notification to at least one of the patient, provider, pharmacy, payor, and PBM. The notification may be triggered when the system determines that the prescribed medication is genetically incompatible with the patient. The notification may serve to inform the recipient that the medication is not advisable and may provide a list of approved replacement drugs that are genetically compatible with the patient.

[0112] The notification module may be further configured to send the notification viavarious communication channels, such as email, text, e-fax, and phone. The choice of communication channel may depend on the preferences of the recipient, the urgency of the notification, and other relevant factors. For instance, in urgent cases, the notification module may send the notification via phone to ensure immediate attention. In less urgent cases, the notification module may send the notification via email, text, or e-fax, which may allow the recipient to review the notification at their convenience.

[0113] In some cases, the content of the notification may vary depending on therecipient. For instance, the notification sent to the patient may include information about the genetic incompatibility of the prescribed medication and the list of approved replacement drugs. The notification sent to the provider may include the same information, as well as438949-000216 additional details about the gene-drug interaction that led to the genetic incompatibility. The notification sent to the pharmacy may include instructions to halt the dispensation of the prescribed medication and to prepare one of the approved replacement drugs instead. The notification sent to the payor and the PBM may include information about the halt of adjudication of the medication and the approval of the replacement drugs.

[0114] In some embodiments, the list of approved replacement drugs provided in thenotification may be tailored to the recipient. For instance, the list provided to the patient may include all medications considered a replacement that works genetically for the patient. The list provided to the provider may be the same, but filtered by the prevailing formulary to ensure that the replacement drugs are covered by the patient's health plan. This tailored approach may enhance the efficiency and accuracy of the medication prescription and dispensation process, as well as the satisfaction of the involved parties.

[0115] In some embodiments, the notification sent by the notification module maycontain specific information tailored to the recipient. For instance, the notification may indicate that the prescribed medication is not advisable due to a determined genetic incompatibility. This information may be particularly useful for the patient and the provider, as it may alert them to the potential risks associated with the prescribed medication.

[0116] In some cases, the notification may also include a reason for the medication beingnot advisable. This reason may be based on the gene-drug interaction identified in the patient's genetic profile. For instance, the notification may state that the prescribed medication is likely to have reduced efficacy or increased toxicity due to a specific gene-drug interaction. This detailed information may provide the recipient with a better understanding of the genetic incompatibility and its implications.

[0117] In addition to the indication and the reason, the notification may also provide alist of approved replacement drugs. These replacement drugs may be selected based on the genetic profile of the patient and the information on gene-drug interactions in the database. The list of approved replacement drugs may include medications that are genetically compatible with the patient and are likely to have a more favorable therapeutic effect.

[0118] In some embodiments, the list of approved replacement drugs may be tailored tothe recipient. For instance, the list provided to the patient may include all medications considered a replacement that works genetically for the patient. On the other hand, the list provided to the provider may be the same, but filtered by the prevailing formulary. This may ensure that the replacement drugs are covered by the patient's health plan and are therefore438949-000216 more likely to be affordable for the patient. This tailored approach may enhance the efficiency and accuracy of the medication prescription and dispensation process, as well as the satisfaction of the involved parties.

[0119] In some embodiments, the system may generate a list of approved replacementdrugs that are genetically compatible with the patient. This list may be generated by the processing module based on the patient's genetic profile and the information on gene-drug interactions in the database. The list of approved replacement drugs may provide alternative options for the patient's medication, which may be considered by the medical provider in prescribing a new medication for the patient. In some embodiments, the system may further check to ensure that the replacement drugs would not cause any negative drug-drug interactions based on any medications currently taken by the patient using the techniques described above.

[0120] In some cases, the system may provide the list of approved replacement drugs ina tailored manner. For instance, the system may send a list of all medications considered a replacement that works genetically for the patient. This list may include all medications that are known to be genetically compatible with the patient based on the patient's genetic profile and the information on gene-drug interactions in the database. This comprehensive list may provide the patient with a wide range of options for their medication.

