Vaccine drug production process quality risk monitoring system and method

Abstract

The invention discloses a vaccine drug production process quality risk monitoring system and method. The system comprises a vaccine drug production process information acquisition module, a vaccine drug production process quality risk supervision module and a resident staff daily work management module. And the vaccine drug production process information acquisition module is used for realizing acquisition of production process information of vaccine drug production enterprises. The vaccine drug production process quality analysis module carries out statistics, analysis, identification and early warning on risks in the whole vaccine drug production process and carries out intelligent assessment on comprehensive risk indexes. The resident daily work management module realizes daily offline supervision work information acquisition of supervisors. The method is based on quality risk monitoring of the vaccine drug production process, can effectively meet the supervision work requirements of drug supervision departments on the vaccine production process, and guarantees the quality safety of vaccine products.

Description

Technical Field

[0001] This invention relates to the field of vaccine and pharmaceutical product manufacturing supervision technology, specifically to a quality risk monitoring system and method for the vaccine and pharmaceutical production process. Background Technology

[0002] Currently, vaccines are high-risk drugs that have attracted widespread attention, and the prevention and control of major risks in their production process has always been a key aspect of vaccine safety. Current risk warning methods for vaccine and drug production primarily rely on manual processes, including periodic on-site inspections by regulatory authorities of companies' historical quality management practices, production operation logs, and short-term workshop visits. This approach has several drawbacks: First, it heavily depends on the professional background and experience of regulatory personnel, making it highly subjective. Second, the periodic nature of these inspections leads to a post-event approach to risk monitoring, focusing primarily on the accuracy and effectiveness of risk assessments and mitigation measures, lacking proactive intervention and resulting in weak risk prevention capabilities. Third, there is a lack of comprehensive risk assessment for the entire enterprise. Past market supervision has focused on monitoring business operations, primarily through credit ratings. However, for high-risk products like drugs, especially vaccines, comprehensive risk assessments related to drug safety are largely limited to historical data analysis. Fourth, risk assessment efficiency is low. Past risk assessment models require preprocessing business data into structured data before quantitative evaluation, and the algorithms often rely on threshold and conditional judgments.

[0003] Furthermore, the current method for automatically collecting drug production process data in the pharmaceutical regulatory industry through information system integration involves placing a hardware server within the enterprise's intranet. This method has several problems: First, the data accessibility is low. This method mainly backs up enterprise data, and if data needs to be viewed, regulatory personnel must go to the site and log in with enterprise personnel using a key, resulting in poor timeliness, and data mining and analysis still mainly rely on manual analysis. Second, the data value density is low. The data collected by the traditional method mainly covers the operation data of auxiliary equipment and workshop environment data in pharmaceutical manufacturing enterprises. This type of data is mostly signal data from IoT sensing devices, which is large in volume, but has a low correlation with drug production quality risks, and its value for risk early warning is not high. Third, the implementation cost is high and the workload is large. The implementation cost is mainly reflected in the hardware server purchase cost and subsequent on-site operation and maintenance costs. The large workload is mainly due to the lack of universal data collection standards applicable to different drug production process characteristics. Each enterprise needs to invest a lot of manpower and time in the initial data collection process.

[0004] Therefore, digital management of the entire vaccine production process is an urgent issue that needs to be addressed in vaccine regulation. Summary of the Invention

[0005] Purpose of the invention: The technical problem to be solved by the present invention is to provide a quality risk monitoring system and method for the vaccine and drug production process, which addresses the shortcomings of the existing technology.

[0006] To address the aforementioned technical issues, firstly, a vaccine and drug production process quality risk monitoring system is disclosed. This system includes a vaccine and drug production process information collection module, a vaccine and drug production process quality risk supervision module, and a resident staff daily work management module. The vaccine and drug production process information collection module enables automatic data collection of vaccine and drug production data, providing users with data on vaccine production process parameters, product batch numbers, process output flow, material balance, raw materials and supplies, inspection and testing results, personnel changes, equipment changes, process changes, system permission changes, and key raw material supplier changes. It also provides manual data entry capabilities for information including deviation reports, OOS (Out of Specification) reports, change reports, batch release records, raw material purchases, and product sales. The vaccine and drug production process quality risk supervision module enables users to view basic information about vaccine and drug manufacturers and automatically identify, issue tiered warnings for, and implement closed-loop management of abnormal data during the production process. The resident staff daily work management module provides resident staff with online services for daily inspection record entry, online batch release sampling information entry, and online review of enterprise handling information.

[0007] Furthermore, the vaccine and drug production process information collection module includes a vaccine and drug production data access submodule and an enterprise manual data entry submodule.

[0008] The vaccine and drug production data access submodule includes access to process parameter data, product batch number data, process output and logistics data, material balance and yield data, raw material and material usage data, inspection and testing results data, key personnel change data, key equipment change data, process change data, system permission change data, and key raw material supplier change data.

[0009] The enterprise manual reporting submodule includes reporting of qualified materials entering the warehouse, reporting of non-production requisition / destruction, reporting of existing inventory, reporting of working seeds, working cells, reporting of non-conforming destruction, reporting of batch release information, reporting of products entering the warehouse after release, reporting of products leaving the warehouse after release, reporting of other changes, reporting of deviations, reporting of OOS, reporting of action limit adjustment, reporting of product retrieval, handling of early warning information, and access to production data logs.

[0010] Furthermore, the vaccine and drug production process quality risk supervision module provides sub-modules for overall status of enterprises under regional supervision, enterprise files, production process management, inventory management, comprehensive analysis, change management, deviation and trend analysis, early warning management, and comprehensive enterprise risk assessment.

