Genetic testing report generation method and system based on medication risk assessment

Abstract

The present application relates to the field of bioinformatics, and provides a method and system for generating a gene test report based on medication risk assessment, the method comprising: obtaining genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type; obtaining variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm; obtaining variant gene-risk drug component association information in a biomedical database, and generating a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information; for each disease type, obtaining medical medication information corresponding to the disease type in a medical medication database; generating a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type. This method improves the effectiveness and accuracy of the medication risk assessment report.

Description

Technical Field

[0001] The present application relates to the field of bioinformatics, and in particular to a method and system for generating a genetic testing report based on medication risk assessment. Background Art

[0002] In recent years, with the rapid development of gene sequencing technology, the application of gene testing in the medical field has become increasingly widespread. Gene testing can reveal an individual's genetic information, help predict disease risks, and guide personalized treatment. Especially in the treatment of cancer, cardiovascular disease and other complex diseases, gene testing provides an important basis for personalized medicine.

[0003] In clinical practice, doctors usually need to develop personalized treatment plans based on the patient's genetic information and disease type. However, due to the complexity of genetic information and the diversity of drug-gene interactions, how to accurately generate a genetic test report to assess the patient's risk of specific drug treatment has become an important challenge. Summary of the invention

[0004] The present application provides a method and system for generating a genetic testing report based on medication risk assessment to solve the problems raised by the above-mentioned background technology.

[0005] In a first aspect, the present application provides a method for generating a genetic testing report based on medication risk assessment, comprising:

[0006] Obtaining genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type;

[0007] Obtaining variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm;

[0008] Acquire variant gene-risk drug component association information in a biomedical database, and generate a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information;

[0009] For each of the disease types, obtaining medical medication information corresponding to the disease type from a medical medication database;

[0010] Generate a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type;

[0011] The medication risk assessment report is sent to the subject's attending physician.

[0012] In a possible implementation, the variant gene annotation information includes multiple variant gene annotations, and generating a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information includes:

[0013] For each of the variant gene annotations, determining the initial risk drug component information corresponding to the variant gene annotation based on the variant gene-risk drug component association information;

[0014] Combining the initial risk drug component information to obtain intermediate risk drug component information, and performing deduplication processing on the intermediate risk drug component information to obtain target risk drug component information;

[0015] Arrange the variant gene annotations in order to obtain a variant gene annotation sequence, and arrange the risk drug components in the target risk drug component information in order to obtain a risk drug component sequence, and place the risk drug component sequence below the variant gene annotation sequence;

[0016] For each variant gene annotation in the variant gene annotation sequence, the relevant risk drug component corresponding to the variant gene annotation is determined in the risk drug component sequence based on the initial drug component information corresponding to the variant gene annotation, and the variant gene annotation and the relevant risk drug component are connected with a straight line to obtain the variant gene-risk drug component association network.

[0017] In a possible implementation, the generating of the subject's medication risk assessment report based on the variant gene-risk drug component association network and the initial medical medication information corresponding to each disease type includes:

[0018] Performing risk scoring on each of the risky drug components based on the variant gene-risky drug component association network to obtain a first risk score corresponding to each of the risky drug components;

[0019] Combining the initial medical medication information to obtain intermediate medical medication information, and performing deduplication processing on the intermediate medical medication information to obtain target medical medication information;

[0020] A medication risk assessment report for the subject is generated based on the target medical medication information and the first risk scores corresponding to each of the risky drug components.

[0021] In a possible implementation, performing risk scoring on each of the risky drug components based on the variant gene-risky drug component association network to obtain a first risk score corresponding to each of the risky drug components includes:

[0022] For each of the risky drug components, the number of straight lines corresponding to the risky drug component in the variant gene-risky drug component association network is determined as a first score corresponding to the risky drug component.

