WO2022111720A1 - 药物开发分析方法、装置、电子设备和存储介质 - Google Patents

药物开发分析方法、装置、电子设备和存储介质 Download PDF

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WO2022111720A1
WO2022111720A1 PCT/CN2021/134234 CN2021134234W WO2022111720A1 WO 2022111720 A1 WO2022111720 A1 WO 2022111720A1 CN 2021134234 W CN2021134234 W CN 2021134234W WO 2022111720 A1 WO2022111720 A1 WO 2022111720A1
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information set
information
target
clinical trial
drug
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PCT/CN2021/134234
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English (en)
French (fr)
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周立运
秦云贺
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北京华彬立成科技有限公司
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H70/00—ICT specially adapted for the handling or processing of medical references
    • G16H70/40—ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2282—Tablespace storage structures; Management thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/288—Entity relationship models
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B15/00—ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
    • G16B15/30—Drug targeting using structural data; Docking or binding prediction
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics

Definitions

  • the present application relates to the technical field of data processing, and in particular, to a drug development analysis method, device electronic device and storage medium.
  • the present application aims to solve one of the technical problems in the related art at least to a certain extent.
  • the first purpose of this application is to propose a drug development analysis method, which establishes the correlation analysis between time, drug target and disease, and generates a target R&D heat map, which can be clearly defined. It reflects the changing trend of research and development hotspots in a certain disease field within a certain period of time, which has important reference significance for innovative drug development companies to quickly understand the mainstream development direction of a certain field, and solve the problems of existing technologies that are limited by data integrity or personal cognition, and consume Time-consuming technical issues.
  • the second object of the present application is to propose a drug development analysis device.
  • the third object of the present application is to propose a computer device.
  • a fourth object of the present application is to propose a non-transitory computer-readable storage medium.
  • a fifth object of the present application is to propose a computer program product.
  • the first aspect embodiment of the present application proposes a drug development analysis method, including:
  • Obtain the indication information query instruction obtain the drug information set corresponding to the indication information, and the clinical trial registration number information set and clinical trial start time information set corresponding to the drug information set from the pre-established data relationship table , the overall evaluation information set and the approval time information set;
  • the drug development analysis method of the embodiment of the present application obtains the indication information query instruction; obtains the drug information set corresponding to the indication information and the clinical trial registration number information set corresponding to the drug information set from the pre-established data relationship table , clinical trial start time information set, overall evaluation information set and approval time information set; according to the drug target relationship map, obtain the target information set corresponding to the drug information set; the clinical trial registration number information set corresponding to the drug information set, The clinical trial start time information set, the overall evaluation information set and the approval time information set are determined as the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set corresponding to the target information set; Analyze the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set, and obtain the analysis results of each target in the target information set.
  • the target R&D heat map can clearly reflect the changing trend of research and development hotspots in a certain disease field in a certain period of time. It is of great reference significance for innovative drug development companies to quickly understand the mainstream development direction in a certain field, and to solve the technical problems that are limited by data integrity or personal cognition, and are time-consuming and labor-intensive in the existing technology.
  • the obtaining the indication information query instruction before the obtaining the indication information query instruction, it further includes:
  • the acquiring data information of different information sources, analyzing the data information, and establishing a data relationship table include:
  • a third data relationship table is established after standardizing the drug information, indication information, original clinical result information and time information set obtained from the third information source.
  • the drug development analysis method further includes:
  • the third data relationship table is updated according to the marked clinical result and the time information set to determine the overall evaluation information set.
  • the drug development analysis method further includes:
  • the data relationship table is updated by acquiring the data information of the different information sources.
  • the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set, and the approval time information set are analyzed to obtain the The analysis results of each target in the target information set, including:
  • Each element in another feature area in the secondary table is the number of overall evaluations corresponding to each target, and the N-year overall evaluation of each target in the target information set is obtained as the total number of first evaluation categories, and each target is obtained.
  • the N-year overall evaluation of each target is the total number of the second evaluation category, and the clinical trial risk is the ratio of the total number of the second evaluation category to the total number of the first evaluation category, and a final table is generated.
  • the second aspect of the present application provides a drug development and analysis device, including:
  • the first obtaining module is used to obtain an indication information query instruction; obtain a drug information set corresponding to the indication information and a clinical trial registration number information set corresponding to the drug information set from the pre-established data relationship table , clinical trial start time information set, overall evaluation information set and approval time information set;
  • the second acquisition module is configured to acquire the target information set corresponding to the drug information set according to the drug target relationship map;
  • a determination module configured to determine the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set corresponding to the drug information set as the clinical trial registration corresponding to the target information set number information set, clinical trial start time information set, overall evaluation information set and approval time information set;
  • the analysis module is configured to analyze the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set, and the approval time information set, and obtain each of the target information sets. Target analysis results.
  • the drug development and analysis device of the embodiment of the present application obtains the indication information query instruction; obtains the drug information set corresponding to the indication information and the clinical trial registration number information set corresponding to the drug information set from the pre-established data relationship table , clinical trial start time information set, overall evaluation information set and approval time information set; according to the drug target relationship map, obtain the target information set corresponding to the drug information set; the clinical trial registration number information set corresponding to the drug information set, The clinical trial start time information set, the overall evaluation information set and the approval time information set are determined as the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set corresponding to the target information set; Analyze the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set, and obtain the analysis results of each target in the target information set.
  • the target R&D heat map can clearly reflect the changing trend of research and development hotspots in a certain disease field in a certain period of time. It is of great reference significance for innovative drug development companies to quickly understand the mainstream development direction in a certain field, and to solve the technical problems that are limited by data integrity or personal cognition, and are time-consuming and labor-intensive in the existing technology.
  • an embodiment of the third aspect of the present application provides a computer device, including: a processor; a memory for storing executable instructions of the processor; wherein the processor reads data stored in the memory by reading The executable program code is used to run the program corresponding to the executable program code, so as to execute the drug development analysis method described in the embodiment of the first aspect.
  • the fifth aspect of the present application provides a computer program product, which implements the drug development and analysis method described in the first aspect of the present application when an instruction processor in the computer program product is executed.