[0011] The overall situation of regionally regulated enterprises submodule includes early warning information statistics, enterprise basic information statistics, material and product statistics, regulatory information correlation analysis, regulatory information statistical query, regulated enterprise map distribution, deviation management and change management statistics, quality trend analysis, and batch release information statistics.

[0012] The statistics on materials and products include statistics on key materials in the region, ranking of vaccine and drug production output, ranking of enterprise output, ranking of existing vaccine and drug inventory, ranking of enterprise inventory, ranking of vaccine and drug sales, ranking of enterprise sales, and statistical analysis of vaccine and drug inventory inflow and outflow.

[0013] Regulatory information statistics query includes regional product statistical analysis and regional early warning statistical analysis.

[0014] The enterprise file submodule includes basic enterprise information, vaccine and drug registration information, batch release sampling information, supervision and inspection, risk control measures, administrative penalties, product retrieval, and credit management.

[0015] Supervision and inspection information includes inspection lists, defect statistics, and defect analysis;

[0016] Risk control measures include risk warnings, interviews, admonitions, rectification within a specified period, and suspension of production and sales.

[0017] The production process management submodule includes material usage, production process parameters, quality inspection, material balance and yield, batch release information, and batch details.

[0018] Material usage includes the use of raw materials and semi-finished materials;

[0019] Production process parameters include raw material process parameters, semi-finished product process parameters, and finished product process parameters;

[0020] Quality inspection includes batch inspection of master cells and master seeds, batch inspection of working seeds and working seed batches, inspection of raw solutions, inspection of semi-finished products, and inspection of finished products;

[0021] The inventory management submodule includes key material inventory, product inventory, seed work inventory, and cell work inventory.

[0022] Key material inventory includes statistics on purchased materials, material inventory, material requisition, production usage, and details of material inbound and outbound processes;

[0023] Product inventory includes production statistics, inventory statistics, sales statistics, and product inbound and outbound details;

[0024] The working seed inventory includes statistics on working seed production, usage, remaining quantity, and details of working seed production and usage.

[0025] The Cells at Work inventory includes statistics on the production of working seeds, usage, remaining quantity, and details of cell at work production and usage.

[0026] The comprehensive analysis submodule includes material and product analysis, correlation analysis, and statistical analysis.

[0027] Correlation analysis includes batch number comparison and batch number tracing.

[0028] The Deviation and Trend Analysis submodule includes Deviation Management, OOS Management, and Trend Analysis.

[0029] Deviation management includes deviation investigation reports, deviation classification, deviation handling conclusions, relevant log information, and deviation closure review;

[0030] OOS management includes OOS investigation reports, OOS handling conclusions, OOS closure review, and related log information;

[0031] Quality trend analysis includes single-value control charts, regression analysis charts, and normal distribution charts.

[0032] Change management includes personnel changes, equipment changes, system permission changes, raw material supplier changes, key production and inspection consumable supplier changes, and other changes.

[0033] Other changes include change initiation information, change level information, change closure, related log information, and change closure approval.

[0034] The early warning management submodule includes red alerts, orange alerts, and information of concern.

[0035] A red alert includes warning information, company feedback, and response information;

[0036] An orange alert includes warning information, enterprise feedback, and response information.

[0037] The intelligent assessment submodule for enterprise risk index includes a risk index model library and intelligent risk index comparison.

[0038] The risk index model library includes risk indicator system management, indicator system weight revision, and risk indicator vectorization. Risk indicator system management establishes a multi-level indicator system based on expert advice, encompassing five dimensions: inherent drug risk, drug production process quality control risk, enterprise management risk, enterprise misconduct risk, and post-marketing risk. The secondary indicators for inherent drug risk include ingredients, category, target population, route of administration, and adverse reaction monitoring. The secondary indicators for drug production process quality control risk include production process, production process control, material balance management, quality inspection, and production process changes. The secondary indicators for enterprise management risk include product quality trend management, deviation handling management, OOS (Out of Service) handling management, batch release results, changes in key enterprise personnel, changes in key raw material suppliers, and changes in enterprise misconduct risk. The secondary indicators for enterprise misconduct risk include inspection defect risk, administrative penalty risk, product sampling failure risk, and exploratory research failure risk. The secondary indicators for post-marketing risk include enterprise product complaint risk, enterprise whistleblower risk, and enterprise product recall risk. In addition, the risk indicator system management also allows for the addition and deletion of secondary and tertiary indicators, so as to update and revise the indicator system through regular expert evaluation.

[0039] The revision of the indicator system weights, based on the traditional combined weighting method, combines four weighting methods—"priority chart," "entropy method," "principal component analysis," and "CRITIC weighting method"—through multiple combined weighting approaches. This approach takes into account the importance of indicators, the differences in information content among different indicators, the volatility of individual indicators, the condensability of evaluation data, and the intrinsic relationships between indicators. It enables the use of different weighting methods to assign values ​​to second- and third-level indicators under different dimensions, or to assign values ​​to evaluation indicators using a comprehensive weighting method, thereby improving the accuracy and flexibility of indicator weight assignment.

[0040] The risk indicator vectorization process uses the word embedding method to vectorize the evaluation indicators and indicator weights of the risk index model. The vectorization results are stored in a vector database to achieve efficient comparison of enterprise risks.

[0041] Intelligent risk index comparison includes enterprise information vectorization, comparison mode selection, and comparison result analysis and judgment. Enterprise information vectorization utilizes data from the enterprise early warning submodule, enterprise file submodule, production process management submodule, change management submodule, deviation and trend analysis submodule, and external data, employing a multidimensional approach and vectorization method to vectorize enterprise information using the risk index model. The comparison mode selection offers two options: periodic comparison and dynamic comparison. The periodic comparison mode uses vectorized enterprise data within a specified period for evaluation, while the dynamic comparison mode uses time series data for dynamic evaluation of enterprise vectorized data. The comparison result analysis and judgment presents the risk index comparison results visually, including the overall enterprise risk index level, risk item ranking, risk item related monitoring data, and a risk comparison radar chart.

