Drug trend analysis system and method

Abstract

The present invention provides a drug trend analysis system that analyzes various biological data files (such as, but not limited to, patents and scientific literature) to derive multiple biological data sets (such as, but not limited to, pharmaceutical data and biotechnology company data). The system can also establish correlations between different biological data sets and / or biological data files. Furthermore, the drug trend analysis system can further generate correlation charts and statistical charts based on the correlations between different biological data sets and / or biological data files, thereby assisting users in research and development (such as, but not limited to, drug development) or in determining research directions, R&D strategies / directions, business strategies, or business layouts.

Description

Technical Field

[0001] The present invention relates to a drug trend analysis system and method thereof, and more particularly to a drug trend analysis system and method thereof that can analyze the correlation of biological data based on file data. Background Art

[0002] Currently, the typical time from clinical trials to drug approval is approximately 7 to 10 years. During this period, relevant information may only appear in patent documents or other documents that are difficult to find. As a result, researchers or institutions may not be aware of the relevant information recorded in these documents. Furthermore, even if researchers or institutions discover these documents, they may still be unable to effectively understand their content due to the excessive number of documents, large amount of data, or complexity. Therefore, a drug trend analysis system and method that can assist in preliminary analysis or statistical analysis of biological file content is needed. Summary of the Invention

[0003] The present invention aims to provide a drug trend analysis system and method that can assist in preliminary analysis or statistics of biological file contents. The system and method can analyze the correlation of biological data based on file data.

[0004] The present invention aims to provide a drug trend analysis system and method that can analyze different biological document data (such as, but not limited to, patents and scientific literature) to obtain multiple biological data (such as, but not limited to, drug data and biological enterprise data), and can establish correlations between different biological data and / or biological document data.

[0005] The present invention aims to provide a drug trend analysis system and method that can further generate correlation charts, statistical charts, etc. based on the correlation between different biological data and / or biological file data, thereby assisting users in research and development (such as, but not limited to, drug development) or helping users determine their research direction, R&D strategy / direction, business strategy, or business layout.

[0006] The above-mentioned object of the present invention is achieved through the following technical means.

[0007] A drug trend analysis method is applied to a drug trend analysis system comprising a database and a server, wherein the server accesses the database. The method comprises: an analysis module of the server analyzing a first file data to obtain a first bio-analysis data set, a second bio-analysis data set, and a plurality of third bio-analysis data sets; a correlation identification module of the server correlating a third file data set from the database based on at least one of the plurality of third bio-analysis data sets and the second bio-analysis data; and the correlation identification module correlating the first bio-analysis data set with the second bio-analysis data set, the plurality of third bio-analysis data sets, and the third file data; wherein the analysis module is communicatively connected to the correlation identification module.

[0008] Preferably, the first file data is clinical file data, the third file data is patent file data, the first biological analysis data is drug code data or drug name data, and the second biological analysis data is biological enterprise entity data.

[0009] Preferably, the plurality of third bioanalytical data are each one of drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank ID data, target data, structure data, species data, pathway data, and bio-enterprise entity data.

[0010] Preferably, the drug trend analysis method further includes: the analysis module analyzing the first file data or the third file data to obtain a ninth biological data; the correlation identification module associating a fourth file data from the database based on at least the ninth biological data; and the correlation identification module associating the first biological analysis data with the ninth biological data and the fourth file data.

[0011] Preferably, the first biological analysis data is drug code data, the ninth biological data is drug name data, and the fourth file data is one of patent file data, clinical file data, scientific publication file data, news file data and company report file data.

[0012] Preferably, the association identification module associates the fourth file data from the database based on at least one of the plurality of third biological analysis data and the ninth biological data.

[0013] Preferably, the drug trend analysis method further includes: the analysis module analyzing the first file data to obtain a first biological data and a second biological data; the analysis module analyzing the second file data to obtain a third biological data and a fourth biological data; and the correlation identification module associating the first biological data with the second biological data, the third biological data, the fourth biological data and the second file data according to an analysis result.

[0014] Preferably, the analysis result indicates that the similarity between the first biological data and the third biological data is greater than a predetermined similarity threshold.

[0015] Preferably, the first biological data and the third biological data are both gene sequence data or protein data, the second biological data is drug data, and the fourth biological data is disease data.

[0016] Preferably, the drug trend analysis method further includes: an image rendering module of the server generates a third image data according to a fifth instruction from a first device, and provides the third image data to the first device; wherein the third image data includes the first bio-analysis data and the second bio-analysis data and the plurality of third bio-analysis data associated with the first bio-analysis data; wherein the image rendering module is communicatively connected to the analysis module and the correlation identification module.

[0017] A drug trend analysis system, characterized in that the drug trend analysis system includes: a database; and a server for accessing the database, the server including: an analysis module for analyzing a first file data to obtain a first bio-analysis data, a second bio-analysis data, and a plurality of third bio-analysis data; and a correlation identification module for correlating a third file data from the database based on at least one of the plurality of third bio-analysis data and the second bio-analysis data, the correlation identification module correlating the first bio-analysis data with the second bio-analysis data, the plurality of third bio-analysis data, and the third file data; wherein the analysis module is communicatively connected to the correlation identification module.

[0018] Preferably, the first file data is clinical file data, the third file data is patent file data, the first biological analysis data is drug code data or drug name data, and the second biological analysis data is biological enterprise entity data.

[0019] Preferably, the plurality of third bioanalytical data are each one of drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank ID data, target data, structure data, species data, pathway data, and bio-enterprise entity data.

[0020] Preferably, the analysis module analyzes the first file data or the third file data to obtain a ninth biological data; the association identification module associates a fourth file data from the database at least based on the ninth biological data; and the association identification module associates the first biological analysis data with the ninth biological data and the fourth file data.

[0021] Preferably, the first biological analysis data is drug code data, the ninth biological data is drug name data, and the fourth file data is one of patent file data, clinical file data, scientific publication file data, news file data and company report file data.

[0022] Preferably, the association identification module associates the fourth file data from the database based on at least one of the plurality of third biological analysis data and the ninth biological data.

[0023] Preferably, the analysis module analyzes the first file data to obtain a first biological data and a second biological data; the analysis module analyzes the second file data to obtain a third biological data and a fourth biological data; and the association identification module associates the first biological data with the second biological data, the third biological data, the fourth biological data and the second file data according to an analysis result.

[0024] Preferably, the analysis result indicates that the similarity between the first biological data and the third biological data is greater than a predetermined similarity threshold.

