Method for monitoring a pharmaceutical production environment based on multi-source data

Abstract

The application provides a drug production environment monitoring method based on multi-source data, relates to the technical field of pharmaceutical environment monitoring, and comprises the following steps: analyzing the environment conditions of each preparation instrument, obtaining common monitoring sources, configuring a multi-source monitoring module, and connecting the platform; monitoring data through the multi-source monitoring module, inputting the environment anomaly monitoring model, generating environment anomaly indexes, generating abnormal reminding information, and feeding back to the integrated drug preparation platform. The application can solve the problems in the prior art that the drug preparation environment condition monitoring is not comprehensive, the multi-source data integration efficiency is poor, the environment condition changes in the drug preparation process cannot be monitored in real time and comprehensively, the environment conditions of multiple preparation instruments in the integrated drug preparation platform are comprehensively and real-timely monitored, the environment anomalies are found in time, and the quality, efficiency and intelligent management level of drug preparation are improved.

Description

Technical Field

[0001] The present application relates to the technical field of pharmaceutical environment monitoring, and in particular to a pharmaceutical production environment monitoring method based on multi-source data. Background Art

[0002] The development of the Internet of Things (IoT) and sensor technology enables the collection of vast amounts of data from diverse devices and sensors. Multi-source data fusion technology can integrate this data, providing a more comprehensive perspective on environmental monitoring. The increasing complexity of production processes and increasing demands for product quality necessitate more intelligent monitoring and analysis methods to identify environmental changes, predict potential issues, and respond quickly.

[0003] At present, the existing technology is unable to monitor the changes in environmental conditions during drug preparation in real time and comprehensively due to the incomplete monitoring of drug preparation environmental conditions and the poor efficiency of multi-source data integration, which further affects the quality and efficiency of drug preparation. Summary of the Invention

[0004] The purpose of this application is to provide a drug production environment monitoring method based on multi-source data to solve the problem that the existing technology is unable to monitor the changes in environmental conditions during the drug preparation process in real time and comprehensively due to incomplete monitoring of drug preparation environmental conditions and poor efficiency in integrating multi-source data.

[0005] In view of the above problems, the present application provides a drug production environment monitoring method based on multi-source data.

[0006] The present application provides a drug production environment monitoring method based on multi-source data, wherein the drug production environment monitoring method based on multi-source data includes: obtaining the drug preparation structure of the integrated drug preparation platform, the drug preparation structure including preparation instruments, connecting pipelines and a compartment, the preparation instruments and the connecting pipelines forming a production line in the compartment; analyzing the environmental conditions of each preparation instrument when preparing drugs to obtain multiple common monitoring sources; configuring a multi-source monitoring module with the multiple common monitoring sources, and the multi-source monitoring module is connected to the integrated drug preparation platform; performing data monitoring according to the multi-source monitoring module and outputting multiple common monitoring data; inputting the multiple common monitoring data into an environmental anomaly monitoring model, and obtaining environmental anomaly indicators according to the environmental anomaly monitoring model; generating environmental anomaly reminder information according to the environmental anomaly indicators, and feeding the environmental anomaly reminder information back to the integrated drug preparation platform.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] By obtaining the drug preparation structure of the integrated drug preparation platform, the drug preparation structure includes preparation instruments, connecting pipelines and a compartment, and the preparation instruments and the connecting pipelines constitute a production line in the compartment; analyzing the environmental conditions of each preparation instrument during drug preparation to obtain multiple common monitoring sources; configuring a multi-source monitoring module with the multiple common monitoring sources, and connecting the multi-source monitoring module to the integrated drug preparation platform; performing data monitoring according to the multi-source monitoring module to output multiple common monitoring data; inputting the multiple common monitoring data into an environmental anomaly monitoring model, and obtaining environmental anomaly indicators according to the environmental anomaly monitoring model; generating environmental anomaly reminder information based on the environmental anomaly indicators, and feeding the environmental anomaly reminder information back to the integrated drug preparation platform, the present invention effectively solves the problem of the existing technology that the environmental conditions of drug preparation are not fully monitored and the efficiency of integrating multi-source data is poor, resulting in the inability to monitor the changes in environmental conditions in the drug preparation process in real time and comprehensively. The present invention realizes comprehensive and real-time monitoring of the environmental conditions of multiple preparation instruments in the integrated drug preparation platform, timely discovers environmental anomalies, and improves the quality, efficiency and intelligent management level of drug preparation.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, which can be implemented in accordance with the contents of the description, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically listed below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without any creative work.