[0042] The on-site staff's daily work management module provides a log information management sub-module, a sampling information management sub-module, and a data collection and record monitoring sub-module.

[0043] The log management submodule includes log editing, viewing, and deletion functions.

[0044] The sampling management submodule includes functions for downloading sampling record templates, importing sampling records, adding sampling records, deleting sampling records, and editing sampling records.

[0045] The data collection and monitoring submodule is used to record access logs for vaccine and drug production data and monitor abnormal logs.

[0046] Secondly, a method for monitoring quality risks in the vaccine and drug production process is disclosed, which involves connecting data from vaccine manufacturers to the aforementioned vaccine and drug production process quality risk monitoring system.

[0047] Enterprise data collection methods include requirements for personnel, data scope and categories, data formats, data access processes, data security, and handling of anomalies related to vaccine products and production processes.

[0048] Personnel requirements include the authorization, responsibilities, and job duties of the operators assigned to vaccine manufacturing companies.

[0049] The data scope includes production management, quality management, and change management data.

[0050] Production management includes data on process control, raw material requisition and delivery, intermediate product circulation, and yield rate during vaccine production.

[0051] The scope of quality management includes data such as the inspection and testing results of vaccine products and intermediate products.

[0052] The scope of change management includes data on changes to vaccine products and related suppliers, personnel, equipment, processes, and information systems.

[0053] Production management data categories include process parameter data, product batch number data, process output flow data, material balance and yield data, and raw material and material usage data.

[0054] The quality management data category includes inspection and testing results data.

[0055] The change management data categories include key personnel change data, key equipment change data, process change data, system permission change data, and key raw material supplier change data.

[0056] Data formats include transmission document formats, file content formats, data content formats, and data packaging formats.

[0057] Data documents must be in LF format.

[0058] The file content format requires that the character encoding be generated according to the UTF-8 encoding rule.

[0059] Data content format requirements: The input data should be generated in CSV format. Each type of data should form a separate CSV file. The first line of the CSV file should be the short name of the data item. Different data items in the CSV file should be separated by English commas. The content of the data items should not contain newline characters or English commas.

[0060] The data packaging format requires that the CSV file name be consistent with the name of each data category, and all CSV files generated daily should be packaged into a zip archive. The archive name should be generated by concatenating the production date of the day with the enterprise's self-built information system name, and "_" should be used as the concatenation character between the enterprise's self-built information system name and the date.

[0061] The data access process requires the following steps: data access preparation, resource preparation, data preparation, data verification, data transmission, data generation, and data access testing.

[0062] Data access preparation requires enterprises to establish a regulatory dataset for vaccine products and related production processes based on risk monitoring needs and vaccine product characteristics, determine the regulatory data items that need to be accessed, and adjust them in a timely manner according to actual needs.

[0063] Before data access, enterprises should install data transmission packages, VPN tools, and data encryption tools.

[0064] Before data access, enterprises should classify the data and clean and repair it.

[0065] Data verification requires that enterprises verify the integrity, accuracy, standardization, and security of data before it is integrated into their systems.

[0066] Data transmission requires the use of the HTTPS protocol.

[0067] The data generation requirements stipulate that vaccine manufacturers encrypt the data, generate and package the previous day's data file at a preset time each day, and check the response after data access every day to promptly identify any abnormal issues that cause access failure.

[0068] Data access testing requires vaccine companies to conduct tests using test data before data access, and only after the tests are passed can production data be accessed.

[0069] Data security includes: data security requirements for vaccine manufacturers and vaccine data storage requirements.

[0070] Vaccine manufacturers are required to ensure physical, operational, cyber, and system security during the data generation and transmission processes.

[0071] Vaccine data storage requirements stipulate that vaccine manufacturers must back up all accessed data electronic batch records and other necessary related documents using magnetic tape, microfilm, paper copies, or other methods. These backups must be retained for at least one year.

[0072] The procedures for handling abnormal situations include requirements for vaccine manufacturers to handle situations where they fail to generate a zip-format compressed file on the same day or where transmission fails.

[0073] If a vaccine manufacturer fails to generate a zip-format compressed file on time, it should troubleshoot the problem and then repackage the data according to the data packaging format requirements.

[0074] The vaccine and drug production process quality risk monitoring system should resume the transmission of zip format compressed files that failed to be transmitted.

[0075] Beneficial effects: The vaccine and drug production process quality risk monitoring system and method proposed in this invention can strengthen the online monitoring of risk points of the entire process of vaccine and drug production by drug production regulatory departments through the vaccine and drug production process information collection module, vaccine and drug production process quality risk supervision module, and on-site staff daily work management module, effectively enhancing the risk prevention and control capabilities of vaccine production quality and safety. Attached Figure Description

[0076] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, and the advantages of the present invention in the above and / or other aspects will become clearer.

[0077] Figure 1This is a diagram showing the overall architecture of the system and the enterprise data access method established in the vaccine and drug production process quality risk monitoring method of the present invention.

[0078] Figure 2 This is an architecture diagram of the vaccine and drug production process information collection module of the present invention.

[0079] Figure 3 This is an architecture diagram of the quality risk monitoring module for the vaccine and drug production process of the present invention.

[0080] Figure 4 This is an architecture diagram of the daily work management module for on-site staff in this invention.

[0081] Figure 5 This is an interaction diagram of the vaccine and drug production process quality risk monitoring system of the present invention.

[0082] Figure 6 This is a business process diagram of the vaccine and drug production process quality risk monitoring method of the present invention.