[0025] Preferably, the first biological data and the third biological data are both gene sequence data or protein data, the second biological data is drug data, and the fourth biological data is disease data.

[0026] Preferably, the server includes an image rendering module, which generates third image data according to a fifth instruction from a first device and provides the third image data to the first device; wherein the third image data includes the first bio-analysis data and the second bio-analysis data and the plurality of third bio-analysis data associated with the first bio-analysis data; wherein the image rendering module is communicatively connected to the analysis module, the correlation identification module and the providing module.

[0027] A drug trend analysis system, characterized in that the drug trend analysis system includes: a database; and a server for accessing the database; the server includes: an analysis module for analyzing first file data to obtain first biological data and second biological data, and analyzing second file data to obtain third biological data and fourth biological data; a correlation identification module for associating the first biological data with the second biological data, the third biological data, the fourth biological data and the second file data according to the analysis results; and a providing module for providing the first biological data, the second biological data associated with the first biological data, the third biological data and the fourth biological data to the first device according to a first instruction from the first device; wherein the first device is communicatively connected to the server; wherein the server stores the first biological data, the second biological data, the third biological data and the fourth biological data in the database; wherein the analysis module is communicatively connected to the correlation identification module and the providing module; and wherein the correlation identification module is communicatively connected to the providing module.

[0028] Preferably, the database stores multiple biological data, and when the analysis module analyzes the first file data and the second file data, it derives the first biological data or the second biological data or the third biological data or the fourth biological data based on at least one biological data among the multiple biological data.

[0029] Preferably, the analysis module includes a first natural language processing module, and the analysis module obtains the first biological data or the second biological data or the third biological data or the fourth biological data through the natural language processing module.

[0030] Preferably, the first biological data, the second biological data, the third biological data and the fourth biological data are respectively one of drug data, drug code data, drug name data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, target data, structure data, species data, pathway data and biological enterprise entity data.

[0031] Preferably, the relevance identification module includes a second natural language processing module, and the relevance identification module obtains the analysis result through the second natural language processing module.

[0032] Preferably, the first biological data is associated with the second biological data, the third biological data, the fourth biological data and the second file data according to the analysis result, and the association identification module generates the first association data according to the analysis result, and the server stores the first association data in the database; wherein the first association data is associated with the first biological data, and the first association data indicates that the first biological data is associated with the second biological data, the third biological data, the fourth biological data and the second file data.

[0033] Preferably, the server includes an image drawing module, which generates first image data according to a second instruction from the first device and provides the first image data to the first device, wherein the first image data includes the first biological data and the second biological data, the third biological data and the fourth biological data associated with the first biological data; wherein the image drawing module is communicatively connected to the analysis module, the correlation identification module and the providing module.

[0034] Preferably, the association identification module associates the first biological data with the first file data and the second file data according to the analysis result.

[0035] Preferably, when the first biometric data, the second biometric data, the third biometric data and the fourth biometric data are all associated with the fifth biometric data, and the first biometric data, the second biometric data, the third biometric data and the fourth biometric data are all data of different contents, the association identification module generates second association data and third association data, and the server stores the second association data and the third association data in the database; wherein the second association data indicates that the first biometric data and the fourth biometric data have a first association; the third association data indicates that the third biometric data and the second biometric data have a second association; wherein the first biometric data and the third biometric data are the same type of biometric data, and the second biometric data and the fourth biometric data are the same type of biometric data.

[0036] Preferably, the first biological data and the third biological data are drug data, and the second biological data and the fourth biological data are disease data.

[0037] Preferably, the database stores a plurality of biological data, and the server further includes a statistical module, which generates statistical data based on the plurality of biological data; wherein the providing module provides the statistical data to the first device according to a third instruction from the first device; wherein the statistical module is communicatively connected to the analysis module, the correlation identification module and the providing module.

[0038] Preferably, the server includes an image drawing module, which generates second image data based on the statistical data; the providing module provides the second image data to the first device according to a fourth instruction from the first device; and the image drawing module is communicatively connected to the analysis module, the correlation identification module, the statistical module and the providing module.

[0039] Preferably, the server further includes a biological data classification module, which classifies the first biological data, the second biological data, the third biological data and the fourth biological data through a third natural language processing module of the biological data classification module; wherein the biological data classification module is communicatively connected to the analysis module, the correlation identification module and the providing module.

[0040] Preferably, the first document data and the second document data are respectively one of patent document data, clinical document data, scientific publication document data, news document data and company report document data.

[0041] Preferably, the analysis result indicates that the similarity between the first biological data and the third biological data is greater than a predetermined similarity threshold.

[0042] Preferably, the first biological data and the third biological data are both gene sequence data or protein data, the second biological data is drug data, and the fourth biological data is disease data.

[0043] A drug trend analysis method is applied to a drug trend analysis system including a database and a server, wherein the server accesses the database; the drug trend analysis method is characterized in that the method includes: an analysis module of the server analyzes first file data to obtain first biological data and second biological data; the analysis module analyzes second file data to obtain third biological data and fourth biological data; the server stores the first biological data, the second biological data, the third biological data and the fourth biological data in the database; the association identification module of the server associates the first biological data with the second biological data, the third biological data, the fourth biological data and the second file data according to the analysis result of the analysis module; and the providing module of the server provides the first biological data, the second biological data associated with the first biological data, the third biological data and the fourth biological data to the first device according to a first instruction from the first device; wherein the first device is communicatively connected to the server; wherein the analysis module is communicatively connected to the association identification module and the providing module; wherein the association identification module is communicatively connected to the providing module.

[0044] Preferably, the database stores a plurality of biological data, and when the analysis module analyzes the first file data and the second file data, it obtains the first biological data or the second biological data or the third biological data or the fourth biological data based on at least one biological data among the plurality of biological data.

[0045] Preferably, the analysis module includes a first natural language processing module, and the analysis module obtains the first biological data or the second biological data or the third biological data or the fourth biological data through the natural language processing module.

[0046] Preferably, the first biological data, the second biological data, the third biological data, and the fourth biological data are respectively one of drug data, drug code data, drug name data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, target data, structure data, species data, pathway data, and biological enterprise entity data.

[0047] Preferably, the relevance identification module includes a second natural language processing module, and the relevance identification module obtains the analysis result through the second natural language processing module.

[0048] Preferably, the first biological data is associated with the second biological data, the third biological data, the fourth biological data and the second file data according to the analysis result, and the association identification module generates the first association data according to the analysis result, and the server stores the first association data in the database; wherein the first association data is associated with the first biological data, and the first association data indicates that the first biological data is associated with the second biological data, the third biological data, the fourth biological data and the second file data.

