WO2022002029A1

WO2022002029A1 - Drug trend analysis system and method therefor

Info

Publication number: WO2022002029A1
Application number: PCT/CN2021/103021
Authority: WO
Inventors: 乌玛尚卡尔·希夫尚卡尔; 库玛·庞卡; 坦·约西亚; 汉斯·马库斯
Original assignee: 智慧芽信息科技(苏州)有限公司
Priority date: 2020-06-29
Filing date: 2021-06-29
Publication date: 2022-01-06
Also published as: CN113934811A

Abstract

A drug trend analysis system, which can perform analysis targeting different biological file data (such as patents and scientific literature, but not limited thereto) to obtain a plurality of pieces of biological data (such as drug data and biological enterprise data, but not limited thereto), and can establish correlations between different biological data and/or biological file data. In addition, the drug trend analysis system can further generate correlation charts, statistical charts, etc. according to the correlations between the different biological data and/or biological file data, so as to assist a user with research and development (such as drug research and development, but not limited thereto), or assist the user with determining a research direction, a research and development strategy/direction, a business strategy or a business layout.

Description

Drug trend analysis system and method therefor

This application claims the priority of the Chinese patent application filed on June 29, 2020 with the application number 2020106052823 and the application name is "Drug Trend Analysis System and Method", the entire contents of which are incorporated in this application by reference .

technical field

The present application relates to a drug trend analysis system and method thereof, in particular to a drug trend analysis system and method that can analyze the correlation of biological data according to file data.

Background technique

The typical time from clinical trials to approved drugs is currently around 7 to 10 years. During this time, the relevant information may only appear in patent documents or other documents that are not easily discovered. Therefore, the relevant researchers or institutions may not be aware of the relevant information recorded in these documents. In addition, even if the relevant researchers or institutions find these documents, they may not be able to effectively understand the contents contained in the documents because of the excessive number of documents, the large or complicated data volume. In this regard, there will be a need for a drug trend analysis system and method that can assist in the preliminary analysis or statistics of the content of biological documents.

SUMMARY OF THE INVENTION

The purpose of the present application is to provide a drug trend analysis system and method that can assist in preliminary analysis or statistics of the content of biological documents, and the system and method can analyze the correlation of biological data according to document data.

The purpose of the present application is to provide a drug trend analysis system and method, which can analyze different biological document data (such as patents, scientific literature, etc., but not limited thereto) to obtain a plurality of biological data (such as drug data, biological enterprise data, etc., but not limited thereto), and can establish correlations between different biological data and/or biological file data.

The purpose of the present application is to provide a drug trend analysis system and method, which can further generate correlation charts, statistical charts, etc. according to the correlation between different biological data and/or biological file data, so as to assist users in research and development (such as drugs research and development, etc., but not limited thereto), or assist users in deciding their research direction, research and development strategy/direction, business strategy or business layout.

The above object of the present application is achieved by the following technical means.

A drug trend analysis method, applied to a drug trend analysis system comprising a database and a server, the server accessing the database; the drug trend analysis method comprising: analyzing first file data by an analysis module of the server to obtain the first bioanalytical data, the second bioanalytical data, and a plurality of third bioanalytical data; the association identification module of the server according to at least one of the plurality of third bioanalytical data and the second bioanalytical data data to associate third document data from the database; and associate the first bioanalytical data with the second bioanalytical data, the plurality of third bioanalytical data by the association identification module with the third file data; wherein the analysis module is communicatively connected to the association 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 The data is biological enterprise entity data.

In one embodiment, the plurality of third biological analysis data are drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, and target data, respectively. One of data, structural data, species data, pathway data, and bioenterprise entity data.

In one embodiment, the drug trend analysis method further includes: analyzing the first file data or the third file data by the analysis module to obtain ninth biological data; associating fourth document data from the database according to the ninth biometric data; and associating the first bioanalytical data with the ninth biometric data and the fourth document by the association identification module data.

In one embodiment, the first biological analysis data is drug code data, the ninth biological data is drug name data, and the fourth file data is patent file data, clinical file data, scientific publication file data , news file data, and company report file data.

In one embodiment, the association identification module associates the fourth file data from the database according to at least one of the plurality of third biometric data and the ninth biometric data.

In one embodiment, the drug trend analysis method further includes: analyzing the first file data by the analysis module to obtain first biological data and second biological data; analyzing the second file data by the analysis module to obtain the third biometric data and the fourth biometric data; the first biometric data is associated with the second biometric data, the third biometric data, the fourth biometric data by the correlation identification module according to the analysis result biological data and the second file data.

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.

In one embodiment, 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.

In one embodiment, the drug trend analysis method further includes: generating, by an image rendering module of the server, third image data according to a fifth instruction from the first device, and providing the third image data to the a first device; wherein the third image data includes the first bioanalytical data and the second bioanalytical data and the plurality of third bioanalytical data associated with the first bioanalytical data; wherein the The image rendering module is communicatively connected to the analysis module and the correlation identification module.

A drug trend analysis system includes: a database; and a server for accessing the database, the server comprising: an analysis module for analyzing first file data to obtain first biological analysis data, second biological analysis data and a plurality of third biological analysis data bioanalytical data; and a relevancy identification module for correlating third document data from the database according to at least one of the plurality of third bioanalytical data and the second bioanalytical data, the relevancy an identification module and associates the first bioanalytical data with the second bioanalytical data, the plurality of third bioanalytical data and the third file data; wherein the analysis module is in communication with the association identification module.

In one embodiment, the analysis module analyzes the first file data or the third file data to obtain ninth biometric data; wherein the association identification module obtains the data from the ninth biometric data at least according to the ninth biometric data. and the association identification module associates the first biological analysis data with the ninth biological data and the fourth document data.

In one embodiment, the analysis module analyzes the first file data to obtain the first biological data and the second biological data; wherein the analysis module analyzes the second file data to obtain the third biological data and the fourth biological data. biometric data; and wherein 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 the analysis result .

