Precise medicine mixing system based on intelligent proportioning

Abstract

The invention relates to the related technical field of precise mixing control, in particular to a precise medicine mixing system based on intelligent proportioning, which comprises the following steps: configuring a dosage standard through user basic information in combination with a medicine use instruction and a dropping liquid control parameter; and the partition storage module manages the drop drugs and generates a mixing working sequence to regulate and control the mixing process so as to realize microfluidic mixing. The technical problems that the dosage control precision of drop drugs is limited due to dependence on a fixed formula proportion, then the mixing uniformity is influenced, and the mixing consistency of the drop drugs is poor are solved, the drop drug proportion is accurately configured according to individual differences and drug concentrations, a plurality of independent storage partitions and a micro-flow mixing module in a mixing working module are utilized, and the dosage control precision of the drop drugs is greatly improved. According to the drop medicine mixing device, the proportion mixing of various drop medicines is efficiently carried out, on the basis of ensuring the mixing efficiency, the release sequence, speed and mixing time of drops are accurately controlled, the mixing consistency and quality stability of the drop medicines are ensured, and the technical effect of efficiently and uniformly mixing the drop medicines is realized.

Description

Technical Field

[0001] The present invention relates to the technical field related to precise mixing control, and in particular to a precise drug mixing system based on intelligent proportioning. Background Art

[0002] In the field of pharmaceutical manufacturing, the drug mixing process is a crucial link, which is directly related to the quality and efficacy of the drugs. However, the single-mapped drug mixing model is prone to problems such as dosage errors, especially for drop-type drugs that require strict proportions. In addition, the drug mixing process is easily affected by external environmental factors such as temperature and humidity fluctuations, which causes changes in the physical properties of the drugs, further affecting the uniformity and effect of the mixing, and the quality of the drugs cannot be guaranteed.

[0003] In summary, the prior art has a technical problem that the dosage control accuracy of drop-type drugs is limited due to reliance on a fixed formula ratio, which in turn affects the mixing uniformity and leads to poor mixing consistency of drop-type drugs. Summary of the invention

[0004] The present application provides a precise drug mixing system based on intelligent proportioning, aiming to solve the technical problem in the prior art that the dosage control accuracy of drop-type drugs is limited due to reliance on fixed formula ratios, thereby affecting the mixing uniformity and resulting in poor mixing consistency of drop-type drugs.

[0005] In view of the above problems, the technical solution to implement this application is: The present application provides a precise drug mixing system based on intelligent proportioning, which includes: a basic information download module for connecting to a recipe storage manager to download user basic information, wherein the user basic information includes weight and age; a first dosage standard configuration module for configuring a first dosage standard based on the user manual of drop-type drugs and in combination with the user basic information, wherein the first dosage standard is a drop-type drug dosage obtained by proportional matching with the user basic information as a constraint; a second dosage standard configuration module for connecting to a drip controller, and configuring a second dosage standard through a drip volume corresponding to a drip control parameter and in combination with the drop-type drug concentration, wherein the second dosage standard is a drop-type drug dosage obtained by clustering and rounding iteratively with the drop-type drug concentration as a constraint; a partition storage module for starting mixing A working module, wherein the mixing working module comprises a plurality of independent storage partitions, each of which is used to store a type of drop-type medicines, and the mixing working module is interactively connected with the drip controller; a mixing working sequence generating module, which is used to generate a mixing working sequence based on the mixing working module and in comparison with V microscale mixing channels corresponding to the built-in microfluidic mixing module, wherein the operating instructions contained in the mixing working sequence are used to activate and control the V microscale mixing channels, and to perform regulation of the drop release sequence, the drop release speed, and the drop mixing time under U drop mixing windows; a microfluidic mixing module, which is used to introduce the drop mixing efficiency based on the mixing working sequence, and to perform microfluidic mixing of the drop-type medicine ratio on the mixing working module in combination with the first dosage standard and the second dosage standard.

[0006] In summary, one or more technical solutions provided in the present application solve the technical problem that the dosage control accuracy of drop-type drugs is limited due to reliance on a fixed formula ratio, which in turn affects the mixing uniformity and the mixing consistency of drop-type drugs is poor. The drop-type drug ratio is accurately configured according to individual differences and drug concentrations, and multiple independent storage partitions and microfluidic mixing modules in the mixing working module are utilized to efficiently mix multiple types of drop-type drugs. On the basis of ensuring the mixing efficiency, the release sequence, speed and mixing time of the drops are accurately controlled to ensure the consistency and quality stability of the mixing of drop-type drugs, thereby achieving the technical effect of efficient and uniform mixing of drop-type drugs. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 A structural schematic diagram of a drug precision mixing system based on intelligent proportioning is provided for this application; Figure 2 This application provides a flowchart of the execution steps for optimizing and adjusting the proportion of drop-type drugs in a microfluidic mixing module in a precise drug mixing system based on intelligent proportioning.