[0049] Preferably, the drug trend analysis method further includes: an image drawing module of the server generates first image data according to a second instruction from the first device, and provides the first image data to the first device, the first image data including the first biological data and the second biological data, the third biological data and the fourth biological data associated with the first biological data; wherein the image drawing module is communicatively connected to the analysis module, the correlation identification module and the providing module.

[0050] Preferably, the association identification module associates the first biological data with the first file data and the second file data according to the analysis result.

[0051] Preferably, the drug trend analysis method further includes: when the first biological data, the second biological data, the third biological data and the fourth biological data are all associated with the fifth biological data, and the first biological data, the second biological data, the third biological data and the fourth biological data are all data of different contents, the correlation identification module generates second correlation data and third correlation data, and the server stores the second correlation data and the third correlation data to the database; wherein the second correlation data indicates that the first biological data and the fourth biological data have a first correlation; the third correlation data indicates that the third biological data and the second biological data have a second correlation; wherein the first biological data and the third biological data are biological data of the same type, and the second biological data and the fourth biological data are biological data of the same type.

[0052] Preferably, the first biological data and the third biological data are drug data, and the second biological data and the fourth biological data are disease data.

[0053] Preferably, the database stores a plurality of biological data; the drug trend analysis method further includes: a statistical module of the server generates statistical data based on the plurality of biological data; and the providing module provides the statistical data to the first device according to a third instruction from the first device; wherein the statistical module is communicatively connected to the analysis module, the correlation identification module and the providing module.

[0054] Preferably, the drug trend analysis method further includes: the image drawing module of the server generates second image data based on the statistical data; and the providing module provides the second image data to the first device according to a fourth instruction from the first device; wherein the image drawing module is communicatively connected to the analysis module, the correlation identification module, the statistical module and the providing module.

[0055] Preferably, the drug trend analysis method further includes: the biological data classification module of the server classifies the first biological data, the second biological data, the third biological data and the fourth biological data through the third natural language processing module of the biological data classification module; wherein the biological data classification module is communicatively connected to the analysis module, the correlation identification module and the providing module.

[0056] Preferably, the first document data and the second document data are respectively one of patent document data, clinical document data, scientific publication document data, news document data and company report document data.

[0057] Preferably, the analysis result indicates that the similarity between the first biometric data and the third biometric data is greater than a predetermined similarity threshold.

[0058] Preferably, the first biological data and the third biological data are both gene sequence data or protein data, the second biological data is drug data, and the fourth biological data is disease data.

[0059] The foregoing and other aspects of the present invention will become more apparent from the following detailed description of non-limiting embodiments and with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A system architecture diagram showing a drug trend analysis system according to an example of the present invention.

[0061] Figure 2 A partial screen diagram of a first device displaying biological data provided by a drug trend analysis system according to an example of the present invention.

[0062] Figure 3A partial screen diagram of a first device displaying biological data provided by a drug trend analysis system according to an example of the present invention.

[0063] Figure 4 A schematic diagram showing a partial screen of a drug trend analysis system according to an example of the present invention.

[0064] Figure 5 Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0065] Figure 6A Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0066] Figure 6B Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0067] Figure 6C Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0068] Figure 6D Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0069] Figure 7 Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0070] Figure 8 Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0071] Figure 9 Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0072] Figure 10 Schematic diagram of part of the screen of the drug trend analysis system according to an example of the present invention.

[0073] Figure 11 Flowchart of a drug trend analysis method according to an example of the present invention.

[0074] Figure 12 Flowchart of a drug trend analysis method according to an example of the present invention.

[0075] Figure 13A Schematic diagram of a specific embodiment of the drug trend analysis method of the present invention.

[0076] Figure 13B Schematic diagram of a specific embodiment of the drug trend analysis method of the present invention.

[0077] Figure 13C Schematic diagram of a specific embodiment of the drug trend analysis method of the present invention. DETAILED DESCRIPTION

[0078] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art. If a definition used herein conflicts or is inconsistent with a definition in other published documents, the definition used herein shall prevail.

[0079] As used herein, the terms "selected from," "composed of," and "comprising" are synonymous. As used herein, the terms "comprises," "comprising," "includes," "including," "has," "having," "contains," "containing," or any other variations thereof, are intended to cover a non-exclusive inclusion. For example, a composition, process, method, article, or apparatus that contains a plurality of listed elements is not necessarily limited to only those elements listed in the list but may include other elements not expressly listed but inherent to the composition, process, method, article, or apparatus.

[0080] See also Figure 1 , which illustrates a system architecture diagram of a drug trend analysis system according to an example of the present invention. Figure 1In the illustrated embodiment, the drug trend analysis system 100 includes a database 110 and a server 120. Database 110 stores a plurality of biological data, and server 110 can access database 120. Server 120 includes an analysis module 121, a correlation identification module 123, a provision module 125, a biological data classification module 126, a statistics module 127, and an image rendering module 129. Analysis module 121 includes a first natural language processing (NLP) module 121A, correlation identification module 123 includes a second NLP module 123A, and biological data classification module 126 includes a third NLP module 126A. In a specific embodiment, the analysis module 121 is communicatively connected to the correlation identification module 123 and the providing module 125, the correlation identification module 123 is communicatively connected to the providing module 125, the statistics module 127 is communicatively connected to the analysis module 121, the correlation identification module 123 and the providing module 125, the image drawing module 129 is communicatively connected to the analysis module 121, the correlation identification module 123, the statistics module 127 and the providing module 125, and the biological data classification module 126 is communicatively connected to the analysis module 121, the correlation identification module 123, the statistics module 127, the image drawing module 129 and the providing module 125. In one embodiment, the drug trend analysis system 100 includes one or more processors and implements a database 110, a server 120, an analysis module 121, a first natural language processing module 121A, a correlation identification module 123, a second natural language processing module 123A, a providing module 125, a biological data classification module 126, a third natural language processing module 126A, a statistics module 127, and an image rendering module 129 in a manner in which hardware and software operate in coordination.

[0081] exist Figure 1In the illustrated embodiment, the analysis module 121 analyzes a first document to obtain first and second biometric data, and analyzes a second document to obtain third and fourth biometric data. The server then stores the first, second, third, and fourth biometric data in the database 110. In one embodiment, when analyzing the first document and / or the second document, the analysis module 121 obtains at least one of the first, second, third, and fourth biometric data based on at least one of the plurality of biometric data stored in the database 110. For example, in one embodiment, if a biometric data stored in the database 110 is identical to the first biometric data, the analysis module 121 may obtain (or analyze) the first biometric data using the biometric data stored in the database 110 that is identical to the first biometric data. In one embodiment, when analyzing the first document and / or the second document, the analysis module 121 uses the natural language processing module 121A to obtain at least one of the first, second, third, and fourth biometric data. In various embodiments, the first document data and / or the second document data may be one of patent documents, clinical trial documents, scientific publication documents, news documents, and company report documents, but is not limited thereto.