In one embodiment, the server includes an image rendering module that generates third image data according to a fifth instruction from the first device, and provides the third image data to the first device; wherein the third image data includes the first bioanalytical data and the second bioanalytical data and the plurality of third bioanalytical data associated with the first bioanalytical data; wherein the image rendering module The analysis module, the correlation identification module and the providing module are communicatively connected.

A 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 the second file data to obtain the third biometric data and the fourth biometric data; the correlation identification module associates the first biometric data with the second biometric data, the third biometric data, and the fourth biometric data according to the analysis result and said second file data; and providing a module for associating said first biometric data, said second biometric data associated with said first biometric data, said third biometric data according to a first instruction from a first device biometric data and the fourth biometric data are provided to the first device; wherein the first device is communicatively connected to the server; wherein the server transmits the first biometric data, the second biometric data, the The third biometric data and the fourth biometric data are stored in the database; wherein the analysis module is communicatively connected to the association identification module and the providing module; and wherein the association identification module is communicatively connected to the providing module .

In one embodiment, the database stores a plurality of biological data, and when the analysis module analyzes the first file data and the second file data, it is obtained according to at least one biological data among the plurality of biological data. The first biometric data or the second biometric data or the third biometric data or the fourth biometric data.

In one embodiment, 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 The third biometric data or the fourth biometric data.

In one embodiment, the first biological data, the second biological data, the third biological data and the fourth biological data are drug data, drug code data, drug name data, disease data, gene data, respectively. One of 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.

In one embodiment, the correlation identification module includes a second natural language processing module, and the correlation identification module obtains the analysis result through the second natural language processing module.

In one embodiment, associating the first biometric data with the second biometric data, the third biometric data, the fourth biometric data and the second file data according to the analysis result is performed by: The correlation identification module generates first correlation data according to the analysis result, and the server stores the first correlation data in the database; wherein the first correlation data is associated with the first biological body data, and the first association data indicates that the first biometric data is associated with the second biometric data, the third biometric data, the fourth biometric data, and the second file data.

In one embodiment, the server includes an image rendering module that generates first image data according to a second instruction from the first device, and provides the first image data to the first apparatus, said first image data comprising said first biometric data and said second biometric data, said third biometric data and said fourth biometric data associated with said first biometric data; wherein said image rendering A module communicatively connects the analysis module, the association identification module and the providing module.

In one embodiment, the association identification module associates the first biological data with the first file data and the second file data according to the analysis result.

In one embodiment, when the first biometric data, the second biometric data, the third biometric data, and the fourth biometric data are all associated with fifth biometric data, and the first biometric data, the When the second biometric data, the third biometric data, and the fourth biometric data are data of different contents, the association identification module generates the second association data and the third association data, and the server does not storing the second association data and the third association data to the database; wherein the second association data indicates that the first biometric data has a first association with the fourth biometric data; 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 biometric data of the same type, and the The second biometric data is the same type of biometric data as the fourth biometric data.

In one embodiment, the first biometric data and the third biometric data are drug data, and the second biometric data and the fourth biometric data are disease data.

In one embodiment, the database stores a plurality of biological data, and the server further includes a statistical module, the statistical module generates statistical data according to the plurality of biological data; wherein the providing module is based on data from the first device. The third instruction of provides the statistical data to the first device; wherein the statistical module communicatively connects the analysis module, the correlation identification module and the providing module.

In one embodiment, the server includes an image rendering module that generates second image data according to the statistical data; wherein the providing module renders the first image data according to a fourth instruction from the first device. Two image data are provided to the first device; wherein the image rendering module is communicatively connected to the analysis module, the correlation identification module, the statistics module and the providing module.

In one embodiment, the server further includes a biological data classification module, and the biological data classification module combines the first biological data, the second biological data and the second biological data with the third natural language processing module of the biological data classification module The data, the third biological data and the fourth biological data are classified; wherein the biological data classification module communicatively connects the analysis module, the correlation identification module and the providing module.

In one embodiment, the first document data and the second document data are one of patent document data, clinical document data, scientific publication document data, news document data, and company report document data, respectively.

A drug trend analysis method, applied to a drug trend analysis system comprising a database and a server, the server accessing the database; the drug trend analysis method comprising: analyzing first file data by an analysis module of the server to obtain The first biological data and the second biological data; the second file data is analyzed by the analysis module to obtain the third biological data and the fourth biological data; the first biological data, the second biological data are analyzed by the server data, the third biological data and the fourth biological data are stored in the database; the first biological data is associated with the first biological data according to the analysis result of the analysis module by the correlation identification module of the server the second biometric data, the third biometric data, the fourth biometric data and the second file data; and the first biometric data is converted by the providing module of the server according to the first instruction from the first device , the second biometric data, the third biometric data and the fourth biometric data associated with the first biometric data are provided to the first device; wherein the first device is communicatively connected to the server; Wherein the analysis module is communicatively connected with the correlation identification module and the providing module; wherein the correlation identification module is communicatively connected with the providing module.

In one embodiment, the database stores a plurality of biological data, and when the analysis module analyzes the first file data and the second file data, obtains the biological data according to at least one biological data of the plurality of biological data. to output the first biometric data or the second biometric data or the third biometric data or the fourth biometric data.

In one embodiment, associating the first biometric data with the second biometric data, the third biometric data, the fourth biometric data and the second file data according to the analysis result is performed by: The relevancy identification module generates first relevancy data according to the analysis result, and the server stores the first relevancy data in the database; wherein the first relevancy data is related to the first relevancy data biometric data, and the first association data indicates that the first biometric data is associated with the second biometric data, the third biometric data, the fourth biometric data, and the second file data.

In one embodiment, the drug trend analysis method further includes: generating, by an image rendering module of the server, first image data according to a second instruction from the first device, and providing the first image data to the first device, the first image data comprising the first biometric data and the second biometric data, the third biometric data and the fourth biometric data associated with the first biometric data; Wherein, the image rendering module is communicatively connected to the analysis module, the correlation identification module and the providing module.