[0008] Description of the accompanying drawings: basic information downloading module M100, configuring the first dose standard module M200, configuring the second dose standard module M300, partition storage module M400, mixing work sequence generating module M500, microfluidic mixing module M600. DETAILED DESCRIPTION

[0009] Example The present application is described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides a precise drug mixing system based on intelligent proportioning, wherein the system comprises: The basic information download module M100 is used to connect to the recipe storage manager and download the user's basic information, which includes weight and age; the first dosage standard configuration module M200 is used to configure the first dosage standard based on the instructions for use of drop-type drugs and the user's basic information. The first dosage standard is the dosage of drop-type drugs obtained by proportional matching based on the user's basic information.

[0010] The basic information download module is used to connect to the recipe storage manager and download the user's basic information from it. It is crucial for the subsequent drug dosage configuration and provides key data about the user's physical condition and needs, specifically, including the user's weight and age, which serve as an important reference for configuring drug dosage.

[0011] The first dosage standard module is based on the instructions for use of drop-type drugs and is configured in combination with the user's basic information. The first dosage standard is obtained by proportionally matching the user's basic information with the recommended dosage in the drug instructions. In other words, the drug dosage is adjusted according to the user's personal characteristics such as weight and age to ensure that the use of the drug is both safe and effective. In this way, personalized drug dosage recommendations are provided to each user, thereby improving the accuracy and effectiveness of drug use.

[0012] A second dosage standard module M300 is configured to connect to the drip controller. The second dosage standard is configured through the drip volume corresponding to the drip control parameter combined with the concentration of the drip drug. The second dosage standard is the dosage of the drip drug obtained by clustering and rounding iteratively with the concentration of the drip drug as the constraint.

[0013] The second dosage standard module is configured to be connected to the drip controller, and the second dosage standard is configured according to the drip volume corresponding to the drip control parameter and the concentration of the drip drug. The second dosage standard is the dosage of the drip drug obtained by clustering and rounding iterative calculation with the concentration of the drip drug as a constraint. Specifically, the drip control parameters provided by the drip controller are first obtained. These parameters determine the volume of each drip. Then, combined with the concentration information of the drip drug, a dosage standard that meets the drug concentration requirements and is convenient for actual operation is obtained through a series of calculations and iterations, that is, the second dosage standard. The second dosage standard is obtained through mathematical methods such as clustering and rounding on the premise of ensuring the accuracy of the drug concentration, so that the dosage of the drug can be controlled more conveniently and accurately in actual applications. In this way, the accuracy and efficiency of drug proportioning can be further improved.

[0014] Furthermore, the second dose standard configuration module M300 is also used to perform the following method: Connect a temperature sensor and a viscosity sensor to collect drip temperature monitoring data and drip viscosity monitoring data; based on the drip temperature monitoring data and the drip viscosity monitoring data, use a machine learning prediction model to predict changes in the physical properties of drop-type drugs under different environmental conditions; and use fuzzy control logic to perform environmental adaptive control on the drip controller based on changes in the physical properties of the drop-type drugs under different environmental conditions.

[0015] In the process of configuring the second dosage standard, the drip controller is connected and the influence of environmental factors such as drip temperature and viscosity on the physical properties of drip drugs is considered. Specifically, the temperature sensor and viscosity sensor are connected to the drip controller to ensure that the temperature and viscosity data of the drip can be collected in real time; the temperature monitoring data and viscosity monitoring data of the drip are continuously collected through the sensor, and the drip temperature monitoring data and the drip viscosity monitoring data will be used for subsequent predictions of changes in physical properties.

[0016] Based on the collected drip temperature monitoring data and viscosity monitoring data, a machine learning prediction model is used to predict the changes in the physical properties of drop-type drugs under different environmental conditions. In the prediction process, in addition to temperature and viscosity, the effects of other environmental factors (such as humidity, pressure, etc.) on the physical properties of drop-type drugs can also be considered. Fuzzy control logic is used to perform environmental adaptive control of the drip controller according to the changes in the physical properties of drop-type drugs under different environmental conditions.

