CN117726186A - Supervision method and system for finished medicine products - Google Patents
Supervision method and system for finished medicine products Download PDFInfo
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Abstract
The application relates to a method and a system for supervising a finished medicine product, wherein the method comprises the following steps: acquiring medicine finished product data of medicine production enterprises; according to the medical finished product data, a first medical analysis result of the medical finished product under a single detection item is obtained through a product quality consistency analysis algorithm, according to the medical finished product data, a second medical analysis result of the medical finished product under different detection items is obtained through a dispersion analysis algorithm, and according to the medical finished product data, a third medical analysis result of the medical finished product under the single detection item is obtained through a finished product trend analysis algorithm; and judging whether the production risk exists in the medicine production enterprises according to the three medicine analysis results. Through this application, solved the problem of how to carry out accurate management and control to the medicine finished product of the processing of medicine manufacturing enterprise, realized managing the production risk of medicine manufacturing enterprise through multiple analysis algorithm, improve the security of the medicine finished product of the processing of medicine manufacturing enterprise and guarantee its quality.
Description
Technical Field
The application relates to the technical field of production management and control, in particular to a supervision method and system of a finished medicine product.
Background
The safety problem of the medicine production industry is related to the life health of people, and a medicine enterprise must establish a quality management system from the social responsibility and quality assurance of the medicine enterprise, and simultaneously establish a complete file and a quality assurance system to ensure the effective operation of the system.
The existing scheme generally only records data information in the medicine production and circulation processes such as medicine marketing and medicine transportation processes, and a medicine field electronic supervision system disclosed in the patent with the application number of CN201110078934.3 is used for realizing low-cost safety certification by using whole-course tracking and traceable supervision for medicine production and circulation, thereby providing medicine anti-counterfeiting technical means and laying a foundation for quick recall of problematic medicines.
At present, no effective solution is proposed for accurately controlling the finished medicine products produced and processed by pharmaceutical production enterprises in the related technology.
Disclosure of Invention
The embodiment of the application provides a supervision method and a supervision system for medical finished products, which are used for at least solving the problem of accurately managing and controlling the medical finished products produced and processed by a medicine production enterprise in the related technology.
In a first aspect, embodiments of the present application provide a method for monitoring a pharmaceutical product, the method comprising:
acquiring medicine finished product data of medicine production enterprises;
obtaining a first medical analysis result of the medical finished product under the single detection item according to the medical finished product data through a product quality consistency analysis algorithm, obtaining a second medical analysis result of the medical finished product under different detection items according to the medical finished product data through a dispersion analysis algorithm, and obtaining a third medical analysis result of the medical finished product under the single detection item according to the medical finished product data through a finished product trend analysis algorithm;
judging whether the production risk exists in the medicine production enterprises according to the first medicine analysis result, the second medicine analysis result and the third medicine analysis result.
In some embodiments, the obtaining, according to the pharmaceutical product data, a first pharmaceutical analysis result of the pharmaceutical product under the single detection item by a product quality consistency analysis algorithm includes:
according to the medicine finished product data, calculating to obtain a product quality consistency analysis result through a product quality consistency analysis formula, wherein the medicine finished product data is single detection item data of all batches of medicine finished products, and the product quality consistency analysis formula is as follows:
in the method, in the process of the invention,k is the detection value of the latest batch of medicine finished products, x i For the detection value of the pharmaceutical product item of the ith batch, </i >>The average value of the detection values of the pharmaceutical product items of all batches is n, and the number of the batches is n.
In some embodiments, determining whether the pharmaceutical manufacturing facility is at risk for production according to the first medical analysis result comprises:
if the product quality consistency analysis result is more close to 0, determining that the production risk of the product quality consistency does not exist in the medicine production enterprises;
if the product quality consistency analysis result deviates from 0 and is larger than a preset early warning value, determining that the production risk of the product quality consistency exists in the medicine production enterprises, and triggering risk early warning.