[0023] In a possible implementation, the target medical medication information includes a plurality of drugs, and generating the medication risk assessment report of the subject based on the target medical medication information and the first risk score corresponding to each of the risky drug components includes:

[0024] For each of the drugs, obtain the component information of the drug, and generate a second risk score corresponding to the drug based on the component information and the first risk score corresponding to each of the risky drug components;

[0025] Generate the medication risk assessment report based on the second risk score corresponding to each of the drugs; the medication risk assessment report includes a mapping relationship between each of the drugs and its corresponding second risk score;

[0026] The step of generating a second risk score corresponding to the drug based on the component information and the first risk score corresponding to each of the risky drug components includes:

[0027] Determining whether the composition information includes any of the risky drug ingredients;

[0028] If not, determining that the second risk score corresponding to the drug is 0;

[0029] If so, the first risk scores corresponding to the risky drug components included in the component information are added together to obtain a second risk score corresponding to the drug.

[0030] In a possible implementation, the method further includes:

[0031] Obtaining clinical medication information of the subject;

[0032] Determine the abnormal medication history information of the subject based on the clinical medication information; the abnormal medication history information includes a plurality of tolerant drugs;

[0033] For each of the tolerant drugs, determining whether the medication risk assessment report includes a mapping relationship corresponding to the tolerant drug, and if the medication risk assessment report includes the mapping relationship corresponding to the tolerant drug, deleting the mapping relationship corresponding to the tolerant drug in the medication risk assessment report;

[0034] Determine each tolerant drug in the historical medication abnormality information as a prohibited medication for the subject, obtain the prohibited medication information for the subject, and optimize the medication risk assessment report after deletion based on the prohibited medication information.

[0035] In a possible implementation, sending the medication risk assessment report to the subject's attending physician includes:

[0036] Obtaining the work code of the attending physician; the work code is a digital sequence;

[0037] For each number in the digital sequence, a plurality of data packets are generated based on the number, and each of the data packets is arranged in sequence to obtain a data packet unit corresponding to the number; wherein the number of the data packets is consistent with the number, and the data information of each of the data packets is different from each other;

[0038] Arrange the data packet units in sequence based on the order of the numbers corresponding to the data packet units in the working code to obtain an initial data packet sequence;

[0039] Encoding the medication risk assessment report based on a preset coding rule to obtain a coding sequence corresponding to the medication risk assessment report;

[0040] The coding sequence is segmented based on the number of the data packet units to obtain a plurality of coding subsequences; the number of the coding subsequences is the number of the data packet units minus 1;

[0041] Based on a preset packaging method, each of the coding subsequences is packaged and processed to obtain a target data packet corresponding to each of the coding subsequences;

[0042] Based on the corresponding order of the coding subsequences corresponding to the target data packets in the coding sequence, the target data packets are sequentially inserted into the gaps between the data packet units of the initial data packet sequence to obtain a target data packet sequence, and the target data packet sequence is sent to the attending physician.

[0043] In a second aspect, the present application provides a gene detection report generation system based on medication risk assessment, comprising:

[0044] A first acquisition module is used to acquire genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type;

[0045] A second acquisition module is used to acquire variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm;

[0046] A first generation module is used to obtain variant gene-risk drug component association information in a biomedical database, and generate a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information;

[0047] A third acquisition module is used to acquire medical medication information corresponding to each disease type from a medical medication database;

[0048] A second generating module is used to generate a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type;

[0049] The sending module is used to send the medication risk assessment report to the subject's attending physician.

[0050] The present application provides a method and system for generating a gene test report based on medication risk assessment, wherein the method includes: obtaining genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type; obtaining variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm; obtaining variant gene-risk drug component association information in a biomedical database, and generating a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information; for each of the disease types, obtaining the medical medication information corresponding to the disease type in a medical medication database; generating a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type; and sending the medication risk assessment report to the subject's attending physician. The method, by combining the subject's genetic information and disease diagnosis information, can generate a personalized medication risk assessment report, improve the effectiveness and accuracy of the medication risk assessment report, provide scientific and comprehensive data support for doctors, and help doctors choose the most suitable drug treatment plan for patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0052] Figure 1 A schematic diagram of a process for generating a genetic testing report based on medication risk assessment provided in an embodiment of the present application;

[0053] Figure 2 A schematic block diagram of the structure of a gene detection report generation system based on medication risk assessment provided in an embodiment of the present application;

[0054] Figure 3 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change based on actual conditions.

[0057] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0058] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0059] In recent years, with the rapid development of gene sequencing technology, the application of gene testing in the medical field has become increasingly widespread. Gene testing can reveal an individual's genetic information, help predict disease risks, and guide personalized treatment. Especially in the treatment of cancer, cardiovascular disease and other complex diseases, gene testing provides an important basis for personalized medicine.