[0017] According to the changes in physical properties, the parameters of the drip controller are adjusted in real time to ensure that the volume and speed of the drip can meet the requirements of the drug ratio; on the basis of environmental adaptive control, the concentration of drop drugs is combined to further optimize the second dose standard to ensure the accuracy and effectiveness of drug ratio. In summary, by connecting the temperature sensor and the viscosity sensor, collecting the temperature and viscosity data of the drip, and using the machine learning prediction model to predict the changes in the physical properties of drop drugs under different environmental conditions, and using fuzzy control logic to perform environmental adaptive control on the drip controller, the second dose standard can be configured more accurately, improving the accuracy and effectiveness of drug ratio.

[0018] The partition storage module M400 is used to start the mixing working module, which includes a plurality of independent storage partitions, each of which is used to store a type of drop-type medicines, and the mixing working module is interactively connected with the drip controller.

[0019] The partition storage module starts and manages the mixing work module, which contains multiple independent storage partitions. Each partition is specially designed to store a specific type of drop-type medicine. This design ensures the classified storage of medicines and avoids confusion or cross-contamination between different medicines. More importantly, an interactive connection is established between the mixing work module and the drop controller, which means that when the medicine needs to be mixed, the drop controller can accurately control the release of drops in each partition to ensure the accuracy and consistency of the mixing. Through the partition storage module, the mixing work module can efficiently perform the task of mixing medicines. Each independent storage partition can be independently controlled and operated as needed, which greatly improves the flexibility and efficiency of medicine mixing. At the same time, since the medicines are stored in categories, the risk of errors in the mixing process is reduced.

[0020] Furthermore, the partition storage module M400 is also used to execute the following method: Using a risk assessment algorithm, the drug type and usage frequency of the drop-type drugs are obtained according to the task manager of the drop controller; the hygiene level corresponding to each independent storage partition is evaluated based on the drug type and usage frequency of the drop-type drugs; the multiple independent storage partitions in the mixed working module are traversed to determine the hygiene levels corresponding to the multiple independent storage partitions, and in the multiple independent storage partitions, a job scheduling algorithm is used to automatically arrange the operation plan of the cleaning subunit and the operation plan of the disinfection subunit; the hygiene status standard verification is performed through the hygiene levels corresponding to the multiple independent storage partitions, as well as the operation plan of the cleaning subunit and the operation plan of the disinfection subunit, and feedback control is performed through the hygiene status standard verification results.

[0021] In the mixing work module, in order to ensure the hygiene standards of the storage and mixing process of drop-type drugs, specifically, a risk assessment algorithm is used to conduct an in-depth analysis of the task manager in the drop controller; the drug types and corresponding usage frequencies of drop-type drugs are extracted from the task manager; different drug types and usage frequencies have different hygiene requirements for the storage environment, and a corresponding hygiene level is evaluated for each independent storage partition.

[0022] Traverse the independent storage partitions, check each independent storage partition in the mixed work module, and determine the hygiene level for each independent storage partition; according to the hygiene level, use the job scheduling algorithm to automatically arrange the operation plan of the cleaning subunit and the disinfection subunit; perform hygiene status standard verification to ensure that the hygiene status of each independent storage partition meets the preset standard, and perform feedback control based on the results of the hygiene status standard verification to make necessary adjustments to the cleaning and disinfection plans. In summary, in order to ensure the hygiene standards of the storage and mixing process of drop-type drugs in the mixed work module, it is necessary to obtain the type and frequency of use of drugs, evaluate the hygiene level, arrange cleaning and disinfection plans, and perform hygiene status standard verification and feedback control to ensure the quality and safety of drugs.

[0023] The mixing work sequence generation module M500 is used to generate a mixing work sequence based on the mixing work module and in comparison with the V microscale mixing channels corresponding to the built-in microfluidic mixing module. The operation instructions contained in the mixing work sequence are used to activate and control the V microscale mixing channels and execute the regulation of the drop release order, drop release speed and drop mixing time under U drop mixing windows.

