A pharmaceutical enterprise document management method, device, system and storage medium

Abstract

The embodiment of the application discloses a kind of management methods, device, system and storage medium of pharmaceutical enterprise document. It is related to pharmaceutical enterprise document management technical field. Among them, the management method includes: obtaining pharmaceutical enterprise document draft and document information and determining approval process and approval node;Receive approval result;If the approval result is approved, determine the training process and training unit;Receive training result information and convert the pharmaceutical enterprise document draft into official pharmaceutical enterprise document.The application obtains and processes document draft and its information automatically through the server, establishes a structured approval process, thereby significantly improving the approval efficiency and accuracy. The approval end quickly locates and approves the key part of the document according to the established process, ensuring the accuracy and compliance of the decision, realizing the full-process automation of document management, reducing human error, and improving the overall work efficiency and transparency of document management.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pharmaceutical enterprise document management, and particularly relates to a pharmaceutical enterprise document management method, device and system and a storage medium. BACKGROUND

[0002] In the pharmaceutical industry, the management of regulatory systems and workflow documents is a key link to ensure the compliance and efficiency of enterprise operation. These documents not only involve the internal management of the enterprise, but also directly relate to product quality and patient safety. With the rapid development of the pharmaceutical industry and the continuous updating of regulations, the complexity and importance of document management are increasing.

[0003] In the prior art, document management mainly relies on traditional paper documents and manual operations. The drafting, approval, distribution, and archiving of documents are mostly carried out through manual methods, which is low in efficiency. Version control of documents is difficult, the approval process is cumbersome, and the information island problem is prominent. These are common problems in the prior art. For example, the continuous revision of documents makes it a challenge to maintain consistency and traceability of different versions, and it is difficult to ensure that all users use the latest version of the document. Traditional paper approval process is time-consuming and inefficient, and communication during the approval process is not smooth, which leads to delays.

[0004] The defects of the prior art in document management mainly manifest in the following aspects: weak version control of documents, cumbersome approval process, serious information island problem, inadequate training management, untimely distribution of documents, inconvenient archiving and retrieval of documents, imperfect review mechanism, low efficiency of document drafting and revision, high risk of legal compliance, inconvenient borrowing management, difficulty in cross-department collaboration, and strong dependence on technical systems. These problems not only affect the efficiency and accuracy of document management, but also increase the operating costs and compliance risks of the enterprise.

[0005] The deficiencies in document management are also manifested in the following aspects: First, inadequate document version control leads to different users potentially using different versions of documents, affecting the consistency of decision-making and execution. Second, cumbersome and time-consuming approval processes affect the timely updating and application of documents. Third, information silos hinder information sharing between different departments, increasing the risk of duplication of work and errors. Furthermore, inadequate training management results in insufficient employee understanding of new policies, affecting the effectiveness of policy implementation. Delayed document distribution means that updated documents cannot be promptly communicated to all relevant personnel, affecting the normal operation of work. Inconvenient document archiving and retrieval increase the difficulty of finding and using documents. An imperfect review mechanism leads to the continued use of outdated documents, increasing compliance risks. Low efficiency in document drafting and revision increases the workload of document management. High legal compliance risks exist; improper document management may lead to legal issues. Inconvenient borrowing management affects the efficiency of document utilization. Difficult cross-departmental collaboration increases the coordination costs of document management. Strong dependence on technical systems increases the impact of system failures or upgrades on document management. These problems seriously affect the efficiency and effectiveness of document management in pharmaceutical companies and urgently require improvement and optimization. Summary of the Invention

[0006] In a first aspect, the present invention provides a method for managing pharmaceutical company documents, comprising:

[0007] The server obtains the draft document from the pharmaceutical company and the corresponding document information, and determines the corresponding approval process and approval node based on the document information, so that the approval end can approve the draft document from the pharmaceutical company based on the approval node and the approval process.

[0008] The server receives the approval result from the approval terminal based on the approval node;

[0009] If the approval result is approved, the server determines the corresponding training process and training unit based on the document information, so as to conduct training for the training unit according to the training process;

[0010] The server receives the training result information from the training unit and converts the draft pharmaceutical company document into the corresponding official pharmaceutical company document based on the training result information.

[0011] In an optional implementation, before receiving the approval result from the approval node, the method further includes:

[0012] The approval terminal obtains the document information and the approval process, and, based on the approval process and the document information, obtains the corresponding approval section in the pharmaceutical company's draft document;

[0013] The approval terminal reviews the approval section and obtains the approval result.

[0014] In an optional implementation, the approval terminal approves the approval portion to obtain the approval result, including:

[0015] The approval terminal obtains the content information corresponding to each analysis unit in the approval section, and confirms the corresponding keywords based on the content information; wherein, the content information includes at least one of text information and chart information;

[0016] The approval process matches relevant regulatory clauses at various levels based on the keywords; these regulatory clauses include departmental laws, administrative regulations, local regulations, departmental rules, and enterprise standards.

[0017] Determine whether the content information corresponding to the analysis unit complies with all the aforementioned regulatory clauses;

[0018] If so, the compliance of the content information corresponding to the analysis unit is determined, and a compliance prompt is generated to prompt the approval end to conduct the approval and generate the approval result;

[0019] If not, the non-compliant regulatory clauses will be listed, and a non-compliance prompt will be generated to prompt the approval end to conduct an approval and generate the approval result.