[0060] In clinical practice, doctors usually need to develop personalized treatment plans based on the patient's genetic information and disease type. However, due to the complexity of genetic information and the diversity of drug-gene interactions, how to accurately and quickly generate a genetic test report to assess the patient's risk of specific drug treatment has become an important challenge. To this end, the present application provides a method and system for generating a genetic test report based on medication risk assessment to solve the above problems.

[0061] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0062] See also Figure 1 , Figure 1 A schematic diagram of a process for generating a genetic testing report based on medication risk assessment provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the method for generating a genetic testing report based on medication risk assessment provided in an embodiment of the present application includes steps S1 to S6.

[0063] Step S1, obtaining genetic information and disease diagnosis information of a subject; wherein the disease diagnosis information includes at least one disease type.

[0064] Specifically, a high-throughput gene sequencing (NGS) method is used to obtain the genetic information, which is whole genome sequencing data. The disease diagnosis information is input into the system by the subject's attending physician through a terminal device.

[0065] Step S2: obtaining variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm.

[0066] Step S3, obtaining variant gene-risk drug component association information in a biomedical database, and generating a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information.

[0067] Among them, the biomedical databases include but are not limited to ClinVar, PharmGKB, and dbSNP, and the variant gene-risk drug component association information includes a mapping relationship between each variant gene annotation and its corresponding risk drug component information, and the risk drug component information corresponding to each variant gene annotation includes at least one risk drug component.

[0068] The variant gene annotation information includes multiple variant gene annotations, including but not limited to a single nucleotide variation, an insertion / deletion variation of a gene fragment, and a structural variation of a gene fragment. The generating a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information includes:

[0069] For each of the variant gene annotations, determine the initial risk drug component information corresponding to the variant gene annotation based on the variant gene-risk drug component association information; specifically, traverse the variant gene-risk drug component association information to determine the initial risk drug component information corresponding to the variant gene annotation;

[0070] Combining each of the initial risk drug component information to obtain intermediate risk drug component information, and performing deduplication processing on the intermediate risk drug component information to obtain target risk drug component information; specifically, firstly, combining each of the initial risk drug component information to obtain intermediate risk drug component information, and then deleting the risk drug components that appear repeatedly in the intermediate risk drug component information, so that each risk drug component appears only once in the target risk drug component information;

[0071] Arrange the variant gene annotations in order to obtain a variant gene annotation sequence, and arrange the risk drug components in the target risk drug component information in order to obtain a risk drug component sequence, and place the risk drug component sequence below the variant gene annotation sequence;

[0072] For each variant gene annotation in the variant gene annotation sequence, the relevant risk drug component corresponding to the variant gene annotation is determined in the risk drug component sequence based on the initial drug component information corresponding to the variant gene annotation, and the variant gene annotation and the relevant risk drug component are connected with a straight line to obtain the variant gene-risk drug component association network. It can be understood that the relevant risk drug component includes at least one, and the information of the composition of each of the relevant risk drug components corresponding to the variant gene annotation is consistent with the initial drug component information corresponding to the variant gene annotation.

[0073] It can be understood that step S3 can systematically integrate the complex association between the genetic information of the subject and the drug components by constructing the variant gene-risk drug component association network, and provide a comprehensive risk assessment framework. The network not only considers the impact of single gene variants, but also integrates the joint effects of multiple variant gene annotations, thereby providing a more comprehensive perspective for drug risk assessment.

[0074] Step S4: for each of the disease types, obtaining medical medication information corresponding to the disease type from a medical medication database;

[0075] Specifically, for each of the disease types, the medical medication database is traversed to obtain the medical medication information corresponding to the disease type.