[0011] Figure 1 This is a flow chart of the drug production environment monitoring method based on multi-source data in this application;

[0012] Figure 2 This is a flow chart of configuring a multi-source monitoring module in the drug production environment monitoring method based on multi-source data in this application. DETAILED DESCRIPTION

[0013] This application provides a drug production environment monitoring method based on multi-source data, which solves the problems of the existing technology that the environmental conditions of drug preparation are not fully monitored and the integration efficiency of multi-source data is poor, resulting in the inability to monitor the changes in environmental conditions during the drug preparation process in real time and comprehensively. It realizes comprehensive and real-time monitoring of the environmental conditions of multiple preparation instruments in an integrated drug preparation platform, timely discovers environmental anomalies, and improves the quality, efficiency and intelligent management level of drug preparation.

[0014] Below, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this application, rather than all of the embodiments of this application. It should be understood that this application is not limited to the example embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should also be noted that, for the sake of ease of description, only the parts related to this application, rather than all of them, are shown in the accompanying drawings.

[0015] Please see the attached Figure 1 The present application provides a method for monitoring a drug production environment based on multi-source data, wherein the method comprises the following steps:

[0016] S1: Obtaining a drug preparation structure of the integrated drug preparation platform, wherein the drug preparation structure includes a preparation instrument, connecting pipelines, and a compartment, wherein the preparation instrument and the connecting pipeline constitute a production line within the compartment.

[0017] Specifically, preparation equipment is used to perform various tasks in the drug preparation process, such as mixing, reaction, filtration, drying, and packaging. These include, but are not limited to, reactors, mixers, centrifuges, tablet presses, and fillers. Connecting piping connects the various preparation equipment, allowing material to flow between different stages of the preparation process. The compartment houses all preparation equipment and connecting piping.

[0018] S2: Analyze the environmental conditions of each preparation instrument when preparing drugs and obtain multiple common monitoring sources.

[0019] Specifically, determine the key environmental parameters that need to be monitored for each preparation instrument during the drug preparation process, such as temperature, humidity, pressure, wind speed, particulate matter content, microbial load, etc. Analyze the process flow of drug preparation, identify the role and importance of each preparation instrument in the process, and determine which changes in environmental conditions may affect the performance of the instrument and the quality of the drug. Conduct a risk assessment of the environmental conditions of each preparation instrument to identify possible risk points and potential environmental influencing factors. Identify environmental monitoring parameters common to multiple preparation instruments. For example, if multiple preparation instruments have the same temperature but different humidity, then temperature is the common monitoring source for multiple preparation instruments. Collect environmental monitoring data for each preparation instrument, including historical data, real-time data, and trend analysis. Compare the environmental monitoring data of different preparation instruments to find commonalities and differences. Based on the data analysis and comparison results, determine multiple common monitoring sources.

[0020] S3: configuring a multi-source monitoring module with the plurality of common monitoring sources, and connecting the multi-source monitoring module to the integrated drug preparation platform.

[0021] Specifically, determine the key environmental parameters that need to be monitored, such as temperature, humidity, particulate matter content, etc., and select appropriate sensors according to monitoring needs, such as temperature sensors, humidity sensors, particulate matter sensors, etc., as well as cameras, airflow monitors, microbial samplers, etc. Integrate the selected sensors into one or more monitoring modules. Install monitoring modules at key locations on the preparation platform to ensure that the sensors can accurately monitor environmental conditions. Wiring and connecting the monitoring modules ensures that data can be transmitted to the main control system of the integrated drug preparation platform. Connect the monitoring module to the control system of the preparation platform through physical connections, such as cables and network interfaces. Integrate the data interface of the monitoring module in the control software of the preparation platform to receive and process monitoring data in real time.

[0022] S4: Perform data monitoring according to the multi-source monitoring module and output a plurality of common monitoring data.