[0083] Figure 7 This is a business process diagram of the intelligent assessment submodule of enterprise risk index in the vaccine and drug production process quality risk monitoring system of the present invention. Detailed Implementation

[0084] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0085] Reference will now be made in detail to embodiments of the invention, examples of which are illustrated in the accompanying drawings. The suffixes “module,” “submodule,” and “function” are used herein for ease of description and are therefore interchangeable without any distinguishing meaning or function.

[0086] While all elements or units constituting embodiments of the invention are described as being incorporated into a single element or operated as a single element or unit, the invention is not necessarily limited to such embodiments. According to embodiments, all elements within the scope and purpose of the invention may be selectively incorporated into one or more elements and operated as one or more elements.

[0087] This application proposes a quality risk monitoring system and method for vaccine and drug production processes, which can effectively meet the regulatory needs of drug regulatory authorities for the vaccine production process.

[0088] The vaccine and drug production process quality risk monitoring method proposed in this application includes a vaccine and drug production process quality risk monitoring system and a data access method for vaccine manufacturers, comprising a vaccine and drug production process information collection module, a vaccine and drug production process quality risk supervision module, and a resident staff daily work management module. The vaccine and drug production process information collection module mainly realizes the access to vaccine and drug production process control data, product batch number data, process output data, material balance and yield data, raw material and material usage data, inspection and testing result data, and change management data directly related to vaccine and drug production for vaccine and drug manufacturers. It also provides vaccine and drug manufacturers with the ability to automatically collect data on vaccine production process parameters, product batch numbers, process output flow, material balance, raw materials and materials, inspection and testing results, personnel changes, equipment changes, process changes, system permission changes, and key raw material supplier changes, as well as deviation reports, OOS reports, change reports, and batch release records. The system includes manual reporting capabilities for information such as raw material purchases and product sales; a vaccine and drug production process quality risk monitoring module that allows users to view basic information about vaccine and drug manufacturers, query, statistically compare, and analyze data on raw material input, process control, intermediate product testing results, material balance, final product yield and output, and product quality trends for each batch of vaccines and drugs; and the ability to automatically identify, issue warnings at different levels, and implement closed-loop management for abnormal data during the production process. It also features the ability to establish a corporate risk index model based on multi-source risk signals collected by the system, and to achieve a comprehensive assessment and quantification of the risk index of pharmaceutical manufacturers by vectorizing risk indicators. Vaccine and drug production regulatory departments can use this module to monitor, analyze, and handle risk points throughout the entire production process of each batch of vaccines and drugs, and to comprehensively assess potential risks to drug quality. The on-site staff daily work management module provides on-site staff with online services for daily inspection record filling, batch release sampling information filling, and online review of corporate handling information. The data access methods for vaccine manufacturers include requirements for personnel, data scope and categories, data formats, data access processes, data security, and handling of abnormal situations related to vaccine products and production processes.

[0089] like Figure 1 As shown, the first embodiment of this application discloses a quality risk monitoring system for vaccine and drug production process, including a vaccine and drug production process information collection module, a vaccine and drug production process quality risk supervision module, and a resident staff daily work management module.

[0090] The vaccine and drug production process information collection module enables access to vaccine and drug production process control data, product batch number data, process output data, material balance and yield data, raw material and material usage data, inspection and testing result data, and change management data directly related to vaccine and drug production for vaccine and drug manufacturers. It also provides vaccine and drug manufacturers with the ability to manually fill in information such as deviation reports, OOS reports, change reports, batch release records, raw material purchases, and product sales.

[0091] The vaccine and drug production process quality risk monitoring module allows users to view basic information about vaccine and drug manufacturers, and to query, statistically analyze, compare, and compare data on raw material input, process control, intermediate product testing results, material balance, final product yield and output, and product quality trends for each batch of vaccines and drugs. It also features the ability to automatically identify, issue tiered warnings for, and implement closed-loop management of abnormal data during the production process. Vaccine and drug production regulatory departments can use this module to monitor, analyze, and handle risk points throughout the entire production process of each batch of vaccines and drugs.

[0092] The on-site staff daily work management module provides on-site staff with services such as online reporting of daily inspection records, online reporting of batch release sampling information, and online review of enterprise disposal information.

[0093] like Figure 2 The vaccine and drug production process information collection module shown includes functions such as a vaccine and drug production data access submodule and a manual data entry submodule for enterprises.

[0094] 1. The vaccine and drug production data access submodule includes process parameter data access, product batch number data access, process output logistics data access, material balance and yield data access, raw material and material usage data access, inspection and testing result data, key personnel change data, key equipment change data access, process change data access, system permission change data access, and key raw material supplier change data access.

[0095] 2. The enterprise manual reporting submodule includes reporting of qualified materials entering the warehouse, reporting of non-production requisition / destruction, reporting of existing inventory, reporting of working seeds, working cells, reporting of non-conforming destruction, reporting of batch release information, reporting of products entering the warehouse after release, reporting of products leaving the warehouse after release, reporting of other changes, reporting of deviations, reporting of OOS, reporting of action limit adjustment, reporting of product retrieval, handling of early warning information, and access to production data logs.

[0096] like Figure 3The vaccine and drug production process quality risk supervision module shown includes a regional supervision enterprise overall situation sub-module, enterprise file sub-module, production process management sub-module, inventory management sub-module, comprehensive analysis sub-module, change management sub-module, deviation and trend analysis sub-module, early warning management sub-module, and enterprise risk comprehensive assessment sub-module.

[0097] 1. The overall situation of enterprises under regional supervision includes early warning information statistics, basic enterprise information statistics, material and product statistics, regulatory information correlation analysis, regulatory information statistical query, map distribution of supervised enterprises, deviation management and change management statistics, quality trend analysis, and batch release information statistics.