[0082] The present invention's methods for obtaining (or analyzing) biological data, obtaining a knowledge structure diagram, or other steps of the present invention may also refer to Patent No. CN109448793A (invention title: "Method for Identifying, Retrieving, and Determining Infringement of Gene Sequence Rights"), Patent No. CN110413814A (invention title: "Image Database Establishment Method, Search Method, Electronic Device, and Storage Medium"), Patent No. US20180276340 (invention title: "SYSTEM AND METHOD FOR DRUG TARGET AND BIOMARKER DISCOVERY AND DIAGNOSIS USING AMULTIDIMENSIONAL MULTISCALE MODULE MAP"), and Patent No. US20190005395 (invention title: "A METHOD AND SYSTEM FOR ONTOLOGY-BASED DYNAMIC LEARNING AND KNOWLEDGE INTEGRATION FROM MEASUREMENT DATA AND TEXT”), the present invention hereby incorporates all the contents of the above-mentioned patents into this document by reference.

[0083] In various embodiments, the first biological data, the second biological data, the third biological data, and the fourth biological data may be one of drug data, drug code data, drug name data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank ID data, target data, structure data, species data, pathway data, and bio-enterprise entity data. For example, the first biological data may be drug data, the second biological data may be protein data, the third biological data may be disease data, and the fourth biological data may be bio-enterprise entity data. The bio-enterprise entity may be, but is not limited to, a company, an academic institution, a government agency, or an individual. For example, the bio-enterprise entity may be an applicant for a drug patent (this applicant may be an individual, a company, or an institution, etc.). In another embodiment, the first biological data, the second biological data, the third biological data, or the fourth biological data may also be other biological-related data.

[0084] exist Figure 1 In the illustrated embodiment, the relevance identification module 123 associates the first biological data with the second biological data, the third biological data, and the fourth biological data based on an analysis result. In a specific embodiment, the relevance identification module 123 obtains the analysis result through the second natural language processing module 123A. In a specific embodiment, the analysis result of the relevance identification module 123 is that the first biological data and the second biological data are both derived from the first file data. Accordingly, the relevance identification module 123 associates the first biological data with the second biological data based on the analysis result. In a specific embodiment, the analysis result of the relevance identification module 123 is that the second biological data and the third biological data have the same content, the first biological data and the second biological data are both derived from the first file data, and the third biological data and the fourth biological data are both derived from the second file data. Accordingly, the relevance identification module 123 associates the first biological data with the second biological data, the third biological data, and the fourth biological data based on the analysis result, and associates the first file data with the second file data. In one embodiment, the analysis result of the association identification module 123 is that the second biometric data is associated with the third biometric data (e.g., a database stores association data indicating that the second biometric data is associated with the third biometric data). The first biometric data and the second biometric data are both derived from the first file data, and the third biometric data and the fourth biometric data are both derived from the second file data. Based on this, the association identification module 123 associates the first biometric data with the second, third, and fourth biometric data, and associates the first file data with the second file data based on the analysis result.

[0085] In one embodiment, the association of the first biometric data with the second, third, and fourth biometric data based on an analysis result involves the association identification module 123 generating first association data based on the analysis result, and the server 120 storing the first association data in the database 110. The first association data is associated with the first biometric data, and the first association data indicates that the first biometric data is associated with the second, third, and fourth biometric data. In one embodiment, the first association data includes three association data items, respectively indicating that the first biometric data is associated with the second biometric data, the first biometric data is associated with the third biometric data, and the first biometric data is associated with the fourth biometric data.

[0086] exist Figure 1 In the illustrated embodiment, the providing module 125 provides the first biometric data and the second, third, and fourth biometric data associated with the first biometric data to the first device in response to a first instruction from the first device (not shown). The first device is communicatively connected to the server 120. In various embodiments, the first device may be a desktop computer, a smartphone, or a laptop computer, but is not limited thereto. In one embodiment, the first instruction is an instruction from a user specifying the first biometric data as a search target or analysis target. In one embodiment, the association identification module 123 associates the first biometric data with the first and second file data based on the analysis results. Thus, when the providing module 125 provides the first biometric data and the second, third, and fourth biometric data associated with the first biometric data to the first device in response to the first instruction from the first device (not shown), the first and second file data associated with the first biometric data may be further provided to the first device in response to the file provision instruction from the first device (or the first and second file data may be directly provided to the first device without the first device inputting a separate file provision instruction).

[0087] exist Figure 1 In the illustrated embodiment, the biological data classification module 126 classifies the first biological data, the second biological data, the third biological data, and the fourth biological data via the third natural language processing module 126A of the biological data classification module. In one embodiment, the third natural language processing module 126A of the biological data classification module classifies the first biological data, the second biological data, the third biological data, and the fourth biological data into one of drug data, disease data, gene data, protein data, enzyme data, organism data, cell line data, cell bank ID data, target data, structure data, species data, pathway data, and bio-enterprise entity data.

[0088] exist Figure 1 In the illustrated embodiment, the image rendering module 129 generates first image data based on a second instruction from the first device and provides the first image data to the first device (in different embodiments, the first image data may be provided to the first device by the providing module 125 or the image rendering module 129). The first image data includes the first biometric data and second, third, and fourth biometric data associated with the first biometric data. In one embodiment, when the first image data is displayed, the first image data also indicates that the first biometric data is associated with the second, third, and fourth biometric data. In one embodiment, the first image data is a knowledge structure graph.

[0089] In one embodiment, when the first, second, third, and fourth biometric data are all associated with the fifth biometric data, and the first, second, third, and fourth biometric data are data of different contents, the relevance identification module 123 generates second and third relevance data, and the server 120 stores the second and third relevance data in the database 110. The second relevance data indicates a first relevance between the first and fourth biometric data, and the third relevance data indicates a second relevance between the third and second biometric data. The first and third biometric data are of the same type, and the second and fourth biometric data are of the same type. In one embodiment, the first and third biometric data are drug data, and the second and fourth biometric data are disease data. The first relevance indicates that the first biometric data may be applicable to the fourth biometric data, and the third relevance data indicates that the third biometric data may be applicable to the second biometric data. In this way, the relevance identification module 123 can identify new potential applications for a drug based on different file data.