[0023] Specifically, the monitoring module is activated, and its sensors begin collecting real-time environmental data, such as temperature, humidity, and particulate matter content. The sensors convert the collected analog signals into digital signals. The monitoring module then transmits the collected data to the integrated drug preparation platform's main control system. After receiving the monitoring data, including temperature and humidity, the main control system extracts common monitoring data and outputs them as multiple common monitoring data. For example, if there are two pharmaceutical equipment A and B, where the temperature of pharmaceutical equipment A is 30°C and the humidity is 20°C, and the temperature of pharmaceutical equipment B is 30°C and the humidity is 45°C, then the temperature is the common monitoring data.

[0024] S5: Inputting the plurality of common monitoring data into an environmental anomaly monitoring model, and obtaining an environmental anomaly indicator according to the environmental anomaly monitoring model.

[0025] Specifically, the environmental anomaly model can be a neural network model, trained using historical data. After training, the resulting environmental anomaly monitoring model removes invalid, erroneous, or anomalous data points, extracts features useful for environmental anomaly monitoring from the raw monitoring data, and then inputs multiple common monitoring data sets into the environmental anomaly monitoring model after preprocessing. Data input can occur in real time or in batches at regular intervals. The model analyzes the input data in real time, applying algorithms such as statistical methods, machine learning algorithms, and pattern recognition to identify anomalous patterns. The model outputs environmental anomaly indicators including anomaly scores, anomaly probabilities, and anomaly levels.

[0026] S6: Generate environmental abnormality reminder information according to the environmental abnormality indicator, and feed the environmental abnormality reminder information back to the integrated drug preparation platform.

[0027] Specifically, skilled practitioners will set specific thresholds for environmental anomaly indicators and define different alert methods, such as color coding and audible alarms, based on different anomaly levels. When an environmental anomaly indicator exceeds a preset threshold, an alert message is automatically generated. This includes the anomaly (specific environmental parameter abnormality, such as temperature exceeding the normal range); the anomaly level (severity of the anomaly, such as warning or severe); the time of occurrence (the exact time the anomaly occurred); and the affected area (the specific location or impact range of the anomaly). This anomaly alert information is then fed back to the integrated drug preparation platform's main control system in real time.

[0028] Further, if Figure 2 As shown, step S3 of this application also includes:

[0029] According to the integrated drug preparation platform, the first external environment area and the second external environment area are divided to extract multiple common monitoring sources of the first external environment area and multiple common monitoring sources of the second external environment area; according to the multiple common monitoring sources of the first external environment area and the multiple common monitoring sources of the second external environment area, a first multi-source monitoring module and a second multi-source monitoring module are configured; with the first multi-source monitoring module and the second multi-source monitoring module, a multi-source monitoring module is configured.

[0030] Specifically, the first external environment zone refers to the interior of the drug preparation compartment, while the second external environment zone refers to the exterior of the compartment. Identify and extract monitoring sources for the first external environment zone, such as temperature, humidity, particulate matter content, and microbial load. Identify and extract monitoring sources for the second external environment zone, such as temperature, humidity, light, security monitoring, and energy consumption. The first multi-source monitoring module selects sensors suitable for internal environments such as clean rooms, such as high-precision temperature and humidity sensors and particulate matter sensors. Configure the monitoring module to ensure it can adapt to the environmental conditions within the compartment, such as dust and moisture resistance. The second multi-source monitoring module selects sensors suitable for external environments, such as standard temperature and humidity sensors and security cameras. Configure the monitoring module to account for the various impacts that the external environment may have on the equipment, such as temperature fluctuations, exposure to sunlight and rain, and so on. Install the corresponding sensors in the first and second external environment zones, connect the sensors to the monitoring modules, and ensure the reliability of the data transmission lines. Integrate the first and second multi-source monitoring modules into the main control system of the drug preparation platform to facilitate unified management and data fusion.

[0031] Furthermore, the first external environment area is the external environment area of ​​the preparation instrument located inside the compartment, and the second external environment area is the external environment area of ​​the preparation instrument located outside the compartment.