In one embodiment, 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 when the first biometric data, the second biometric data, the third biometric data and the fourth biometric data are data of different contents, the association identification module generates the second association data and third association data, the server stores the second association data and the third association data in the database; wherein the second association data indicates that the first biological data is associated with the first biometric data Four biometric data has a first association; the third association data indicates that the third biometric data has a second association with the second biometric data; wherein the first biometric data and the third biometric data are the same type of biological data, and the second biological data and the fourth biological data are the same type of biological data.

In one embodiment, the database stores a plurality of biological data; the drug trend analysis method further comprises: generating, by a statistical module of the server, statistical data according to the plurality of biological data; The third instruction of the first device provides the statistical data to the first device; wherein the statistics module communicatively connects the analysis module, the correlation identification module and the providing module.

In one embodiment, the drug trend analysis method further includes: generating, by an image rendering module of the server, second image data according to the statistical data; and generating, by the providing module, based on fourth image data from the first device The instruction provides the second image data to the first device; wherein the image rendering module communicatively connects the analysis module, the correlation identification module, the statistics module and the providing module.

In one embodiment, the drug trend analysis method further comprises: by the biological data classification module of the server through the third natural language processing module of the biological data classification module, the first biological data, the second biological data The second biological data, the third biological data and the fourth biological data are classified; wherein the biological data classification module communicatively connects the analysis module, the correlation identification module and the providing module.

The foregoing and other aspects of the present application will be more apparent in light of the following detailed description of non-limiting specific examples and with reference to the accompanying drawings.

Description of drawings

FIG. 1 shows a system architecture diagram of the drug trend analysis system exemplified in the present application.

FIG. 2 is a partial screen diagram of the first device displaying biological data provided by the drug trend analysis system exemplified in the present application.

FIG. 3 is a partial screen diagram of the first device displaying biological data provided by the drug trend analysis system exemplified in the present application.

FIG. 4 shows a schematic diagram of part of the screen of the drug trend analysis system exemplified in the present application.

FIG. 5 is a partial screen schematic diagram of the drug trend analysis system exemplified in this application.

FIG. 6A is a partial screen schematic diagram of the drug trend analysis system exemplified in the present application.

FIG. 6B is a partial screen schematic diagram of the drug trend analysis system exemplified in the present application.

FIG. 6C is a partial screen diagram of the drug trend analysis system exemplified in the present application.

FIG. 6D is a partial screen diagram of the drug trend analysis system exemplified in the present application.

FIG. 7 is a partial screen schematic diagram of the drug trend analysis system exemplified in the application.

FIG. 8 is a partial screen schematic diagram of the drug trend analysis system exemplified in the application.

FIG. 9 is a partial screen schematic diagram of the drug trend analysis system exemplified in the application.

FIG. 10 is a schematic diagram of part of the screen of the drug trend analysis system of the example of the application.

FIG. 11 is a flow chart of the drug trend analysis method exemplified in the application.

FIG. 12 is a flow chart of the drug trend analysis method exemplified in the application.

FIG. 13A is a schematic diagram of a specific embodiment of the drug trend analysis method of the present application.

FIG. 13B is a schematic diagram of a specific embodiment of the drug trend analysis method of the present application.

FIG. 13C is a schematic diagram of a specific embodiment of the drug trend analysis method of the present application.

detailed description

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. In the event of conflict or inconsistency between definitions used herein and definitions contained in other publications, the definitions used herein shall control.

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 variation thereof, are It is intended to cover non-exclusive inclusions. For example, a composition, process, method, article or device containing a plurality of listed elements is not necessarily limited to only those listed elements, but may include compositions that are not expressly listed but are , process, method, article or other element inherent in the device.

Please refer to FIG. 1 , which illustrates a system architecture diagram of a drug trend analysis system according to an example of the present application. In the embodiment shown in FIG. 1 , the drug trend analysis system 100 includes a database 110 and a server 120 , wherein the database 110 stores a plurality of biological data, and the server 120 can access the database 110 . The 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 . The analysis module 121 includes a first natural language processing (NLP) module 121A, the correlation identification module 123 includes a second natural language processing module 123A, and the biological data classification module 126 includes a third natural language processing 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 , and 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 communicates with the connection analysis module 121, the association identification module 123, the statistics module 127 and the providing module 125, the biological data classification module 126 communicates with the connection analysis module 121, the association identification module 123, the statistics module 127, and the image rendering module 129 and provision module 125. In a specific embodiment, the drug trend analysis system 100 includes one or more processors, and implements the database 110 , the server 120 , the analysis module 121 , the first natural language processing module 121A, the correlation Sex recognition module 123 , second natural language processing module 123A, providing module 125 , biological data classification module 126 , third natural language processing module 126A, statistics module 127 and image rendering module 129 .

In the embodiment shown in FIG. 1 , the analysis module 121 analyzes the first file data to obtain the first biological data and the second biological data, and analyzes the second file data to obtain the third biological data and the fourth biological data. The server then stores the first biometric data, the second biometric data, the third biometric data and the fourth biometric data to the database 110 . In a specific embodiment, when analyzing the first file data and/or the second file data, the analysis module 121 obtains the first biological data and the second biological data according to at least one of the plurality of biological data stored in the database 110 , at least one of the third biometric data and the fourth biometric data. For example, in a specific embodiment, when a certain biological data stored in the database 110 is the same as the first biological data, the analysis module 121 can obtain the biological data stored in the database 110 by the biological data that is the same as the first biological data to generate (or analyze) the first biological data. In a specific embodiment, when the analysis module 121 analyzes the first document data and/or the second document data, the natural language processing module 121A is used to obtain the first biological data, the second biological data, the third biological data and the At least one of the fourth biometric data. In different 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 not limited thereto.

This application can also refer to the patent No. CN109448793A (the title of invention is "The right to gene sequence recognition, Retrieval and Infringement Determination Method”), Patent No. CN110413814A (named “Image Database Establishment Method, Search Method, Electronic Device and Storage Medium”), Patent No. US20180276340 (named “SYSTEM AND METHOD FOR DRUG TARGET AND BIOMARKER” DISCOVERY AND DIAGNOSIS USING A MULTIDIMENSIONAL MULTISCALE MODULE MAP") and US20190005395 (named "A METHOD AND SYSTEM FOR ONTOLOGY-BASED DYNAMIC LEARNING AND KNOWLEDGE INTEGRATION FROM MEASUREMENT DATA AND TEXT"), which are hereby incorporated by reference The entire contents of each of the aforementioned patents are incorporated herein.