  • FIG. 1 is a schematic flowchart of a drug development analysis method provided in Embodiment 1 of the application;
  • FIG. 2 is an example diagram of a data relationship table provided by Embodiment 1 of the present application.
  • Embodiment 3 is an example diagram of a data relationship table provided by Embodiment 1 of the present application.
  • Embodiment 4 is an example diagram of a data relationship table provided by Embodiment 1 of the present application.
  • FIG. 5 is an example diagram of a data relationship table provided by Embodiment 1 of the present application.
  • FIG. 6 is an example diagram of a target R&D heat map provided in Example 1 of the present application.
  • FIG. 7 is an example diagram of a target R&D heat map provided by Embodiment 1 of the present application.
  • FIG. 8 is a schematic structural diagram of a drug development analysis device provided by an embodiment of the present application.
  • Figure 9 shows a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present application.
  • FIG. 1 is a schematic flowchart of a drug development analysis method provided in Example 1 of the present application.
  • the drug development analysis method includes the following steps:
  • Step 101 Obtain an indication information query instruction; obtain a drug information set corresponding to the indication information, and a clinical trial registration number information set corresponding to the drug information set from the pre-established data relationship table, and start the clinical trial Time Information Set, Overall Evaluation Information Set, and Approved Time to Market Information Set.
  • the method before acquiring the indication information query instruction, the method further includes: acquiring data information from different information sources, analyzing the data information, and establishing a data relationship table.
  • the clinical indication information, drug information, trial registration number information and clinical trial start time information are obtained from the first information source, and the indication information and drug information are cleaned and matched in the dictionary;
  • the matched indication information, drug information, trial registration number information and clinical trial start time information establish a first data relationship table.
  • clinical indication information obtained from including but not limited to ClinicalTrials.gov
  • clean the indication information and drug information match them in a dictionary, and store them. ,as shown in picture 2.
  • the drug information and the approval time to market information are obtained from the second information source, and the second data relationship table is established after standardizing the drug information and the approved time to market information.
  • the drug information, indication information, original clinical result information, and time information set are obtained from the third information source, and the third data relationship table is established after standardization processing.
  • the original information of the clinical result is marked, the marked clinical result is obtained, the overall evaluation information set is determined according to the marked clinical result and the time information set, and the third data relationship table is updated.
  • the marked clinical result includes but is not limited to: termination, poor, and positive.
  • the above marked clinical results contain negative words (including but not limited to: poor, terminated, etc.) and the time interval between the latest date and data in the time information set is ⁇ 6 years, and the overall evaluation is set as: inactive (negative); The time interval between the calculation dates of the late date data is 3-5 years, and the overall evaluation is set to: unknown (uncertain); the time interval of the latest data calculation dates in the time information set is less than or equal to 2 years, and the overall evaluation is set to: active (positive), As shown in Figure 5.
  • the data relationship table is updated by acquiring data information from different information sources according to preset time intervals.
  • data is acquired from each of the above-mentioned information sources at a fixed time and the above-mentioned data information is updated.
  • Step 102 Acquire a target information set corresponding to the drug information set according to the drug target relationship map.
  • Step 103 Determine the clinical trial registration number information set, clinical trial start time information set, overall evaluation information set and approval time information set corresponding to the drug information set as the clinical trial registration number information set, clinical trial information set corresponding to the target information set Start time information set, overall evaluation information set and approved time to market information set.
  • Step 104 analyze the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set, and obtain the analysis result of each target in the target information set.
  • the indication information query instruction is obtained, and the drug information set corresponding to the target indication information, and the clinical trial registration number information set and the clinical trial start time information set corresponding to the drug information set are obtained according to FIG. 2 and FIG. 5 .
  • the overall evaluation information set through the above drug information set matching the drug information in Table 2, obtain the approval time information set corresponding to the drug information set; according to the drug-target relationship map, obtain the target information set corresponding to the above drug information set, Thereby, the approval time information set, the clinical trial registration number information set, the clinical trial start time information set, and the overall evaluation information set corresponding to the target information set are obtained.
  • a primary table is generated, and two characteristic areas are set in the primary table to store elements of different categories; the clinical trial registration number of each target in the above-mentioned clinical trial start time in the same year in the statistical target information set number; preset a time period of N years, in which each element in a feature area is the number of clinical trial registration numbers in the same year above; obtain the information set of approval time for each target in the target information set, and obtain each The median time of approval to market for each target is sorted in ascending order of the median time; the target information set of the data with the same median time value or an empty median time value is obtained, and each target in the target information is obtained.
  • the number of N-year clinical trial registration number information of the point, and the secondary sorting is performed according to the number of numerical values in descending order; the target information set with the same number of N-year clinical trial registration number information is obtained, and each target in the target information set is obtained.
  • the first letter of the point is sorted in three levels in alphabetical order to generate a secondary table; each element in another feature area of the secondary table is the overall evaluation number corresponding to each target point, and each target in the target point information set is obtained.
  • the N-year overall evaluation of the point is the total number of the first evaluation category
  • the N-year overall evaluation of each target is obtained as the total number of the second evaluation category
  • the clinical trial risk is the ratio of the total number of the second evaluation category to the total number of the first evaluation category
  • the final grade is generated. sheet.
  • a primary table of m*n is generated, and there are two characteristic areas in the table for storing elements of different categories; each target in the above-mentioned target information set is in the same year in the above-mentioned clinical trial start time The number of clinical trial registration numbers in the same year; the preset N-year time period (eg: 20 years), each element in one of the feature areas is the number of clinical trial registration numbers in the same year as above; obtain each target in the above target information set The information set corresponding to the time of approval to market is obtained, and the median time of approval to market for each target is obtained, and the first-level sorting is performed according to the ascending order of the median time; the targets whose median time value is the same or whose median time value is empty are obtained Information set, obtain the number of N-year clinical trial registration number information for each target in the target information, and perform secondary sorting according to the number of numerical values; Point information set, obtain the first letter of each target in the target information set, and perform three-level sorting
  • NSCLC new clinical trial registrations for each target under the disease from 2000 to 2020, and screen out the top50 targets according to the tertiary ranking method.