In some embodiments, obtaining the second medical analysis result of the medical finished product under different detection projects through a dispersion analysis algorithm according to the medical finished product data comprises:
calculating to obtain a dispersion analysis result through a dispersion analysis formula according to the medicine finished product data, wherein the medicine finished product data is all detection item data of a single batch of medicine finished products,the dispersion analysis formula is as follows:
wherein x is i The medical finished product item detection value of the ith detection item,the average value of the detection values of the pharmaceutical product items corresponding to the detection items is n, and the number of the detection items is n.
In some embodiments, determining whether the pharmaceutical manufacturing facility is at risk for production according to the second medical analysis result comprises:
if the dispersion analysis result is more similar to 1, determining that the medicine production enterprises do not have discrete production risks;
if the dispersion analysis result deviates from 1 and is larger than a preset early warning value, determining that the medicine production enterprises have discrete production risks, and triggering risk early warning.
In some embodiments, the obtaining, according to the pharmaceutical product data, a third pharmaceutical analysis result of the pharmaceutical product under a single test item by a product trend analysis algorithm includes:
and performing data cleaning on the medicine finished product data, and generating a medicine finished product trend chart of the medicine production enterprise based on the medicine finished product data subjected to data cleaning and a preset upper and lower limit range.
In some embodiments, determining whether the pharmaceutical manufacturing company has a manufacturing risk according to the third medical analysis result includes:
if the medicine finished product data in the medicine finished product trend chart is always within the preset upper and lower limit ranges, determining that the medicine production enterprises do not have production risks of medicine finished product trend;
if the medical product data in the medical product trend chart exceeds the preset upper and lower limit ranges, determining that the production risk of medical product trend exists in the medicine production enterprises, and triggering risk early warning.
In some of these embodiments, the method further comprises:
acquiring medical middleware data of the medicine production enterprises;
and obtaining a fourth medical analysis result of the medicine production enterprise through a similarity analysis algorithm according to the medical finished product data and the medical middleware data.
In some embodiments, the obtaining the fourth medical analysis result of the pharmaceutical manufacturing company through the similarity analysis algorithm according to the medical product data and the medical middleware data comprises:
matching the medical finished product data and the medical intermediate data with corresponding relations;
and generating an index superposition graph of the drug manufacturing enterprise based on the drug product data, the pharmaceutical middleware data and a plurality of preset indexes, wherein the index superposition graph is used for judging whether the drug manufacturing enterprise has production risk or not.
In a second aspect, embodiments of the present application provide a system for monitoring a pharmaceutical product, the system for performing the method of any one of the first aspects above, the system comprising a data acquisition module and a black box module;
the data acquisition module is used for acquiring the medicine finished product data of a medicine production enterprise;
the black box module is used for obtaining a first medical analysis result of the medical finished product under the single detection item through a product quality consistency analysis algorithm according to the medical finished product data, obtaining a second medical analysis result of the medical finished product under different detection items through a dispersion analysis algorithm according to the medical finished product data, and obtaining a third medical analysis result of the medical finished product under the single detection item through a finished product trend analysis algorithm according to the medical finished product data;
the black box module is used for judging whether the production risk exists in the medicine production enterprises according to the first medicine analysis result, the second medicine analysis result and the third medicine analysis result.
Compared with the related art, the method and the system for supervising the medical finished product provided by the embodiment of the application are characterized in that the method is used for acquiring medical finished product data of a medicine production enterprise; according to the medical finished product data, a first medical analysis result of the medical finished product under a single detection item is obtained through a product quality consistency analysis algorithm, according to the medical finished product data, a second medical analysis result of the medical finished product under different detection items is obtained through a dispersion analysis algorithm, and according to the medical finished product data, a third medical analysis result of the medical finished product under the single detection item is obtained through a finished product trend analysis algorithm; according to the first medical analysis result, the second medical analysis result and the third medical analysis result, whether the production risk exists in the medicine production enterprises or not is judged, the problem of how to accurately manage and control the medical finished products produced and processed by the medicine production enterprises is solved, the production risk of the medicine production enterprises is managed and controlled through various analysis algorithms, the safety of the medical finished products produced and processed by the medicine production enterprises is improved, and the quality of the medical finished products is guaranteed.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flow chart of steps of a method of pharmaceutical product administration according to an embodiment of the present application;
FIG. 2 is a block diagram of a pharmaceutical end product monitoring system according to an embodiment of the present application;
FIG. 3 is a hardware schematic of a black box module according to an embodiment of the present application;
fig. 4 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application.