[0090] In one embodiment, the analysis result indicates that the similarity between the first biological data and the third biological data is greater than a predetermined similarity threshold, which means that the first biological data and the third biological data have great similarity or correlation. In one embodiment, the first biological data and the third biological data are both gene sequence data, the second biological data is drug data (for example, drug name data or drug code data), and the fourth biological data is disease data. In another embodiment, the first biological data and the third biological data are both protein data, the second biological data is drug data (for example, drug name data or drug code data), and the fourth biological data is disease data. In this way, the correlation identification module 123 can find out new application areas that a certain drug may have based on different file data, or can find existing potentially useful drugs for a certain disease (for example, COVID 19 (Coronavirus Disease)).

[0091] exist Figure 1 In the illustrated embodiment, the statistics module 127 generates statistics (these are first statistics) based on the plurality of biological data stored in the database 110. The providing module 125 may provide the statistics to the first device in response to a third instruction from the first device. In one specific embodiment, the image rendering module 129 may generate second image data based on the statistics. The providing module may also provide the second image data to the first device in response to a fourth instruction from the first device. In one specific embodiment, the database 110 also stores a plurality of file data. The statistics module 127 may generate the second statistics based on the plurality of file data stored in the database 110. The providing module 125 may provide at least one of the plurality of file data stored in the database 110 to the first device in response to an instruction from the first device. The providing module 125 may also provide the second statistics to the first device in response to another instruction from the first device. In one specific embodiment, the second image data is a knowledge structure graph.

[0092] exist Figure 1In the illustrated embodiment, the analysis module 121 may analyze the first file data to obtain first bioanalysis data, second bioanalysis data, and a plurality of third bioanalysis data. The association identification module 123 may associate a third file data from the database 110 based on at least one of the plurality of third bioanalysis data and the second bioanalysis data. The association identification module 123 may further associate the first bioanalysis data with the second bioanalysis data, the plurality of third bioanalysis data, and the third file data. In one embodiment, the first file data is clinical file data, the third file data is patent file data, the first bioanalysis data is drug data (e.g., drug code data or drug name data), and the second bioanalysis data is bio-enterprise entity data. In one embodiment, the plurality of third bioanalysis data are each selected from the group consisting of drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank ID data, target data, structure data, species data, pathway data, and bio-enterprise entity data.

[0093] In one embodiment, the analysis module 121 may analyze the first or third file data to obtain the ninth biological data. The association identification module 123 may associate the fourth file data from the database 110 based on at least the ninth biological data. The association identification module 123 may also associate the first biological analysis data with the ninth biological data and the fourth file data. In one embodiment, the first biological analysis data is drug code data, and the ninth biological data is drug name data. The fourth file data is one of patent document data, clinical document data, scientific publication document data, news document data, and company report document data. In one embodiment, the association identification module 123 may associate the fourth file data from the database 110 based on at least one of the plurality of third biological analysis data and the ninth biological data.

[0094] In one embodiment, the analysis module 121 may analyze the first file data to obtain first and second biological data. The analysis module 121 may analyze the second file data to obtain third and fourth biological data. The correlation identification module 123 may associate the first biological data with the second, third, and fourth biological data, and the second file data, based on an analysis result. In one embodiment, the analysis result indicates that the similarity between the first and third biological data is greater than a predetermined similarity threshold, indicating that the first and third biological data have a high degree of similarity or correlation. In one embodiment, the first and third biological data are both gene sequence data, the second biological data is drug data (e.g., drug name data or drug code data), and the fourth biological data is disease data. In another embodiment, the first and third biological data are both protein data, the second biological data is drug data (e.g., drug name data or drug code data), and the fourth biological data is disease data. In this way, the relevance identification module 123 can find out new application areas that a certain drug may have based on different file data, or find out existing drugs that may be useful for a certain disease (such as COVID 19 (Coronavirus Disease)).

[0095] In one embodiment, the image rendering module 129 of the server 120 may generate third image data based on a fifth instruction from the first device and provide the third image data to the first device. The third image data includes the first biometric analysis data, second biometric analysis data associated with the first biometric analysis data, and a plurality of third biometric analysis data. In one embodiment, the third image data also includes the ninth biometric data, the first file data, the third file data, and the fourth file data.

[0096] See also Figure 2 , which illustrates a partial screen diagram of a first device displaying biological data provided by the drug trend analysis system of the present invention. Figure 2 As shown, when the first device inputs the first instruction 212, the providing module provides the first biometric data, the second biometric data associated with the first biometric data, the third biometric data, the fourth biometric data, and the first file data and the second file data associated with the first biometric data to the first device according to the first instruction 212 from the first device. Figure 2 2 shows a screen displayed on the display of the first device. In particular, link 211 includes the first biometric data, link 213 includes the second biometric data, link 215 includes the third biometric data, link 217 includes the fourth biometric data, link 214 includes the first file data, and link 216 includes the second file data.

[0097] See also Figure 3 , which illustrates a partial screen diagram of a specific embodiment of the first device displaying biological data provided by the drug trend analysis system of the present invention. Figure 3 As shown, when the first device provides a first instruction to the drug trend analysis system, the providing module of the drug trend analysis system provides the first biological data, the second biological data associated with the first biological data, the third biological data, the fourth biological data and the first file data and the second file data associated with the first biological data to the first device according to the first instruction. Figure 3 3 shows a screen displayed on the display of the first device. In particular, link 312 includes the first biometric data, link 314 includes the second biometric data and the third biometric data, link 316 includes the fourth biometric data, and link 311 includes the first file data and the second file data.

[0098] See also Figure 4 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present invention. Figure 4 In the illustrated embodiment, since the biological data classification module categorizes each biological data, a user can search or query biological data through links 411-417 and search or query document data through links 421-423. It should be understood that the screen of the drug trend analysis system can be displayed on the display of the first device.

[0099] See also Figure 5 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present invention. Figure 5 As shown, the drug trend analysis system has already classified the biological data using the biological data classification module and has generated first and second statistical data based on the biological data and the document data using the statistical module to achieve various analyses. Therefore, the user can view different analysis results through links 511 to 516.