[0024] The core task of the mixing work sequence generation module is to generate a mixing work sequence based on the specific configuration of the mixing work module and the V microscale mixing channels of the built-in microfluidic mixing module. The mixing work sequence is a collection of operation instructions, and its main function is to activate and accurately control these V microscale mixing channels. During the mixing process, the mixing work sequence generation module will ensure that the release order of the drops is strictly implemented, the release speed of the drops is accurately controlled, and the mixing time of the drops is accurately controlled under the U drop mixing windows, in order to ensure the uniformity and consistency of the drug mixing, thereby achieving the best mixing effect. Through the mixing work sequence generated by the above steps, the entire mixing process becomes highly automated and precise, which improves the mixing efficiency and makes the mixing process of drop drugs more reliable and stable.

[0025] The microfluidic mixing module M600 is used to introduce the drop mixing efficiency based on the mixing working sequence, and combine the first dosage standard and the second dosage standard to perform microfluidic mixing of the drop drug ratio on the mixing working module.

[0026] The microfluidic mixing module is a crucial component of the microfluidic system. It is responsible for precise microfluidic mixing of drop-type drugs in the mixing working module based on the mixing working sequence, combined with the drop mixing efficiency, the first dosage standard and the second dosage standard. The microfluidic mixing module achieves efficient mixing of drop-type drugs by precisely controlling the fluid flow in the microscale mixing channel. It integrates microfluidic technology and can complete complex fluid operations in a very small space, thereby ensuring the accuracy and consistency of drug proportioning.

[0027] The working principle of the microfluidic mixing module is as follows: specifically, the mixing work sequence generated by the mixing work sequence generation module M500 is received, and the mixing work sequence includes the operation instructions required to activate and control V micro-scale mixing channels, as well as detailed parameters of the drop release order, speed and mixing time; the drop mixing efficiency is introduced, and the mixing efficiency is affected by many factors, including the design of the microchannel, the physical properties of the fluid, and the operating conditions; by optimizing these factors, efficient drop mixing is ensured within the mixing window; the drop ratio is accurately controlled according to the first dosage standard (derived based on the user's basic information) and the second dosage standard (derived based on the drop concentration and the drop control parameter), which jointly ensures that the dosage of the mixed drug meets the safety requirements; after receiving all necessary instructions and parameters, V micro-scale mixing channels are activated and controlled, and the drop drug ratio and mixing can be completed under U drop mixing windows by accurately controlling the flow speed and direction of the fluid. The entire mixing process is highly automated and precise, ensuring the stability and repeatability of the mixing results.

[0028] Precisely control the flow speed and direction of the fluid, and further, precisely control the flow of the fluid at the micrometer scale, including flow rate, flow rate and direction, so as to achieve precise proportioning and mixing of drop-type drugs. The use of special microfluidic structure design, such as asymmetric fishbone-shaped protrusions, T-shaped or Y-shaped structures, can accelerate the mass transfer process and liquid mixing, improve the mixing efficiency, and ensure the consistency and quality stability of the mixing of drop-type drugs. The microfluidic mixing includes passive micromixing and active micromixing. Method 1: Passive micromixing relies on the geometric shape design in the microfluidic chip to achieve mixing. For example, by designing a complex microchannel structure (such as serpentine, spiral, etc.), the fluid is stretched, folded and split during the flow process, thereby increasing the contact area and promoting mixing. This method does not involve the input of external energy and has the advantage of simple structure. Method 2: Active micromixing achieves mixing through the action of external energy (such as sound waves, electric fields, magnetic fields, etc.). For example, a sound wave-driven micromixer uses the pressure fluctuations generated by sound waves in the fluid to stir the fluid and promote mixing. This method has the advantages of fast mixing speed and high efficiency.

[0029] Through the above steps, microfluidic technology can accurately control fluid flow at the micron scale, thereby achieving high-precision drug proportioning and mixing; by optimizing microchannel design and operating conditions, the drop mixing efficiency can be significantly improved and the mixing time can be shortened; microfluidic systems usually have a smaller volume and flow range, so the consumption of reagents and samples can be significantly reduced; microfluidic mixing modules can be easily integrated with other microfluidic components or systems to form a complete microfluidic system, which achieves efficient mixing and precise proportioning of drop-type drugs by precisely controlling the fluid flow in the microscale mixing channel.

[0030] Furthermore, if Figure 2 As shown, the microfluidic mixing module M600 is also used to perform the following method: Connect a user terminal and design a user interface for inputting the basic information of the user; use a rule-based reasoning algorithm to establish a user knowledge graph based on the basic information of the user, combined with allergy history and real-time health data; based on the user knowledge graph, use an adaptive control algorithm to optimize and adjust the adaptability of the ratio of drop-type medicines.