In different embodiments, the first biological data and/or the second biological data and/or the third biological data and/or the fourth biological data may be drug data, drug code data, drug name data, disease data, genetic 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. For example, the first biological data can be a drug data, the second biological data can be a protein data, the third biological data can be a disease data, and the fourth biological data can be a biological enterprise entity data. Among them, the bio-enterprise entity may be a company, academic unit, institution, government agency or individual, but not limited thereto, for example, a bio-enterprise entity may be an applicant for a drug patent (this applicant may be an individual, a company or an organization, etc. ). In another specific embodiment, the first biometric data or the second biometric data or the third biometric data or the fourth biometric data can also be other bio-related data.

In the embodiment shown in FIG. 1 , the association identification module 123 associates the first biometric data with the second biometric data, the third biometric data and the fourth biometric data according to the analysis result. In a specific embodiment, the correlation identification module 123 obtains the analysis result through the second natural language processing module 123A. In a specific embodiment, the analysis result of the correlation identification module 123 is that both the first biometric data and the second biometric data come from the first file data. Accordingly, the association identification module 123 associates the first biometric data with the second biometric data according to the analysis result. In a specific embodiment, the analysis result of the correlation identification module 123 is that the content of the second biometric data and the third biometric data are the same, the first biometric data and the second biometric data are both from the first file data, and the third biometric data and the fourth biometric data are all derived from the second file data. Accordingly, the association identification module 123 associates the first biometric data with the second biometric data, the third biometric data and the fourth biometric data according to the analysis result, and associates the first file data with the second file data. In a specific embodiment, the analysis result of the association identification module 123 is that the second biometric data is associated with the third biometric data (for example, the database stores a association data indicating that the second biometric data is associated with the third biometric data) , the first biometric data and the second biometric data both come from the first file data, and the third biometric data and the fourth biometric data both come from the second file data. Accordingly, the association identification module 123 associates the first biometric data with the second biometric data, the third biometric data and the fourth biometric data according to the analysis result, and associates the first file data with the second file data.

In a specific embodiment, associating the first biometric data with the second biometric data, the third biometric data and the fourth biometric data according to the analysis result is performed by the association identification module 123 to generate the first association according to the analysis result The server 120 stores the first correlation data in the database 110 . The first correlation data is related to the first biological data, and the first correlation data indicates that the first biological data is related to the second biological data, the third biological data and the fourth biological data. In a specific embodiment, the first association data includes three association data, which respectively indicate that the first biometric data is related to the second biometric data, the first biometric data is related to the third biometric data and the first biometric data A relationship is associated with the fourth biological data.

In the embodiment shown in FIG. 1 , the providing module 125 associates the first biometric data with the second biometric data and the third biometric data associated with the first biometric data according to the first instruction from the first device (not shown). The fourth biometric data is provided to the first device. The first device is communicatively connected to the server 120 . In different specific embodiments, the first device may be a desktop computer, a smart phone, or a notebook computer, but not limited thereto. In a specific embodiment, the first instruction is an instruction of the user to take the first biological data as a retrieval target or an analysis target. In a specific embodiment, the association identification module 123 associates the first biological data with the first file data and the second file data according to the analysis result. In this way, the providing module 125 provides the first biometric data, the second biometric data, the third biometric data and the fourth biometric data associated with the first biometric data to the first biometric data according to the first instruction from the first device (not shown). When a device is used, the first file data and the second file data associated with the first biological data can be provided to the first device according to the file providing instruction from the first device (or the first file data and the second file data can be directly provided. The two file data are provided to the first device without the need for the first device to additionally input a file providing instruction).

In the embodiment shown in FIG. 1 , the biological data classification module 126 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 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 and/or the second biological data and/or the third biological data and/or the fourth biological data as drugs data, disease data, gene data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, target data, structure data, species data, pathway data and One of the biological enterprise entity data.

In the embodiment shown in FIG. 1 , the image rendering module 129 generates the first image data according to the second instruction from the first device, and provides the first image data to the first device (in different specific embodiments, by providing The module 125 or the image rendering module 129 provides the first image data to the first device). Wherein, the first image data includes the first biometric data and second biometric data, third biometric data and fourth biometric data associated with the first biometric data. In a specific embodiment, when the first image data is displayed, the first image data also shows that the first biometric data is related to the second biometric data, the third biometric data and the fourth biometric data. In a specific embodiment, the first image data is a knowledge structure graph.

In a specific embodiment, 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, and the third biometric data When the fourth biometric data is data of different content, the association identification module 123 generates the second association data and the third association data, and the server 120 stores the second association data and the third association data in the database 110 . The second correlation data indicates that the first biological data has a first correlation with the fourth biological data, and the third correlation data indicates that the third biological data has a second correlation with the second biological data. 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. In a specific embodiment, the first biometric data and the third biometric data are drug data, and the second biometric data and the fourth biometric data are disease data. The first association indicates that the first biometric data may be applicable to the fourth biometric data, and the third association data indicates that the third biometric data may be applicable to the second biometric data. Therefore, the correlation identification module 123 can find out the possible new application fields of a certain medicine according to different file data.

In a specific 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 a great similarity or correlation . In a specific embodiment, the first biological data and the third biological data are both gene sequence data, the second biological data is drug data (eg, drug name data or drug code data), and the fourth biological data is disease data. In another specific embodiment, the first biological data and the third biological data are both protein data, the second biological data is drug data (eg, 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 the possible new application fields of a certain medicine according to different file data, or can find out the existing medicines that may be useful for a certain disease (eg, COVID 19 (Coronavirus Disease)). .

