WO2022095870A1 - 一种针对靶点药物的数据分析方法及装置 - Google Patents

一种针对靶点药物的数据分析方法及装置 Download PDF

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WO2022095870A1
WO2022095870A1 PCT/CN2021/128305 CN2021128305W WO2022095870A1 WO 2022095870 A1 WO2022095870 A1 WO 2022095870A1 CN 2021128305 W CN2021128305 W CN 2021128305W WO 2022095870 A1 WO2022095870 A1 WO 2022095870A1
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target
information
drug
indication
drug information
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PCT/CN2021/128305
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English (en)
French (fr)
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周立运
谢伟
张秋颖
阳晓文
曾冬琳
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北京华彬立成科技有限公司
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Publication of WO2022095870A1 publication Critical patent/WO2022095870A1/zh

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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
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • 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

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  • the present application relates to the technical field of computer applications, in particular to a data analysis method and device for target drugs.
  • the present application also relates to an electronic device and a non-transitory computer-readable storage medium.
  • Drug targets refer to the binding sites of drugs in the body, including biological macromolecules such as genetic loci, receptors, enzymes, ion channels, and nucleic acids.
  • biological macromolecules such as genetic loci, receptors, enzymes, ion channels, and nucleic acids.
  • the embodiments of the present application provide a data analysis method and device for target drugs, so as to solve the problem that the statistical analysis method in the prior art is time-consuming and labor-intensive, and is prone to data missing, resulting in poor user experience.
  • the embodiments of the present application provide a data analysis method for target drugs, including:
  • the target target and the preset relationship map obtain the drug information corresponding to the target target, as well as the indication information corresponding to the drug information and its research and development stage;
  • the clinical indication development progress information of the drug corresponding to the target target is determined.
  • obtaining the drug information corresponding to the target target, and the indication information corresponding to the drug information and its research and development stage according to the target target and the preset relationship map specifically includes:
  • an indication information set corresponding to each drug information in the first drug information set according to a preset relationship map between drug information and indication information, and determine a second drug corresponding to each indication in the indication information set an information set; wherein the second drug information set is a subset of the first drug information set;
  • the indication information set, the second drug information set, and the relationship map among the preset drug information, indication information, and research and development stages obtain the research and development stage information set corresponding to each drug information, and obtain each drug information set.
  • the drug information and the indication information are sorted according to the weight value to obtain the corresponding sorting order difference, which specifically includes:
  • the data analysis method for the target drug also includes:
  • the sub-table includes the drug information, the indication information, the R&D stage and its weight value;
  • the drug information and the indication information are sorted according to the weight value in the secondary table to generate a target table.
  • the research and development stages include: preclinical, clinical application, clinical phase I, clinical phase I/II, clinical phase II, clinical phase II/III, clinical phase III, clinical phase III/IV, clinical phase IV, application At least one stage of development in marketing and approval for marketing.
  • the embodiments of the present application also provide a data analysis device for target drugs, including:
  • a target information acquisition unit configured to acquire the drug information corresponding to the target target, and the indication information corresponding to the drug information and its research and development stage according to the target target and a preset relationship map;
  • the weight setting unit is used to set the corresponding weight value for each R&D stage
  • a sorting unit configured to sort the drug information and the indication information according to the weight value every preset time interval, and obtain a corresponding sorting order difference value
  • a data analysis unit configured to determine the clinical indication research and development progress information of the drug corresponding to the target target according to the sorting order difference.
  • target information acquisition unit is specifically used for:
  • an indication information set corresponding to each drug information in the first drug information set according to a preset relationship map between drug information and indication information, and determine a second drug corresponding to each indication in the indication information set an information set; wherein the second drug information set is a subset of the first drug information set;
  • the indication information set, the second drug information set, and the relationship map among the preset drug information, indication information, and research and development stages obtain the research and development stage information set corresponding to each drug information, and obtain each drug information set.
  • sorting unit is specifically used for:
  • the data analysis device for the target drug also includes:
  • a basic table generation unit configured to generate a basic table based on the drug information, the indication information corresponding to the drug information and the development stage thereof;
  • a sub-table generating unit configured to set corresponding weight values for each R&D stage in the basic table, and generate a sub-table; the sub-table includes the drug information, the indication information, the R&D stage and its weight value;
  • the target table generating unit is configured to sort the drug information and the indication information according to the weight value in the secondary table every preset time interval to generate a target table.
  • the research and development stages include: preclinical, clinical application, clinical phase I, clinical phase I/II, clinical phase II, clinical phase II/III, clinical phase III, clinical phase III/IV, clinical phase IV, application At least one stage of development in marketing and approval for marketing.