[0020] In an optional implementation, the approval process matches corresponding regulatory clauses at various levels based on the keywords, including:

[0021] Construct a semantic matching model and a regulatory clause database; wherein the semantic matching model includes keyword vectors corresponding to keywords and regulatory clause vectors; the regulatory clause data includes index information corresponding to each regulatory clause;

[0022] Based on the semantic matching model, the similarity between the keyword vector domain and the legal clause vectors is calculated; wherein, the method for calculating the similarity includes:

[0023]

[0024] Similarity represents the similarity; A represents the keyword vector; B represents the legal clause vector; A·B represents the dot product of the keyword vector and the legal clause vector; ||A|| and ||B|| represent the Euclidean norms of the keyword vector and the legal clause vector.

[0025] The similarity is filtered according to a preset threshold, and regulatory clause information at each level that matches the keyword is obtained through the regulatory clause database.

[0026] In an optional implementation, the approval process of the approval terminal further includes:

[0027] The approval section is divided into multiple sequentially connected grid cells; and a membership function is set for each grid cell.

[0028] Listen for mouse movement events and obtain the current mouse position where the mouse is hovering based on the movement events;

[0029] Calculate the center distance between the current position of the mouse and the geometric center of each of the grid cells;

[0030] Calculate the membership value of each grid cell based on the center distance;

[0031] Based on the membership value, the fuzziness of the grid cell is set; and the display effect of each grid cell is set based on the fuzziness.

[0032] In an optional implementation, the method for calculating the center distance includes:

[0033]

[0034] Where d represents the center distance; (x mouse -x center (y) represents the current coordinates of the mouse; mouse -y center ) represents the coordinates of the geometric center of the grid cell.

[0035] In an optional implementation, the method for calculating the membership value includes:

[0036]

[0037] Where d represents the center distance; σ represents the ambiguity control coefficient; and e represents the membership value.

[0038] Secondly, the present invention provides a pharmaceutical company document management device, comprising:

[0039] The determination module is used by the server to obtain the draft document of the pharmaceutical company and the corresponding document information, and determine the corresponding approval process and approval node based on the document information, so that the approval end can approve the draft document of the pharmaceutical company based on the approval node and the approval process.

[0040] A receiving module is used for the server to receive the approval result from the approval terminal based on the approval node;

[0041] The determining module is further configured to, if the approval result is approval, determine the corresponding training process and training unit based on the document information, so as to conduct training on the training unit according to the training process;

[0042] The generation module is used by the server to receive the training result information from the training unit and convert the pharmaceutical company document draft into the corresponding pharmaceutical company official document based on the training result information.

[0043] Thirdly, the present invention provides a pharmaceutical company document management system, including a memory and a processor. The memory stores a pharmaceutical company document management program, and the processor runs the pharmaceutical company document management program to enable the pharmaceutical company document management system to perform the pharmaceutical company document management method as described in any of the foregoing embodiments.

[0044] Fourthly, the present invention provides a computer-readable storage medium storing a pharmaceutical company document management program, wherein the pharmaceutical company document management program, when executed by a processor, implements the pharmaceutical company document management method as described in any of the foregoing embodiments.

[0045] This invention provides a method for managing pharmaceutical company documents, comprising: a server acquiring a draft pharmaceutical company document and corresponding document information, and determining a corresponding approval process and approval node based on the document information, so that an approval end can approve the draft pharmaceutical company document based on the approval node and the approval process; the server receiving the approval result from the approval end based on the approval node; if the approval result is "approved," the server determining a corresponding training process and training unit based on the document information, so that training is conducted on the training unit according to the training process; the server receiving training result information from the training unit and converting the draft pharmaceutical company document into a corresponding formal pharmaceutical company document based on the training result information. In an optional embodiment, before receiving the approval result from the approval node, the method further comprises: the approval end acquiring the document information and the approval process, and, based on the approval process and the document information, acquiring the corresponding approval portion in the draft pharmaceutical company document; the approval end approving the approval portion to obtain the approval result.

[0046] This invention establishes a structured approval process by automating the acquisition and processing of draft documents and their information on the server side, thereby significantly improving approval efficiency and accuracy. The approval end quickly locates and approves key parts of the document according to the established process, ensuring the accuracy and compliance of decisions. Furthermore, once approved, the server immediately initiates a customized training process to provide targeted training to relevant personnel, further ensuring the standardization and effectiveness of document execution. Finally, the server automatically converts the draft document into a final document based on the training results, achieving full automation of the document management process, reducing human error, and improving overall work efficiency and transparency in document management. Attached Figure Description

[0047] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope of protection of the present invention. In the various drawings, similar components are numbered similarly.

[0048] Figure 1 This is a schematic diagram of the hardware operating environment involved in an embodiment of the pharmaceutical enterprise document management method of the present invention;

[0049] Figure 2 This is a flowchart illustrating Example 1 of the pharmaceutical company document management method of the present invention;

[0050] Figure 3 This is a supplementary flowchart before step S200 in Embodiment 2 of the pharmaceutical company document management method of the present invention;

[0051] Figure 4 This is a detailed flowchart illustrating step S600 (including steps S610 to S650) in Embodiment 2 of the pharmaceutical company document management method of the present invention.