[0121] In other cases, the system may send the same list of replacement drugs for themedical provider to choose from, but filtered by the prevailing formulary. The prevailing formulary refers to a list of medications that are covered by the patient's health plan. By filtering the list of approved replacement drugs by the prevailing formulary, the system may ensure that the replacement drugs are affordable for the patient. This may enhance the efficiency and accuracy of the medication prescription and dispensation process, as well as the satisfaction of the patient and the provider.

[0122] In some embodiments, the list of approved replacement drugs may be included inthe notification sent by the notification module. The notification may be sent to one or more of the patient, provider, pharmacy, payor, and PBM. The inclusion of the list of approved replacement drugs in the notification may provide the recipient with immediate access to alternative options for the patient's medication. This may facilitate the quick and efficient resolution of the issue of genetic incompatibility, thereby enhancing the overall efficiency of the medication prescription and dispensation process.438949-000216

[0123] In some embodiments, the system 100 described above can further be utilized toautomatically provide notifications to PBMs 120 and other parties when a problematic drug interaction identified. As described above in connection with FIG.1, the computer system 102 can be communicably coupled to healthcare providers 114, PBMs 120, pharmacies 122, and other entities. In one embodiment, the computer system 102 can be configured to transmit a notification to a PBM 120 and / or pharmacy 122 when a problematic drug interaction is identified (e.g., in order to halt the fulfillment of a prescription for a problematic drug). In one embodiment, the computer system 102 can further be configured to suggest one or more alternative drugs to the PBM 120 and / or pharmacy 122.

[0124] One embodiment of a process 400 for automatically notifying entities ofidentified problematic drug-drug and / or gene-drug interactions is illustrated in FIG.5. In this process 400, the healthcare provider 114 (e.g., doctor) submits 402 a prescription for a drug associated with a patient 112. In some instances, the healthcare provider 114 can enter the prescription via an EMR that is received by the PBM 120. In other instances, the healthcare provider 114 can submit a paper prescription that is transmitted to a pharmacy 122, which then submits the prescription to the PBM 120. In this embodiment, the PBM 120 is communicably coupled to the drug interaction analysis computer system 102 via the API, as described above. Accordingly, the computer system 102 receives the information related to the prescription, including the prescribed drug and the patient data (e.g., from the EMR associated with the patient), and determines whether there would be a problematic drug-drug and / or gene-drug interaction associated with the prescribed drug using the techniques described above.

[0125] Once the drug-drug and / or gene-drug analysis has been performed, the computersystem 102 transmits a notification 406 indicating whether any problematic interactions have been identified (i.e., whether the prescribed drug is approved or denied for the patient 112) to one or more relevant parties (e.g., the patient 112, healthcare provider 116, PBM 120, and / or the pharmacy 122). If the prescribed drug is approved, no further action is required by the system 100 and the prescription can be fulfilled. If the prescribed drug is denied (i.e., a problematic drug-drug or gene-drug interaction was identified), the provided notification 406 can include a recommendation 408 for one or more alternative drugs that would be suitable for the patient 112 using the techniques described above. Accordingly, the alternative drug(s) can be transmitted to the PBM 120 and the prescription for the patient 112 can be switched to an alternative drug. In one embodiment, the alternative drug can be selected by the computer438949-000216 system 102. In another embodiment, the alternative drug can be selected from a provided list of alternative drugs included in the notification 406 by the healthcare provider 114, PBM 120, or pharmacy 122. Further, the patient 112 can receive a notification from the computer system 102 that his or her prescription has been modified to the alternative drug. In one embodiment, the recommended alternative drugs can be sorted by prevailing formulary. Once the alternative drug has been selected, the PBM 120 can then process the prescription as normal for fulfillment by the pharmacy 122.

[0126] Accordingly, the process 400 described herein allows the drug interactionanalysis computer system 102 to automatically identify and correct problematic prescriptions, with minimal to no further action required by the patient 112. Therefore, the computer system 102 can ensure that patients 112 are not being provided with safe, effective drugs based on the full suite of drug and genetic information available for the patient 112.