[0032] Specifically, the first external environment area refers to the environment inside the drug preparation compartment, directly surrounding the preparation instruments. It includes clean rooms, operating areas, etc., and is the core area of ​​drug preparation. Parameters that need to be monitored include temperature, humidity, particulate matter, microbial load, airflow, etc., to ensure that the preparation process is carried out under controlled environmental conditions. The second external environment area refers to the outside of the drug preparation compartment, including storage areas, loading and unloading areas, office areas, etc., which have an indirect impact on the preparation process. Monitoring parameters include temperature, humidity, light, safety monitoring, energy consumption, etc.

[0033] Furthermore, this application also includes:

[0034] Analyze the internal environmental conditions of each preparation instrument during drug preparation to obtain monitoring sources for multiple internal environmental areas, wherein each internal environmental area is the internal preparation environment corresponding to each preparation instrument; configure a third multi-source monitoring module based on the monitoring sources of the multiple internal environmental areas; and optimize the configuration of the multi-source monitoring module based on the third multi-source monitoring module.

[0035] Specifically, the internal environment corresponding to each preparation instrument is identified. Each internal environment zone is analyzed to determine key parameters requiring monitoring, including temperature, pressure, pH, dissolved oxygen, and component concentrations. Based on the analysis results, the specific parameters (i.e., monitoring sources) to be monitored in each internal environment zone are determined. Data collection points are then set up in each internal environment zone to ensure that the sensors can accurately capture the required monitoring data. Based on the internal environment monitoring requirements, appropriate sensors are selected, such as temperature sensors, pressure sensors, and component analysis sensors. The selected sensors are integrated into the third multi-source monitoring module to ensure that the module can adapt to the internal environment conditions, such as pressure resistance and corrosion resistance. This enables the third multi-source monitoring module to transmit the collected data in real time to the main control system of the drug preparation platform. The third multi-source monitoring module is integrated with the monitoring sources of the first and second multi-source monitoring modules to ensure that all monitoring data can be managed and analyzed on a unified platform. Based on the characteristics of the internal environment monitoring data, the configuration of the monitoring module is adjusted, such as increasing the number of specific sensors and adjusting the sampling frequency, to optimize monitoring results. Using data fusion technology, data from different monitoring modules is comprehensively analyzed to improve monitoring accuracy and efficiency.

[0036] Furthermore, this application also includes:

[0037] The environmental conditions of each connecting pipeline during drug preparation are analyzed to obtain multiple common monitoring sources for the pipelines, wherein the multiple common monitoring sources for the pipelines include a common monitoring source at the pipeline interface and a common monitoring source at the pipeline body; a fourth multi-source monitoring module is configured based on the common monitoring source at the pipeline interface and the common monitoring source at the pipeline body; and the configuration of the multi-source monitoring module is optimized based on the fourth multi-source monitoring module.

[0038] Specifically, analyze the environmental conditions of each connected pipeline and identify key monitoring points, including leaks, pressure, and temperature at pipeline interfaces, as well as flow and pressure within the pipeline body. Pay particular attention to pipeline interfaces, as these are prone to leaks or other connection issues. Identify common monitoring sources at pipeline interfaces, such as interface pressure, temperature, and sealing status. Identify common monitoring sources within the pipeline body. If the interface pressures of multiple pipelines are the same, interface pressure is the common monitoring source, while other monitoring data are not. Select appropriate sensors based on monitoring requirements, such as pressure sensors, temperature sensors, and flow meters. Integrate these sensors into the fourth multi-source monitoring module to ensure it adapts to pipeline environmental conditions. Configure a data transmission system to enable the fourth multi-source monitoring module to transmit collected data in real time to the drug preparation platform's main control system. Integrate the fourth multi-source monitoring module with the existing monitoring sources of the first, second, and third multi-source monitoring modules to ensure that all monitoring data can be managed and analyzed on a unified platform. Adjust the monitoring module configuration based on the characteristics of the pipeline monitoring data, such as increasing the number of specific sensor types or adjusting their installation locations, to optimize monitoring effectiveness. Using data fusion technology, the data from different monitoring modules are comprehensively analyzed to improve the accuracy and efficiency of monitoring.

[0039] Furthermore, step S5 of this application also includes:

[0040] The preparation sequence of each preparation instrument in the integrated drug preparation platform is identified to obtain a preparation sequence table; according to the preparation sequence table, a historical preparation data set is extracted; time series nodes are extracted based on the historical preparation data set to obtain a preparation time series table corresponding to the preparation sequence table; the environmental anomaly monitoring model identifies anomalies of the multiple common monitoring data according to the preparation time series table to obtain environmental anomaly indicators.