[0052] Figure 5 This is a detailed flowchart of step S620 in Embodiment 2 of the pharmaceutical company document management method of the present invention;

[0053] Figure 6 This is a detailed flowchart illustrating step S600 (including steps S660-1 to S660-4) in Embodiment 3 of the pharmaceutical company document management method of the present invention.

[0054] Figure 7 This is a schematic diagram of the module connection of the pharmaceutical company document management device in an embodiment of the present invention. Detailed Implementation

[0055] The embodiments of the present invention are described in detail below, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout.

[0056] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0057] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0058] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0059] like Figure 1 The diagram shown is a structural schematic of the hardware operating environment of the terminal involved in an embodiment of the present invention.

[0060] The pharmaceutical document management system provided in this embodiment of the invention can be a PC, or a mobile terminal device such as a smartphone, tablet, or laptop. The pharmaceutical document management system may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen, an input unit such as a keyboard, or a remote control; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM memory or a stable memory, such as a disk storage device. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001. Optionally, the pharmaceutical document management system may also include RF (Radio Frequency) circuitry, audio circuitry, a Wi-Fi module, etc. In addition, the pharmaceutical company's document management system can also be configured with other sensors such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, which will not be elaborated here.

[0061] Those skilled in the art will understand that Figure 1The pharmaceutical company document management system shown is not intended to limit it and may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. Figure 1 As shown, the memory 1005, which is a computer-readable storage medium, may include an operating system, a data interface control program, a network connection program, and a pharmaceutical company document management program.

[0062] Example 1

[0063] Reference Figure 2 Embodiment 1 of the present invention provides a method for managing pharmaceutical company documents, including:

[0064] Step S100: The server obtains the draft document of the pharmaceutical company and the corresponding document information, and determines the corresponding approval process and approval node based on the document information, so that the approval end can approve the draft document of the pharmaceutical company based on the approval node and the approval process.

[0065] The aforementioned pharmaceutical company documents may include, but are not limited to: rules and regulations and work process documents, for example, such as:

[0066] Standard Management Documents (SMP): These documents cover the company's quality objectives and policies, the responsibilities, authority, working relationships, and communication methods of various departments / positions within the organization, such as management procedures for facilities and equipment, materials and products, validation and verification, production, quality control, and quality assurance.

[0067] Technical Standards (TS): This includes quality standard documents for raw materials, auxiliary materials, packaging materials, semi-finished products, intermediates, and finished products, as well as product process specifications, product inspection procedures, and validation procedures.

[0068] Standard Operating Procedures (SOPs): Documents that guide employees to complete specific operations, such as job operation procedures, equipment operation, cleaning and maintenance operation procedures, etc.

[0069] The above method can be applied to the server and the clients of each node connected to the server.

[0070] The first step in the server-side document management process is to collect draft documents and related information from pharmaceutical companies.

[0071] Draft pharmaceutical company documentation is a draft submitted by the applicant for pharmaceutical company documentation, used for approval processes and internal training.

[0072] A draft document refers to a draft document awaiting approval. Document information may include document type (SOP, TS, etc.), content summary, creator, creation time, etc. This provides the basic data for the document, laying the foundation for subsequent approval processes. It ensures that the approval process has sufficient information, improving accuracy and efficiency.

[0073] Based on the above, the corresponding approval process and each approval node can be determined. The server then identifies the necessary procedures and key approval nodes for document approval. The approval process refers to the sequence of approval steps, while approval nodes are the critical decision points within that process. A clear approval path ensures the orderly progress of the approval process. Providing clear approval guidance reduces approval time and avoids confusion.

[0074] Then, the approval process can be used to approve the draft document based on the approval workflow and timelines provided by the server. The approval process may include multiple approvers, each of whom makes or modifies the document according to their own responsibilities.

[0075] Step S200: The server receives the approval result from the approval terminal based on the approval node;

[0076] As mentioned above, the server receives the approval result from the approval server as the basis for the next step.

[0077] The approval result may be approved, rejected, or in other states (such as requiring modification, conditionally approved, etc.). Obtaining formal feedback from the approval process provides decision support for subsequent document processing and ensures the real-time updating and accuracy of the document status.

[0078] Step S300: If the approval result is "approved", the server determines the corresponding training process and training unit based on the document information, so as to conduct training for the training unit according to the training process.

[0079] If the approval result is passed, the server will determine the training process and training unit based on the document information.

[0080] The training process refers to the steps and plans for training, while the training unit refers to the department or personnel who need to receive training. It ensures that relevant personnel fully understand the document content, improving execution efficiency and enhancing the relevance and effectiveness of the training.

[0081] In step S400, the server receives the training result information from the training unit and converts the draft pharmaceutical document into the corresponding official pharmaceutical document based on the training result information.

[0082] The server receives training outcome information from training institutions and converts the draft document into a formal document based on the results. The conversion process may include formatting adjustments, version updates, and stamping, thus formalizing the document and giving it official validity. The final version of the document is ensured to be accurate and error-free, ready for official release and use.