  • an embodiment of the present application further provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements any of the above-mentioned programs when executing the program.
  • the steps of a data analysis method for a target drug including: a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements any of the above-mentioned programs when executing the program.
  • the embodiments of the present application further provide a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, realizes the target drug according to any one of the above. Steps of a data analysis method.
  • the drugs corresponding to the targets and their indication data are sorted by the weights set in the research and development stage, and the sorting order is recalculated in a preset time interval.
  • the difference value can accurately obtain the research and development status of clinical indications of different drugs under each target, and timely reflect the changing trend of clinical trials, allowing users to quickly obtain information on the development progress of clinical indications of different drugs under the target.
  • the efficiency of R&D data analysis is improved, and the comprehensiveness and accuracy of the data must also be greatly improved.
  • FIG. 1 is a schematic flowchart of a data analysis method for a target drug provided by an embodiment of the application
  • FIG. 2 is a schematic structural diagram of a data analysis device for target drugs provided by an embodiment of the present application.
  • FIG. 3 is a schematic diagram of a physical structure of an electronic device according to an embodiment of the present application.
  • Step S101 Obtain a target query request.
  • the target is a drug target
  • the drug target refers to a binding site between a drug and a biological macromolecule, such as a PDI (Protein disulfide isomerase) target.
  • PDI Protein disulfide isomerase
  • Step S102 According to the target target and a preset relationship map, obtain drug information corresponding to the target target, and indication information corresponding to the drug information and its development stage.
  • the drug information corresponding to the target target is obtained.
  • the specific implementation process includes: : According to the inputted target and the preset relationship map between the target and the drug information, obtain the first drug information set corresponding to the target.
  • the input target target is a PDI target
  • the corresponding first drug information set may include pembrolizumab, nivolumab, camrelizumab, toripalizumab, and the like.
  • the indication information set corresponding to each drug information in the first drug information set can be obtained according to a preset relationship map between drug information and indication information, and determining a second drug information set corresponding to each indication in the indication information set.
  • the second drug information set is a subset of the first drug information set.
  • the indication information set may include: non-small cell lung cancer, solid tumor, gastric cancer, and the like.
  • the second drug information set corresponding to each indication in the indication information set corresponds to part of the above-mentioned first drug information set, for example, the second drug information set corresponding to non-small cell lung cancer indications includes the first drug information set Pembrolizumab, nivolumab, and camrelizumab in the Drug Information Center.
  • the research and development stage information set corresponding to each drug information can be obtained, And obtain the R&D stage information set corresponding to each indication.
  • the research and development stages include: preclinical, clinical application, phase I clinical, phase I/II clinical, phase II clinical, phase II/III clinical, phase III clinical, phase III/IV clinical, phase IV clinical, application for listing and approval for marketing and other research and development stages.
  • a basic m*n table for recording the above information is generated, and each element in the table records the corresponding R&D stage .
  • Step S103 corresponding weight values are respectively set for each R&D stage.
  • a corresponding weight value may be further set for each R&D stage in the basic table to generate a corresponding secondary table.
  • the sub-table includes the drug information, the indication information, the development stage and its weight value, and the like.
  • each R&D stage after assigning weights to each R&D stage one by one, with the advancement of the R&D stage, the corresponding weight value of each R&D stage can be gradually increased.
  • Set the weight difference between two adjacent R&D stages to be 0.5, resulting in a sub-table of m*n.
  • each The weights corresponding to the R&D stage are set to 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, and 5.5, respectively.
  • Step S104 at preset time intervals, sort the drug information and the indication information according to the weight value to obtain a corresponding sorting order difference.
  • the drug information and the indication information are sorted according to the weight value, and the corresponding sorting order difference is obtained.
  • the specific implementation process includes: every The preset time interval sums up the weight values of the information sets of the research and development stage corresponding to each type of drug information to obtain a first target weight value, and sorts the drug information according to the size of the first target weight value to obtain The respective sorting order difference values corresponding to the drug information; and, summing the weight values of the obtained R&D stage information set corresponding to each indication at every preset time interval to obtain a second target weight value, according to the Sort the indication information according to the size of the second target weight value, and obtain the sorting order difference values corresponding to the indication information respectively.
  • Table 1.1 and Table 1.2 are the generated secondary table and the generated target table reordered after a preset time interval, respectively.
  • the generated secondary table can be sorted by rows of drug information and columns of indication information at preset time intervals, such as every month, that is, the drug information and indication information can be sorted according to Sorting is performed corresponding to the sum of the weights of the R&D stage sets.