[0041] Specifically, based on the process flow of drug preparation, the preparation order of each preparation instrument is determined, a unique identifier is assigned to each preparation step, and a preparation sequence table is formed. Historical preparation data related to each preparation step is collected, including environmental monitoring data, operating parameters, output, etc., and a time series analysis is performed on the historical data set to identify the start and end time points of each preparation step. Based on the results of the time series analysis, the time series nodes corresponding to each preparation step are extracted to form a preparation time series table. The extracted preparation time series table is input into the environmental anomaly monitoring model, and the model identifies anomalies of multiple common monitoring data based on the preparation time series table. The model outputs environmental anomaly indicators, which can be used to assess whether environmental conditions deviate from the normal range, thereby identifying potential environmental anomalies.

[0042] Furthermore, this application also includes:

[0043] According to the prepared timing table, each common monitoring data in the multiple common monitoring data is time-aligned, and the multiple common monitoring data after time alignment are output; data deviation anomaly identification is performed according to the multiple common monitoring data after time alignment to obtain multiple common deviation degrees; according to the multiple common deviation degrees, the environmental anomaly index is output.

[0044] Specifically, according to the prepared time series table, multiple common monitoring data are time-aligned to ensure that the time series of each common monitoring data corresponds to the time point in the prepared time series table, and multiple common monitoring data after time alignment are output. The deviation of each common monitoring data from its normal range is calculated. When the deviation of the common monitoring data exceeds the preset threshold, it is identified as an anomaly. Based on the deviation calculation result, the common deviation of each common monitoring data is output, and based on the multiple common deviations, the environmental anomaly index is output. The environmental anomaly index includes the frequency, severity, and scope of impact of the anomaly.

[0045] Furthermore, this application also includes:

[0046] Obtain a persistence index of each common deviation degree among the multiple common deviation degrees; if the persistence index is greater than a preset persistence index, identify it as an abnormal preparation instrument, locate the abnormal environment of the abnormal preparation instrument and generate environmental abnormality reminder information.

[0047] Specifically, the time series of each common deviation is analyzed, and the duration that each common deviation exceeds a preset threshold, i.e., the persistence index, is calculated. The calculated persistence index is then compared with the preset persistence index threshold. If the persistence index is greater than the preset persistence index, the preparation instrument is identified as an abnormal preparation instrument. Based on the identification of the abnormal preparation instrument, the abnormal environmental conditions associated with it are located, and the located environmental parameters are analyzed to determine the cause of the anomaly. An environmental anomaly alert is generated, including the identification of the abnormal preparation instrument, the abnormal environmental conditions, the duration, etc.

[0048] In summary, the drug production environment monitoring method based on multi-source data provided by this application has the following technical effects:

[0049] By obtaining the drug preparation structure of the integrated drug preparation platform, the drug preparation structure includes preparation instruments, connecting pipelines and a compartment, and the preparation instruments and the connecting pipelines constitute a production line in the compartment; analyzing the environmental conditions of each preparation instrument during drug preparation to obtain multiple common monitoring sources; configuring a multi-source monitoring module with the multiple common monitoring sources, and connecting the multi-source monitoring module to the integrated drug preparation platform; performing data monitoring according to the multi-source monitoring module to output multiple common monitoring data; inputting the multiple common monitoring data into an environmental anomaly monitoring model, and obtaining environmental anomaly indicators according to the environmental anomaly monitoring model; generating environmental anomaly reminder information based on the environmental anomaly indicators, and feeding the environmental anomaly reminder information back to the integrated drug preparation platform, the present invention effectively solves the problem of the existing technology that the environmental conditions of drug preparation are not fully monitored and the efficiency of integrating multi-source data is poor, resulting in the inability to monitor the changes in environmental conditions in the drug preparation process in real time and comprehensively. The present invention realizes comprehensive and real-time monitoring of the environmental conditions of multiple preparation instruments in the integrated drug preparation platform, timely discovers environmental anomalies, and improves the quality, efficiency and intelligent management level of drug preparation.