[0083] In summary, this embodiment establishes a structured approval process by automating the acquisition and processing of draft documents and their information on the server side, thereby significantly improving approval efficiency and accuracy. The approval end quickly locates and approves key parts of the document according to the established process, ensuring the accuracy and compliance of decisions. Furthermore, once approved, the server immediately initiates a customized training process to provide targeted training to relevant personnel, further ensuring the standardization and effectiveness of document execution. Finally, the server automatically converts the draft document into a formal document based on the training results, achieving full automation of the document management process, reducing human error, and improving overall work efficiency and transparency in document management.

[0084] Example 2

[0085] Reference Figure 3 Embodiment 2 of the present invention provides a method for managing pharmaceutical company documents. Based on Embodiment 1 above, before receiving the approval result of the approval node in step S200, the method further includes:

[0086] Step S500: The approval terminal obtains the document information and the approval process, and obtains the corresponding approval section in the pharmaceutical company's draft document based on the approval process and the document information;

[0087] As described above, the approval end (an individual with approval authority operating through their own client or system) first needs to obtain relevant document information and the approval process. Document information may include document type, bibliographic information, content, version, author, etc., while the approval process specifies the order and steps of the approval.

[0088] The approval process obtains all the information required for approval, which helps approvers fully understand the document content and approval requirements, ensuring the accuracy of the approval.

[0089] Specifically, access interfaces for document information and approval processes can be provided through the document management system.

[0090] In step S600, the approval terminal approves the approval portion and obtains the approval result.

[0091] Based on the approval process and document information, the approval team identifies sections of the document that require special attention and approval. This may involve specific chapters, clauses, or key content points. By focusing on the critical parts of the document, the approval team can process applications more efficiently, ensuring that critical information is thoroughly reviewed.

[0092] Further reference Figure 4 In step S600, the approval end reviews the approval portion to obtain the approval result, including:

[0093] Step S610: The approval terminal obtains the content information corresponding to each analysis unit in the approval section, and confirms the corresponding keywords based on the content information; wherein, the content information includes at least one of text information and chart information;

[0094] As mentioned above, the approval process requires extracting the content information of each analytical unit from the approval section of the draft document. An analytical unit can be a paragraph, a data table, a chart, etc., and is the basic unit that the approval process needs to focus on reviewing.

[0095] By focusing on key analytical units within a document, the approval process can conduct more detailed reviews, ensuring the accuracy and completeness of the document content. The document management system's structured features identify these individual analytical units.

[0096] For example, the system can automatically identify titles, subheadings, tables, charts, etc. in a document and provide them to the approval end as separate analysis units.

[0097] As described above, the approval process identifies and confirms keywords based on the content information from the analysis unit. Keywords are the core of the document content and help the approval process quickly grasp the key points of the document.

[0098] Identifying keywords helps the approval process match legal provisions in subsequent steps, improving the targeting and efficiency of the approval process.

[0099] Text analysis techniques, such as Natural Language Processing (NLP), can be used to automatically identify and extract keywords.

[0100] For example, text mining algorithms such as TF-IDF or topic modeling can be used to extract keywords from each analysis unit.

[0101] Step S620: The approval terminal matches the corresponding regulatory clause information at each level based on the keywords; wherein, the regulatory clause information includes departmental laws, administrative regulations, local regulations, departmental rules and enterprise standards;

[0102] As described above, the approval process matches the extracted keywords with relevant legal provisions. This step is to ensure that the document content complies with legal requirements.

[0103] It should be noted that pharmaceutical company documents include management documents, technical documents, and standard documents. Among these documents, such as the pharmaceutical company's technical standard operating procedures (SOP) documents, they must comply with the requirements of laws, relevant judicial interpretations, regulations, and local regulations.

[0104] Pharmaceutical companies' SOP documents must comply with relevant drug management laws and regulations, such as the "Drug Administration Law," to ensure the legality of the drug production process.

[0105] GMP (Good Manufacturing Practice) is the international standard for pharmaceutical production and quality management. Pharmaceutical companies' SOP documents must comply with GMP standards to ensure product quality and safety.

[0106] Different regions may have specific regulatory requirements, and pharmaceutical companies' SOP documents need to take into account the specific requirements of local regulations to ensure compliance in a particular region.

[0107] In addition to laws and regulations, pharmaceutical companies also need to follow industry guidelines and best practices, which may be issued by professional organizations or regulatory agencies.

[0108] In some cases, judicial interpretations may provide guidance on specific issues related to drug production and quality management. Pharmaceutical companies' SOP documents need to take these interpretations into account to avoid legal risks.

[0109] Laws, regulations, and industry standards may be updated and changed, and pharmaceutical companies' SOP documents need to be reviewed and updated regularly to ensure continued compliance.

[0110] SOP documents should include risk management measures to ensure that potential risks can be identified, assessed and controlled during the drug manufacturing process.

[0111] Regulatory agencies may impose specific requirements on pharmaceutical companies regarding the development and implementation of their Standard Operating Procedures (SOPs), which pharmaceutical companies must meet in order to pass regulatory reviews.