[0098] The statistics on materials and products include statistics on key materials in the region, ranking of vaccine and drug production output, ranking of enterprise output, ranking of existing vaccine and drug inventory, ranking of enterprise inventory, ranking of vaccine and drug sales, ranking of enterprise sales, and statistical analysis of vaccine and drug inventory inflow and outflow.

[0099] Regulatory information statistics query includes regional product statistical analysis and regional early warning statistical analysis.

[0100] 2. The Enterprise File sub-module includes basic enterprise information, vaccine and drug registration information, batch release sampling information, supervision and inspection, risk control measures, administrative penalties, product retrieval, and credit management.

[0101] Supervision and inspection information includes inspection lists, defect statistics, and defect analysis;

[0102] Risk control measures include risk warnings, interviews, admonitions, rectification within a specified period, and suspension of production and sales.

[0103] 3. The production process management submodule includes material usage, production process parameters, quality inspection, material balance and yield, batch release information, and batch details.

[0104] Material usage includes the use of raw materials and semi-finished materials;

[0105] Production process parameters include raw material process parameters, semi-finished product process parameters, and finished product process parameters;

[0106] Quality inspection includes batch inspection of master cells and master seeds, batch inspection of working seeds and working seed batches, inspection of raw solutions, inspection of semi-finished products, and inspection of finished products;

[0107] 4. The inventory management submodule includes key material inventory, product inventory, working seed inventory, and working cell inventory.

[0108] Key material inventory includes material purchase statistics, material inventory statistics, material requisition statistics, production usage statistics, and material inbound and outbound details;

[0109] Product inventory includes production statistics, inventory statistics, sales statistics, and product inbound and outbound details;

[0110] The working seed inventory includes statistics on working seed production, usage, remaining quantity, and details of working seed production and usage.

[0111] The working cell inventory includes working cell production statistics, usage statistics, remaining quantity statistics, and working cell production and usage details.

[0112] 5. The comprehensive analysis submodule includes material and product analysis, correlation analysis, and statistical analysis.

[0113] Correlation analysis includes batch number comparison and batch number tracing.

[0114] 6. The Deviation and Trend Analysis submodule includes Deviation Management, OOS Management, and Trend Analysis.

[0115] Deviation management includes deviation investigation reports, deviation classification, deviation handling conclusions, relevant log information, and deviation closure review;

[0116] OOS management includes OOS investigation reports, OOS handling conclusions, OOS closure review, and related log information;

[0117] Quality trend analysis includes single-value control charts, regression analysis charts, and normal distribution charts.

[0118] 7. The Change Management submodule includes personnel changes, equipment changes, system permission changes, raw material supplier changes, key production and inspection consumable supplier changes, and other changes.

[0119] Other changes include change initiation information, change level information, change closure, related log information, and change closure approval.

[0120] 8. The early warning management submodule includes red warnings, orange warnings, and information of concern.

[0121] A red alert includes warning information, company feedback, and response information;

[0122] An orange alert includes warning information, enterprise feedback, and response information.

[0123] 9. Enterprise Risk Index Intelligent Assessment Submodule: This module is used to build a risk index model library and perform intelligent comparison of risk indices.

[0124] The construction of the risk index model library includes risk indicator system management, risk indicator vectorization, and indicator system weight revision. The risk indicator system management establishes a multi-level indicator system based on expert advice, encompassing five dimensions: inherent drug risk, drug production process quality control risk, enterprise management risk, enterprise misconduct risk, and post-marketing risk. The secondary indicators for inherent drug risk include ingredients, category, target population, route of administration, and adverse reaction monitoring. The secondary indicators for drug production process quality control risk include production process, production process control, material balance management, quality inspection, and production process changes. The secondary indicators for enterprise management risk include product quality trend management, deviation handling management, OOS handling management, batch release results, changes in key enterprise personnel, changes in key raw material suppliers, and changes in enterprise misconduct risk. The secondary indicators for enterprise misconduct risk include inspection defect risk, administrative penalty risk, product sampling failure risk, and exploratory research failure risk. The secondary indicators for post-marketing risk include enterprise product complaint risk, enterprise whistleblower risk, and enterprise product recall risk. Furthermore, the risk indicator system management also allows for the addition and deletion of secondary and tertiary indicators, enabling regular updates and revisions of the indicator system through expert evaluation.

[0125] The risk index vectorization adopts word embedding method, which vectorizes the evaluation index of the risk index model into a dimensionless vector, and the vectorization result is stored in a vector database.

[0126] The revised weighting of the indicator system, based on the traditional combined weighting method, combines four weighting methods—ranking graph, entropy method, principal component analysis, and CRITIC weighting method—through multiple combined weighting approaches. This approach takes into account the importance of indicators, the differences in information content among different indicators, the volatility of individual indicators, the condensability of evaluation data, and the intrinsic relationship between indicators. It achieves the assignment of values ​​to second- and third-level indicators under different dimensions using different weighting methods and normalizes the overall weighting distribution of evaluation indicators.

[0127] The intelligent risk index comparison includes enterprise information vectorization, comparison mode selection, and comparison result analysis and judgment. Enterprise information vectorization involves using data from the enterprise early warning submodule, enterprise file submodule, production process management submodule, change management submodule, deviation and trend analysis submodule, and other external data, along with a risk index model, to vectorize enterprise information using a multidimensional and vectorized approach. The comparison mode selection includes two modes: periodic comparison and dynamic comparison. The periodic comparison mode uses enterprise vectorized data within a specified period for evaluation, while the dynamic comparison mode uses time series data for dynamic evaluation of enterprise vectorized data. The comparison result analysis and judgment presents the risk index comparison results in a visual manner, including the enterprise's overall risk index level, risk item ranking, risk item related monitoring data, and a risk comparison radar chart.