[0050] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

[0051] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A drug production environment monitoring method based on multi-source data, characterized in that: The drug production environment monitoring method based on multi-source data is applied to an integrated drug preparation platform, including: Obtaining a drug preparation structure of the integrated drug preparation platform, wherein the drug preparation structure includes a preparation instrument, connecting pipelines, and a compartment, wherein the preparation instrument and the connecting pipeline constitute a production line within the compartment; Analyze the environmental conditions of each preparation instrument during drug preparation to obtain multiple common monitoring sources; configuring a multi-source monitoring module with the plurality of common monitoring sources, wherein the multi-source monitoring module is connected to the integrated drug preparation platform; Perform data monitoring according to the multi-source monitoring module and output a plurality of common monitoring data; Inputting the plurality of common monitoring data into an environmental anomaly monitoring model, and obtaining an environmental anomaly indicator according to the environmental anomaly monitoring model; generating environmental abnormality reminder information according to the environmental abnormality indicator, and feeding back the environmental abnormality reminder information to the integrated drug preparation platform; Wherein, obtaining an environmental anomaly indicator according to the environmental anomaly monitoring model further includes: Identify the preparation sequence of each preparation instrument in the integrated drug preparation platform to obtain a preparation sequence table; Extracting historical preparation data sets according to the preparation sequence table; Extracting time series nodes according to the historical preparation data set to obtain a preparation time series table corresponding to the preparation sequence table; The environmental anomaly monitoring model identifies anomalies on the plurality of common monitoring data according to the prepared time sequence table to obtain environmental anomaly indicators; The environmental anomaly monitoring model performs anomaly identification on the plurality of common monitoring data according to the preparation time sequence table, including: Performing a time sequence alignment process on each of the plurality of common monitoring data according to the prepared time sequence table, and outputting a plurality of common monitoring data after time sequence alignment; Data deviation anomalies are identified based on multiple common monitoring data after time series alignment to obtain multiple common deviation degrees; Outputting an environmental anomaly indicator based on the multiple common deviations; According to the environmental abnormality indicator, generating environmental abnormality reminder information includes: Obtaining a continuous indicator of each common deviation degree among the plurality of common deviation degrees; If the persistence index is greater than a preset persistence index, it is identified as an abnormal preparation instrument, the abnormal environment of the abnormal preparation instrument is located, and environmental abnormality reminder information is generated.

2. The drug production environment monitoring method based on multi-source data according to claim 1, characterized in that: Configuring a multi-source monitoring module with the plurality of common monitoring sources includes: According to the integrated drug preparation platform, a first external environment area and a second external environment area are divided; Extracting a plurality of common monitoring sources of the first external environmental area and a plurality of common monitoring sources of the second external environmental area; configuring a first multi-source monitoring module and a second multi-source monitoring module according to the plurality of common monitoring sources of the first external environment area and the plurality of common monitoring sources of the second external environment area; A multi-source monitoring module is configured with the first multi-source monitoring module and the second multi-source monitoring module.

3. The drug production environment monitoring method based on multi-source data according to claim 2, characterized in that: The first external environmental area is the external environmental area of ​​the preparation instrument located inside the compartment, and the second external environmental area is the external environmental area of ​​the preparation instrument located outside the compartment.

4. The drug production environment monitoring method based on multi-source data according to claim 2, characterized in that: The configuration of the multi-source monitoring module also includes: Analyze the internal environmental conditions of each preparation instrument during drug preparation to obtain monitoring sources for multiple internal environmental areas, where each internal environmental area is the preparation internal environment corresponding to each preparation instrument; configuring a third multi-source monitoring module according to the monitoring sources of the multiple internal environment areas; The configuration of the multi-source monitoring module is optimized according to the third multi-source monitoring module.

5. The drug production environment monitoring method based on multi-source data according to claim 2, characterized in that: The configuration of the multi-source monitoring module also includes: Analyze the environmental conditions of each connected pipeline during drug preparation to obtain multiple common monitoring sources for the pipelines, including common monitoring sources at pipeline interfaces and common monitoring sources at pipeline bodies; configuring a fourth multi-source monitoring module according to the common monitoring source at the pipeline interface and the common monitoring source at the pipeline body; The configuration of the multi-source monitoring module is optimized according to the fourth multi-source monitoring module.

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