The attached drawings are identified: 21. a data acquisition module; 22. and a black box module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described and illustrated below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden on the person of ordinary skill in the art based on the embodiments provided herein, are intended to be within the scope of the present application.
It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is possible for those of ordinary skill in the art to apply the present application to other similar situations according to these drawings without inventive effort. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the embodiments described herein can be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar terms herein do not denote a limitation of quantity, but rather denote the singular or plural. The terms "comprising," "including," "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The terms "connected," "coupled," and the like in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as used herein refers to two or more. "and/or" describes an association relationship of an association object, meaning that there may be three relationships, e.g., "a and/or B" may mean: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. The terms "first," "second," "third," and the like, as used herein, are merely distinguishing between similar objects and not representing a particular ordering of objects.
An embodiment of the present application provides a method for monitoring a finished medical product, and fig. 1 is a flowchart of steps of the method for monitoring a finished medical product according to an embodiment of the present application, as shown in fig. 1, and the method includes the following steps:
step S102, obtaining medicine finished product data of medicine production enterprises;
the medicine products are different from medicine intermediates, raw auxiliary materials and the like, and the medicine products refer to finished medicine agents which are produced and packaged and meet the related pharmacopoeia, specifications and standards, and are prepared from medicine raw materials through a certain process and formula so as to be used clinically. The finished medicine has certain medicine activity and dosage form characteristics, and has passed the relevant medicine quality control and safety evaluation. The finished medicine is usually in the form of solid, liquid, powder and the like, such as tablets, capsules, oral liquid, injection and the like. During the circulation and use of the medicine market, the finished medicine should meet the quality standard, the label requirement and the related legal and regulatory regulations.
Step S104, obtaining a first medical analysis result of the medical finished product under a single detection project through a product quality consistency analysis algorithm according to the medical finished product data;
step S104, specifically, calculating and obtaining a product quality consistency analysis node through a product quality consistency analysis formula according to the medicine finished product dataThe method comprises the steps of determining the content of a finished product, determining the dissolution rate of the finished product (2 hours/3 hours/5 hours) and determining the content uniformity of the finished product, wherein the data of the finished product is single detection item data of all batches of finished products, and the analysis formula of the quality uniformity of the finished product is as follows:
in the method, in the process of the invention,k is the detection value of the latest batch of medicine finished products, x i For the detection value of the pharmaceutical product item of the ith batch, </i >>The average value of the detection values of the pharmaceutical product items of all batches is n, and the number of the batches is n.
It should be noted that the product quality consistency analysis result is an analysis result of a single detection item. If the product quality consistency analysis result is closer to 0, the quality consistency of the medicine finished product of the same detection item is strong. Therefore, when the analysis result of the product quality consistency deviates from 0 and is larger than a preset early warning value (for example, 3 times of standard deviation larger than the data of the medical finished products), the product quality consistency is deviated from a reasonable fluctuation range, and risk early warning is performed, so that the safety of the medical finished products produced and processed by a medicine production enterprise can be improved, and the quality of the medical finished products can be ensured.
Step S106, obtaining second medical analysis results of the medical finished products under different detection projects through a dispersion analysis algorithm according to the medical finished product data;
in step S106, specifically, a dispersion analysis result is obtained by calculating a dispersion analysis formula according to the pharmaceutical product data, wherein the pharmaceutical product data is all detection item data of a single batch of pharmaceutical products, and the detection items include product content measurement, product dissolution measurement (2 hours/3 hours/5 hours dissolution) and product content uniformity measurement, and the dispersion analysis formula is:
wherein x is i The medical finished product item detection value of the ith detection item,the average value of the detection values of the pharmaceutical product items corresponding to the detection items is n, and the number of the detection items is n.