[0128] like Figure 4 The on-site staff daily work management module shown provides a log information management sub-module, a sampling information management sub-module, and a data collection and record monitoring sub-module.

[0129] The log management submodule includes log editing, viewing, and deletion functions.

[0130] The sampling management submodule includes functions for downloading sampling record templates, importing sampling records, adding sampling records, deleting sampling records, and editing sampling records.

[0131] The data collection and monitoring submodule is used to record access logs for vaccine and drug production data and monitor abnormal logs.

[0132] The second embodiment of this application discloses a method for monitoring quality risks in the vaccine and drug production process, which involves connecting data from vaccine manufacturers to a vaccine and drug production process quality risk monitoring system.

[0133] Enterprise data collection methods include requirements for personnel, data scope and categories, data formats, data access processes, data security, and handling of anomalies related to vaccine products and production processes.

[0134] Personnel requirements include the authorization, responsibilities, and job duties of the operators assigned to vaccine manufacturing companies.

[0135] The data scope includes production management, quality management, and change management data.

[0136] Production management includes data on process control, raw material requisition and delivery, intermediate product circulation, and yield rate during vaccine production.

[0137] The scope of quality management includes data such as the inspection and testing results of vaccine products and intermediate products.

[0138] The scope of change management includes data on changes to vaccine products and related suppliers, personnel, equipment, processes, and information systems.

[0139] Production management data categories include process parameter data, product batch number data, process output flow data, material balance and yield data, and raw material and material usage data.

[0140] The quality management data category includes inspection and testing results data.

[0141] The change management data categories include key personnel change data, key equipment change data, process change data, system permission change data, and key raw material supplier change data.

[0142] Data formats include transmission document formats, file content formats, data content formats, and data packaging formats.

[0143] Data documents must be in LF format.

[0144] The file content format requires that the character encoding be generated according to the UTF-8 encoding rule.

[0145] Data content format requirements: The input data should be generated in CSV format. Each type of data should form a separate CSV file. The first line of the CSV file should be the short name of the data item. Different data items in the CSV file should be separated by English commas. The content of the data items should not contain newline characters or English commas.

[0146] The data packaging format requires that the CSV file name be consistent with the name of each data category, and all CSV files generated daily should be packaged into a zip archive. The archive name should be generated by concatenating the production date of the day with the enterprise's self-built information system name, and "_" should be used as the concatenation character between the enterprise's self-built information system name and the date.

[0147] The data access process requires the following steps: data access preparation, resource preparation, data preparation, data verification, data transmission, data generation, and data access testing.

[0148] Data access preparation requires enterprises to establish a regulatory dataset for vaccine products and related production processes based on risk monitoring needs and vaccine product characteristics, determine the regulatory data items that need to be accessed, and adjust them in a timely manner according to actual needs.

[0149] Before data access, enterprises should install data transmission packages, VPN tools, and data encryption tools.

[0150] Before data access, enterprises should classify the data and clean and repair it.

[0151] Data verification requires that enterprises verify the integrity, accuracy, standardization, and security of data before it is integrated into their systems.

[0152] Data transmission requires the use of the HTTPS protocol.

[0153] The data generation requirement is that vaccine manufacturers encrypt the data, generate and package the previous day's data file at a preset time each day (e.g., 2:00), and check the response after data access every day to promptly identify any abnormal issues that cause access failure.

[0154] Data access testing requires vaccine companies to conduct tests using test data before data access, and only after the tests are passed can production data be accessed.

[0155] Data security includes: data security requirements for vaccine manufacturers and vaccine data storage requirements.

[0156] Vaccine manufacturers are required to ensure physical, operational, cyber, and system security during the data generation and transmission processes.

[0157] Vaccine data storage requirements stipulate that vaccine manufacturers must back up all accessed data electronic batch records and other necessary related documents using magnetic tape, microfilm, paper copies, or other methods. These backups must be retained for at least one year.

[0158] The procedures for handling abnormal situations include requirements for vaccine manufacturers to handle situations where they fail to generate a zip-format compressed file on the same day or where transmission fails.

[0159] If a vaccine manufacturer fails to generate a zip-format compressed file on time, it should troubleshoot the problem and then repackage the data according to the data packaging format requirements.

[0160] The vaccine and drug production process quality risk monitoring system should resume the transmission of zip format compressed files that failed to be transmitted.

[0161] like Figure 5 The interactive relationships of the vaccine and drug manufacturing process quality risk monitoring system are shown below:

[0162] 1. The vaccine and drug production process information collection module collects key information generated during the production process of vaccine manufacturers into the vaccine and drug production process quality risk monitoring system through system collection and manual entry.

[0163] 2. The vaccine and drug production process quality risk monitoring system will use the collected vaccine production process data to perform production process information query, statistics, analysis, and early warning and handling in the vaccine and drug production process quality risk supervision module.

[0164] 3. Vaccine on-site personnel conduct online and offline supervision of the vaccine production process through the vaccine and drug production process quality risk supervision module and the vaccine on-site personnel daily work management module.

[0165] 4. When the vaccine and drug production process quality risk monitoring system identifies an early warning, the early warning information is simultaneously pushed to the vaccine and drug production process quality risk supervision module and the vaccine and drug production process information collection module. Enterprise users can use the vaccine and drug production process information collection module to provide feedback on the handling method of the early warning information to the supervision users. Supervision users can use the vaccine and drug production process quality risk supervision module to view the enterprise's handling information and conduct review.

[0166] like Figure 6 The diagram shows the business process of a quality risk monitoring system for vaccine and drug production.

[0167] During system use, business processes are divided into several stages: data collection, risk identification, early warning and handling, and handling review. Enterprise users and vaccine regulatory personnel perform different operations in the business process.