  • the specific sorting method can be: sort in descending order according to the sum of the weights of the R&D stage sets corresponding to the drug information of each row or the indications of each column, and generate the target table.
  • Step S105 According to the sorting order difference, determine the clinical indication development progress information of the drug corresponding to the target target.
  • the difference value of the sorting order corresponding to the indication is a negative value, it means that the research and development progress of the clinical indication of the drug corresponding to the target target is slowed down.
  • the slower the research and development of clinical indications the slower the progress of research and development of clinical indications;
  • the difference in the sorting order corresponding to the indication is a positive value, it means that the research and development of clinical indications of the drug corresponding to the target target is progressing faster or the number of drugs under research increases.
  • the larger the absolute value of the difference the faster the clinical indication research and development of the drug or the more drugs under development.
  • the difference value of the sorting order corresponding to the drug is a negative value, it means that the development progress of the drug corresponding to the target target has slowed down or the clinical indication research and development has failed. The slower the speed or the more failures in the research and development of indications; if the difference in the sorting order corresponding to the drug is a positive value, it means that the development of the drug corresponding to the target target is progressing faster or the research and development of clinical indications increases. The larger the absolute value of the value, the faster the progress of drug research and development or the more clinical indications that increase the research and development.
  • the drugs corresponding to the targets and their indication data are sorted by the weights set in the research and development stage, and the sorting order is recalculated in a preset time interval.
  • the difference value can accurately obtain the research and development status of different drug clinical indications under each target, and timely reflect the changing trend of clinical trials, allowing users to quickly obtain the development progress information of different drugs under the target.
  • the changing trend and success probability of clinical trials allow users to accurately and intuitively obtain information on the development progress of clinical indications of different drugs under the target, which greatly improves the efficiency of research and development data analysis. promote.
  • the present application also provides a data analysis device for target drugs. Since the embodiments of the device are similar to the above method embodiments, the description is relatively simple. For relevant details, please refer to the descriptions in the above method embodiments.
  • the embodiments of the data analysis device for target drugs described below are only Schematic. Please refer to FIG. 2 , which is a schematic structural diagram of a data analysis device for target drugs provided by an embodiment of the present application.
  • a data analysis device for target drugs described in this application specifically includes the following parts:
  • the request obtaining unit 201 is configured to obtain a target query request.
  • the target information obtaining unit 202 is configured to obtain the drug information corresponding to the target target, the indication information corresponding to the drug information and the development stage thereof according to the target target and a preset relationship map.
  • the weight setting unit 203 is configured to respectively set corresponding weight values for each R&D stage.
  • the sorting unit 204 is configured to sort the drug information and the indication information according to the weight value every preset time interval, and obtain a corresponding sorting order difference value.
  • the data analysis unit 205 is configured to determine the clinical indication research and development progress information of the drug corresponding to the target target according to the sorting order difference.
  • the drugs corresponding to the targets and their indication data are sorted according to the weights set in the research and development stage, and the sorting order is recalculated in a preset time interval.
  • the difference value can accurately obtain the research and development status of different drug clinical indications under each target, and timely reflect the changing trend of clinical trials, allowing users to quickly obtain the development progress information of different drugs under the target.
  • the changing trend and success probability of clinical trials allow users to accurately and intuitively obtain information on the development progress of clinical indications of different drugs under the target, which greatly improves the efficiency of research and development data analysis. promote.
  • the present application also provides an electronic device. Since the embodiment of the electronic device is similar to the above-mentioned method embodiment, the description is relatively simple, and for related details, please refer to the description of the above-mentioned method embodiment part, and the electronic device described below is only illustrative.
  • FIG. 3 which is a schematic diagram of a physical structure of an electronic device disclosed in an embodiment of the present application.
  • the electronic device may include: a processor 301 , a memory 302 and a communication bus 303 , wherein the processor 301 and the memory 302 communicate with each other through the communication bus 303 .
  • the processor 301 can call the logic instruction in the memory 302 to execute the data analysis method for the target drug, the method includes: obtaining a target target query request; according to the target target and a preset relationship map, obtaining the target The drug information corresponding to the target target, as well as the indication information corresponding to the drug information and its research and development stage; corresponding weight values are respectively set for each research and development stage; every preset time interval, according to the weight value The drug information and the indication information are sorted to obtain the corresponding sorting order difference; according to the sorting order difference, the clinical indication research and development progress information of the drug corresponding to the target target is determined.
  • the above-mentioned logic instructions in the memory 302 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.
  • the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution.
  • the computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes .
  • an embodiment of the present application further provides a computer program product
  • the computer program product includes a computer program stored on a non-transitory computer-readable storage medium
  • the computer program includes program instructions, when the program instructions When executed by the computer, the computer can execute the data analysis method for the target drug provided by the above method embodiments.
  • the method includes: according to the target target and a preset relational map, acquiring the corresponding data of the target target.
  • Drug information as well as indication information corresponding to the drug information and its research and development stage; corresponding weight values are respectively set for each research and development stage; every preset time interval, according to the weight value, the drug information and the The indication information is sorted, and the corresponding sorting order difference is obtained; according to the sorting order difference, the clinical indication research and development progress information of the drug corresponding to the target target is determined.
  • the embodiments of the present application further provide a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, is implemented to execute the target drug provided by the above embodiments.
  • a data analysis method comprising: obtaining drug information corresponding to the target target, and indication information corresponding to the drug information and its research and development stage according to the target target and a preset relationship map; The corresponding weight values are respectively set in each stage; every preset time interval, the drug information and the indication information are sorted according to the weight values, and the corresponding sorting order difference values are obtained; according to the sorting order difference values , and determine the development progress information of the clinical indications of the drug corresponding to the target target.
  • the device embodiments described above are only illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed over multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment. Those of ordinary skill in the art can understand and implement it without creative effort.
  • each embodiment can be implemented by means of software plus a necessary general hardware platform, and certainly can also be implemented by hardware.
  • the above-mentioned technical solutions can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic A disc, an optical disc, etc., includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in various embodiments or some parts of the embodiments.