The dispersion analysis result is a single batch of analysis result. If the dispersion analysis result is closer to 1, the quality consistency of the same batch of medical finished products is strong. Therefore, when the dispersion analysis result deviates from 1 and is larger than a preset early warning value, the deviation from a reasonable fluctuation range is indicated, and risk early warning is carried out, so that the safety of the finished medicine products produced and processed by the medicine production enterprises can be improved, and the quality of the finished medicine products can be ensured.
Step S108, obtaining a third medical analysis result of the medical finished product under a single detection item through a finished product trend analysis algorithm according to the medical finished product data;
specifically, in step S108, data cleaning is performed on the pharmaceutical product data, and a pharmaceutical product trend chart of the pharmaceutical production enterprise is generated based on the pharmaceutical product data after data cleaning and the preset upper and lower limit ranges, wherein the pharmaceutical product data is single detection item data of all batches of pharmaceutical products, and the detection items include product content measurement, product dissolution amount measurement (2 hours/3 hours/5 hours dissolution amount) and product content uniformity measurement.
The medical product trend graph is generated based on the preset upper and lower limit ranges, so that the fluctuation condition of medical product data can be intuitively reflected. If the data of the finished medicine exceeds the standard limit, risk early warning is carried out, so that the safety of the finished medicine produced and processed by a medicine production enterprise can be improved, and the quality of the finished medicine can be ensured.
In addition, the method further comprises step S109, obtaining medical middleware data of a medicine production enterprise; and obtaining a fourth medical analysis result of the medicine production enterprise through a similarity analysis algorithm according to the medical finished product data and the medical middleware data.
Step S109 specifically, matching out the medical finished product data and the medical intermediate data with corresponding relations; and generating an index superposition graph of the drug manufacturing enterprise based on the drug product data, the drug middleware data and a plurality of preset indexes, wherein the index superposition graph is used for judging whether the drug manufacturing enterprise has production risk or not.
It should be noted that, based on a plurality of preset relevance indexes, the medicine product data and the medicine intermediate data are superimposed and mapped to analyze the difference condition between the medicine product and the medicine intermediate, if the content trend of the same preset index of the medicine intermediate and the medicine product has a significant difference, risk early warning should be performed, and the production process from the medicine intermediate to the medicine product is investigated and analyzed, so that the safety of the medicine product produced and processed by a medicine production enterprise can be improved and the quality of the medicine product can be ensured.
Step S110, judging whether the production risk exists in the medicine production enterprises according to the first medicine analysis result, the second medicine analysis result and the third medicine analysis result.
The method for determining the production risk in step S110 specifically includes:
(1) and judging whether the production risk exists in the medicine production enterprises according to the first medicine analysis result.
If the product quality consistency analysis result is more close to 0, determining that the production risk of the product quality consistency does not exist in the medicine production enterprises;
if the product quality consistency analysis result deviates from 0 and is larger than a preset early warning value, determining that the production risk of the product quality consistency exists in the medicine production enterprises, and triggering risk early warning.
(2) And judging whether the production risk exists in the medicine production enterprises according to the second medicine analysis result.
If the dispersion analysis result is more similar to 1, determining that the medicine production enterprises do not have discrete production risks;
if the dispersion analysis result deviates from 1 and is larger than a preset early warning value, determining that the medicine production enterprises have discrete production risks, and triggering risk early warning.
(3) And judging whether the production risk exists in the medicine production enterprises according to the third medicine analysis result.
If the medicine finished product data in the medicine finished product trend chart is always within the preset upper and lower limit ranges, determining that the medicine production enterprises do not have production risks of medicine finished product trend;
if the medical product data in the medical product trend chart exceeds the preset upper and lower limit ranges, determining that the production risk of the medical product trend exists in the medicine production enterprises, and triggering risk early warning.
Through step S102 to step S110 in this application embodiment, the problem of how to carry out accurate management and control to the medicine finished product of processing that the medicine manufacturing enterprise produced is solved, the production risk of managing the medicine manufacturing enterprise through multiple analysis algorithm has been realized, the security of the medicine finished product of processing that the medicine manufacturing enterprise produced is improved and its quality is guaranteed.