[0112] In summary, pharmaceutical companies' technical standard operating procedures (SOPs) are crucial documents for ensuring drug quality and safety, and must fully comply with legal, regulatory, and industry standards. This is not only a mandatory legal requirement but also a reflection of corporate social responsibility.

[0113] In the above steps, when conducting approval at the approval end, the first step is to conduct a legality approval. Matching the legal provisions with relevant information helps to identify potential compliance risks in the document and ensures the document's legality.

[0114] By searching for keywords in the legal database, relevant legal provisions can be found.

[0115] For example, by building a regulatory database, the approval process can retrieve all relevant regulatory clauses through keyword searches.

[0116] Step S630: Determine whether the content information corresponding to the analysis unit complies with all the legal and regulatory clauses.

[0117] As mentioned above, the approval end determines whether the content of the analysis unit fully complies with the regulatory requirements based on the matched regulatory clause information.

[0118] Compliance assessment is a crucial step in the approval process, ensuring that document content does not violate laws and regulations and reducing legal risks for the company. This assessment can be conducted through manual review or automated compliance checking tools. For example, the approval team can compare and analyze the unit's content with regulatory clauses, or use compliance checking software to automatically evaluate the content's compliance.

[0119] Step S640: If yes, then determine the compliance of the content information corresponding to the analysis unit and generate a regulatory compliance prompt message so as to prompt the approval end to conduct approval and generate the approval result;

[0120] Step S650: If not, list the non-compliant regulatory clauses and generate a non-compliance prompt message to prompt the approval end to conduct an approval and generate the approval result.

[0121] Based on the compliance assessment results, the approval process generates corresponding prompts. If the content is compliant, a compliance prompt is generated; if the content is non-compliant, the non-compliant legal provisions are listed, and a non-compliance prompt is generated.

[0122] The notification information provides the approval authorities with clear approval criteria, thus speeding up the approval decision-making process.

[0123] The system generates notification messages through its automated feedback mechanism.

[0124] For example, the system can automatically generate prompts based on the results of compliance checks and display them to users on the approval side.

[0125] The above steps further refine the document approval process, particularly in compliance checks. Through keyword extraction, regulatory clause matching, and compliance assessment, this step ensures the legality and compliance of the document content. These steps can be implemented using modern text analysis techniques and regulatory database query tools, as well as automated compliance checking software. The combined use of these technologies can significantly improve the efficiency and accuracy of pharmaceutical company document approvals.

[0126] Further reference Figure 5In step S620, the approval end matches the corresponding regulatory clauses at each level based on the keywords, including:

[0127] Step S621: Construct a semantic matching model and a regulatory clause database; wherein, the semantic matching model includes keyword vectors corresponding to keywords and regulatory clause vectors; the regulatory clause data includes index information corresponding to each regulatory clause;

[0128] The above describes the creation of a model for comparing the similarity between document keywords and regulatory clauses, as well as a database containing information on regulatory clauses. This model will help the approval process understand the relationship between document content and regulatory clauses.

[0129] By constructing a semantic matching model, the relevance between keywords in documents and regulatory clauses can be identified more accurately. The regulatory clause database provides a comprehensive source of regulatory information, ensuring the comprehensiveness and accuracy of approvals.

[0130] Natural language processing techniques are used to build a semantic matching model, and a database of legal provisions is built using a database management system.

[0131] For example, a semantic matching model can be trained using machine learning algorithms, while legal provisions can be digitized and stored in a database, with each provision having corresponding index information.

[0132] Step S622: Based on the semantic matching model, calculate the similarity between the keyword vector domain and the legal clause vector; wherein, the method for calculating the similarity includes:

[0133]

[0134] Similarity represents the similarity; A represents the keyword vector; B represents the legal clause vector; A·B represents the dot product of the keyword vector and the legal clause vector; ||A|| and ||B|| represent the Euclidean norms of the keyword vector and the legal clause vector.

[0135] The above steps involve converting keywords and regulatory clauses in the document into vector form and calculating their similarity. This step quantitatively assesses the degree of matching between the document content and regulatory clauses, providing a quantified similarity index to help the approval process quickly identify the consistency between document content and regulatory clauses.

[0136] Similarity can be calculated using the vector space model and the cosine similarity formula.

[0137] For example, word embedding techniques such as Word2Vec or BERT can be used to convert keywords and legal clauses into vectors, and then the cosine similarity formula can be applied to calculate the similarity between them.

[0138] Formula 1 provides a standardized method to measure the similarity between two vectors, allowing the approval process to compare the degree of matching between different documents and regulatory clauses. The cosine similarity is calculated programmatically.

[0139] For example, in Python, the NumPy library can be used to calculate the dot product and norm of vectors, and then the above formula can be applied to obtain the similarity.

[0140] Step S623: Filter the similarity according to a preset threshold, and obtain regulatory clause information at each level that matches the keyword through the regulatory clause database.

[0141] As mentioned above, a preset threshold is set, and only when the similarity exceeds this threshold is the document content considered to match the legal provisions.

[0142] By filtering out regulatory clauses highly relevant to document keywords, the number of regulatory clauses that need to be considered by the approval process is reduced, thus improving approval efficiency. This can be achieved by setting a threshold and filtering the similarity calculation results.