  • the X-axis goes from top to bottom.
  • the well-researched targets are generally ranked higher, and emerging targets are ranked lower.
  • the heat map of target R&D drawn by comprehensive target-approval time-number of clinical registrations over the years can be seen: microtubule, DNA drugs are ranked on the upper left, representing a relatively well-researched target in this field; EGFR clinical registration since 2004 They are all active, representing a class of therapies with adequate research and frequent drug innovations; anaplastic lymphoma kinase (ALK), ROS1, PD-(L)1, TROP2, and other targets are ranked on the lower right, and clinically registered
  • ALK anaplastic lymphoma kinase
  • ROS1 ROS1, PD-(L)1, TROP2
  • Other targets are ranked on the lower right, and clinically registered
  • the increase in activity generally occurs in the last 5 years, representing a new class of targets.
  • the depth of the target R&D heat map established by the above method is shown in Figure 7, which sorts out the top50 target R&D trends in a certain field. Provide a reference for quickly understanding the mainstream development direction of
  • the collected and summarized clinical results are analyzed, the overall evaluation of the clinical results is generated, and the clinical trial risk value (risk) is calculated, which can reflect the development risk of drugs with different mechanisms of action in a certain disease area.
  • Indicators provide a new reference point for innovative drug development companies to comprehensively understand the development of a certain field.
  • the drug development analysis method of the embodiment of the present application obtains the indication information query instruction; obtains the drug information set corresponding to the indication information and the clinical trial registration number information set corresponding to the drug information set from the pre-established data relationship table , clinical trial start time information set, overall evaluation information set and approval time information set; according to the drug target relationship map, obtain the target information set corresponding to the drug information set; the clinical trial registration number information set corresponding to the drug information set, The clinical trial start time information set, the overall evaluation information set and the approval time information set are determined as the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set corresponding to the target information set; Analyze the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set, and obtain the analysis results of each target in the target information set.
  • the target R&D heat map can clearly reflect the changing trend of research and development hotspots in a certain disease field in a certain period of time. It is of great reference significance for innovative drug development companies to quickly understand the mainstream development direction in a certain field, and to solve the technical problems that are limited by data integrity or personal cognition, and are time-consuming and labor-intensive in the existing technology.
  • the present application also proposes a drug development analysis device.
  • FIG. 8 is a schematic structural diagram of a drug development analysis device provided by an embodiment of the present application.
  • the drug development analysis device includes: a first acquisition module 210 , a second acquisition module 220 , a determination module 230 and an analysis module 240 .
  • the first acquisition module 210 is configured to acquire an indication information query instruction; acquire the drug information set corresponding to the indication information and the clinical trial registration number information corresponding to the drug information set from the pre-established data relationship table information set, clinical trial start time information set, overall evaluation information set and approval time information set.
  • the second acquiring module 220 is configured to acquire the target information set corresponding to the drug information set according to the drug target relationship map.
  • a determination module 230 configured to determine the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set corresponding to the drug information set as the clinical trials corresponding to the target information set Registration number information set, clinical trial start time information set, overall evaluation information set and approval time information set.
  • the analysis module 240 is configured to analyze the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time to market information set, and obtain each information set in the target information set. The results of the analysis of the target.
  • the drug development and analysis device of the embodiment of the present application obtains the indication information query instruction; obtains the drug information set corresponding to the indication information and the clinical trial registration number information set corresponding to the drug information set from the pre-established data relationship table , clinical trial start time information set, overall evaluation information set and approval time information set; according to the drug target relationship map, obtain the target information set corresponding to the drug information set; the clinical trial registration number information set corresponding to the drug information set, The clinical trial start time information set, the overall evaluation information set and the approval time information set are determined as the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set corresponding to the target information set; Analyze the clinical trial registration number information set, the clinical trial start time information set, the overall evaluation information set and the approval time information set, and obtain the analysis results of each target in the target information set.
  • the target R&D heat map can clearly reflect the changing trend of research and development hotspots in a certain disease field in a certain period of time. It is of great reference significance for innovative drug development companies to quickly understand the mainstream development direction in a certain field, and to solve the technical problems that are limited by data integrity or personal cognition, and are time-consuming and labor-intensive in the existing technology.
  • the present application further provides a computer device, including: a processor, and a memory for storing instructions executable by the processor.
  • the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the drug development analysis method proposed in the foregoing embodiments of the present application.
  • the present application also proposes a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor, the processor can perform the drug development proposed in the foregoing embodiments of the present application Analytical method.
  • the present application also proposes a computer program product, when the instructions in the computer program product are executed by the processor, the method for drug development and analysis proposed in the foregoing embodiments of the present application is implemented.
  • Figure 9 shows a block diagram of an exemplary computer apparatus suitable for use in implementing embodiments of the present application.
  • the computer device 12 shown in FIG. 9 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present application.
  • computer device 12 takes the form of a general-purpose computing device.
  • Components of computer device 12 may include, but are not limited to, one or more processors or processing units 16 , system memory 28 , and a bus 18 connecting various system components including system memory 28 and processing unit 16 .
  • Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of a variety of bus structures.
  • these architectures include, but are not limited to, Industry Standard Architecture (hereinafter referred to as: ISA) bus, Micro Channel Architecture (hereinafter referred to as: MAC) bus, enhanced ISA bus, video electronics Standards Association (Video Electronics Standards Association; hereinafter referred to as: VESA) local bus and Peripheral Component Interconnection (Peripheral Component Interconnection; hereinafter referred to as: PCI) bus.
  • ISA Industry Standard Architecture
  • MAC Micro Channel Architecture
  • VESA Video Electronics Standards Association
  • PCI Peripheral Component Interconnection
  • Computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 12, including both volatile and nonvolatile media, removable and non-removable media.
  • the memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (Random Access Memory; hereinafter: RAM) 30 and/or cache memory 32 .
  • Computer device 12 may further include other removable/non-removable, volatile/non-volatile computer system storage media.