In the embodiment shown in FIG. 1 , the statistics module 127 generates statistical data (this is the first statistical data) according to a plurality of biological data stored in the database 110 . The providing module 125 may provide the statistical data to the first device according to the third instruction from the first device. In a specific embodiment, the image rendering module 129 may generate the second image data according to the statistical data. The providing module may provide the second image data to the first device according to the fourth instruction from the first device. In a specific embodiment, the database 110 also stores a plurality of file data. The statistics module 127 may generate the second statistical data according to the plurality of document 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 according to an instruction of the first device. The providing module 125 may provide the second statistical data to the first device according to another instruction of the first device. In a specific embodiment, the second image data is a knowledge structure graph.

In the embodiment shown in FIG. 1 , the analysis module 121 may analyze the first document data to obtain first bioanalytical data, second bioanalytical data and a plurality of third bioanalytical data. The association identification module 123 can associate the third document data from the database 110 according to at least one of the plurality of third bioanalytical data and the second bioanalytical data. The association identification module 123 further associates the first bioanalytical data with the second bioanalytical data, the plurality of third bioanalytical data, and the third document data. In a specific embodiment, the first file data is clinical file data, the third file data is patent file data, the first bioanalysis data is drug data (for example, it can be drug code data or drug name data), and the second bioanalysis data is drug data. The data is biological enterprise entity data. In a specific embodiment, the plurality of third biological analysis data are respectively drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, label data. One of target data, structural data, species data, pathway data, and bioenterprise entity data.

In a specific embodiment, the analysis module 121 may analyze the first file data or the third file data to derive ninth biological data. The correlation identification module 123 can associate the fourth document data from the database 110 according to at least the ninth biological data, and the correlation identification module 123 can associate the first biological analysis data with the ninth biological data and the fourth document data . In a specific embodiment, the first biological analysis data is drug code data, and the ninth biological data is drug name data. The fourth document data is one of patent document data, clinical document data, scientific publication document data, news document data, and company report document data. In a specific embodiment, the association identification module 123 can associate the fourth document data from the database 110 according to at least one of the plurality of third biometric analysis data and the ninth biometric data.

In a specific embodiment, the analysis module 121 may analyze the first document data to obtain the first biological data and the second biological data. The analysis module 121 can analyze the second file data to obtain the third biological data and the fourth biological data. The association identification module 123 can associate the first biometric data with the second biometric data, the third biometric data, the fourth biometric data and the second file data according to the analysis result. In a specific embodiment, the analysis result indicates that the similarity between the first biometric data and the third biometric data is greater than a predetermined similarity threshold, which means that the first biometric data and the third biometric data have a great similarity or Relevance. In a specific embodiment, the first biological data and the third biological data are both gene sequence data, the second biological data is drug data (eg, drug name data or drug code data), and the fourth biological data is disease data. In another specific embodiment, the first biological data and the third biological data are both protein data, the second biological data is drug data (eg, 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 the possible new application fields of a certain medicine according to different file data, or can find out the existing medicines that may be useful for a certain disease (eg, COVID 19 (Coronavirus Disease)) .

In a specific embodiment, the image rendering module 129 of the server 120 may generate the third image data according to the fifth instruction from the first device, and provide the third image data to the first device. The third image data includes first bioanalytical data and second bioanalytical data and a plurality of third bioanalytical data associated with the first bioanalytical data. In a specific embodiment, the third image data further includes ninth biological data, first file data, third file data and fourth file data.

Please refer to FIG. 2 , which illustrates a partial screen diagram of the first device displaying the biological data provided by the drug trend analysis system of the example of the present application. As shown in FIG. 2, 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 and the third biometric data according to the first instruction 212 from the first device. The biometric data, the fourth biometric data, and the first file data and the second file data associated with the first biometric data are provided to the first device. FIG. 2 shows a picture displayed on the display of the first device. The link 211 includes the first biological data, the link 213 includes the second biological data, the link 215 includes the third biological data, the link 217 includes the fourth biological data, the link 214 includes the first file data, and the link 216 includes the first file data. Include second file data.

Please refer to FIG. 3 , which illustrates a partial screen diagram of a specific embodiment in which the first device displays the biological data provided by the drug trend analysis system of the present application. As shown in FIG. 3 , when the first device provides the first instruction to the drug trend analysis system, the providing module of the drug trend analysis system converts the first biological data, the second biological data associated with the first biological data, The third biometric data, the fourth biometric data, and the first and second file data associated with the first biometric data are provided to the first device. FIG. 3 shows a picture displayed on the display of the first device. The link 312 includes the first biometric data, the link 314 includes the second biometric data and the third biometric data, the link 316 includes the fourth biometric data, and the link 311 includes the first file data and the second file data.

Please refer to FIG. 4 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present application. In the embodiment shown in FIG. 4 , since the biological data classification module classifies each biological data, the user can search or query the biological data through the links 411 - 417 , and can search or query the document data through the links 421 - 423 . It should be understood that the picture of the drug trend analysis system can be displayed on the display of the first device.

Please refer to FIG. 5 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present application. As shown in FIG. 5 , because the drug trend analysis system has classified biological data through the biological data classification module, and has generated the first statistical data and the second statistical data according to the biological data and the document data through the statistical module, so as to achieve various differences analysis. Therefore, the user can view different analysis results through the links 511-516.

Please refer to FIG. 6A to FIG. 6D , which illustrate some schematic diagrams of different specific embodiments of the drug trend analysis system of the present application. As shown in the figure, because the drug trend analysis system has classified the biological data through the biological data classification module, and has generated the first statistical data and the second statistical data according to the biological data and the file data through the statistical module, so as to achieve various analyze. Therefore, the user can view different analysis results or statistical results by selection. For example, one may choose to view analysis or statistics of patent document data (eg, see images 611, 612), or may choose to view analysis or statistics of ontology biological data (eg, see image 613), or may choose to view drugs Analytical results or statistical results of biological data of drug classes (see eg image 614), or optionally viewing analytical results or statistical results of biological data of the clinical trial study phase (see eg image 615), or Option to view analytical results or statistics of biological data of drug target classes (see eg image 616), or option to view analytical results or statistical results of biological data of drugs (eg see

images

621, 622, 624) , or optionally to view analysis results or statistical results of functional pointer biometric data (see, eg, image 623).