[0100] See also 6A to 6D, which illustrates partial screen diagrams of various embodiments of the drug trend analysis system of the present invention. As shown, the drug trend analysis system classifies biological data using the biological data classification module and generates first and second statistical data based on the biological data and file data using the statistics module, thereby achieving various analyses. Therefore, users can select and view different analysis or statistical results. For example, you can choose to view the analysis results or statistical results of patent document data (for example, see images 611 and 612), or you can choose to view the analysis results or statistical results of ontology biological data (for example, see image 613), or you can choose to view the analysis results or statistical results of drug class biological data (for example, see image 614), or you can choose to view the analysis results or statistical results of clinical trial study phase biological data (for example, see image 615), or you can choose to view the analysis results or statistical results of drug target class biological data (for example, see image 616), or you can choose to view the analysis results or statistical results of drug biological data (for example, see images 621, 622, 624), or you can choose to view the analysis results or statistical results of function pointer biological data (for example, see image 623).

[0101] See also Figure 7 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present invention. Figure 7 As shown, image 713 shows that drug trend analysis, based on multiple sets of file data, has revealed that ventricular biodata is associated with 123 literature files, 265 patent files, 422 news files, 54 serial biodata, 23 compound biodata, 87 clinical trial biodata, and 25 drug data. Furthermore, images 715, 717, and 719 between images 711 and 713 can be used to view target biodata, drug biodata, and patent file data associated with both ventricular and left ventricular biodata, respectively.

[0102] See also Figure 8 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present invention. Figure 8As shown, the statistics module of the drug trend analysis system can count the number of times different biological data appear in the file data of different companies in different years, and thereby generate a plurality of corresponding statistical data. The image rendering module of the drug trend analysis system can generate a second image 810 based on these statistical data. Point 812 in image 810 represents the number of times the biological data "neoplasm" appeared in the file data associated with the biological enterprise entity data "PFIZER" in 2017 (darker colors indicate more occurrences). Point 814 in image 810 represents the number of times the disease data "virus disease" appeared in the file data associated with the biological enterprise entity data "GSK" in 2011 (lighter colors indicate fewer occurrences).

[0103] See also Figure 9 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present invention. Figure 9 As shown, the statistics module of the drug trend analysis system can count the number of clinical trials conducted by different biotechnology entities for different biological data, thereby generating a plurality of corresponding statistical data. The image rendering module of the drug trend analysis system can generate a second image 910 based on these statistical data. Segment 912 in image 910 indicates the number of clinical trials conducted by the biotechnology entity "Merk Sharp & Dohme Corp." for the disease data "gastrointestinal disease."

[0104] See also Figure 10 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present invention. Figure 10 As shown, image 1010 shows first biometric data 1011 and second biometric data 1012, third biometric data 1013, and fourth biometric data 1014 associated with the first biometric data 1011. Image 1010 also indicates with arrow 1016 that the second biometric data 1012 is associated with the first biometric data 1011, with arrow 1017 that the third biometric data 1013 is associated with the first biometric data 1011, and with arrow 1018 that the fourth biometric data 1014 is associated with the first biometric data 1011.

[0105] See also Figure 11 , which illustrates a flow chart of a specific embodiment of the drug trend analysis method of the present invention. Figure 11As shown, a drug trend analysis method 1100 is applied to a drug trend analysis system including a database and a server, wherein the server accesses the database and includes an analysis module, a correlation identification module, and a provision module. The analysis module is communicatively connected to the correlation identification module and the provision module, the correlation identification module is communicatively connected to the provision module, and the server is communicatively connected to a first device. Drug trend analysis method 1100 begins at step 1110, where the analysis module of the server analyzes first file data to obtain first and second biological data. Next, step 1120 is performed, where the analysis module analyzes second file data to obtain third and fourth biological data. Next, step 1130 is performed, where the server stores the first, second, third, and fourth biological data in the database.

[0106] In one embodiment, a database stores multiple biometric data. When analyzing the first and second file data, the analysis module derives the first and / or second and / or third and / or fourth biometric data based on at least one of the multiple biometric data. In one embodiment, the analysis module includes a first natural language processing module, and the analysis module derives the first and / or second and / or third and / or fourth biometric data through the natural language processing module.

[0107] In one embodiment, the first biological data, the second biological data, the third biological data, and the fourth biological data are each one of drug data, drug code data, drug name data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank ID data, target data, structure data, species data, pathway data, and bio-enterprise entity data. For example, the first biological data may be drug data, the second biological data may be pathway data, the third biological data may be target data, and the fourth biological data may be bio-enterprise entity data. The bio-enterprise entity may be, but is not limited to, a company, an academic institution, an institution, a government agency, or an individual. In another embodiment, the first biological data, the second biological data, the third biological data, or the fourth biological data may also be other biological-related data.

[0108] Next, step 1140 is performed, and the relevance identification module of the server associates the first biological data with the second biological data, the third biological data, and the fourth biological data based on the analysis result. In a specific embodiment, the relevance identification module includes a second natural language processing module, and the relevance identification module obtains the analysis result through the second natural language processing module. In a specific embodiment, the first biological data is associated with the second biological data, the third biological data, and the fourth biological data based on the analysis result, and the relevance identification module generates first relevance data based on the analysis result, and the server stores the first relevance data in a database. The first relevance data is associated with the first biological data, and the first relevance data indicates that the first biological data is associated with the second biological data, the third biological data, and the fourth biological data. In a specific embodiment, the relevance identification module associates the first biological data with the first file data and the second file data based on the analysis result.

[0109] Next, step 1150 is performed, where the providing module of the server provides the first biometric data, the second biometric data associated with the first biometric data, the third biometric data, and the fourth biometric data to the first device according to the first instruction from the first device.

[0110] In one embodiment, a server of a drug trend analysis system includes an image rendering module, which is communicatively connected to an analysis module, a correlation identification module, and a provision module. A drug trend analysis method further includes the following steps: the image rendering module of the server generates first image data based on a second instruction from a first device, and provides the first image data to the first device. The first image data includes first biometric data and second, third, and fourth biometric data associated with the first biometric data.

[0111] In one embodiment, the drug trend analysis method further includes the following steps: when the first biological data, the second biological data, the third biological data, and the fourth biological data are all associated with a fifth biological data, and the first biological data, the second biological data, the third biological data, and the fourth biological data are data of different contents, the correlation identification module generates second correlation data and third correlation data, and the server stores the second correlation data and the third correlation data in a database. The second correlation data indicates that the first biological data and the fourth biological data have a first correlation, and the third correlation data indicates that the third biological data and the second biological data have a second correlation. The first biological data and the third biological data are biological data of the same type, and the second biological data and the fourth biological data are biological data of the same type. For example, in one embodiment, the first biological data and the third biological data are drug data, and the second biological data and the fourth biological data are disease data.