  • storage system 34 may be used to read and write to non-removable, non-volatile magnetic media (not shown in FIG. 9, commonly referred to as a "hard disk drive").
  • a magnetic disk drive for reading and writing to removable non-volatile magnetic disks (eg "floppy disks") and removable non-volatile optical disks (eg compact disk read only memory) may be provided Disc Read Only Memory; hereinafter referred to as: CD-ROM), Digital Video Disc Read Only Memory (hereinafter referred to as: DVD-ROM) or other optical media) read and write optical drives.
  • CD-ROM Disc Read Only Memory
  • DVD-ROM Digital Video Disc Read Only Memory
  • Memory 28 may include at least one program product having a set (eg, at least one) of program modules configured to perform the functions of various embodiments of the present application.
  • a program/utility 40 having a set (at least one) of program modules 42, which may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data , each or some combination of these examples may include an implementation of a network environment.
  • Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
  • the computer device 12 may also communicate with one or more external devices 14 (eg, keyboard, pointing device, display 24, etc.), and may also communicate with one or more devices that enable a user to interact with the computer system/server 12, and/or Or with any device (eg, network card, modem, etc.) that enables the computer system/server 12 to communicate with one or more other computing devices. Such communication may take place through input/output (I/O) interface 22 .
  • external devices 14 eg, keyboard, pointing device, display 24, etc.
  • any device eg, network card, modem, etc.
  • I/O input/output
  • the computer device 12 can also communicate with one or more networks (such as a local area network (Local Area Network; hereinafter referred to as: LAN), a wide area network (Wide Area Network; hereinafter referred to as: WAN) and/or a public network, such as the Internet, through the network adapter 20 ) communication.
  • networks such as a local area network (Local Area Network; hereinafter referred to as: LAN), a wide area network (Wide Area Network; hereinafter referred to as: WAN) and/or a public network, such as the Internet
  • network adapter 20 communicates with other modules of computer device 12 via bus 18 .
  • other hardware and/or software modules may be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives and data backup storage systems.
  • the processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28, such as implementing the drug development analysis method mentioned in the foregoing embodiments.
  • first and second are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, a feature delimited with “first”, “second” may expressly or implicitly include at least one of that feature.
  • plurality means at least two, such as two, three, etc., unless expressly and specifically defined otherwise.
  • a "computer-readable medium” can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or apparatus.
  • computer readable media include the following: electrical connections with one or more wiring (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), Read Only Memory (ROM), Erasable Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM).
  • the computer readable medium may even be paper or other suitable medium on which the program may be printed, as the paper or other medium may be optically scanned, for example, followed by editing, interpretation, or other suitable medium as necessary process to obtain the program electronically and then store it in computer memory.