[0143] For example, a threshold of 0.8 can be set, so only regulatory clauses with a similarity higher than 0.8 are considered to match the keywords and require further review by the approval process.

[0144] The steps in this embodiment deepen the regulatory compliance check during the document approval process. By constructing a semantic matching model and a regulatory clause database, the similarity between keywords and regulatory clauses is calculated, and filtering is performed based on thresholds. This step ensures the regulatory compliance of the document content. These steps can be implemented using existing natural language processing and database management technologies, as well as machine learning algorithms to improve automation and accuracy. The combined use of these technologies can significantly improve the efficiency and compliance of pharmaceutical company document approval.

[0145] Example 3

[0146] Reference Figure 6 Embodiment 3 of the present invention provides a method for managing pharmaceutical company documents. Based on Embodiment 1 above, step S600, in which the approval end approves the approval portion, further includes:

[0147] Step S660-1: The approval section is divided into multiple sequentially connected grid cells; and a membership function is set for each grid cell.

[0148] Maintaining confidentiality in pharmaceutical company documents during the review process is extremely important because these documents typically contain the company's trade secrets and technical secrets, such as research and development materials, experimental data, manufacturing processes, formulations, technical secrets, marketing strategies, sales data, customer lists, financial data, and patented technologies. Confidentiality not only protects the company's legitimate rights and interests and maintains fair market competition, but also ensures the quality and safety of pharmaceutical products. Furthermore, document management that complies with GMP (Good Manufacturing Practice) requirements is key to ensuring that the entire pharmaceutical production process consistently meets legal requirements.

[0149] In addition to security measures such as encryption and decryption, pharmaceutical companies need to consider anti-peeping strategies during document review to protect sensitive information on multiple levels. First, encryption technology primarily addresses the confidentiality of data storage and transmission, while anti-peeping strategies add protection during document use and display, preventing unauthorized personnel from visually accessing sensitive information. Second, regulations and standards such as GMP require pharmaceutical companies to ensure the security and integrity of documents and data; anti-peeping technology, as an additional security measure, helps meet these stringent compliance requirements.

[0150] Furthermore, internal personnel may pose a risk of information leakage, and anti-spying strategies can effectively reduce the risk of sensitive information being leaked due to human negligence or intentional acts. Raising employees' security awareness is also an important aspect of implementing anti-spying strategies, helping to create a more cautious and secure work environment throughout the company. With the development of information technology, integrating multiple security measures, including anti-spying technologies, can enhance the innovation and effectiveness of pharmaceutical company document management systems.

[0151] Conventional techniques typically only involve encrypting and decrypting documents, without considering the issue of preventing eavesdropping on pharmaceutical company document archives during the review process. In this application, to address the aforementioned problem, a strategy for preventing eavesdropping on draft pharmaceutical company documents during the review process is provided.

[0152] The above approach first divides the document's approval section into multiple small grid units, each representing a portion of the document, which could be a paragraph of text or a part of a chart. This grid-based processing allows for more detailed approval and analysis of each small part of the document. Specifically, document processing software or a custom algorithm can be used to divide the document content into grid units.

[0153] For example, text can be divided into grids based on paragraphs or sentences; charts can be divided based on different parts of the chart or data points.

[0154] As described above, a membership function is set for each grid cell. A membership function is defined to evaluate the display clarity of the cell when the mouse hovers over it.

[0155] Membership functions help dynamically adjust the display of each grid cell, achieving anti-peeping functionality. Specifically, this can be achieved by programming a membership function associated with each grid cell.

[0156] For example, the membership function can be a Gaussian function, which adjusts the membership value based on the distance between the mouse hover position and the center of the grid cell.

[0157] Step S660-2: Listen for mouse movement events and obtain the current position of the mouse when it is hovering based on the movement events;

[0158] As described above, event listening technology is used to capture mouse movement on the document and obtain the current mouse position. Real-time mouse position acquisition allows for processing of the corresponding grid cells, enhancing the user experience.

[0159] Listen for mouse events using a front-end scripting language such as JavaScript.

[0160] For example, use a mousemove event listener to track mouse position.

[0161] Step S660-3: Calculate the center distance between the current position of the mouse and the geometric center of each grid cell;

[0162] The above describes the calculation of the distance between the mouse pointer position and the center point of each grid cell. The resulting distance value will be used to determine the input to the membership function, thus affecting the display effect of the grid cells.

[0163] Step S660-4: Calculate the membership value of each grid cell based on the center distance;

[0164] The membership function and center distance are used to calculate the membership value of each grid cell. The membership value reflects the clarity that the grid cell should appear when the mouse hovers over it.

[0165] Substitute the calculated distance value into the membership function.

[0166] For example, if the membership function is a Gaussian function, the distance value can be substituted to obtain the membership value.

[0167] Step S660-5: Set the fuzziness of the grid cell according to the membership value; and set the display effect of each grid cell according to the fuzziness.

[0168] As described above, the fuzziness of each grid cell is adjusted based on its membership value; the higher the membership value, the lower the fuzziness. This achieves a dynamic blurring effect, protecting document content from unauthorized viewing.

[0169] Specifically, the blur level can be adjusted using CSS filters or graphics processing libraries.