Please refer to FIG. 7 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present application. As shown in Figure 7, the user can know from the image 713 that the drug trend analysis analyzes the ventricular biological data according to the data of multiple files and is related to 123 literature file data, 265 patent file data, 422 news file data, 54 serial number biological data data, 23 compound biological data, 87 clinical trial biological data, and 25 drug data. The user can view the target biological data, drug biological data, and patent document data simultaneously associated with the ventricular biological data and the left ventricular biological data according to the

images

715 , 717 , and 719 between the image 711 and the image 713 , respectively.

Please refer to FIG. 8 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present application. As shown in FIG. 8 , the statistics module of the drug trend analysis system can count the number of occurrences of different biological data in the file data of different companies in different years, and then generate a plurality of corresponding statistical data. The image drawing module of the drug trend analysis system can generate the second image 810 according to the statistical data. Among them, the point 812 in the 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 (the darker the color, the more appearance). more times). The point 814 in the image 810 indicates the number of times the disease data "virus disease" appeared in the document data associated with the bio-enterprise entity data "GSK Corporation" in 2011 (lighter colors indicate occur less frequently).

Please refer to FIG. 9 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present application. As shown in FIG. 9 , the statistics module of the drug trend analysis system can count the number of clinical trials of different biological enterprise entities for different biological data, and then generate a plurality of corresponding statistical data. The image drawing module of the drug trend analysis system can generate the second image 910 according to the statistical data. The section 912 in the image 910 indicates the number of clinical trials of the biological enterprise entity data "Merk Sharp & Dohme Corp." for the disease data "gastrointestinal disease".

Please refer to FIG. 10 , which illustrates a partial screen diagram of a specific embodiment of the drug trend analysis system of the present application. As shown in FIG. 10 , the image 1010 displays the first biometric data 1011 and the second biometric data 1012 , the third biometric data 1013 and the fourth biometric data 1014 associated with the first biometric data 1011 . Image 1010 and arrows 1016 indicate that the second biometric data 1012 is associated with the first biometric data 1011, arrows 1017 indicate that the third biometric data 1013 is associated with the first biometric data 1011, and arrows 1018 indicate that the fourth biometric data 1014 is associated with the first biometric data 1011 Biodata 1011.

Please refer to FIG. 11 , which illustrates a flow chart of a specific embodiment of the drug trend analysis method of the present application. As shown in FIG. 11 , 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 the server includes an analysis module, a correlation identification module, and a provision module. The module is communicatively connected to the correlation identification module and the providing module, the correlation identification module is communicatively connected to the providing module, and the server is communicatively connected to the first device. The drug trend analysis method 1100 starts at step 1110, where the analysis module of the server analyzes the first file data to obtain the first biological data and the second biological data. Next, in step 1120, the analysis module analyzes the second file data to obtain the third biological data and the fourth biological data. Next, in step 1130, the server stores the first biometric data, the second biometric data, the third biometric data and the fourth biometric data in the database.

In a specific embodiment, the database stores a plurality of biological data, and when analyzing the first file data and the second file data, the analysis module obtains the first biological data and/or the second biological data according to at least one of the plurality of biological data data and/or third biometric data and/or fourth biometric data. In a specific embodiment, the analysis module includes a first natural language processing module, and the analysis module obtains the first biological data and/or the second biological data and/or the third biological data and/or the natural language processing module through the natural language processing module. or fourth biometric data.

In a specific embodiment, the first biological data, the second biological data, the third biological data and the fourth biological data are drug data, drug code data, drug name data, disease data, gene data, gene sequence data, protein data, respectively. One of data, enzyme data, organism data, cell line data, cell bank serial number data, target data, structure data, species data, pathway data, and bioenterprise 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 biological enterprise entity data. Among them, the biological enterprise entity may be a company, an academic unit, an institution, a government agency or an individual, but not limited thereto. In another specific embodiment, the first biometric data or the second biometric data or the third biometric data or the fourth biometric data can also be other bio-related data.

Next, go to step 1140, the association identification module of the server associates the first biometric data with the second biometric data, the third biometric data and the fourth biometric data according to the analysis result. In a specific embodiment, the correlation identification module includes a second natural language processing module, and the correlation identification module obtains the analysis result through the second natural language processing module. In a specific embodiment, the associating the first biological data with the second biological data, the third biological data and the fourth biological data according to the analysis result is that the correlation identification module generates the first correlation data according to the analysis result, The server stores the first association data to the database. 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 biometric data, the third biometric data and the fourth biometric data. In a specific embodiment, the association identification module associates the first biological data with the first file data and the second file data according to the analysis result.

Next, go to step 1150, the providing module of the server provides the first biometric data, the second biometric data related to the first biometric data, the third biometric data and the fourth biometric data to the user according to the first instruction from the first device. first device.

In a specific embodiment, the server of the drug trend analysis system includes an image drawing module, and the image drawing module communicates with the analysis module, the correlation identification module and the providing module. The drug trend analysis method further includes the steps of: generating, by an image rendering module of the server, first image data according to a second instruction from the first device, and providing the first image data to the first device. The first image data includes first biometric data and second biometric data, third biometric data and fourth biometric data associated with the first biometric data.

In a specific 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 related to the fifth biological data, and the first biological data, When the second biometric data, the third biometric data, and the fourth biometric data are data of different contents, the association identification module generates the second association data and the third association data, and the server stores the second association data and the third association data. The relational data is stored in the database. The second correlation data indicates that the first biological data has a first correlation with the fourth biological data, and the third correlation data indicates that the third biological data has a second correlation with the second biological data. 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. For example, in a specific 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.

In a specific embodiment, the database stores a plurality of biological data, and the server of the drug trend analysis system includes a statistics module and an image drawing module. The statistics module communicates and connects the analysis module, the correlation identification module and the providing module, and the image drawing module communicates and connects the analysis module, the correlation identification module, the statistics module and the providing module. The drug trend analysis method further includes the following steps: generating statistical data according to a plurality of biological data by a statistical module of the server; providing the statistical data to the first device by the providing module according to a third instruction from the first device; image drawing module of the server generating second image data according to the statistical data; and providing, by the providing module, the second image data to the first device according to a fourth instruction from the first device.