[0127] The disclosed methods and systems may offer several benefits. For instance, theymay improve the efficiency of drug prescription by reducing the trial-and-error approach often used in finding the right drug and dosage for a patient. This is achieved by integrating pharmacogenomics into the process of medication prescription and dispensation, which involves complex data analysis and real-time communication among various parties. The disclosed methods and systems may therefore provide a solution to technical problems in the field of healthcare technology, such as the efficient and accurate prescription of medication based on a patient's genetic profile.

[0128] While various illustrative embodiments incorporating the principles of the presentteachings have been disclosed, the present teachings are not limited to the disclosed embodiments. Instead, this application is intended to cover any variations, uses, or adaptations of the present teachings and use its general principles. Further, this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which these teachings pertain.

[0129] In the above detailed description, reference is made to the accompanyingdrawings, which form a part hereof. In the drawings, similar symbols typically identify similar components, unless context dictates otherwise. The illustrative embodiments described in the present disclosure are not meant to be limiting. Other embodiments may be used, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that various features of the present disclosure, as generally described herein, and illustrated in the Figures, can be438949-000216 arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.

[0130] The present disclosure is not to be limited in terms of the particular embodimentsdescribed in this application, which are intended as illustrations of various features. Many modifications and variations can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. It is to be understood that this disclosure is not limited to particular methods, reagents, compounds, compositions or biological systems, which can, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

[0131] With respect to the use of substantially any plural and / or singular terms herein,those having skill in the art can translate from the plural to the singular and / or from the singular to the plural as is appropriate to the context and / or application. The various singular / plural permutations may be expressly set forth herein for sake of clarity.

[0132] It will be understood by those within the art that, in general, terms used herein aregenerally intended as “open” terms (for example, the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” et cetera). While various compositions, methods, and devices are described in terms of “comprising” various components or steps (interpreted as meaning “including, but not limited to”), the compositions, methods, and devices can also “consist essentially of” or “consist of” the various components and steps, and such terminology should be interpreted as defining essentially closed-member groups.

[0133] In addition, even if a specific number is explicitly recited, those skilled in the artwill recognize that such recitation should be interpreted to mean at least the recited number (for example, the bare recitation of "two recitations," without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, et cetera” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C438949-000216 together, B and C together, and / or A, B, and C together, et cetera). In those instances where a convention analogous to “at least one of A, B, or C, et cetera” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, et cetera). It will be further understood by those within the art that virtually any disjunctive word and / or phrase presenting two or more alternative terms, whether in the description, sample embodiments, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or “B” or “A and B.”

[0134] In addition, where features of the disclosure are described in terms of Markushgroups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.

[0135] As will be understood by one skilled in the art, for any and all purposes, such asin terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, et cetera. As a non-limiting example, each range discussed herein can be readily broken down into a lower third, middle third and upper third, et cetera. As will also be understood by one skilled in the art, all language such as “up to,” “at least,” and the like include the number recited and refer to ranges that can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1–3 cells refers to groups having 1, 2, or 3 cells. Similarly, a group having 1–5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so forth.

[0136] The term “about,” as used herein, refers to variations in a numerical quantity thatcan occur, for example, through measuring or handling procedures in the real world; through inadvertent error in these procedures; through differences in the manufacture, source, or purity of compositions or reagents; and the like. Typically, the term “about” as used herein means greater or lesser than the value or range of values stated by 1 / 10 of the stated values, e.g., ±10%. The term “about” also refers to variations that would be recognized by one skilled in the art as being equivalent so long as such variations do not encompass known438949-000216 values practiced by the prior art. Each value or range of values preceded by the term “about” is also intended to encompass the embodiment of the stated absolute value or range of values. Whether or not modified by the term “about,” quantitative values recited in the present disclosure include equivalents to the recited values, e.g., variations in the numerical quantity of such values that can occur, but would be recognized to be equivalents by a person skilled in the art.