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Abstract

一种针对靶点药物的数据分析方法以及装置。其中，该方法包括：获取目标靶点查询请求；根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；每隔预设的时间间隔，根据预设的权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。采用上述针对靶点药物的数据分析方法，能够实时更新各靶点下不同药物的临床适应症研发进展数据，极大地提高了数据分析效率，有效提升了用户的使用体验。

Description

一种针对靶点药物的数据分析方法及装置
相关申请的交叉引用
本申请要求于2020年11月04日提交的申请号为202011219306.8，发明名称为“一种针对靶点药物的数据分析方法及装置”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
本申请涉及计算机应用技术领域，具体涉及一种针对靶点药物的数据分析方法和装置。另外，本申请还涉及一种电子设备及非暂态计算机可读存储介质。
背景技术
药物靶点是指药物在体内的作用结合位点，包括基因位点、受体、酶、离子通道、核酸等生物大分子。现代新药研究与开发的关键首先是寻找、确定和制备药物筛选靶点。如何通过查询药物靶点的方式快速获取靶点下不同药物的临床适应症研发进展信息和变化趋势成为人们关注的重点。
目前，传统的对同一个靶点下各个药物的研发适应症的信息进行分析和挖掘，通常是通过企业公告、资讯、官网等多渠道数据进行人工整理获取，其统计分析方式费时费力，且容易存在数据缺失。因此，如何快速、有效的对靶点下不同药物的临床适应症研发数据进行数据汇集、统计和分析成为目前业界亟待解决的需要课题。
发明内容
为此，本申请实施例提供一种针对靶点药物的数据分析方法及装置，以解决现有技术中存在的统计分析方法费时费力，且容易存在数据缺失，导致用户使用体验较差的问题。
第一方面，本申请实施例提供一种针对靶点药物的数据分析方法，包括：
获取目标靶点查询请求；
根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；
针对各个研发阶段分别设置相应的权重值；
每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；
根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
进一步的，所述根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段，具体包括：
根据所述目标靶点以及预设的靶点与药品信息的关系图谱，获取所述目标靶点对应的第一药品信息集；
根据预设的药品信息与适应症信息的关系图谱，获取所述第一药品信息集中每种药品信息对应的适应症信息集，并确定所述适应症信息集中每种适应症对应的第二药品信息集；其中，所述第二药品信息集是所述第一药品信息集的子集；
根据所述适应症信息集、所述第二药品信息集以及预设的药品信息、适应症信息以及研发阶段之间的关系图谱，获取每种药品信息对应的研发阶段信息集，并获取每种适应症对应的研发阶段信息集。
进一步的，所述每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值，具体包括：
每隔预设的时间间隔对所述每种药品信息对应的研发阶段信息集的权重值求和，得到第一目标权重值；根据所述第一目标权重值的大小对所述药品信息进行排序，获得所述药品信息分别对应的排序次序差值；以及，
每隔预设的时间间隔对所述获取每种适应症对应的研发阶段信息集的权重值求和，得到第二目标权重值；根据所述第二目标权重值的大小对所述适应症信息进行排序，获得所述适应症信息分别对应的排序次序差值。
进一步的，所述的针对靶点药物的数据分析方法，还包括：
基于所述药品信息，所述药品信息对应的适应症信息及其研发阶段， 生成基础表格；
对所述基础表格中的各个研发阶段分别设置相应的权重值，生成次级表格；所述次级表格包含所述药品信息、所述适应症信息、所述研发阶段及其权重值；
每隔预设的时间间隔，根据所述次级表格中的所述权重值对所述药品信息和所述适应症信息进行排序，生成目标表格。
进一步的，所述研发阶段包括：临床前、申报临床、I期临床、I/II期临床、II期临床、II/III期临床、III期临床、III/IV期临床、IV期临床、申请上市和批准上市中的至少一个研发阶段。
第二方面，本申请实施例还提供一种针对靶点药物的数据分析装置，包括：
请求获取单元，用于获取目标靶点查询请求；
目标信息获取单元，用于根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；
权重设置单元，用于针对各个研发阶段分别设置相应的权重值；
排序单元，用于每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；
数据分析单元，用于根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
进一步的，所述目标信息获取单元，具体用于：
根据所述目标靶点以及预设的靶点与药品信息的关系图谱，获取所述目标靶点对应的第一药品信息集；
根据预设的药品信息与适应症信息的关系图谱，获取所述第一药品信息集中每种药品信息对应的适应症信息集，并确定所述适应症信息集中每种适应症对应的第二药品信息集；其中，所述第二药品信息集是所述第一药品信息集的子集；
根据所述适应症信息集、所述第二药品信息集以及预设的药品信息、适应症信息以及研发阶段之间的关系图谱，获取每种药品信息对应的研发阶段信息集，并获取每种适应症对应的研发阶段信息集。
进一步的，所述排序单元，具体用于：
每隔预设的时间间隔对所述每种药品信息对应的研发阶段信息集的权重值求和，得到第一目标权重值；根据所述第一目标权重值的大小对所述药品信息进行排序，获得所述药品信息分别对应的排序次序差值；以及，