[0168] like Figure 7 The diagram illustrates the business process of intelligent enterprise risk index assessment within a vaccine and drug production process quality risk monitoring system. The intelligent assessment first requires establishing an indicator system based on business experience, considering factors such as product, enterprise, personnel, management, and external influences, while incorporating traditional expertise. Then, using text vectorization technology, each indicator in the system is converted into vectorized data for comparison with actual enterprise information, identifying indicator items triggered during the enterprise's actual production and operation. Finally, by combining the weights assigned to each indicator item, a weighted calculation is performed to obtain the final risk index level for the enterprise, achieving a comprehensive assessment of enterprise risk.

[0169] In its specific implementation, this application provides a computer storage medium and a corresponding data processing unit. The computer storage medium is capable of storing a computer program, which, when executed by the data processing unit, can run the invention's content regarding a method for monitoring quality risks in the vaccine and drug production process, as well as some or all of the steps in various embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0170] Those skilled in the art will clearly understand that the technical solutions in the embodiments of the present invention can be implemented using computer programs and their corresponding general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of computer programs, i.e., software products. These computer program software products can be stored in a storage medium and include several instructions to cause a device containing a data processing unit (which may be a personal computer, server, microcontroller, MUU, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.

[0171] This invention provides a quality risk monitoring system and method for vaccine and drug production processes. Many methods and approaches exist for implementing this technical solution; the above description is merely a preferred embodiment. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention. All components not explicitly stated in this embodiment can be implemented using existing technologies.

Claims

1. A quality risk monitoring system for vaccine and drug manufacturing process, characterized in that, This includes modules for collecting information on the vaccine and drug production process, monitoring quality risks in the vaccine and drug production process, and managing the daily work of on-site personnel. The vaccine and drug production process information collection module is used to access vaccine and drug production data. It provides vaccine and drug manufacturers with the ability to automatically collect data on vaccine production process parameters, product batch numbers, process output flow, material balance, raw materials and materials, inspection and testing results, personnel changes, equipment changes, process changes, system permission changes, and key raw material supplier changes. It also provides the ability to manually fill in information including deviation reports, OOS reports, change reports, batch release records, raw material purchases, and product sales. The vaccine and drug production process quality risk monitoring module is used to view the basic information of vaccine and drug manufacturers, monitor the entire production process of each batch of vaccines and drugs, and automatically identify, classify and issue early warnings for, and handle abnormal data in the production process in a closed loop. The on-site staff daily work management module is used to provide on-site vaccine staff with online services for daily inspection record filling, batch release sampling information filling, and enterprise disposal information review.

2. The vaccine and drug production process quality risk monitoring system according to claim 1, characterized in that, The vaccine and drug production process information collection module includes a vaccine and drug production data access submodule and an enterprise manual data entry submodule. The vaccine and drug production data access submodule is used for accessing process parameter data, product batch number data, process output logistics data, material balance and yield data, raw material and material usage data, inspection and testing result data, key personnel change data, key equipment change data, process change data, system permission change data, and key raw material supplier change data. The enterprise manual reporting submodule is used for reporting qualified material warehousing, non-production requisition / destruction, existing inventory, working seeds, working cells, non-conforming destruction, batch release information, product warehousing after release, product outbound after release, other changes, deviations, OOS, action limit adjustments, product retrieval, early warning information processing, and production data access to logs.

3. The vaccine and drug production process quality risk monitoring system according to claim 2, characterized in that, The vaccine and drug production process quality risk supervision module includes a regional supervision enterprise overall situation submodule, an enterprise file submodule, a production process management submodule, an inventory management submodule, a comprehensive analysis submodule, a change management submodule, a deviation and trend analysis submodule, an early warning management submodule, and an enterprise risk comprehensive assessment submodule. The regional regulatory enterprise overall situation submodule is used for early warning information statistics, enterprise basic information statistics, material and product statistics, regulatory information correlation analysis, regulatory information statistical query, regulatory enterprise map distribution, deviation management and change management statistics, quality trend analysis, and batch release information statistics. The enterprise file submodule is used for basic enterprise information, vaccine and drug registration information, batch release sampling information, supervision and inspection, risk control measures, administrative penalties, product retrieval and credit management; The production process management submodule is used for managing material usage, production process parameters, quality inspection, material balance and yield, batch release information, and batch details. The inventory management submodule is used for the management of key material inventory, product inventory, working seed inventory, and working cell inventory. The comprehensive analysis submodule is used for material and product analysis, correlation analysis, and statistical analysis; The deviation and trend analysis submodule is used for deviation management, OOS management, and quality trend analysis. The change management submodule is used for personnel changes, equipment changes, system permission changes, raw material supplier changes, key production and inspection consumable supplier changes, and other change management. The early warning management submodule includes red and orange early warnings, both of which include early warning information, enterprise feedback, and handling information. The intelligent assessment submodule for enterprise risk index is used to build a risk index model library and perform intelligent comparison of risk indices.