[0170] For example, use the CSS property filter:blur(value); where value is determined based on the membership value.

[0171] As described above, the final display effect of each grid cell on the screen is adjusted based on the degree of blur. Only the grid cell where the mouse hovers is displayed clearly, while other cells are blurred, achieving an anti-peeping effect.

[0172] Blur effects can be achieved by dynamically adjusting the CSS properties of each grid cell or by using a graphics library to draw the blur effect.

[0173] For example, by setting different CSS classes for each grid cell and dynamically switching these classes based on membership values, a blurring effect can be achieved.

[0174] The steps in this embodiment enhance the protection of visual information during the document approval process. Through gridding, membership function settings, mouse event monitoring, and dynamic adjustment of fuzziness, this step ensures the security of document content during approval. These steps can be implemented using front-end development technologies such as HTML, CSS, and JavaScript, as well as mathematical computation and natural language processing techniques. The combined use of these technologies can significantly improve the security and user experience of pharmaceutical company document approval.

[0175] Furthermore, the method for calculating the center distance includes:

[0176]

[0177] Where d represents the center distance; (x mouse -x center (y) represents the current coordinates of the mouse; mouse -y center ) represents the coordinates of the geometric center of the grid cell.

[0178] The formula above calculates the distance between the mouse hover position and the center of each grid cell in the document, which is the basis for implementing the anti-peeping function. A mathematical formula is used to calculate the Euclidean distance between the current mouse coordinates and the coordinates of the center of each grid cell, thus obtaining the specific distance value between the mouse and the center of each grid cell.

[0179] Formula 2 accurately reflects the position of the mouse relative to the document content, providing a basis for setting the blur level.

[0180] Coordinate distances can be calculated programmatically, for example, using JavaScript in a web environment.

[0181] Furthermore, the method for calculating the membership value includes:

[0182]

[0183] Where d represents the center distance; σ represents the ambiguity control coefficient; and e represents the membership value.

[0184] The above describes the calculation of the membership value of each grid cell based on the center distance, used to determine the display clarity of that cell. A Gaussian function is used to calculate the membership value f(d) based on the center distance d. The Gaussian function is a common membership function used in fuzzy logic, thus obtaining the membership value of each grid cell based on its distance from the mouse position. The higher the membership value, the more important or relevant the cell is.

[0185] Formula 3 achieves the effect of dynamically adjusting the display of document content based on the mouse position, thus enhancing the document's ability to prevent peeping.

[0186] Further reference Figure 7 This application also provides a pharmaceutical company document management device, including:

[0187] The determination module 10 is used for the server to obtain the draft document of the pharmaceutical company and the corresponding document information, and to determine the corresponding approval process and approval node based on the document information, so that the approval end can approve the draft document of the pharmaceutical company based on the approval node and the approval process.

[0188] The receiving module 20 is used for the server to receive the approval result from the approval terminal based on the approval node;

[0189] The determining module 10 is further configured to, if the approval result is approval, determine the corresponding training process and training unit based on the document information, so as to conduct training on the training unit according to the training process;

[0190] The generation module 30 is used to receive the training result information from the training unit shown on the server side, and convert the draft pharmaceutical document into the corresponding formal pharmaceutical document based on the training result information.

[0191] Furthermore, this application embodiment also provides a pharmaceutical company document management system, including a memory and a processor. The memory stores a pharmaceutical company document management program, and the processor runs the pharmaceutical company document management program to enable the pharmaceutical company document management system to perform the pharmaceutical company document management method as described in any of the foregoing embodiments.

[0192] Furthermore, this application embodiment also provides a computer-readable storage medium storing a pharmaceutical company document management program, which, when executed by a processor, implements the pharmaceutical company document management method as described in any of the foregoing embodiments.