每隔预设的时间间隔对所述获取每种适应症对应的研发阶段信息集的权重值求和，得到第二目标权重值；根据所述第二目标权重值的大小对所述适应症信息进行排序，获得所述适应症信息分别对应的排序次序差值。
进一步的，所述的针对靶点药物的数据分析装置，还包括：
基础表格生成单元，用于基于所述药品信息，所述药品信息对应的适应症信息及其研发阶段，生成基础表格；
次级表格生成单元，用于对所述基础表格中的各个研发阶段分别设置相应的权重值，生成次级表格；所述次级表格包含所述药品信息、所述适应症信息、所述研发阶段及其权重值；
目标表格生成单元，用于每隔预设的时间间隔，根据所述次级表格中的所述权重值对所述药品信息和所述适应症信息进行排序，生成目标表格。
进一步的，所述研发阶段包括：临床前、申报临床、I期临床、I/II期临床、II期临床、II/III期临床、III期临床、III/IV期临床、IV期临床、申请上市和批准上市中的至少一个研发阶段。
第三方面，本申请实施例还提供一种电子设备，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上述任意一项所述的针对靶点药物的数据分析方法的步骤。
第四方面，本申请实施例还提供一种非暂态计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现如上述任意一项所述的针对靶点药物的数据分析方法的步骤。
采用本申请实施例所述的针对靶点药物的数据分析方法，通过对研发阶段设置的权重对靶点对应的药品及其适应症数据进行排序，并通过在预设时间间隔中重新计算排序次序差值，准确获取各靶点下不同药物临床适 应症的研发情况，及时的反应临床试验的变化趋势，让用户快速获取靶点下不同药物的临床适应症研发进展信息，数据实时更新，极大地提高了研发数据分析效率，同时数据的全面性和准确性也得有极大提升。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获取其他的附图。
图1为本申请实施例提供的一种针对靶点药物的数据分析方法的流程示意图；
图2为本申请实施例提供的一种针对靶点药物的数据分析装置的结构示意图；
图3为本申请实施例提供的一种电子设备的实体结构示意图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获取的所有其他实施例，都属于本申请保护的范围。
下面基于本申请所述的针对靶点药物的数据分析方法，对其实施例进行详细描述。如图1所示，其为本申请实施例提供的针对靶点药物的数据分析方法的流程图，具体实现过程包括以下步骤：
步骤S101：获取目标靶点查询请求。
具体的，所述目标靶点为药物靶点，该药物靶点是指药物与机体生物大分子的结合部位，比如PDI(Protein disulfide isomerase)靶点。
本申请实施例中，在获取所述目标靶点查询请求之前，需要预先建立了药物信息与靶点信息的知识图谱，标准化适应症数据，并把药物信息和 临床数据等进行关联，构建包含药物信息、靶点信息、适应症信息以及对应的研发阶段信息等信息的关系图谱。
步骤S102：根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段。
在本步骤中，所述根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段，具体实现过程包括：根据输入的所述目标靶点以及预设的靶点与药品信息的关系图谱，获取该目标靶点对应的第一药品信息集。比如输入的目标靶点为PDI靶点，此时对应的第一药品信息集可以包括帕博利珠单抗、纳武利尤单抗、卡瑞利珠单抗、特瑞普利单抗等。通过将所述第一药品信息集中的每个药品作为索引，根据预设的药品信息与适应症信息的关系图谱，能够获取所述第一药品信息集中每种药品信息对应的适应症信息集，并确定所述适应症信息集中每种适应症对应的第二药品信息集。其中，所述第二药品信息集是所述第一药品信息集的子集。与上述PDI靶点以及所列举的药物相对应，所述的适应症信息集可以包括：非小细胞肺癌、实体瘤、胃癌等。其中，所述的适应症信息集中每种适应症对应的第二药品信息集对应上述第一药品信息集中的部分内容，比如非小细胞肺癌适应症对应的第二药品信息集包含所述第一药品信息集中的帕博利珠单抗、纳武利尤单抗、卡瑞利珠单抗。
进一步的，根据所述适应症信息集、所述第二药品信息集以及预设的药品信息、适应症信息以及研发阶段之间的关系图谱，能够获取每种药品信息对应的研发阶段信息集，并获取每种适应症对应的研发阶段信息集。其中，所述研发阶段包括：临床前、申报临床、I期临床、I/II期临床、II期临床、II/III期临床、III期临床、III/IV期临床、IV期临床、申请上市和批准上市等研发阶段。
在具体实施过程中，基于所述药品信息，所述药品信息对应的适应症信息及其研发阶段，生成用于记录上述信息的m*n的基础表格，表格中每个元素记录相应的研发阶段。
步骤S103：针对各个研发阶段分别设置相应的权重值。
在步骤中，可进一步对所述基础表格中的各个研发阶段分别设置相应 的权重值，生成相应的次级表格。所述次级表格包含所述药品信息、所述适应症信息、所述研发阶段及其权重值等。
具体的，对各个研发阶段逐个赋予权重之后，随着研发阶段的推进，各研发阶段对应的权重值可以逐渐增加，比如预设每个研发阶段转换升级成功或者失败的概率均为50％，因此设置两个相邻研发阶段的权重差应为0.5，生成m*n的次级表格。比如针对临床前、申报临床、I期临床、I/II期临床、II期临床、II/III期临床、III期临床、III/IV期临床、IV期临床、申请上市和批准上市，每个研发阶段对应的权重分别设置为0.5、1.0、1.5、2.0、2.5、3.0、3.5、4.0、4.5、5.0和5.5。
需要说明的是，本申请所述的赋予权重的规则不限于上述所列举的情形，在实施过程中可按照实际需要进行变通，在此不做具体限定
步骤S104：每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值。
在本步骤中，所述的每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值，具体实现过程包括：每隔预设的时间间隔对所述每种药品信息对应的研发阶段信息集的权重值求和，得到第一目标权重值，根据所述第一目标权重值的大小对所述药品信息进行排序，获得所述药品信息分别对应的排序次序差值；以及，每隔预设的时间间隔对所述获取每种适应症对应的研发阶段信息集的权重值求和，得到第二目标权重值，根据所述第二目标权重值的大小对所述适应症信息进行排序，获得所述适应症信息分别对应的排序次序差值。