[0031] When microfluidic mixing of drop-type drugs is carried out, a connection is further established with the user terminal, which can be achieved through wired or wireless means to ensure real-time transmission and interaction of data; in order to facilitate users to enter basic information, it is necessary to design an intuitive and easy-to-use user interface, which should include input boxes, selection boxes and other controls so that users can easily enter key information such as weight and age; users enter basic information such as weight, age, etc. through the user interface, and this information is an important basis for subsequent drug mixing.

[0032] A rule-based reasoning algorithm is used to conduct a comprehensive analysis based on the basic information entered by the user, combined with multi-dimensional information such as allergy history and real-time health data. Based on the analysis results of the rule-based reasoning algorithm, the system builds a knowledge graph for the user, which fully reflects the user's physical condition, health needs, and potential risks of medication. When preparing medicines, the information in the user's knowledge graph will be fully considered to ensure that the drug ratio is highly matched with the user's actual needs. An adaptive control algorithm is used to dynamically adjust the ratio of drop-type drugs based on the real-time data in the user's knowledge graph. This adjustment is real-time and accurate, and can ensure that the drug ratio is always consistent with the user's physical condition. Through the continuous iteration and optimization of the adaptive control algorithm, the most suitable drug ratio scheme for the user is found, which takes into account both the efficacy of the drug and the individual differences of the user.

[0033] In summary, when performing microfluidic mixing of drop-type drug proportions in the mixing working module, a series of steps such as connecting the user terminal, designing the user interface, establishing the user knowledge graph, and using the adaptive control algorithm to optimize the fitness adjustment are implemented to achieve personalized, precise and intelligent drug proportions, thereby improving the efficacy and safety of drugs.

[0034] Furthermore, the microfluidic mixing module M600 is also used to perform the following method: Using data mining algorithms, the drop mixing efficiency is sorted from high to low, and historical drop mixing instances are extracted from historical mixing data; through the user knowledge graph, combined with a deep learning algorithm, the model is trained to predict the sensitivity of various types of drop drugs associated with the user's corresponding drug type; through the sensitivity of various types of drop drugs, the first dosage standard and the second dosage standard are continuously updated.

[0035] The adaptability optimization and adjustment of the ratio of drop-type drugs is based on the user knowledge graph and uses an adaptive control algorithm. Specifically, Select a suitable data mining algorithm to conduct an in-depth analysis of the historical mixing data; sort the historical mixing data based on the drop mixing efficiency from high to low; extract historical drop mixing instances with high drop mixing efficiency (for example, the top 20% of the sort) from the sorted historical data as the basis for subsequent analysis.

[0036] The rich information in the user knowledge graph, including the user's physical condition, medication history, etc., is used to provide input for the deep learning algorithm. Through the deep learning algorithm, the model is trained to predict the sensitivity of various types of drop drugs associated with the user's corresponding drug type, and understand the user's reaction to different drop drugs; the sensitivity of various types of drop drugs predicted by the deep learning model is deeply analyzed; according to the results of the drug sensitivity analysis, the first dosage standard and the second dosage standard are continuously updated, and the personalized needs of users are better met by continuously updating the dosage standards.

[0037] In summary, based on the user knowledge graph and using the adaptive control algorithm, the adaptation of the drop drug ratio is optimized and adjusted by extracting historical drop mixing instances, predicting drug sensitivity, and updating dosage standards, which helps to improve the accuracy of drug ratio and user satisfaction.

[0038] Furthermore, the microfluidic mixing module M600 is also used to perform the following method: A chemical reaction kinetic model is used to analyze the chemical reaction rate constant in the mixing process of the drop-type drug after the drop-type drug executes the drop release operation instruction under U drop-mixing windows; historical drop-mixing instances are extracted, and the mixing conditions are optimized in combination with the chemical reaction rate constant in the mixing process to find the optimal mixing condition parameters marked by the drug type, and the optimal mixing condition parameters are used to accelerate the chemical reaction of any type of drop-type drug marked with the corresponding drug type; based on the optimal mixing condition parameters marked by the drug type, the drop mixing efficiency is introduced in combination with the PID control algorithm to adjust the mixing working sequence.