  • each functional unit in each embodiment of the present application may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module.
  • the above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.
  • the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, and the like.

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Abstract

一种药物开发分析方法、装置、电子设备和存储介质，涉及数据处理技术领域，其中，方法包括：获取适应症信息查询指令；获取适应症信息对应的药品信息集、以及药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；根据药品靶点关系图谱，获取药品信息集对应的靶点信息集；确定靶点信息集的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集并进行分析，获取靶点信息集中每个靶点的分析结果。由此，获取靶点研发热力图，能够清晰反应一定时期内某疾病领域内研发热点的变化趋势，以使快速理解某领域主流开发方向具有重要参考意义。

Description

药物开发分析方法、装置、电子设备和存储介质
相关申请的交叉引用
本申请要求于2020年11月30日提交的申请号为2020113801944，发明名称为“药物开发分析方法、装置、电子设备和存储介质”的中国专利申请的优先权，其通过引用方式全部并入本文。
技术领域
本申请涉及数据处理技术领域，尤其涉及一种药物开发分析方法、装置电子设备和存储介质。
背景技术
创新药物开发是医药企业最重要的业务分支之一，创新药物开发的趋势对于企业创新药物研发立项具有一定参考意义。目前，创新药物开发的趋势并无商业化数据库支持，一般的，开发趋势解读常见两种方式：第一种方式是小样本的分析和研究；第二种方式是基于创新药物管线数量分析统计；这两种方式均受限于数据完整性或个人认知、且耗时耗力。
发明内容
本申请旨在至少在一定程度上解决相关技术中的技术问题之一。
为此，本申请的第一个目的在于提出一种药物开发分析方法，建立了时间、药物靶点、疾病之间的关联关系解析生成了靶点研发热力图，该靶点研发热力图能够清晰反应一定时期内某疾病领域内研发热点的变化趋势，这对创新药物开发企业快速理解某领域主流开发方向具有重要参考意义，解决现有技术中受限于数据完整性或个人认知、且耗时耗力的技术问题。
本申请的第二个目的在于提出一种药物开发分析装置。
本申请的第三个目的在于提出一种计算机设备。
本申请的第四个目的在于提出一种非临时性计算机可读存储介质。
本申请的第五个目的在于提出一种计算机程序产品。
为达上述目的，本申请第一方面实施例提出了一种药物开发分析方法，包括：
获取适应症信息查询指令；从预先建立的所述数据关系表中获取所述适应症信息对应的药品信息集、以及所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
根据药品靶点关系图谱，获取所述药品信息集对应的靶点信息集；
将所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为所述靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
对所述临床试验登记号信息集、所述临床试验开始时间信息集、所述总体评价信息集和所述批准上市时间信息集进行分析，获取所述靶点信息集中每个靶点的分析结果。
本申请实施例的药物开发分析方法，通过获取适应症信息查询指令；从预先建立的所述数据关系表中获取适应症信息对应的药品信息集、以及药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；根据药品靶点关系图谱，获取药品信息集对应的靶点信息集；将药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；对临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集进行分析，获取靶点信息集中每个靶点的分析结果。由此，建立了时间、药物靶点、疾病之间的关联关系解析生成了靶点研发热力图，该靶点研发热力图能够清晰反应一定时期内某疾病领域内研发热点的变化趋势，这对创新药物开发企业快速理解某领域主流开发方向具有重要参考意义，解决现有技术中受限于数据完整性或个人认知、且耗时耗力的技术问题。
在本申请的一个实施例中，在所述获取适应症信息查询指令之前，还包括：
获取不同信息源的数据信息，对数据信息进行分析，建立数据关系表。
在本申请的一个实施例中，所述获取不同信息源的数据信息，对数据信息进行分析，建立数据关系表，包括：
从第一信息源中获取临床适应症信息、药品信息、试验登记号信息和临床试验开始时间信息，对所述适应症信息和所述药品信息进行清洗后在字典中进行匹配；
根据匹配后的所述适应症信息、所述药品信息、以及所述试验登记号信息和所述临床试验开始时间信息建立第一数据关系表；
从第二信息源中获取药品信息和批准上市时间信息，对所述药品信息和所述批准上市时间信息进行标准化处理后建立第二数据关系表；
从第三信息源中获取药品信息、适应症信息、临床结果原始信息和时间信息集进行标准化处理后建立第三数据关系表。
在本申请的一个实施例中，所述的药物开发分析方法，还包括：
对所述临床结果原始信息进行标记，获取标记临床结果；
根据所述标记临床结果和所述时间信息集确定总体评价信息集更新所述第三数据关系表。
在本申请的一个实施例中，所述药物开发分析方法，还包括：
按照预设时间间隔，获取所述不同信息源的数据信息更新所述数据关系表。
在本申请的一个实施例中，所述对所述临床试验登记号信息集、所述临床试验开始时间信息集、所述总体评价信息集和所述批准上市时间信息集进行分析，获取所述靶点信息集中每个靶点的分析结果，包括：
生成初级表格，所述初级表格中设置两个特征区域用于存放不用类别的元素；
统计所述靶点信息集中每个靶点在上述临床试验开始时间中相同年份的临床试验登记号个数；预设N年时间段，其中，一个特征区域中每个元素为上述相同年份的临床试验登记号个数；
获取所述靶点信息集中每个靶点对应的批准上市时间信息集，得到每个靶点的批准上市时间中位数，按照中位时间升序进行一级排序；
获取中位时间值相同或中位时间值为空的数据的靶点信息集，获取靶 点信息中每个靶点的N年临床试验登记号信息的个数，按照个数值的数量降序进行二级排序；
获取N年临床试验登记号信息的个数相同的靶点信息集，获取靶点信息集中每个靶点的首字母，按照字母顺序进行三级排序，生成次级表格；
所述次级表格中另一个特征区域中每个元素为每个靶点对应的总体评价个数，获取所述靶点信息集中每个靶点N年总体评价为第一评价类别总数，获取每个靶点N年总体评价为第二评价类别总数，以及临床试验风险为所述第二评价类别总数与所述第一评价类别总数的比值，生成终级表格。
为达上述目的，本申请第二方面实施例提出了一种药物开发分析装置，包括：
第一获取模块，用于获取适应症信息查询指令；从预先建立的所述数据关系表中获取所述适应症信息对应的药品信息集、以及所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
第二获取模块，用于根据药品靶点关系图谱，获取所述药品信息集对应的靶点信息集；
确定模块，用于将所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为所述靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
分析模块，用于对所述临床试验登记号信息集、所述临床试验开始时间信息集、所述总体评价信息集和所述批准上市时间信息集进行分析，获取所述靶点信息集中每个靶点的分析结果。