[0076] Step S5, generating a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type;

[0077] Specifically, the generating of the subject's medication risk assessment report based on the variant gene-risk drug component association network and the initial medical medication information corresponding to each disease type includes:

[0078] Based on the variant gene-risk drug component association network, each of the risk drug components is risk-scored to obtain a first risk score corresponding to each of the risk drug components; specifically, for each of the risk drug components, the number of straight lines corresponding to the risk drug component in the variant gene-risk drug component association network is determined as the first score corresponding to the risk drug component. For example, if the number of straight lines corresponding to the risk drug component in the variant gene-risk drug component association network is 18, then the first risk score corresponding to the risk drug component is 18;

[0079] Combining each of the initial medical medication information to obtain intermediate medical medication information, and performing deduplication processing on the intermediate medical medication information to obtain target medical medication information; specifically, firstly, combining each of the initial medical medication information to obtain intermediate medical medication information, and then deleting drugs that appear repeatedly in the intermediate medical medication information, so that each drug appears only once in the target medical medication information;

[0080] A medication risk assessment report for the subject is generated based on the target medical medication information and the first risk scores corresponding to the risky drug components.

[0081] Furthermore, the target medical medication information includes a plurality of drugs, and the generating of the subject's medication risk assessment report based on the target medical medication information and the first risk score corresponding to each of the risky drug components includes:

[0082] For each of the drugs, obtain the component information of the drug, and generate a second risk score corresponding to the drug based on the component information and the first risk score corresponding to each of the risky drug components;

[0083] Generate the medication risk assessment report based on the second risk score corresponding to each of the drugs; the medication risk assessment report includes a mapping relationship between each of the drugs and its corresponding second risk score;

[0084] The step of generating a second risk score corresponding to the drug based on the component information and the first risk score corresponding to each of the risky drug components includes:

[0085] Determining whether the composition information includes any of the risky drug ingredients;

[0086] If not, determining that the second risk score corresponding to the drug is 0;

[0087] If so, the first risk scores corresponding to the risky drug components included in the component information are added together to obtain a second risk score corresponding to the drug.

[0088] Step 5 generates a second risk score corresponding to the drug based on the component information and the first risk scores corresponding to each of the risky drug components, thereby achieving specific quantification of the potential risks that exist when an individual uses a specific drug, which helps to provide more accurate personalized medication recommendations to the attending physician.

[0089] Step S6: Send the medication risk assessment report to the subject's attending physician.

[0090] Specifically, the generating of the subject's medication risk assessment report based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type includes:

[0091] Obtaining the work code of the attending physician; the work code is a digital sequence;

[0092] For each number in the digital sequence, a plurality of data packets are generated based on the number, and each of the data packets are arranged in sequence to obtain a data packet unit corresponding to the number; wherein the number of the data packets is consistent with the number, and the data information of each of the data packets is different from each other; for example, if the number is 5, the number of the data packets is 5; it should be noted that when the data packets are arranged, they are arranged randomly;

[0093] Arrange the data packet units in sequence based on the order of the numbers corresponding to the data packet units in the working code to obtain an initial data packet sequence;

[0094] Encoding the medication risk assessment report based on a preset coding rule to obtain a coding sequence corresponding to the medication risk assessment report;

[0095] The coding sequence is segmented based on the number of the data packet units to obtain a plurality of coding subsequences; the number of the coding subsequences is the number of the data packet units minus 1;

[0096] Based on a preset packaging method, each of the coding subsequences is packaged and processed to obtain a target data packet corresponding to each of the coding subsequences;

[0097] Based on the corresponding order of the coding subsequences corresponding to the target data packets in the coding sequence, the target data packets are sequentially inserted into the gaps between the data packet units of the initial data packet sequence to obtain a target data packet sequence, and the target data packet sequence is sent to the attending physician. It can be understood that in the target data packet sequence, there is only one target data packet between two adjacent data packet units.

[0098] It can be understood that step S6, on the one hand, encodes the medication risk assessment report based on a preset encoding rule to obtain a coding sequence corresponding to the medication risk assessment report, and divides the coding sequence based on the number of data packet units to obtain multiple coding subsequences, and packages each of the coding subsequences based on a preset packaging method to obtain a target data packet corresponding to each of the coding subsequences, and then, based on the order of the coding subsequences corresponding to each of the target data packets in the coding sequence, insert each of the target data packets into the gaps between each of the data packet units of the initial data packet sequence in sequence to obtain the target data packet. The packet sequence can effectively prevent the data packet from being tampered with or intercepted during the transmission process, thereby improving the security and confidentiality of data transmission. On the other hand, by obtaining the working code of the attending physician; the working code is a digital sequence, and for each number in the digital sequence, multiple data packets are generated based on the numbers, and each of the data packets is arranged in sequence to obtain a data packet unit corresponding to the number, and then, based on the order of the numbers corresponding to each of the data packet units in the working code, each of the data packet units is arranged in sequence to obtain an initial data packet sequence, which can generate a personalized transmission sequence according to the doctor's working code, further improving the security and confidentiality of data transmission.