[0137] Various of the above-disclosed and other features and functions, or alternativesthereof, may be combined into many other different systems or applications. Various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art, each of which is also intended to be encompassed by the disclosed embodiments.

[0138] The functions and process steps herein may be performed automatically orwholly or partially in response to user command. An activity (including a step) performed automatically is performed in response to one or more executable instructions or device operation without user direct initiation of the activity.

Claims

438949-000216 CLAIMS 1. A method for managing a prescription for a user, the method comprising: receiving genetic test results for the user and a drug taken by the user, wherein the drug is in a drug category; (a) determining whether the drug is present in an internal database, wherein theinternal database comprises a list of genes are associated with a plurality of drugs based on clinical relevance of the gene to the actions of the plurality of drugs; (i) in response to determining that the drug is not present in the internal database: searching an external database for a major metabolite and an enzyme responsible for forming the major metabolite, wherein the major metabolite and the enzyme are associated with the drug, and determining whether there is a mutation in a gene associated with the enzyme that pharmacokinetically impacts the drug based on the genetic tests results; or, (ii) in response to determining that the drug is present in the internal database: determining a clinically relevant enzyme associated with the drug from the internal database, and determining whether there is a mutation in the clinically relevant gene based on the genetic tests results; (b) determining whether there is a problematic gene-drug interaction associated withthe drug; and (c) in response to determining that there is the problematic gene-drug interaction:identifying one or more alternative drugs from the drug category, notifying a pharmacy benefit manager to halt the prescription for the drug associated with the user, and providing the one or more alternative drugs to the pharmacy benefit manager for fulfillment for the user.

2. The method of claim 1, wherein the one or more alternative drugs are arranged by prevailing formulary.

3. A method for managing a prescription associated with a user, the method comprising:438949-000216 receiving genetic test results and a drug for the user; determining a primary metabolite for the drug and a pathway for the primary metabolite; determining a category for the drug; determining a primary enzyme pharmacokinetically associated with the drug based at least in part on the primary metabolite and the pathway; determining, based on the genetic test results, whether the user has a genetic mutation associated with the determined primary enzyme that would pharmacokinetically impact the drug; in response to a determination that the user has the genetic mutation, determining whether the genetic mutation has a threshold pharmacokinetic impact on the primary enzyme; and in response to a determination that the genetic mutation has the threshold impact pharmacokinetic impact: determining one or more alternative drugs to the drug based on the determined category for the drug; notifying a pharmacy benefit manager to halt the prescription for the drug associated with the user, and providing the one or more alternative drugs to the pharmacy benefit manager for fulfillment for the user.

4. The method of claim 3, wherein the one or more alternative drugs are arranged by prevailing formulary.

5. A system for managing a prescription associated with a user, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the system to: receive genetic test results for the user and a drug taken by the user, wherein the drug is in a drug category, determine whether the drug is present in an internal database, wherein the internal database comprises a list of genes are associated with a plurality of drugs based on clinical relevance of the gene to the actions of the plurality of drugs;438949-000216 in response to determining that the drug is not present in the internal database: search an external database for a major metabolite and an enzyme responsible for forming the major metabolite, wherein the major metabolite and the enzyme are associated with the drug, and determine whether there is a mutation in a gene associated with the enzyme that pharmacokinetically impacts the drug based on the genetic tests results, in response to determining that the drug is present in the internal database: determine a clinically relevant enzyme associated with the drug from the internal database, and determine whether there is a mutation in the clinically relevant gene based on the genetic tests results; determine whether there is a problematic gene-drug interaction associated with the drug; and in response to determining that there is the problematic gene-drug interaction: identify one or more alternative drugs from the drug category, notifying a pharmacy benefit manager to halt a prescription for the drug associated with the user, and providing the alternative drug to the pharmacy benefit manager for fulfillment for the user.

6. The system of claim 5, wherein the one or more alternative drugs are sorted by prevailing formulary.

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