本申请实施例的药物开发分析装置，通过获取适应症信息查询指令；从预先建立的所述数据关系表中获取适应症信息对应的药品信息集、以及药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；根据药品靶点关系图谱，获取药品信息集对应的靶点信息集；将药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为 靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；对临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集进行分析，获取靶点信息集中每个靶点的分析结果。由此，建立了时间、药物靶点、疾病之间的关联关系解析生成了靶点研发热力图，该靶点研发热力图能够清晰反应一定时期内某疾病领域内研发热点的变化趋势，这对创新药物开发企业快速理解某领域主流开发方向具有重要参考意义，解决现有技术中受限于数据完整性或个人认知、且耗时耗力的技术问题。
为达上述目的，本申请第三方面实施例提出了一种计算机设备，包括：处理器；用于存储所述处理器可执行指令的存储器；其中，所述处理器通过读取存储器中存储的可执行程序代码来运行与可执行程序代码对应的程序，用于执行第一方面实施例所述的药物开发分析方法。
为了实现上述目的，本申请第四方面实施例提出了一种非临时性计算机可读存储介质，其上存储有计算机程序，其特征在于，该程序被处理器执行时实现如本申请第一方面实施例所述的药物开发分析方法。
为了实现上述目的，本申请第五方面实施例提出了一种计算机程序产品，当所述计算机程序产品中的指令处理器执行时实现如本申请第一方面实施例所述的药物开发分析方法。
本申请附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本申请的实践了解到。
附图说明
本申请上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解，其中：
图1为本申请实施例一所提供的一种药物开发分析方法的流程示意图；
图2为本申请实施例一所提供的数据关系表的示例图；
图3为本申请实施例一所提供的数据关系表的示例图；
图4为本申请实施例一所提供的数据关系表的示例图；
图5为本申请实施例一所提供的数据关系表的示例图；
图6为本申请实施例一所提供的靶点研发热力图的示例图；
图7为本申请实施例一所提供的靶点研发热力图的示例图；
图8为本申请实施例所提供的一种药物开发分析装置的结构示意图；以及
图9示出了适于用来实现本申请实施方式的示例性计算机设备的框图。
具体实施方式
下面详细描述本申请的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本申请，而不能理解为对本申请的限制。
下面参考附图描述本申请实施例的药物开发分析方法、装置、电子设备和存储介质。
图1为本申请实施例一所提供的一种药物开发分析方法的流程示意图。
如图1所示，该药物开发分析方法包括以下步骤：
步骤101，获取适应症信息查询指令；从预先建立的所述数据关系表中获取所述适应症信息对应的药品信息集、以及所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集。
在本申请实施例中，在获取适应症信息查询指令之前，还包括：获取不同信息源的数据信息，对数据信息进行分析，建立数据关系表。
在本申请实施例中，从第一信息源中获取临床适应症信息、药品信息、试验登记号信息和临床试验开始时间信息，对适应症信息和药品信息进行清洗后在字典中进行匹配；根据匹配后的适应症信息、药品信息、以及试验登记号信息和临床试验开始时间信息建立第一数据关系表。
具体地，从包括但不限于ClinicalTrials.gov中获取临床适应症信息、药品信息、试验登记号信息、临床试验开始时间信息，对适应症信息，药品信息进行清洗后于字典中进行匹配，并存储，如图2所示。
在本申请实施例中，从第二信息源中获取药品信息和批准上市时间信息，对药品信息和所述批准上市时间信息进行标准化处理后建立第二数据关系表。
具体地，从包括但不限于FDA(美国食品药品监督管理局)、EMA(欧洲药品管理局)、PMDA(日本药品和医疗器械管理局)、NMPA(国家药品监督管理局)等各国家官网获取药品信息和批准上市时间信息，数据进行标准化处理并存储，如图3所示。
在本申请实施例中，从第三信息源中获取药品信息、适应症信息、临床结果原始信息和时间信息集进行标准化处理后建立第三数据关系表。
在本申请实施例中，对临床结果原始信息进行标记，获取标记临床结果，根据标记临床结果和时间信息集确定总体评价信息集更新第三数据关系表。
在本申请实施例中，从国内各种一级信息源，包括但不限于：官方资料、资讯、clinical trials、学术会议、医学论文，从中获取药品信息，适应症信息，临床结果原始信息，时间信息集(包括但不限于信息源的信息发布时间，发布临床结果时间等时间信息)，数据进行标准化处理并存储，如图4所示。
具体地，对临床结果原始信息进行直接获取或人工判断或自动化判断，得到标记临床结果，标记临床结果包括但不限于：终止、不佳、积极。上述标记临床结果包含消极词语(包括但不限于：不佳，终止等)且时间信息集中最晚日期据计算日期的时间间隔≥6年，总体评价设为：inactive(消极)；时间信息集中最晚日期据计算日期的时间间隔3-5年，总体评价设为：unknown(不确定)；时间信息集中最晚日期据计算日期的时间间隔≤2年，总体评价设为：active(积极)，如图5所示。
在本申请实施例中，按照预设时间间隔，获取不同信息源的数据信息更新数据关系表。
具体地，固定时间从上述各信息源获取数据并对上述数据信息进行更新。
步骤102，根据药品靶点关系图谱，获取药品信息集对应的靶点信息集。
步骤103，将药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集。
步骤104，对临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集进行分析，获取靶点信息集中每个靶点的分析结果。
在本申请实施例中，获取适应症信息查询指令，根据图2和图5获取目标适应症信息对应的药品信息集，及药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集；通过上述药品信息集匹配表2中药品信息，获取药品信息集对应的批准上市时间信息集；根据药品-靶点关系图谱，获取上述药品信息集对应的靶点信息集，从而获取靶点信息集对应的批准上市时间信息集、临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集。
在本申请实施例中，生成初级表格，初级表格中设置两个特征区域用于存放不用类别的元素；统计靶点信息集中每个靶点在上述临床试验开始时间中相同年份的临床试验登记号个数；预设N年时间段，其中，一个特征区域中每个元素为上述相同年份的临床试验登记号个数；获取靶点信息集中每个靶点对应的批准上市时间信息集，得到每个靶点的批准上市时间中位数，按照中位时间升序进行一级排序；获取中位时间值相同或中位时间值为空的数据的靶点信息集，获取靶点信息中每个靶点的N年临床试验登记号信息的个数，按照个数值的数量降序进行二级排序；获取N年临床试验登记号信息的个数相同的靶点信息集，获取靶点信息集中每个靶点的首字母，按照字母顺序进行三级排序，生成次级表格；次级表格中另一个特征区域中每个元素为每个靶点对应的总体评价个数，获取靶点信息集中每个靶点N年总体评价为第一评价类别总数，获取每个靶点N年总体评价为第二评价类别总数，以及临床试验风险为第二评价类别总数与第一评价类别总数的比值，生成终级表格。
在本申请实施例中，生成m*n的初级表格，表格中设有两个特征区域用于存放不用类别的元素；统计上述靶点信息集中每个靶点在上述临床试 验开始时间中相同年份的临床试验登记号个数；预设N年时间段(如：20年)，其中一个特征区域中每个元素为上述相同年份的临床试验登记号个数；获取上述靶点信息集中每个靶点对应的批准上市时间信息集，得到每个靶点的批准上市时间中位数，按照中位时间升序进行一级排序；获取中位时间值相同或中位时间值为空的数据的靶点信息集，获取靶点信息中每个靶点的N年临床试验登记号信息的个数，按照个数值的数量降序进行二级排序；获取上述N年临床试验登记号信息的个数相同的靶点信息集，获取靶点信息集中每个靶点的首字母，按照A-Z进行三级排序；生成m*n的次级表格；表格中另外一个特征区域中每个元素为每个靶点对应的总体评价个数；获取上述靶点信息集中每个靶点N年总体评价为inactive+unknown+active的总数，获取每个靶点N年总体评价为inactive+unknown的总数，临床试验风险risk＝(inactive+unknown)总数/(inactive+unknown+active)总数；生成m*n的终级表格如图6所示。