[0039] In order to ensure the high efficiency and consistency of drop-type drugs in the mixing process, it is necessary to introduce the drop mixing efficiency based on the mixing work sequence. Specifically, the chemical reaction kinetics model is used to deeply understand the chemical reaction mechanism of drop-type drugs in the mixing process; under U drop mixing windows, the drop release is executed according to the drop release operation instructions in the mixing work sequence, and the chemical reaction rate constant is analyzed by monitoring various parameters in the mixing process. The chemical reaction rate constant reflects the speed of the chemical reaction.

[0040] Historical drop mixing examples are extracted from the historical mixing process as a reference for optimizing mixing conditions; historical drop mixing examples are combined with chemical reaction rate constants to more comprehensively understand the effects of different mixing conditions on chemical reactions; through comparison and analysis, the optimal mixing condition parameters that can accelerate the chemical reaction of any type of drop drug labeled with the corresponding drug type are found.

[0041] The drop mixing efficiency is taken as an important consideration and introduced into the adjustment of the mixing work sequence; the PID control algorithm is used to accurately control the mixing process to ensure the stability and consistency of the mixing conditions; based on the optimal mixing condition parameters marked by the drug type, necessary adjustments are made to the mixing work sequence to improve the efficiency and consistency of drop mixing.

[0042] In summary, by using the chemical reaction kinetics model to analyze the chemical reaction rate constants, extracting historical drop mixing examples to optimize the mixing conditions, introducing the drop mixing efficiency based on the optimal mixing condition parameters and combining the PID control algorithm to adjust the mixing working sequence, the efficiency and consistency of drop drugs in the mixing process can be effectively improved.

[0043] Furthermore, the drug precision mixing system based on intelligent proportioning is used to perform the following method: The Internet of Things communication protocol is used to start the synchronous monitoring unit to remotely monitor the mixing process of various types of drop-type drugs and obtain synchronous monitoring information. Based on the synchronous monitoring information and combined with the abnormality detection algorithm, abnormal situations in the mixing process are automatically identified, and an event-driven algorithm is used to perform microfluidic mixing initialization recovery of the drop-type drug ratio of the mixing working module based on the first dosage standard and the second dosage standard.

[0044] In order to ensure the smooth progress of the mixing process of drop-type drugs, realize remote monitoring and automatic identification and recovery of abnormal situations, specifically, select the Internet of Things communication protocol to ensure the real-time transmission of data and the realization of remote monitoring; through the Internet of Things communication protocol, start the synchronous monitoring unit to remotely monitor the mixing process of various types of drop-type drugs; the synchronous monitoring unit will transmit various data in the mixing process in real time, including temperature, pressure, flow, etc.; through the Internet of Things communication protocol, obtain various types of monitoring information transmitted by the synchronous monitoring unit for subsequent analysis and processing.

[0045] The synchronous monitoring information is combined with the anomaly detection algorithm to perform real-time analysis of the mixing process. The anomaly detection algorithm can automatically identify abnormal conditions in the mixing process, such as temperature abnormalities, pressure abnormalities, etc. Once an abnormal condition is identified, an event-driven algorithm will be used to trigger the corresponding recovery operation. Based on the first dosage standard and the second dosage standard, the mixing working module will be initialized and restored for the microfluidic mixing of the drop-type drug ratio to ensure the smooth progress of the mixing process.

[0046] In summary, by using the Internet of Things communication protocol to start the synchronous monitoring unit, obtain the synchronous monitoring information, automatically identify abnormal situations in combination with the anomaly detection algorithm, and use the event-driven algorithm to perform the microfluidic mixing initialization recovery of the drop-type drug ratio of the mixing working module according to the dosage standard, comprehensive monitoring of the drop-type drug mixing process and timely handling of abnormal situations can be achieved.

[0047] Furthermore, the drug precision mixing system based on intelligent proportioning is used to perform the following method: After completing the initialization and recovery of the microfluidic mixing, the drug files are added to the database; blockchain technology is used to perform distributed management of the drug files added to the database, and the compliance verification of the microfluidic mixing process of the drop-type drug ratio is automatically performed based on the first dosage standard and the second dosage standard.

[0048] After completing the microfluidic mixing initialization recovery, in order to ensure the security and compliance of the drug archives, specifically, after completing the microfluidic mixing initialization recovery, generate the corresponding drug archives, including drug type, production date, batch number, ratio information, etc.; add the generated drug archives to the database for subsequent management and query; select a suitable blockchain platform to establish distributed management of drug archives; synchronize the drug archives in the database to the blockchain network to realize distributed storage and management of drug archives; through the consensus mechanism of the blockchain, ensure the consistency and immutability of the drug archives.