[0193] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, as an alternative implementation, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0194] In addition, the functional modules or units in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0195] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a smartphone, personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0196] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method of managing pharmaceutical documents, characterized by, The method comprises the following steps: The server obtains a pharmaceutical enterprise document draft and corresponding document information, and determines a corresponding approval process and an approval node according to the document information, so that the approval end performs approval on the pharmaceutical enterprise document draft according to the approval process based on the approval node; The approval end obtains the document information and the approval process, and obtains a corresponding approval part in the pharmaceutical enterprise document draft according to the approval process and the document information; The approval end performs approval on the approval part to obtain an approval result; The approval end obtains content information corresponding to each analysis unit in the approval part, and confirms a corresponding keyword according to the content information; wherein the content information comprises at least one of text information and chart information; The approval end matches corresponding regulation clause information of each level according to the keyword; wherein, the regulation clause information includes department law, administrative regulations, local regulations, department rules and enterprise standards; the approval end matches corresponding regulation clause information of each level according to the keyword, including: constructing a semantic matching model and a regulation clause database; wherein, the semantic matching model includes keyword vector corresponding to the keyword and regulation clause vector; the regulation clause database includes index information corresponding to each regulation clause; based on the semantic matching model, the similarity between the keyword vector and the regulation clause vector is calculated; wherein, the calculation method of the similarity includes: ; similarity represents the similarity; A represents the keyword vector; B represents the regulation clause vector; represents the dot product of the keyword vector and the regulation clause vector; and represents the Euclidean norm of the keyword vector and the regulation clause vector; the similarity is screened according to a preset threshold, and the regulation clause information of each level matched with the keyword is obtained through the regulation clause database. It is judged whether the content information corresponding to the analysis unit conforms to all the regulation clause information; If yes, it is determined that the content information corresponding to the analysis unit is compliant, and a regulation compliance prompt information is generated to prompt the approval end to perform approval and generate the approval result; If no, the regulation clause information that does not conform is listed, and a non-compliance prompt information is generated to prompt the approval end to perform approval and generate the approval result; If the approval result is passed, the server determines a corresponding training process and a training unit according to the document information, so as to perform training on the training unit according to the training process; The server receives training result information of the training unit, and converts the pharmaceutical enterprise document draft into a corresponding pharmaceutical enterprise formal document according to the training result information; The approval end performs approval on the approval part, and further comprises: The approval part is cut into a plurality of grid units connected in sequence, and a membership function is set for each grid unit; A mouse movement event is listened to, and a current position of the mouse hovering is obtained according to the movement event; A center distance between the current position of the mouse and a geometric center of each grid unit is calculated; the calculation method of the center distance comprises: ； wherein d represents the center distance; representing the current coordinates of the mouse; representing the coordinates of the geometric center of the grid cell; According to the center distance, a membership value of each grid unit is calculated; the calculation method of the membership value comprises: ； Wherein, d represents the center distance; sigma represents the control coefficient of fuzziness; e represents the membership value; According to the membership value, the fuzziness of the grid unit is set, and the display effect of each grid unit is set according to the fuzziness.

2. A pharmaceutical document management apparatus characterized by comprising: The method comprises the following steps: A determination module is configured to enable the server to obtain a pharmaceutical enterprise document draft and corresponding document information, and to determine a corresponding approval process and an approval node according to the document information, so that the approval end performs approval on the pharmaceutical enterprise document draft according to the approval process based on the approval node; A receiving module is configured to enable the approval end to obtain the document information and the approval process, and to obtain a corresponding approval part in the pharmaceutical enterprise document draft according to the approval process and the document information; The approval end performs approval on the approval part to obtain an approval result; The approval end obtains content information corresponding to each analysis unit in the approval part, and determines the corresponding keyword according to the content information; wherein the content information includes at least one of text information and chart information; The approval end matches corresponding regulation clause information of each level according to the keyword; wherein, the regulation clause information includes department law, administrative regulations, local regulations, department rules and enterprise standards; the approval end matches corresponding regulation clause information of each level according to the keyword, including: constructing a semantic matching model and a regulation clause database; wherein, the semantic matching model includes keyword vector corresponding to the keyword and regulation clause vector; the regulation clause database includes index information corresponding to each regulation clause; based on the semantic matching model, the similarity between the keyword vector and the regulation clause vector is calculated; wherein, the calculation method of the similarity includes: ; similarity represents the similarity; A represents the keyword vector; B represents the regulation clause vector; represents the dot product of the keyword vector and the regulation clause vector; and represents the Euclidean norm of the keyword vector and the regulation clause vector; the similarity is screened according to a preset threshold, and the regulation clause information of each level matched with the keyword is obtained through the regulation clause database. It is judged whether the content information corresponding to the analysis unit conforms to all the regulation clause information; If yes, it is determined that the content information corresponding to the analysis unit is compliant, and a regulation-compliant prompt information is generated to prompt the approval end to perform approval and generate the approval result; If not, the regulation clause information that does not conform is listed, and a non-compliant prompt information is generated to prompt the approval end to perform approval and generate the approval result; The determination module is further configured to, if the approval result is passing the approval, determine a corresponding training process and a training unit according to the document information, so as to train the training unit according to the training process; The generation module is configured to receive training result information of the training unit by the service end, and convert the pharmaceutical enterprise document draft into a corresponding formal pharmaceutical enterprise document according to the training result information; The approval end performs approval on the approval part, and further includes: The approval part is cut into a plurality of grid units connected in sequence, and a membership function is set for each grid unit; A moving event of a mouse is listened to, and a current position of the mouse hovering over the mouse is obtained according to the moving event; A center distance between the current position of the mouse and a geometric center of each grid unit is calculated; the calculation method of the center distance includes: ； wherein d represents the center distance; representing the current coordinates of the mouse; representing the coordinates of the geometric center of the grid cell; According to the center distance, a membership value of each grid unit is calculated; the calculation method of the membership value includes: ； Wherein, d represents the center distance; σ represents a control coefficient of fuzziness; e represents the membership value; According to the membership value, the fuzziness of the grid unit is set, and the display effect of each grid unit is set according to the fuzziness.

3. A system for managing pharmaceutical documents, characterized by The memory has a pharmaceutical enterprise document management program stored therein, and the processor runs the pharmaceutical enterprise document management program to enable the pharmaceutical enterprise document management system to perform the pharmaceutical enterprise document management method of claim 1.

4. A computer-readable storage medium, characterized in that, The computer readable storage medium has a pharmaceutical enterprise document management program stored therein, and the pharmaceutical enterprise document management program is executed by the processor to implement the pharmaceutical enterprise document management method of claim 1.

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