In a specific embodiment, the server of the drug trend analysis system includes a biological data classification module, wherein the biological data classification module communicates with the analysis module, the correlation identification module and the providing module. The drug trend analysis method further includes the following steps: the first biological data, the second biological data, the third biological data and the fourth biological data are processed by the biological data classification module of the server through the third natural language processing module of the biological data classification module. Classification.

In a specific embodiment, the analysis result indicates that the similarity between the first biometric data and the third biometric data is greater than a predetermined similarity threshold, which indicates that the first biometric data and the third biometric data have a great similarity or correlation sex. In a specific embodiment, the first biological data and the third biological data are both gene sequence data, the second biological data is drug data (eg, drug name data or drug code data), and the fourth biological data is disease data. In another specific embodiment, the first biological data and the third biological data are both protein data, the second biological data is drug data (eg, 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 the possible new application fields of a certain medicine according to different file data, or can find out the existing medicines that may be useful for a certain disease (eg, COVID 19 (Coronavirus Disease)). .

Please refer to FIG. 12 , which illustrates a flow chart of a specific embodiment of the drug trend analysis method of the present application. As shown in FIG. 12, a drug trend analysis method 1200 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 1200 starts at step 1210, and the analysis module of the server analyzes the first file data to obtain first bioanalytical data, second bioanalytical data and a plurality of third bioanalytical data. Next, go to step 1120, the association identification module of the server associates the third file data from the database according to at least one of the plurality of third bioanalysis data and the second bioanalysis data. Next, go to step 1130 , the association identifying module associates the first bioanalytical data with the second bioanalytical data, a plurality of third bioanalytical data and the third file data. The analysis module communicates with the correlation identification module. In a specific embodiment, the first file data is clinical file data, the third file data is patent file data, the first bio-analysis data is drug code data or drug name data, and the second bio-analysis data is bio-enterprise entity data. In a specific embodiment, the plurality of third biological analysis data are respectively drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, cell bank serial number data, and target data. , structural data, species data, pathway data, and one of bioenterprise entity data.

In a specific embodiment, the drug trend analysis method 1200 further includes: analyzing the first file data or the third file data by the analyzing module to obtain ninth biological data; and correlate the fourth file data with the correlation identification module; and correlate the first biological analysis data with the ninth biological data and the fourth file data by the correlation identification module. In a specific embodiment, the first biological analysis data is drug code data, and the ninth biological data is drug name data. The fourth document data is one of patent document data, clinical document data, scientific publication document data, news document data and company report document data. In a specific embodiment, the association identification module associates the fourth document data from the database according to at least one of the plurality of third biometric analysis data and the ninth biometric data.

In a specific embodiment, the drug trend analysis method 1200 further includes: analyzing the first file data by the analysis module to obtain the first biological data and the second biological data; analyzing the second file data by the analysis module to obtain the third biological data data and the fourth biological data; the correlation 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 the analysis result. In a specific embodiment, the analysis result indicates that the similarity between the first biometric data and the third biometric data is greater than a predetermined similarity threshold, which means that the first biometric data and the third biometric data have a great similarity or correlation sex. In a specific embodiment, the first biological data and the third biological data are both gene sequence data, the second biological data is drug data (eg, drug name data or drug code data), and the fourth biological data is disease data. In another specific 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 the possible new application fields of a certain medicine according to different file data, or can find out the existing medicines that may be useful for a certain disease (eg, COVID 19 (Coronavirus Disease)). .

In a specific embodiment, the drug trend analysis method 1200 further includes: generating, by the image rendering module of the server, third image data according to the fifth instruction from the first device, and providing the third image data to the first device. The third image data includes first bioanalytical data and second bioanalytical data and a plurality of third bioanalytical data associated with the first bioanalytical data. And wherein the image drawing module communicates with the analysis module and the correlation identification module. In a specific embodiment, the third image data further includes ninth biological data, first file data, third file data and fourth file data.

Please refer to FIG. 13A , which illustrates a schematic diagram of a specific embodiment of the drug trend analysis method of the present application. As shown in FIG. 13A , the analysis module of the server can first analyze the drug code data 1311 , the biological enterprise entity data 1312 and the third

biological analysis data

1313 , 1314 , 1315 , 1316 and 1317 from the clinical file data 1310 . The clinical file data 1310 is the first file data, the drug code data 1311 is the first bioanalysis data, and the biological enterprise entity data 1312 is the second bioanalysis data. The third bioanalytical data 1313 is disease data indicating that the drugs in the clinical file data 1310 are available for osteoporosis. Then, the association identification module of the server can obtain the associated patent document data 1322 , 1324 , 1326 according to at least one of the third

biometric analysis data

1313 , 1314 , 1315 , 1316 , and 1317 and the biological enterprise entity data 1312 .

Please refer to FIG. 13B , which illustrates a schematic diagram of a specific embodiment of the drug trend analysis method of the present application. As shown in FIG. 13B , the association identification module may derive associated scientific publication file data 1331- 1336. And drug name data 1339 may be derived from scientific publication file data 1332 by the analysis module. It should be understood that the association identification module may not only derive the associated patent document data or scientific publication document from at least one of the third

bioanalytical data

1313 , 1314 , 1315 , 1316 , 1317 and/or the biological enterprise entity data 1312 Data, the correlation identification module can also obtain news file data, company report file data, etc. according to at least one of the third

bioanalytical data

1313, 1314, 1315, 1316, 1317 and/or the bio-enterprise entity data 1312. This is limited.

Please refer to FIG. 13C , which illustrates a schematic diagram of a specific embodiment of the drug trend analysis method of the present application. As shown in FIG. 13C , the analysis module can analyze the sequence 1340 of drugs in the clinical document data 1310 from the document data obtained by the association identification module. In this way, the correlation identification module can further correlate various related document data 1351-1356 (in this example, patent document data, etc., but it is not limited in practice). Then, the drug trend analysis system can use the obtained bioanalytical data, document data (such as patent document data, etc., but not limited thereto) and related data of document data (such as the filing date of patent document data, applicant, etc.) data) to analyze and predict trends for this drug.