如下述表1.1和表1.2所示，其分别为生成的次级表格以及预设的时间间隔之后重新排序生成的目标表格。
在具体实施过程中，可每隔预设的时间间隔，比如每个一个月，对生成的次级表格进行药物信息的行排序及适应症信息的列排序，即对药品信息和适应症信息按照对应研发阶段集的权重值之和进行排序，具体的排序方式可以是：按照每一行的药品信息或每一列的适应症所对应的研发阶段集的权重之和进行降序排列，生成目标表格。
Figure PCTCN2021128305-appb-000001
表1.1
Figure PCTCN2021128305-appb-000002
表1.2
步骤S105：根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
具体的，若适应症对应的所述排序次序差值为负值，则表示所述目标靶点对应药品的临床适应症研发进展变慢，此时所述差值的绝对值越大则表示药品的临床适应症研发进展速度越慢；若适应症对应的所述排序次序差值为正值，则表示所述目标靶点对应药品的临床适应症研发进展变快或在研药物变多，此时所述差值的绝对值越大则表示药品的临床适应症研发进展速度越快或在研药物越多。若药品对应的所述排序次序差值为负值，则表示所述目标靶点对应药品研发进展变慢或临床适应症研发失败消失，此时所述差值的绝对值越大表示药品研发进展速度越慢或适应症研发失败越多；若药品对应的所述排序次序差值为正值，则表示所述目标靶点对应药品研发进展变快或临床适应症研发增加，此时所述差值的绝对值越大 表示药品研发进展速度越快或增加研发的临床适应症越多。
采用本申请实施例所述的针对靶点药物的数据分析方法，通过对研发阶段设置的权重对靶点对应的药品及其适应症数据进行排序，并通过在预设时间间隔中重新计算排序次序差值，准确获取各靶点下不同药物临床适应症的研发情况，及时的反应临床试验的变化趋势，让用户快速获取靶点下不同药物的临床适应症研发进展信息，可以全面、及时的反应临床试验的变化趋势和成功概率，让用户准确直观的获取靶点下不同药物的临床适应症研发进展信息，极大地提高了研发数据分析效率，同时数据的全面性和准确性也得有极大提升。
与上述提供的一种针对靶点药物的数据分析方法相对应，本申请还提供一种针对靶点药物的数据分析装置。由于该装置的实施例相似于上述方法实施例，所以描述的比较简单，相关之处请参见上述方法实施例部分的说明即可，下面描述的针对靶点药物的数据分析装置的实施例仅是示意性的。请参考图2所示，其为本申请实施例提供的一种针对靶点药物的数据分析装置的结构示意图。
本申请所述的一种针对靶点药物的数据分析装置具体包括如下部分：
请求获取单元201，用于获取目标靶点查询请求。
目标信息获取单元202，用于根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段。
权重设置单元203，用于针对各个研发阶段分别设置相应的权重值。
排序单元204，用于每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值。
数据分析单元205，用于根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
采用本申请实施例所述的针对靶点药物的数据分析装置，通过对研发阶段设置的权重对靶点对应的药品及其适应症数据进行排序，并通过在预设时间间隔中重新计算排序次序差值，准确获取各靶点下不同药物临床适应症的研发情况，及时的反应临床试验的变化趋势，让用户快速获取靶点下不同药物的临床适应症研发进展信息，可以全面、及时的反应临床试验 的变化趋势和成功概率，让用户准确直观的获取靶点下不同药物的临床适应症研发进展信息，极大地提高了研发数据分析效率，同时数据的全面性和准确性也得有极大提升。
与上述提供的针对靶点药物的数据分析方法相对应，本申请还提供一种电子设备。由于该电子设备的实施例相似于上述方法实施例，所以描述的比较简单，相关之处请参见上述方法实施例部分的说明即可，下面描述的电子设备仅是示意性的。如图3所示，其为本申请实施例公开的一种电子设备的实体结构示意图。该电子设备可以包括：处理器(processor)301、存储器(memory)302和通信总线303，其中，处理器301，存储器302通过通信总线303完成相互间的通信。处理器301可以调用存储器302中的逻辑指令，以执行针对靶点药物的数据分析方法，该方法包括：获取目标靶点查询请求；根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；针对各个研发阶段分别设置相应的权重值；每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
此外，上述的存储器302中的逻辑指令可以通过软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
另一方面，本申请实施例还提供一种计算机程序产品，所述计算机程序产品包括存储在非暂态计算机可读存储介质上的计算机程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，计算机能够执行上述各方法实施例所提供的针对靶点药物的数据分析方法，该方法包括： 根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；针对各个研发阶段分别设置相应的权重值；每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
又一方面，本申请实施例还提供一种非暂态计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现以执行上述各实施例提供的针对靶点药物的数据分析方法，该方法包括：根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；针对各个研发阶段分别设置相应的权重值；每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到各实施方式可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件。基于这样的理解，上述技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行各个实施例或者实施例的某些部分所述的方法。