It should be noted that the steps illustrated in the above-described flow or flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein.
Example 2
An embodiment of the present application provides a system for monitoring and managing finished medical products, the system is used for executing the method in the above embodiment, fig. 2 is a block diagram of the system for monitoring and managing finished medical products according to the embodiment of the present application, as shown in fig. 2, the system includes a data acquisition module 21 and a black box module 22;
a data acquisition module 21 for acquiring pharmaceutical product data of a pharmaceutical manufacturing enterprise;
the black box module 22 is configured to obtain a first medical analysis result of the medical finished product under a single detection item according to the medical finished product data through a product quality consistency analysis algorithm, obtain a second medical analysis result of the medical finished product under different detection items according to the medical finished product data through a dispersion analysis algorithm, and obtain a third medical analysis result of the medical finished product under the single detection item according to the medical finished product data through a product trend analysis algorithm;
the black box module 22 is configured to determine whether the pharmaceutical manufacturing enterprise has a production risk according to the first medical analysis result, the second medical analysis result, and the third medical analysis result.
Through the data acquisition module 21 and the black box module 22 in the embodiment of the application, the problem of how to accurately manage and control the finished medicine products produced and processed by the medicine production enterprises is solved, the production risk of the medicine production enterprises is managed and controlled through various analysis algorithms, the safety of the finished medicine products produced and processed by the medicine production enterprises is improved, and the quality of the finished medicine products is guaranteed.
The above-described respective modules may be functional modules or program modules, and may be implemented by software or hardware. For modules implemented in hardware, the various modules described above may be located in the same processor; or the above modules may be located in different processors in any combination.
Example 3
Based on the above embodiment 2, the embodiment of the present application provides a black box module for drug production supervision, and fig. 3 is a hardware schematic diagram of the black box module according to the embodiment of the present application, as shown in fig. 3, where the black box module provided in the embodiment of the present application is a matched integrated hardware device of a drug safety production management platform. The equipment is provided with a touch display screen, a multifunctional control panel, a power module, a UPS, a main board, a data storage module and various function output interfaces (an internal network and an external network connection network interface, HDMI and USB interfaces).
The black box module in this embodiment of the present application has the following functions in addition to the function of "analyzing according to the medicine product data, judging whether or not there is a production risk for the medicine production enterprise" in the above embodiment 2:
(1) the main control is provided with a GPS positioning sensor and a 4G module base station for positioning, and the longitude and latitude can be displayed on a display screen; when the equipment abnormality log is stored, the longitude and latitude at the time are stored. The GPS positioning is preferred over the base station positioning, when the GPS can acquire data, the GPS positioning is used, and when the GPS does not acquire data, the base station is used for acquiring longitude and latitude information positioning. The method comprises the following steps: 1. and a GPS antenna is inserted, the tail end of the antenna is connected to the outside, longitude and latitude information can be obtained within 5 minutes, and the longitude and latitude information is displayed in the display screen information of the black box module. 2. When the tail end of the GPS antenna cannot be connected to the outside, a base station positioning function is adopted, the base station positioning function needs to ensure that a 4G card is inserted (the GPS antenna is pulled out), longitude and latitude information can be obtained within 5 minutes after the card is inserted, and the state in the display screen information of the black box module is changed from 'no positioning' to longitude and latitude data.
(2) The temperature and humidity of the current place can be acquired through the node temperature and humidity sensor, and the temperature and humidity can be transmitted to the main control display through wireless transmission. The transmission distance of the temperature and humidity sensor is different due to different environments, and the transmission distance is as close to a medicine safety intelligent supervision black box host as possible during installation.
(3) The equipment shakes, moves beyond the abnormal conditions such as the set distance (the settable distance), violent unlocking or low voltage, and the like, and the buzzer sounds and simultaneously sends an alarm short message (the alarm mobile phone number can be set). It should be noted that any one of the anomalies that the input voltage is lower than 210 v, the power is off, the vibration, the moving distance is greater than the set value, the violent unlocking and the like can give out an audible alarm. The alarm mobile phone number is supported to be set, and a black box supports 5 mobile phone numbers at most.