So far, the drug trend analysis system and method of the present application have been described by the above description and drawings. However, it should be understood that the specific embodiments of the present application are only for illustration, and various changes can be made without departing from the scope and spirit of the patent application of the application, and should be included in the patent scope of the application. Therefore, the specific embodiments described in this specification are not intended to limit the application, and the true scope and spirit of the application are disclosed in the scope of the appended claims.

Although the present application has been disclosed above with preferred embodiments, it is not intended to limit the present application. Any person skilled in the art can change and combine the above-mentioned various embodiments without departing from the spirit and scope of the present application. .

Claims

A drug trend analysis method is applied to a drug trend analysis system comprising a database and a server, and the server accesses the database; the drug trend analysis method comprises:

Analyzing the first file data by the analysis module of the server to obtain first bioanalytical data, second bioanalytical data and a plurality of third bioanalytical data;

Correlating third document data from the database by the association identification module of the server according to at least one of the plurality of third bioanalytical data and the second bioanalytical data; and

associating the first bioanalytical data with the second bioanalytical data, the plurality of third bioanalytical data, and the third file data by the correlation identification module;

Wherein the analysis module is communicatively connected to the correlation identification module.
The drug trend analysis method according to claim 1, wherein the first file data is clinical file data, the third file data is patent file data, and the first biological analysis data is drug code data or drug name data , the second biological analysis data is biological enterprise entity data.
The drug trend analysis method according to claim 1, wherein the plurality of third biological analysis data are drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, One of cell bank serial number data, target data, structural data, species data, pathway data, and bioenterprise entity data.
The drug trend analysis method of claim 1, further comprising:

analyzing the first file data or the third file data by the analysis module to derive ninth biological data;

by the association identification module to associate fourth document data from the database based on at least the ninth biometric data; and

The first bioanalytical data is associated with the ninth biometric data and the fourth file data by the association identification module.
The drug trend analysis method according to claim 4, wherein the first biological analysis data is drug code data, the ninth biological data is drug name data, and wherein the fourth document data is patent document data, clinical document data One of data, scientific publication file data, news file data, and company report file data.
The drug trend analysis method according to claim 4, wherein the correlation identification module is based on at least one of the plurality of third biological analysis data and the ninth biological data to correlate all the data from the database. Describe the fourth file data.
The drug trend analysis method of claim 1, further comprising:

Analyzing the first file data by the analysis module to obtain first biological data and second biological data;

analyzing the second file data by the analysis module to obtain third biological data and fourth biological 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 the analysis result.
The drug trend analysis method of claim 7, 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.
The drug trend analysis method according to claim 8, wherein the first biological data and the third biological data are both gene sequence data or both are protein data, the second biological data is drug data, and the first biological data is drug data. Four biological data are disease data.
The drug trend analysis method of claim 1, further comprising:

generating third image data by an image rendering module of the server according to a fifth instruction from the first device, and providing the third image data to the first device;

wherein the third image data includes the first bioanalytical data and the second bioanalytical data and the plurality of third bioanalytical data associated with the first bioanalytical data;

Wherein, the image rendering module is communicatively connected to the analysis module and the correlation identification module.
A drug trend analysis system including:

database; and

A server, accessing the database, the server comprising:

an analysis module that analyzes the first file data to obtain first bioanalytical data, second bioanalytical data and a plurality of third bioanalytical data; and

A correlation identification module, according to at least one of the plurality of third biological analysis data and the second biological analysis data, to correlate third file data from the database, the correlation identification module and the the first bioanalytical data is associated with the second bioanalytical data, the plurality of third bioanalytical data and the third file data;

Wherein the analysis module is communicatively connected to the correlation identification module.
The drug trend analysis system of claim 11, wherein the first file data is clinical file data, the third file data is patent file data, and the first bioanalysis data is drug code data or drug name data , the second biological analysis data is biological enterprise entity data.
The drug trend analysis system according to claim 11, wherein the plurality of third biological analysis data are drug data, disease data, gene data, gene sequence data, protein data, enzyme data, organism data, cell line data, One of cell bank serial number data, target data, structural data, species data, pathway data, and bioenterprise entity data.
The drug trend analysis system of claim 11, wherein the analysis module analyzes the first file data or the third file data to derive ninth biological data; wherein the correlation identification module is based on at least the The ninth biological data is associated with fourth document data from the database; and wherein the association identification module associates the first biological analysis data with the ninth biological data and the fourth document data.
The drug trend analysis system according to claim 14, wherein the first biological analysis data is drug code data, the ninth biological data is drug name data, wherein the fourth document data is patent document data, clinical document data One of data, scientific publication file data, news file data, and company report file data.
15. The drug trend analysis system of claim 14, wherein the correlation identification module correlates all the data from the database according to at least one of the plurality of third biological analysis data and the ninth biological data Describe the fourth file data.
The drug trend analysis system of claim 11, wherein the analysis module analyzes the first file data to derive first biological data and second biological data; wherein the analysis module analyzes the second file data to derive the third biometric data and the fourth biometric data; and wherein the association identification module associates the first biometric data with the second biometric data, the third biometric data, and the fourth biometric data according to the analysis result with the second file data.
The drug trend analysis system of claim 17, 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.
The drug trend analysis system according to claim 18, wherein the first biological data and the third biological data are both gene sequence data or both are protein data, the second biological data is drug data, and the first biological data is drug data. Four biological data are disease data.
The drug trend analysis system of claim 11, wherein the server comprises an image rendering module, the image rendering module generates third image data according to the fifth instruction from the first device, and provides the third image data to the first device; wherein the third image data includes the first bioanalytical data and the second bioanalytical data and the plurality of third bioanalytical data associated with the first bioanalytical data ; wherein the image rendering module is communicatively connected to the analysis module, the correlation identification module and the providing module.