[0112] In one embodiment, a database stores multiple biological data, and a server of the drug trend analysis system includes a statistics module and an image rendering module. The statistics module is communicatively connected to the analysis module, the correlation identification module, and the provision module, and the image rendering module is communicatively connected to the analysis module, the correlation identification module, the statistics module, and the provision module. The drug trend analysis method further includes the following steps: the statistics module of the server generates statistical data based on the multiple biological data; the provision module provides the statistical data to the first device in response to a third instruction from the first device; the image rendering module of the server generates second image data based on the statistical data; and the provision module provides the second image data to the first device in response to a fourth instruction from the first device.

[0113] In one embodiment, a server of the drug trend analysis system includes a biological data classification module, wherein the biological data classification module is communicatively connected to the analysis module, the correlation identification module, and the provision module. The drug trend analysis method further includes the following steps: the biological data classification module of the server classifies the first biological data, the second biological data, the third biological data, and the fourth biological data using a third natural language processing module of the biological data classification module.

[0114] In one embodiment, the analysis result indicates that the similarity between the first biological data and the third biological data is greater than a predetermined similarity threshold value, which indicates that the first biological data and the third biological data have a great similarity or correlation. In one embodiment, the first biological data and the third biological data are both gene sequence data, the second biological data is drug data (for example, drug name data or drug code data), and the fourth biological data is disease data. In another embodiment, the first biological data and the third biological data are both protein data, the second biological data is drug data (for example, drug name data or drug code data), and the fourth biological data is disease data. In this way, the correlation identification module 123 can find out new application areas that a certain drug may have based on different file data, or can find existing potentially useful drugs for a certain disease (for example, COVID 19 (Coronavirus Disease)).

[0115] Please refer to Figure 12 , which illustrates a flow chart of a specific embodiment of the drug trend analysis method of the present invention. Figure 12As shown, a drug trend analysis method 1200 is applied to a drug trend analysis system comprising a database and a server, wherein the server accesses the database. Drug trend analysis method 1200 begins at step 1210, where an analysis module on the server analyzes first file data to obtain first bioanalysis data, second bioanalysis data, and a plurality of third bioanalysis data. Next, step 1120 is performed, where a relevance identification module on the server associates third file data from the database based on at least one of the plurality of third bioanalysis data and the second bioanalysis data. Next, step 1130 is performed, where the relevance identification module associates the first bioanalysis data with the second bioanalysis data, the plurality of third bioanalysis data, and the third file data. The analysis module is communicatively connected to the relevance identification module. In one embodiment, the first file data is clinical file data, the third file data is patent file data, the first bioanalysis data is drug code data or drug name data, and the second bioanalysis data is bio-enterprise entity data. In one embodiment, the plurality of third bioanalysis data are each one of drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank ID data, target data, structure data, species data, pathway data, and bio-enterprise entity data.

[0116] In one embodiment, the drug trend analysis method 1200 further includes: analyzing the first or third file data by an analysis module to obtain ninth biological data; associating, by a relevance identification module, fourth file data from a database based on at least the ninth biological data; and associating, by the relevance identification module, the first biological analysis data with the ninth biological data and the fourth file data. In one embodiment, the first biological analysis data is drug code data, and the ninth biological data is drug name data. The fourth file data is one of patent document data, clinical document data, scientific publication document data, news document data, and company report document data. In one embodiment, the relevance identification module associates the fourth file data from the database based on at least one of the plurality of third biological analysis data and the ninth biological data.

[0117] In one embodiment, the drug trend analysis method 1200 further includes: analyzing the first file data by an analysis module to obtain first and second biological data; analyzing the second file data by an analysis module to obtain third and fourth biological data; and correlating the first biological data with the second, third, and fourth biological data, and the second file data, based on the analysis results, by a correlation identification module. In one embodiment, the analysis results indicate that the similarity between the first and third biological data exceeds a predetermined similarity threshold, indicating that the first and third biological data have a significant similarity or correlation. In one embodiment, the first and third biological data are both gene sequence data, the second biological data is drug data (e.g., drug name data or drug code data), and the fourth biological data is disease data. In another embodiment, the first and third biological data are both protein data, the second biological data is drug data (e.g., drug name data or drug code data), and the fourth biological data is disease data. In this way, the relevance identification module 123 can find out new application areas that a certain drug may have based on different file data, or find out existing drugs that may be useful for a certain disease (such as COVID 19 (Coronavirus Disease)).

[0118] In one embodiment, the drug trend analysis method 1200 further includes generating, by an image rendering module of the server, third image data based on a fifth instruction from a first device, and providing the third image data to the first device. The third image data includes the first biological analysis data, as well as second biological analysis data and a plurality of third biological analysis data associated with the first biological analysis data. The image rendering module is communicatively connected to the analysis module and the correlation identification module. In one embodiment, the third image data also includes the ninth biological data, the first file data, the third file data, and the fourth file data.

[0119] See also Figure 13A , which illustrates a schematic diagram of a specific embodiment of the drug trend analysis method of the present invention. Figure 13AAs shown, the server's analysis module may first analyze clinical document data 1310 to obtain drug code data 1311, bio-enterprise entity data 1312, and third bio-analysis data 1313, 1314, 1315, 1316, and 1317. Clinical document data 1310 is the first document data, drug code data 1311 is the first bio-analysis data, and bio-enterprise entity data 1312 is the second bio-analysis data. Third bio-analysis data 1313 is disease data indicating that the drug in clinical document data 1310 is useful for osteoporosis. Next, the server's association identification module may derive associated patent document data 1322, 1324, and 1326 based on at least one of the third bio-analysis data 1313, 1314, 1315, 1316, and 1317 and bio-enterprise entity data 1312.

[0120] See also Figure 13B , which illustrates a schematic diagram of a specific embodiment of the drug trend analysis method of the present invention. Figure 13B As shown, the relevance identification module can derive associated scientific publication document data 1331-1336 based on at least one of the third biological analysis data 1313, 1314, 1315, 1316, and 1317 and / or the biological business entity data 1312. Furthermore, the analysis module can derive drug name data 1339 from the scientific publication document data 1332. It should be understood that the relevance identification module is not limited to deriving associated patent document data or scientific publication document data based on at least one of the third biological analysis data 1313, 1314, 1315, 1316, and 1317 and / or the biological business entity data 1312. The relevance identification module can also derive news document data, company report document data, etc. based on at least one of the third biological analysis data 1313, 1314, 1315, 1316, and 1317 and / or the biological business entity data 1312, but is not limited thereto.