举例而言，以NSCLC为例，通过上述方法我们可以很快清洗并标准化出该疾病下各个靶点2000年至2020年新增临床试验登记数量，并根据三级排序方法能够筛选出top50靶点。X轴由上至下，研究充分靶点排位一般地会越靠上，新兴靶点会越靠下。综合靶点-批准时间-历年临床登记数量所绘制的靶点研发热力图能够看出：microtubule，DNA类药物排位偏左上，代表该领域内研究较为充分的靶点；EGFR临床登记2004年至今均处于活跃状态，代表着一类研究充分同时药物创新频繁的一类疗法；anaplastic lymphoma kinase(ALK),ROS1,PD-(L)1,TROP2,等靶点排位偏右下，临床登记的活跃增加一般出现在最近5年，代表着一类新兴的靶点，于上述方法所建立的靶点研发热力图深度如图7所示，梳理了某领域内的top50靶点研发动态，这给快速理解某领域主流开发方向提供参考。
因此，对收集汇总的临床结果进行分析，生成临床结果的总体评价，计算得到临床试验风险值(risk)，能够反应某个疾病领域下不同作用机制药物的开发风险，如：通过对一个疾病领域内两个靶点之间的临床试验风险值进行比较riskDNA＝0.6＞riskDHFR＝0.5，说明该适应症下基于DNA的作用机制的临床研究风险程度要高于基于DHFR的作用机制的临床研究，该指标给创新药开发企业综合理解某领域的开发提供一个新的参考 点。
本申请实施例的药物开发分析方法，通过获取适应症信息查询指令；从预先建立的所述数据关系表中获取适应症信息对应的药品信息集、以及药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；根据药品靶点关系图谱，获取药品信息集对应的靶点信息集；将药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；对临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集进行分析，获取靶点信息集中每个靶点的分析结果。由此，建立了时间、药物靶点、疾病之间的关联关系解析生成了靶点研发热力图，该靶点研发热力图能够清晰反应一定时期内某疾病领域内研发热点的变化趋势，这对创新药物开发企业快速理解某领域主流开发方向具有重要参考意义，解决现有技术中受限于数据完整性或个人认知、且耗时耗力的技术问题。
为了实现上述实施例，本申请还提出一种药物开发分析装置。
图8为本申请实施例提供的一种药物开发分析装置的结构示意图。
如图8所示，该药物开发分析装置包括：第一获取模块210、第二获取模块220、确定模块230和分析模块240。
第一获取模块210，用于获取适应症信息查询指令；从预先建立的所述数据关系表中获取所述适应症信息对应的药品信息集、以及所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集。
第二获取模块220，用于根据药品靶点关系图谱，获取所述药品信息集对应的靶点信息集。
确定模块230，用于将所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为所述靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集。
分析模块240，用于对所述临床试验登记号信息集、所述临床试验开 始时间信息集、所述总体评价信息集和所述批准上市时间信息集进行分析，获取所述靶点信息集中每个靶点的分析结果。
本申请实施例的药物开发分析装置，通过获取适应症信息查询指令；从预先建立的所述数据关系表中获取适应症信息对应的药品信息集、以及药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；根据药品靶点关系图谱，获取药品信息集对应的靶点信息集；将药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；对临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集进行分析，获取靶点信息集中每个靶点的分析结果。由此，建立了时间、药物靶点、疾病之间的关联关系解析生成了靶点研发热力图，该靶点研发热力图能够清晰反应一定时期内某疾病领域内研发热点的变化趋势，这对创新药物开发企业快速理解某领域主流开发方向具有重要参考意义，解决现有技术中受限于数据完整性或个人认知、且耗时耗力的技术问题。
需要说明的是，前述对药物开发分析方法实施例的解释说明也适用于该实施例的药物开发分析装置，此处不再赘述。
为了实现上述实施例，本申请还提出一种计算机设备，包括：处理器，以及用于存储所述处理器可执行指令的存储器。
其中，所述处理器通过读取所述存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于实现如本申请前述实施例提出的药物开发分析方法。
为了实现上述实施例，本申请还提出一种非临时性计算机可读存储介质，当所述存储介质中的指令由处理器被执行时，使得处理器能够执行本申请前述实施例提出的药物开发分析方法。
为了实现上述实施例，本申请还提出一种计算机程序产品，当所述计算机程序产品中的指令由处理器执行时，执行实现本申请前述实施例提出的药物开发分析方法。
图9示出了适于用来实现本申请实施方式的示例性计算机设备的框 图。图9显示的计算机设备12仅仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。
如图9所示，计算机设备12以通用计算设备的形式表现。计算机设备12的组件可以包括但不限于：一个或者多个处理器或者处理单元16，系统存储器28，连接不同系统组件(包括系统存储器28和处理单元16)的总线18。
总线18表示几类总线结构中的一种或多种，包括存储器总线或者存储器控制器，外围总线，图形加速端口，处理器或者使用多种总线结构中的任意总线结构的局域总线。举例来说，这些体系结构包括但不限于工业标准体系结构(Industry Standard Architecture；以下简称：ISA)总线，微通道体系结构(Micro Channel Architecture；以下简称：MAC)总线，增强型ISA总线、视频电子标准协会(Video Electronics Standards Association；以下简称：VESA)局域总线以及外围组件互连(Peripheral Component Interconnection；以下简称：PCI)总线。
计算机设备12典型地包括多种计算机系统可读介质。这些介质可以是任何能够被计算机设备12访问的可用介质，包括易失性和非易失性介质，可移动的和不可移动的介质。
存储器28可以包括易失性存储器形式的计算机系统可读介质，例如随机存取存储器(Random Access Memory；以下简称：RAM)30和/或高速缓存存储器32。计算机设备12可以进一步包括其它可移动/不可移动的、易失性/非易失性计算机系统存储介质。仅作为举例，存储系统34可以用于读写不可移动的、非易失性磁介质(图9未显示，通常称为“硬盘驱动器”)。尽管图9中未示出，可以提供用于对可移动非易失性磁盘(例如“软盘”)读写的磁盘驱动器，以及对可移动非易失性光盘(例如：光盘只读存储器(Compact Disc Read Only Memory；以下简称：CD-ROM)、数字多功能只读光盘(Digital Video Disc Read Only Memory；以下简称：DVD-ROM)或者其它光介质)读写的光盘驱动器。在这些情况下，每个驱动器可以通过一个或者多个数据介质接口与总线18相连。存储器28可以包括至少一个程序产品，该程序产品具有一组(例如至少一个)程序模块，这些程序模块被配置以执行本申请各实施例的功能。
具有一组(至少一个)程序模块42的程序/实用工具40，可以存储在例如存储器28中，这样的程序模块42包括但不限于操作系统、一个或者多个应用程序、其它程序模块以及程序数据，这些示例中的每一个或某种组合中可能包括网络环境的实现。程序模块42通常执行本申请所描述的实施例中的功能和/或方法。