4. The vaccine and drug production process quality risk monitoring system according to claim 3, characterized in that, The construction of the risk index model library includes risk indicator system management, risk indicator vectorization, and indicator system weight revision. The risk indicator system management establishes a multi-level indicator system based on expert advice, encompassing five dimensions: inherent drug risk, drug production process quality control risk, enterprise management risk, enterprise misconduct risk, and post-marketing risk. The secondary indicators for inherent drug risk include ingredients, category, target population, route of administration, and adverse reaction monitoring. The secondary indicators for drug production process quality control risk include production process, production process control, material balance management, quality inspection, and production process changes. The secondary indicators for enterprise management risk include product quality trend management, deviation handling management, OOS handling management, batch release results, changes in enterprise leadership, changes in key production personnel, and changes in key raw material suppliers. The secondary indicators for enterprise misconduct risk include inspection defect risk, administrative penalty risk, product sampling failure risk, and exploratory research failure risk. The secondary indicators for post-marketing risk include enterprise product complaint risk, enterprise whistleblower risk, and enterprise product recall risk. Furthermore, the risk indicator system management also allows for the addition and deletion of secondary and tertiary indicators, enabling regular updates and revisions of the indicator system through expert evaluation. The risk index vectorization adopts word embedding method, which vectorizes the evaluation index of the risk index model into a dimensionless vector, and the vectorization result is stored in a vector database. The revised weighting of the indicator system, based on the traditional combined weighting method, combines four weighting methods—ranking graph, entropy method, principal component analysis, and CRITIC weighting method—through multiple combined weighting approaches. This approach takes into account the importance of indicators, the differences in information content among different indicators, the volatility of individual indicators, the condensability of evaluation data, and the intrinsic relationship between indicators. It achieves the assignment of values ​​to second- and third-level indicators under different dimensions using different weighting methods and normalizes the overall weighting distribution of evaluation indicators.

5. The vaccine and drug production process quality risk monitoring system according to claim 4, characterized in that, The intelligent risk index comparison includes enterprise information vectorization, comparison mode selection, and comparison result analysis and judgment. Enterprise information vectorization utilizes data from the enterprise early warning submodule, enterprise file submodule, production process management submodule, change management submodule, deviation and trend analysis submodule, and external data, employing a multidimensional and vectorized approach similar to the risk index model to vectorize enterprise information. The comparison mode selection includes two modes: periodic comparison and dynamic comparison. The periodic comparison mode uses enterprise vectorized data within a specified period for evaluation, while the dynamic comparison mode uses time series data for dynamic evaluation of enterprise vectorized data. The comparison result analysis and judgment presents the risk index comparison results in a visual manner, including the enterprise's overall risk index level, risk item ranking, risk item related monitoring data, and a risk comparison radar chart.

6. The vaccine and drug production process quality risk monitoring system according to claim 5, characterized in that, The on-site staff daily work management module includes a log information management submodule, a sampling information management submodule, and a data collection and recording monitoring submodule. The log information management submodule is used for editing, viewing, and deleting logs. The sampling information management submodule is used for downloading sampling record templates, importing sampling records, adding sampling records, deleting sampling records, and editing sampling records. The data collection and monitoring submodule is used to record the access logs of vaccine and drug production data and monitor abnormal logs.

7. A method for monitoring quality risks in the vaccine manufacturing process, characterized in that, The vaccine manufacturer's data is connected to the vaccine drug production process quality risk monitoring system as described in any one of claims 1-6; the connection of the vaccine manufacturer's data includes personnel requirements for accessing vaccine product and production process related data, data scope and data category, data format, data access process, data security and abnormal situation handling.

8. The method for monitoring quality risks in the vaccine manufacturing process according to claim 7, characterized in that, The personnel requirements include the authorization, responsibilities, and job duties of the operators employed by vaccine manufacturers; The data scope includes production management data, quality management data, and change management data. Production management data includes data on process control, raw material requisition and distribution, intermediate product flow, and yield during vaccine production. Quality management data includes testing and inspection results for vaccine products and intermediate products. Change management data includes data on changes in suppliers, personnel, equipment, processes, and information systems related to vaccine products and the vaccine production process. Production management data categories include process parameter data, product batch number data, process output flow data, material balance and yield data, and raw material and material usage data. Quality management data categories include testing and inspection results data. Change management data categories include key personnel change data, key equipment change data, process change data, system permission change data, and key raw material supplier change data. The data formats include document formats, file content formats, data content formats, and data packaging formats.

9. The method for monitoring quality risks in the vaccine manufacturing process according to claim 8, characterized in that, The data access process includes data access preparation, resource preparation, data preparation, data verification, data transmission, data generation, and data access testing. The data access preparation requires vaccine manufacturers to establish a regulatory dataset of vaccine products and related production processes based on risk warning needs and product characteristics, determine the regulatory data items that need to be accessed, and determine the data scope and data category based on the data items, thus completing the access preparation for vaccines in production and related production process data. The resource preparation mentioned above requires enterprises to install data transmission packages, VPN tools, and data encryption tools before data access; Before data access, enterprises should classify the data and clean and repair it. The data verification requires that the integrity, accuracy, standardization, and security of the data be verified before it is accessed; the data transmission adopts the HTTPS protocol and accesses the data through an interface. Vaccine manufacturers generate the previous day's data files before a preset time each day. The data generation uses a data encryption tool to encrypt and package the prepared data into a data file package. After the data package is generated, the success of the data package generation is verified. Review the responses after data access daily to promptly identify any abnormal issues that lead to access failures; The data access test is conducted by the vaccine and drug production process quality risk monitoring system as described in any one of claims 1-6. After the test is passed, the data is officially accessed.

10. The method for monitoring quality risks in the vaccine and drug manufacturing process according to claim 9, characterized in that, The data security includes the security of the data generation and transmission process and the data storage requirements. The data generation and transmission process security requirements ensure data security in multiple aspects, including physical security, operational security, network security, and system security, during the data generation and transmission process. The data is stored by backing up all accessed data electronically and related documents using methods including magnetic tape, microfilm, and paper copies, with the backup period lasting until one year after the expiration date of the vaccine product. The exception handling includes failure to generate a zip archive on time and failure to successfully transmit a zip archive. If a vaccine manufacturer fails to generate a zip archive on time, it should investigate the problem and repackage the data. The vaccine and drug production process quality risk monitoring system should be able to resume the transmission of zip-format compressed files that failed to be transmitted.

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