(4) Various abnormal alarm logs can be recorded, and the logs comprise a mobile log, a starting log, a low-voltage log, a vibration log and an abnormal unlocking log.
(5) The unlocking password can be input through a software interface of the display screen, and the case of the black box module can be automatically opened (unauthorized personnel cannot unlock without the password).
(6) The abnormal conditions such as vibration, movement exceeding a set distance, violent unlocking or low voltage are recorded and stored, time, longitude and latitude and events are included, and related logs can be checked on a liquid crystal screen.
(7) The temperature sensor is arranged in the equipment, and the temperature in the equipment is detected in real time and displayed.
(8) TFT LCD clock, working hour meter, log, company name LOGO and pilot lamp, etc. can realize touch selection menu page and slip selection menu page. The device is powered on to start timing, data is stored in real time, the data is stored in time when the device is powered off, the black box leaves the factory until the total running time is 0.1 hour, and the data is refreshed every 0.1 hour.
(9) The system can be in interface connection with a server to transmit related data, and can also view the connection state of the server.
And the data transmission between the master control and the sensor nodes adopts the LORA wireless technology to realize wireless point distribution.
The present embodiment also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
It should be noted that, specific examples in this embodiment may refer to examples described in the foregoing embodiments and alternative implementations, and this embodiment is not repeated herein.
In addition, in combination with the method for supervising the pharmaceutical product in the above embodiment, the embodiment of the application may provide a storage medium for implementation. The storage medium has a computer program stored thereon; the computer program, when executed by a processor, implements the method of supervision of any one of the pharmaceutical products of the above embodiments.
In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements a method of supervision of a pharmaceutical product. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
In one embodiment, fig. 4 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application, as shown in fig. 4, and an electronic device, which may be a server, may be provided, and an internal structure diagram thereof may be shown in fig. 4. The electronic device includes a processor, a network interface, an internal memory, and a non-volatile memory connected by an internal bus, where the non-volatile memory stores an operating system, computer programs, and a database. The processor is used for providing computing and control capability, the network interface is used for communicating with an external terminal through network connection, the internal memory is used for providing environment for the operation of an operating system and a computer program, the computer program is executed by the processor to realize a supervision method of a finished medicine product, and the database is used for storing data.
It will be appreciated by those skilled in the art that the structure shown in fig. 4 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the electronic device to which the present application is applied, and that a particular electronic device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It should be understood by those skilled in the art that the technical features of the above-described embodiments may be combined in any manner, and for brevity, all of the possible combinations of the technical features of the above-described embodiments are not described, however, they should be considered as being within the scope of the description provided herein, as long as there is no contradiction between the combinations of the technical features.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A method of supervising a finished pharmaceutical product, the method comprising:
acquiring medicine finished product data of medicine production enterprises;
obtaining a first medical analysis result of the medical finished product under a single detection item according to the medical finished product data through a product quality consistency analysis algorithm, obtaining a second medical analysis result of the medical finished product under different detection items according to the medical finished product data through a dispersion analysis algorithm, and obtaining a third medical analysis result of the medical finished product under the single detection item according to the medical finished product data through a finished product trend analysis algorithm;
judging whether the production risk exists in the medicine production enterprises according to the first medicine analysis result, the second medicine analysis result and the third medicine analysis result.
2. The method of claim 1, wherein deriving a first medical analysis result for the finished medical product for a single test item from the finished medical product data by a product quality consistency analysis algorithm comprises:
according to the medicine finished product data, a product quality consistency analysis result is obtained through calculation of a product quality consistency analysis formula, wherein the medicine finished product data is single detection item data of all batches of medicine finished products, the detection items comprise finished product content measurement, finished product dissolution amount measurement and finished product content uniformity measurement, and the product quality consistency analysis formula is as follows:
in (1) the->K is the detection value of the latest batch of medicine finished products, x i For the detection value of the pharmaceutical product item of the ith batch, </i >>The average value of the detection values of the pharmaceutical product items of all batches is n, and the number of the batches is n.