[0049] Based on the first dosage standard and the second dosage standard, formulate compliance rules for the microfluidic mixing process of drop-type drug formulation; use smart contract technology to encode the compliance rules into automatically executable contract codes; when performing microfluidic mixing of drop-type drug formulations, trigger the smart contract to automatically perform compliance verification. Exemplarily, compliance verification is performed using public industry standards. Common ones include the "Technical Guidelines for Pharmaceutical Research of Generic Chemical Drug Solution Eye Drops" and the "Technical Guidelines for Research on Mixing Uniformity and Central Control Dose Unit Uniformity of Chemical Oral Solid Preparations (Trial)". The verification results will be recorded on the blockchain for subsequent audits and inquiries.

[0050] In summary, the safety and compliance of the microfluidic mixing process for drop-type drug formulations can be ensured by adding drug files to the database, using blockchain technology for distributed management, and performing compliance verification.

[0051] In summary, the beneficial effects of the embodiments of the present application are: 1. Through the intelligent proportioning system, the drug dosage can be automatically calculated and adjusted according to the user's individual information and drug characteristics to improve the accuracy of the proportioning. It integrates temperature sensors, viscosity sensors and other equipment, and combines machine learning prediction models to monitor and adjust the mixing environment in real time to ensure that the quality of drug mixing is not affected by environmental factors.

[0052] 2. Use chemical reaction kinetics models and PID control algorithms to optimize mixing conditions, speed up chemical reaction rates, build user knowledge graphs, and use adaptive control algorithms and deep learning technology to continuously learn and optimize the ratio scheme to better meet the specific needs of users.

[0053] 3. Through the synchronous monitoring unit and anomaly detection algorithm, the mixing process can be monitored in real time, and abnormal situations can be discovered and corrected in time. Combined with blockchain technology, it ensures that the data of the drug mixing process cannot be tampered with and meets compliance requirements.

[0054] 4. By using the chemical reaction kinetics model, the chemical reaction rate constants in the mixing process of drop-type drugs are analyzed after the drop-type drugs execute the drop-release operation instructions under U drop-mixing windows; historical drop-mixing examples are extracted, and the mixing conditions are optimized in combination with the chemical reaction rate constants in the mixing process to find the optimal mixing condition parameters marked by the drug type. The optimal mixing condition parameters are used to accelerate the chemical reaction of any type of drop-type drugs marked with the corresponding drug type; based on the optimal mixing condition parameters marked by the drug type, the drop-mixing efficiency is introduced and combined with the PID control algorithm to adjust the mixing work sequence. By using the chemical reaction kinetics model to analyze the chemical reaction rate constants, extracting historical drop-mixing examples to optimize the mixing conditions, introducing the drop-mixing efficiency based on the optimal mixing condition parameters and combining the PID control algorithm to adjust the mixing work sequence, the efficiency and consistency of the drop-type drugs in the mixing process are effectively improved.

[0055] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor, and no unnecessary restrictions are made here.

[0056] Furthermore, the above-mentioned technical scheme only reflects the preferred technical scheme of the technical scheme of the embodiment of the present application. Some changes that may be made to some parts thereof by technicians in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technicians in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. Precision drug mixing system based on intelligent proportioning, It is characterized in that The system comprises: A basic information download module is used to connect to the recipe storage manager and download user basic information, including weight and age; A first dosage standard module is configured, which is used to configure a first dosage standard based on the instructions for use of the drop-type medicine and the basic user information, wherein the first dosage standard is a dosage of the drop-type medicine obtained by proportional matching with the basic user information as a constraint; A second dosage standard module is configured to be connected to the drip controller, and a second dosage standard is configured by combining the drip volume corresponding to the drip control parameter and the concentration of the drip drug, wherein the second dosage standard is a drip drug dosage obtained by clustering and rounding iteratively with the concentration of the drip drug as a constraint; A partition storage module, used to start a mixing working module, the mixing working module includes a plurality of independent storage partitions, each independent storage partition is used to store a type of drop-type medicine, and the mixing working module is interactively connected with the drip controller; A mixing work sequence generation module is used to generate a mixing work sequence based on the mixing work module and in comparison with the V microscale mixing channels corresponding to the built-in microfluidic mixing module. The operation instructions contained in the mixing work sequence are used to activate and control the V microscale mixing channels and perform the regulation of the drop release sequence, the drop release speed, and the drop mixing time under U drop mixing windows; The microfluidic mixing module is used to introduce the drop mixing efficiency based on the mixing working sequence, and combine the first dosage standard and the second dosage standard to perform microfluidic mixing of the drop drug ratio on the mixing working module.