[0099] The method provided in this embodiment can generate a personalized medication risk assessment report by combining the genetic information and disease diagnosis information of the subject, improve the effectiveness and accuracy of the medication risk assessment report, provide scientific and comprehensive data support for doctors, and help doctors choose the drug treatment plan that best suits the patient.

[0100] In some embodiments, the method further comprises:

[0101] Obtaining clinical medication information of the subject;

[0102] Determining the abnormal medication history information of the subject based on the clinical medication information; the abnormal medication history information includes a plurality of tolerant drugs;

[0103] For each of the tolerant drugs, determining whether the medication risk assessment report includes a mapping relationship corresponding to the tolerant drug, and if the medication risk assessment report includes the mapping relationship corresponding to the tolerant drug, deleting the mapping relationship corresponding to the tolerant drug in the medication risk assessment report;

[0104] Determine each tolerant drug in the historical medication abnormality information as a prohibited medication for the subject, obtain the prohibited medication information for the subject, and optimize the deleted medication risk assessment report based on the prohibited medication information. Specifically, fill the prohibited medication information in the medication risk assessment report.

[0105] The method provided in this embodiment optimizes the medication risk assessment report through the clinical medication information of the subject, which helps to further improve the accuracy of personalized medicine.

[0106] See also Figure 2 , Figure 2 A schematic block diagram of the structure of a gene detection report generation system 100 based on medication risk assessment provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, a gene test report generation system 100 based on medication risk assessment includes:

[0107] The first acquisition module 110 is used to acquire genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type.

[0108] The second acquisition module 120 is used to acquire variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm.

[0109] The first generation module 130 is used to obtain variant gene-risk drug component association information in a biomedical database, and generate a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information.

[0110] The third acquisition module 140 is used to acquire medical medication information corresponding to each disease type from the medical medication database.

[0111] The second generating module 150 is used to generate a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type.

[0112] The sending module 160 is used to send the medication risk assessment report to the subject's attending physician.

[0113] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and conciseness of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned embodiment of the genetic testing report generation method based on medication risk assessment, and will not be repeated here.

[0114] The terminal device 200 provided in the above embodiment can be implemented in the form of a computer program. The computer program can be Figure 3 The system is run on the terminal device 200 shown.

[0115] See also Figure 3 , Figure 3 The present invention provides a schematic block diagram of the structure of a terminal device 200 according to an embodiment of the present application. The terminal device 200 includes a processor 201 and a memory 202. The processor 201 and the memory 202 are connected via a device bus 203, wherein the memory 202 may include a non-volatile storage medium and an internal memory.

[0116] The non-volatile storage medium can store a computer program. The computer program includes program instructions, and when the program instructions are executed by the processor 201, the processor 201 can execute any of the above-mentioned methods for generating a genetic test report based on medication risk assessment.

[0117] The processor 201 is used to provide computing and control capabilities to support the operation of the entire terminal device 200.

[0118] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor 201, the processor 201 can execute any of the above-mentioned methods for generating a genetic test report based on medication risk assessment.

[0119] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the terminal device 200 involved in the scheme of the present application. The specific terminal device 200 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0120] It should be understood that the processor 201 may be a central processing unit (CPU), and the processor 201 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0121] In some embodiments, the processor 201 is used to run a computer program stored in the memory to implement the following steps:

[0122] Obtaining genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type;

[0123] Obtaining variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm;

[0124] Acquire variant gene-risk drug component association information in a biomedical database, and generate a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information;

[0125] For each of the disease types, obtaining medical medication information corresponding to the disease type from a medical medication database;

[0126] Generate a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type;

[0127] The medication risk assessment report is sent to the subject's attending physician.

[0128] It should be noted that technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working process of the terminal device 200 described above can refer to the corresponding process of the aforementioned genetic testing report generation method based on medication risk assessment, and will not be repeated here.