[0121] See also Figure 13C , which illustrates a schematic diagram of a specific embodiment of the drug trend analysis method of the present invention. Figure 13C As shown, the analysis module can analyze the drug sequence 1340 in the clinical document data 1310 from the document data obtained by the correlation identification module. Thus, the correlation identification module can further associate various related document data 1351-1356 (in this example, patent document data, etc., but this is not limited to this). The drug trend analysis system can then analyze and predict the trend of this drug using the obtained biological analysis data, document data (such as, but not limited to, patent document data), and related data of the document data (such as the application date of the patent document data, applicant data, etc.).

[0122] The drug trend analysis system and method of the present invention have been described above and illustrated. However, it should be understood that the various embodiments of the present invention are for illustrative purposes only. Various modifications may be made without departing from the scope and spirit of the present invention and are intended to be encompassed by the scope of the present invention. Therefore, the various embodiments described in this specification are not intended to limit the present invention. The true scope and spirit of the present invention are set forth in the following claims.

[0123] Although the present invention has been disclosed above with reference to preferred embodiments, this is not intended to limit the present invention. Any person skilled in the art can modify and combine the various embodiments described above without departing from the spirit and scope of the present invention.

Claims

1. A drug trend analysis method, applied to a drug trend analysis system comprising a database and a server, wherein the server accesses the database; The drug trend analysis method comprises: An analysis module of the server analyzes a first file data to obtain a first bio-analysis data, a second bio-analysis data, and a plurality of third bio-analysis data; A correlation identification module of the server associates a third file data from the database based on at least one of the plurality of third bio-analysis data and the second bio-analysis data; and The association identification module associates the first bioanalysis data with the second bioanalysis data, the plurality of third bioanalysis data, and the third file data to identify new application areas of a predetermined drug or to identify existing available drugs for a predetermined disease; wherein the analysis module is communicatively connected to the relevance identification module; The first file data is clinical file data, the third file data is patent file data, the first biological analysis data is drug code data or drug name data, the second biological analysis data is biological enterprise entity data, and the third biological analysis data is one of drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, target data, structure data, species data, pathway data, and biological enterprise entity data.

2. The drug trend analysis method according to claim 1, further comprising: The analyzing module analyzes the first file data or the third file data to obtain ninth biological data; The association identification module associates a fourth file data from the database based on at least the ninth biological data; as well as The association identification module associates the first biological analysis data with the ninth biological data and the fourth file data.

3. The drug trend analysis method of claim 2, wherein the first biological analysis data is drug code data, the ninth biological data is drug name data, and the fourth file data is one of patent file data, clinical file data, scientific publication file data, news file data, and company report file data. 4 . The drug trend analysis method according to claim 2 , wherein the correlation identification module correlates the fourth file data from the database based on at least one of the plurality of third biological analysis data and the ninth biological data.

5. The drug trend analysis method according to claim 1, further comprising: The analyzing module analyzes the first file data to obtain a first biometric data and a second biometric data; The analyzing module analyzes a second file data to obtain a third biometric data and a fourth biometric data; The association identification module associates the first biometric data with the second biometric data, the third biometric data, the fourth biometric data, and the second file data according to an analysis result. 6 . The drug trend analysis method according to claim 5 , wherein the analysis result indicates that the similarity between the first biological data and the third biological data is greater than a predetermined similarity threshold.

7. The drug trend analysis method according to claim 6, wherein the first biological data and the third biological data are both gene sequence data or protein data, the second biological data are drug data, and the fourth biological data are disease data.

8. The drug trend analysis method according to claim 1, further comprising: generating, by an image rendering module of the server, third image data according to a fifth instruction from a first device, and providing the third image data to the first device; wherein the third image data includes the first biological analysis data, the second biological analysis data associated with the first biological analysis data, and the plurality of third biological analysis data; The image drawing module is communicatively connected to the analysis module and the relevance identification module.

9. A drug trend analysis system, characterized in that: The drug trend analysis system includes: a database; and a server, accessing the database, the server comprising: an analysis module that analyzes a first file data to obtain a first biological analysis data, a second biological analysis data, and a plurality of third biological analysis data; and a correlation identification module, configured to associate third file data from the database based on at least one of the plurality of third biological analysis data and the second biological analysis data, and to associate the first biological analysis data with the second biological analysis data, the plurality of third biological analysis data, and the third file data to identify new application areas for a drug or to identify existing available drugs for a disease; wherein the analysis module is communicatively connected to the relevance identification module; The first file data is clinical file data, the third file data is patent file data, the first biological analysis data is drug code data or drug name data, the second biological analysis data is biological enterprise entity data, and the third biological analysis data is one of drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, target data, structure data, species data, pathway data, and biological enterprise entity data.

10. The drug trend analysis system of claim 9, wherein the analysis module analyzes the first file data or the third file data to obtain a ninth biological data; wherein the association identification module associates a fourth file data from the database based on at least the ninth biological data; and wherein the association identification module associates the first biological analysis data with the ninth biological data and the fourth file data.

11. The drug trend analysis system of claim 10, wherein the first biological analysis data is drug code data, the ninth biological data is drug name data, and the fourth file data is one of patent file data, clinical file data, scientific publication file data, news file data, and company report file data. 12 . The drug trend analysis system of claim 10 , wherein the correlation identification module correlates the fourth file data from the database based on at least one of the plurality of third biological analysis data and the ninth biological data.

13. The drug trend analysis system according to claim 9, wherein the analysis module analyzes the first file data to obtain a first biological data and a second biological data; wherein the analysis module analyzes the second file data to obtain a third biological data and a fourth biological data; and wherein the correlation identification module converts the first biological data into a third biological data according to an analysis result. The first biometric data is associated with the second biometric data, the third biometric data, the fourth biometric data, and the second file data. 14 . The drug trend analysis system of claim 13 , wherein the analysis result indicates that the similarity between the first biological data and the third biological data is greater than a predetermined similarity threshold.

15. The drug trend analysis system according to claim 14, wherein the first biological data and the third biological data are both gene sequence data or protein data, the second biological data are drug data, and the fourth biological data are disease data.

16. The drug trend analysis system of claim 9, wherein the server comprises an image rendering module, wherein the image rendering module generates third image data according to a fifth instruction from a first device and provides the third image data to the first device; wherein the third image data comprises the first bio-analytical data and the second bio-analytical data and the plurality of third bio-analytical data associated with the first bio-analytical data; and wherein the image rendering module is communicatively connected to the analysis module and the correlation identification module.

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