最后应说明的是：以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修 改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。

Claims (10)

  1. 一种针对靶点药物的数据分析方法，其特征在于，包括：
    获取目标靶点查询请求；
    根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；
    针对各个研发阶段分别设置相应的权重值；
    每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；
    根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
  2. 根据权利要求1所述的针对靶点药物的数据分析方法，其特征在于，所述根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段，具体包括：
    根据所述目标靶点以及预设的靶点与药品信息的关系图谱，获取所述目标靶点对应的第一药品信息集；
    根据预设的药品信息与适应症信息的关系图谱，获取所述第一药品信息集中每种药品信息对应的适应症信息集，并确定所述适应症信息集中每种适应症对应的第二药品信息集；其中，所述第二药品信息集是所述第一药品信息集的子集；
    根据所述适应症信息集、所述第二药品信息集以及预设的药品信息、适应症信息以及研发阶段之间的关系图谱，获取每种药品信息对应的研发阶段信息集，并获取每种适应症对应的研发阶段信息集。
  3. 根据权利要求2所述的针对靶点药物的数据分析方法，其特征在于，所述每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值，具体包括：
    每隔预设的时间间隔对所述每种药品信息对应的研发阶段信息集的权重值求和，得到第一目标权重值；根据所述第一目标权重值的大小对所述药品信息进行排序，获得所述药品信息分别对应的排序次序差值；以及，每隔预设的时间间隔对所述获取每种适应症对应的研发阶段信息集的权 重值求和，得到第二目标权重值；根据所述第二目标权重值的大小对所述适应症信息进行排序，获得所述适应症信息分别对应的排序次序差值。
  4. 根据权利要求1所述的针对靶点药物的数据分析方法，其特征在于，还包括：
    基于所述药品信息，所述药品信息对应的适应症信息及其研发阶段，生成基础表格；
    对所述基础表格中的各个研发阶段分别设置相应的权重值，生成次级表格；所述次级表格包含所述药品信息、所述适应症信息、所述研发阶段及其权重值；
    每隔预设的时间间隔，根据所述次级表格中的所述权重值对所述药品信息和所述适应症信息进行排序，生成目标表格。
  5. 根据权利要求1-4任意一项所述的针对靶点药物的数据分析方法，其特征在于，所述研发阶段包括：临床前、申报临床、I期临床、I/II期临床、II期临床、II/III期临床、III期临床、III/IV期临床、IV期临床、申请上市和批准上市中的至少一个研发阶段。
  6. 一种针对靶点药物的数据分析装置，其特征在于，包括：
    请求获取单元，用于获取目标靶点查询请求；
    目标信息获取单元，用于根据所述目标靶点以及预设的关系图谱，获取所述目标靶点对应的药品信息，以及所述药品信息对应的适应症信息及其研发阶段；
    权重设置单元，用于针对各个研发阶段分别设置相应的权重值；
    排序单元，用于每隔预设的时间间隔，根据所述权重值对所述药品信息和所述适应症信息进行排序，获得相应的排序次序差值；
    数据分析单元，用于根据所述排序次序差值，确定所述目标靶点对应药品的临床适应症研发进展信息。
  7. 根据权利要求6所述的针对靶点药物的数据分析装置，其特征在于，所述目标信息获取单元，具体用于：
    根据所述目标靶点以及预设的靶点与药品信息的关系图谱，获取所述目标靶点对应的第一药品信息集；
    根据预设的药品信息与适应症信息的关系图谱，获取所述第一药品信 息集中每种药品信息对应的适应症信息集，并确定所述适应症信息集中每种适应症对应的第二药品信息集；其中，所述第二药品信息集是所述第一药品信息集的子集；
    根据所述适应症信息集、所述第二药品信息集以及预设的药品信息、适应症信息以及研发阶段之间的关系图谱，获取每种药品信息对应的研发阶段信息集，并获取每种适应症对应的研发阶段信息集。
  8. 根据权利要求7所述的针对靶点药物的数据分析方法，其特征在于，所述排序单元，具体用于：
    每隔预设的时间间隔对所述每种药品信息对应的研发阶段信息集的权重值求和，得到第一目标权重值；根据所述第一目标权重值的大小对所述药品信息进行排序，获得所述药品信息分别对应的排序次序差值；以及，每隔预设的时间间隔对所述获取每种适应症对应的研发阶段信息集的权重值求和，得到第二目标权重值；根据所述第二目标权重值的大小对所述适应症信息进行排序，获得所述适应症信息分别对应的排序次序差值。
  9. 一种电子设备，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，其特征在于，所述处理器执行所述程序时实现如权利要求1-5任意一项所述的针对靶点药物的数据分析方法的步骤。
  10. 一种非暂态计算机可读存储介质，其特征在于，其上存储有计算机程序，其特征在于，该计算机程序被处理器执行时实现如权利要求1-5任意一项所述的针对靶点药物的数据分析方法的步骤。
PCT/CN2021/128305 2020-11-04 2021-11-03 一种针对靶点药物的数据分析方法及装置 WO2022095870A1 (zh)

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