[0129] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by one or more processors, the one or more processors implement a method for generating a genetic testing report based on medication risk assessment as provided in an embodiment of the present application.

[0130] The computer-readable storage medium may be an internal storage unit of the terminal device 200 in the aforementioned embodiment, such as a hard disk or memory of the terminal device 200. The computer-readable storage medium may also be an external storage device of the terminal device 200, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped with the terminal device 200.

[0131] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for generating a genetic testing report based on medication risk assessment, It is characterized in that include: Obtaining genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type; Obtaining variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm; Acquire variant gene-risk drug component association information in a biomedical database, and generate a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information; For each of the disease types, obtaining medical medication information corresponding to the disease type from a medical medication database; Generate a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type; Sending the medication risk assessment report to the subject's attending physician; The variant gene annotation information includes multiple variant gene annotations, and generating a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information includes: For each of the variant gene annotations, determining the initial risk drug component information corresponding to the variant gene annotation based on the variant gene-risk drug component association information; Combining the initial risk drug component information to obtain intermediate risk drug component information, and performing deduplication processing on the intermediate risk drug component information to obtain target risk drug component information; Arrange the variant gene annotations in order to obtain a variant gene annotation sequence, and arrange the risk drug components in the target risk drug component information in order to obtain a risk drug component sequence, and place the risk drug component sequence below the variant gene annotation sequence; For each variant gene annotation in the variant gene annotation sequence, determining the relevant risk drug component corresponding to the variant gene annotation in the risk drug component sequence based on the initial drug component information corresponding to the variant gene annotation, and connecting the variant gene annotation and the relevant risk drug component with a straight line to obtain the variant gene-risk drug component association network; The step of sending the medication risk assessment report to the subject's attending physician includes: Obtaining the work code of the attending physician; the work code is a digital sequence; For each number in the digital sequence, a plurality of data packets are generated based on the number, and each of the data packets is randomly arranged to obtain a data packet unit corresponding to the number; wherein the number of the data packets is consistent with the number, and the data information of each of the data packets is different from each other; Arrange the data packet units in sequence based on the order of the numbers corresponding to the data packet units in the working code to obtain an initial data packet sequence; Encoding the medication risk assessment report based on a preset coding rule to obtain a coding sequence corresponding to the medication risk assessment report; The coding sequence is segmented based on the number of the data packet units to obtain a plurality of coding subsequences; the number of the coding subsequences is the number of the data packet units minus 1; Based on a preset packaging method, each of the coding subsequences is packaged and processed to obtain a target data packet corresponding to each of the coding subsequences; Based on the corresponding order of the coding subsequences corresponding to the target data packets in the coding sequence, the target data packets are sequentially inserted into the gaps between the data packet units of the initial data packet sequence to obtain a target data packet sequence, and the target data packet sequence is sent to the attending physician.

2. The method for generating a gene testing report based on medication risk assessment according to claim 1, It is characterized in that The generating of the subject's medication risk assessment report based on the variant gene-risk drug component association network and the initial medical medication information corresponding to each disease type includes: Performing risk scoring on each of the risky drug components based on the variant gene-risky drug component association network to obtain a first risk score corresponding to each of the risky drug components; Combining the initial medical medication information to obtain intermediate medical medication information, and performing deduplication processing on the intermediate medical medication information to obtain target medical medication information; A medication risk assessment report for the subject is generated based on the target medical medication information and the first risk scores corresponding to each of the risky drug components.

3. The method for generating a gene testing report based on medication risk assessment according to claim 2, It is characterized in that The step of performing risk scoring on each of the risky drug components based on the variant gene-risky drug component association network to obtain a first risk score corresponding to each of the risky drug components includes: For each of the risky drug components, the number of straight lines corresponding to the risky drug component in the variant gene-risky drug component association network is determined as a first score corresponding to the risky drug component.