3. The method of claim 2, wherein determining whether the pharmaceutical manufacturing facility is at risk for manufacturing based on the first medical analysis result comprises:
if the product quality consistency analysis result is more close to 0, determining that the production risk of the product quality consistency does not exist in the medicine production enterprises;
if the product quality consistency analysis result deviates from 0 and is larger than a preset early warning value, determining that the production risk of the product quality consistency exists in the medicine production enterprises, and triggering risk early warning.
4. The method of claim 1, wherein deriving a second medical analysis result for the medical finished product for different test projects from the medical finished product data by a dispersion analysis algorithm comprises:
calculating and obtaining a dispersion analysis result through a dispersion analysis formula according to the medicine finished product data, wherein the medicine finished product data is all detection item data of single-batch medicine finished products, the detection items comprise finished product content measurement, finished product dissolution measurement and finished product content uniformity measurement, and the dispersion analysis formula is as follows:
wherein x is i A pharmaceutical product item detection value of the ith detection item,/-for the i-th detection item>The average value of the detection values of the pharmaceutical product items corresponding to the detection items is n, and the number of the detection items is n.
5. The method of claim 4, wherein determining whether the pharmaceutical manufacturing facility is at risk for manufacturing based on the second medical analysis result comprises:
if the dispersion analysis result is more similar to 1, determining that the medicine production enterprises do not have discrete production risks;
if the dispersion analysis result deviates from 1 and is larger than a preset early warning value, determining that the medicine production enterprises have discrete production risks, and triggering risk early warning.
6. The method of claim 1, wherein deriving a third medical analysis result for the finished medical product under a single test item from the finished medical product data by a product trend analysis algorithm comprises:
and performing data cleaning on the medical finished product data, and generating a medical finished product trend chart of the medicine production enterprise based on the medical finished product data subjected to data cleaning and a preset upper and lower limit range, wherein the medical finished product data is single detection item data of all batches of medical finished products, and the detection items comprise finished product content measurement, finished product dissolution measurement and finished product content uniformity measurement.
7. The method of claim 6, wherein determining whether the pharmaceutical manufacturing facility is at risk for manufacturing based on the third medical analysis result comprises:
if the medicine finished product data in the medicine finished product trend chart is always within the preset upper and lower limit ranges, determining that the medicine production enterprises do not have production risks of medicine finished product trend;
if the medical product data in the medical product trend chart exceeds the preset upper and lower limit ranges, determining that the production risk of medical product trend exists in the medicine production enterprises, and triggering risk early warning.
8. The method according to claim 1, wherein the method further comprises:
acquiring medical middleware data of the medicine production enterprises;
and obtaining a fourth medical analysis result of the medicine production enterprise through a similarity analysis algorithm according to the medical finished product data and the medical middleware data.
9. The method of claim 8, wherein deriving a fourth medical analysis result for the pharmaceutical manufacturing facility from the medical end product data and the medical middleware data via a similarity analysis algorithm comprises:
matching the medical finished product data and the medical intermediate data with corresponding relations;
and generating an index superposition graph of the drug manufacturing enterprise based on the drug product data, the pharmaceutical middleware data and a plurality of preset indexes, wherein the index superposition graph is used for judging whether the drug manufacturing enterprise has production risk or not.
10. A system of supervision of pharmaceutical products, characterized in that it is adapted to perform the method of any one of claims 1 to 9, said system comprising a data acquisition module and a black box module;
the data acquisition module is used for acquiring the medicine finished product data of a medicine production enterprise;
the black box module is used for obtaining a first medical analysis result of the medical finished product under a single detection item through a product quality consistency analysis algorithm according to the medical finished product data, obtaining a second medical analysis result of the medical finished product under different detection items through a dispersion analysis algorithm according to the medical finished product data, and obtaining a third medical analysis result of the medical finished product under the single detection item through a finished product trend analysis algorithm according to the medical finished product data;
the black box module is used for judging whether the production risk exists in the medicine production enterprises according to the first medicine analysis result, the second medicine analysis result and the third medicine analysis result.
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