计算机设备12也可以与一个或多个外部设备14(例如键盘、指向设备、显示器24等)通信，还可与一个或者多个使得用户能与该计算机系统/服务器12交互的设备通信，和/或与使得该计算机系统/服务器12能与一个或多个其它计算设备进行通信的任何设备(例如网卡，调制解调器等等)通信。这种通信可以通过输入/输出(I/O)接口22进行。并且，计算机设备12还可以通过网络适配器20与一个或者多个网络(例如局域网(Local Area Network；以下简称：LAN)，广域网(Wide Area Network；以下简称：WAN)和/或公共网络，例如因特网)通信。如图所示，网络适配器20通过总线18与计算机设备12的其它模块通信。应当明白，尽管图中未示出，可以结合计算机设备12使用其它硬件和/或软件模块，包括但不限于：微代码、设备驱动器、冗余处理单元、外部磁盘驱动阵列、RAID系统、磁带驱动器以及数据备份存储系统等。
处理单元16通过运行存储在系统存储器28中的程序，从而执行各种功能应用以及数据处理，例如实现前述实施例中提及的药物开发分析方法。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本申请的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有 “第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本申请的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于实现定制逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本申请的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本申请的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本申请的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。如，如果用硬件来实现和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)， 现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本申请各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本申请的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本申请的限制，本领域的普通技术人员在本申请的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (10)

  1. 一种药物开发分析方法，其特征在于，包括以下步骤：
    获取适应症信息查询指令；从预先建立的数据关系表中获取所述适应症信息对应的药品信息集、以及所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
    根据药品靶点关系图谱，获取所述药品信息集对应的靶点信息集；
    将所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为所述靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
    对所述临床试验登记号信息集、所述临床试验开始时间信息集、所述总体评价信息集和所述批准上市时间信息集进行分析，获取所述靶点信息集中每个靶点的分析结果。
  2. 如权利要求1所述的药物开发分析方法，其特征在于，在所述获取适应症信息查询指令之前，还包括：
    获取不同信息源的数据信息，对数据信息进行分析，建立数据关系表。
  3. 如权利要求2所述的药物开发分析方法，其特征在于，所述获取不同信息源的数据信息，对数据信息进行分析，建立数据关系表，包括：
    从第一信息源中获取临床适应症信息、药品信息、试验登记号信息和临床试验开始时间信息，对所述适应症信息和所述药品信息进行清洗后在字典中进行匹配；
    根据匹配后的所述适应症信息、所述药品信息、以及所述试验登记号信息和所述临床试验开始时间信息建立第一数据关系表；
    从第二信息源中获取药品信息和批准上市时间信息，对所述药品信息和所述批准上市时间信息进行标准化处理后建立第二数据关系表；
    从第三信息源中获取药品信息、适应症信息、临床结果原始信息和时间信息集进行标准化处理后建立第三数据关系表。
  4. 如权利要求3所述的药物开发分析方法，其特征在于，还包括：
    对所述临床结果原始信息进行标记，获取标记临床结果；
    根据所述标记临床结果和所述时间信息集确定总体评价信息集更新 所述第三数据关系表。
  5. 如权利要求2所述的药物开发分析方法，其特征在于，还包括：
    按照预设时间间隔，获取所述不同信息源的数据信息更新所述数据关系表。
  6. 如权利要求1所述的药物开发分析方法，其特征在于，所述对所述临床试验登记号信息集、所述临床试验开始时间信息集、所述总体评价信息集和所述批准上市时间信息集进行分析，获取所述靶点信息集中每个靶点的分析结果，包括：
    生成初级表格，所述初级表格中设置两个特征区域用于存放不同类别的元素；
    统计所述靶点信息集中每个靶点在上述临床试验开始时间中相同年份的临床试验登记号个数；预设N年时间段，其中，一个特征区域中每个元素为上述相同年份的临床试验登记号个数；
    获取所述靶点信息集中每个靶点对应的批准上市时间信息集，得到每个靶点的批准上市时间中位数，按照中位时间升序进行一级排序；
    获取中位时间值相同或中位时间值为空的数据的靶点信息集，获取靶点信息中每个靶点的N年临床试验登记号信息的个数，按照个数值的数量降序进行二级排序；
    获取N年临床试验登记号信息的个数相同的靶点信息集，获取靶点信息集中每个靶点的首字母，按照字母顺序进行三级排序，生成次级表格；
    所述次级表格中另一个特征区域中每个元素为每个靶点对应的总体评价个数，获取所述靶点信息集中每个靶点N年总体评价为第一评价类别总数，获取每个靶点N年总体评价为第二评价类别总数，以及临床试验风险为所述第二评价类别总数与所述第一评价类别总数的比值，生成终级表格。
  7. 一种药物开发分析装置，其特征在于，所述装置包括：
    第一获取模块，用于获取适应症信息查询指令；从预先建立的数据关系表中获取所述适应症信息对应的药品信息集、以及所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
    第二获取模块，用于根据药品靶点关系图谱，获取所述药品信息集对应的靶点信息集；
    确定模块，用于将所述药品信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集确定为所述靶点信息集对应的临床试验登记号信息集、临床试验开始时间信息集、总体评价信息集和批准上市时间信息集；
    分析模块，用于对所述临床试验登记号信息集、所述临床试验开始时间信息集、所述总体评价信息集和所述批准上市时间信息集进行分析，获取所述靶点信息集中每个靶点的分析结果。
  8. 如权利要求7所述的药物开发分析装置，其特征在于，还包括：
    建立模块，用于获取不同信息源的数据信息，对数据信息进行分析，建立数据关系表。
  9. 一种计算机设备，其特征在于，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时，实现如权利要求1-6中任一所述的药物开发分析方法。
  10. 一种非临时性计算机可读存储介质，其上存储有计算机程序，其特征在于，该程序被处理器执行时实现如权利要求1-6中任一所述的药物开发分析方法。
PCT/CN2021/134234 2020-11-30 2021-11-30 药物开发分析方法、装置、电子设备和存储介质 WO2022111720A1 (zh)

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