4. The method for generating a gene testing report based on medication risk assessment according to claim 2, It is characterized in that The target medical medication information includes a plurality of drugs, and generating the medication risk assessment report of the subject based on the target medical medication information and the first risk score corresponding to each of the risky drug components includes: For each of the drugs, obtain the component information of the drug, and generate a second risk score corresponding to the drug based on the component information and the first risk score corresponding to each of the risky drug components; Generate the medication risk assessment report based on the second risk score corresponding to each of the drugs; the medication risk assessment report includes a mapping relationship between each of the drugs and its corresponding second risk score; The step of generating a second risk score corresponding to the drug based on the component information and the first risk score corresponding to each of the risky drug components includes: Determining whether the composition information includes any of the risky drug ingredients; If not, determining that the second risk score corresponding to the drug is 0; If so, the first risk scores corresponding to the risky drug components included in the component information are added together to obtain a second risk score corresponding to the drug.

5. The method for generating a gene testing report based on medication risk assessment according to claim 4, It is characterized in that The method further comprises: Obtaining clinical medication information of the subject; Determine the abnormal medication history information of the subject based on the clinical medication information; the abnormal medication history information includes a plurality of tolerant drugs; For each of the tolerant drugs, determining whether the medication risk assessment report includes a mapping relationship corresponding to the tolerant drug, and if the medication risk assessment report includes the mapping relationship corresponding to the tolerant drug, deleting the mapping relationship corresponding to the tolerant drug in the medication risk assessment report; Determine each tolerant drug in the historical medication abnormality information as a prohibited medication for the subject, obtain the prohibited medication information for the subject, and optimize the medication risk assessment report after deletion based on the prohibited medication information.

6. A gene testing report generation system based on medication risk assessment, It is characterized in that include: A first acquisition module is used to acquire genetic information and disease diagnosis information of the subject; wherein the disease diagnosis information includes at least one disease type; A second acquisition module is used to acquire variant gene annotation information corresponding to the genetic information based on a preset variant gene annotation detection algorithm; A first generation module is used to obtain variant gene-risk drug component association information in a biomedical database, and generate a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information; A third acquisition module is used to acquire medical medication information corresponding to each disease type from a medical medication database; A second generating module is used to generate a medication risk assessment report for the subject based on the variant gene-risk drug component association network and the medical medication information corresponding to each disease type; A sending module, used for sending the medication risk assessment report to the subject's attending physician; The variant gene annotation information includes multiple variant gene annotations, and generating a variant gene-risk drug component association network corresponding to the variant gene annotation information based on the variant gene-risk drug component association information includes: For each of the variant gene annotations, determining the initial risk drug component information corresponding to the variant gene annotation based on the variant gene-risk drug component association information; Combining the initial risk drug component information to obtain intermediate risk drug component information, and performing deduplication processing on the intermediate risk drug component information to obtain target risk drug component information; Arrange the variant gene annotations in order to obtain a variant gene annotation sequence, and arrange the risk drug components in the target risk drug component information in order to obtain a risk drug component sequence, and place the risk drug component sequence below the variant gene annotation sequence; For each variant gene annotation in the variant gene annotation sequence, determining the relevant risk drug component corresponding to the variant gene annotation in the risk drug component sequence based on the initial drug component information corresponding to the variant gene annotation, and connecting the variant gene annotation and the relevant risk drug component with a straight line to obtain the variant gene-risk drug component association network; The step of sending the medication risk assessment report to the subject's attending physician includes: Obtaining the work code of the attending physician; the work code is a digital sequence; For each number in the digital sequence, a plurality of data packets are generated based on the number, and each of the data packets is arranged in sequence to obtain a data packet unit corresponding to the number; wherein the number of the data packets is consistent with the number, and the data information of each of the data packets is different from each other; Based on the order of the numbers corresponding to the data packet units in the working code, the data packet units are randomly arranged to obtain an initial data packet sequence; Encoding the medication risk assessment report based on a preset coding rule to obtain a coding sequence corresponding to the medication risk assessment report; The coding sequence is segmented based on the number of the data packet units to obtain a plurality of coding subsequences; the number of the coding subsequences is the number of the data packet units minus 1; Based on a preset packaging method, each of the coding subsequences is packaged and processed to obtain a target data packet corresponding to each of the coding subsequences; Based on the corresponding order of the coding subsequences corresponding to the target data packets in the coding sequence, the target data packets are sequentially inserted into the gaps between the data packet units of the initial data packet sequence to obtain a target data packet sequence, and the target data packet sequence is sent to the attending physician.

Images