2. The precise drug mixing system based on intelligent proportioning as claimed in claim 1, It is characterized in that The mixing working module is subjected to microfluidic mixing of drop-type drug proportions, and the system further comprises: Connecting to a user terminal and designing a user interface, wherein the user interface is used to input basic information of the user; Using rule inference algorithms, based on the basic information of the user, combined with allergy history and real-time health data, a user knowledge graph is established; Based on the user knowledge graph, an adaptive control algorithm is used to optimize and adjust the adaptability of the drop-type drug ratio.

3. The precise drug mixing system based on intelligent proportioning as claimed in claim 2, It is characterized in that Connecting to the drip controller, configuring the second dosage standard by the drip volume corresponding to the drip control parameter and the concentration of the drip drug, the system includes: Connect the temperature sensor and viscosity sensor to collect the drip temperature monitoring data and the drip viscosity monitoring data; Based on the drip temperature monitoring data and the drip viscosity monitoring data, a machine learning prediction model is used to predict the changes in physical properties of drop-type drugs under different environmental conditions; Through fuzzy control logic, the drip controller is subjected to environmental adaptive control according to the changes in the physical properties of the drip-type medicine under different environmental conditions.

4. The precise drug mixing system based on intelligent proportioning as claimed in claim 3, It is characterized in that The mixing working module includes a plurality of independent storage partitions, each of which is used to store a type of drop-type medicine. The mixing working module is interactively connected with the drip controller. The system includes: Using a risk assessment algorithm, based on the task manager of the drip controller, the drug type and usage frequency of the drip drug are obtained; Evaluate the hygiene level corresponding to each independent storage partition based on the drug type and usage frequency of the drop-type drugs; Traversing multiple independent storage partitions in the hybrid working module, determining the hygiene levels corresponding to the multiple independent storage partitions, and automatically arranging the operation plan of the cleaning subunit and the operation plan of the disinfection subunit in the multiple independent storage partitions by using a job scheduling algorithm; The hygienic status standard verification is performed based on the hygienic levels corresponding to the multiple independent storage partitions, as well as the operation plan of the cleaning subunit and the operation plan of the disinfection subunit, and feedback control is performed based on the hygienic status standard verification results.

5. The precise drug mixing system based on intelligent proportioning as claimed in claim 4, It is characterized in that Based on the mixing working sequence, the drop mixing efficiency is introduced, and the system includes: Using a chemical reaction kinetic model, analyzing the chemical reaction rate constant during the mixing process of the drop-type drug after executing the drop-release operation instruction under U drop-mixing windows; Extract historical drop mixing examples, optimize the mixing conditions in combination with the chemical reaction rate constants during the mixing process, and find the optimal mixing condition parameters marked by the drug type, wherein the optimal mixing condition parameters are used to accelerate the chemical reaction of any type of drop drugs marked by the corresponding drug type; Based on the optimal mixing condition parameters marked by the drug type, the drop mixing efficiency is introduced in combination with the PID control algorithm to adjust the mixing work sequence.

6. The precise drug mixing system based on intelligent proportioning as claimed in claim 5, It is characterized in that Based on the user knowledge graph, an adaptive control algorithm is used to optimize and adjust the fitness of the drop-type drug ratio. The system includes: Using data mining algorithms, historical drop mixing instances are extracted from historical mixing data by sorting the drop mixing efficiency from high to low; Through the user knowledge graph and deep learning algorithm, the model is trained to predict the sensitivity of various types of drop drugs associated with the user's corresponding drug type; The first dosage standard and the second dosage standard are continuously updated based on the sensitivity of various types of drop-type drugs.

7. The precise drug mixing system based on intelligent proportioning as claimed in claim 1, It is characterized in that The system comprises: Using the Internet of Things communication protocol, the synchronous monitoring unit is started to remotely monitor the mixing process of various drop-type drugs and obtain synchronous monitoring information; Based on the synchronous monitoring information and combined with the abnormality detection algorithm, abnormal situations in the mixing process are automatically identified, and an event-driven algorithm is used to perform microfluidic mixing initialization recovery of the drop-type drug ratio of the mixing working module according to the first dosage standard and the second dosage standard.

8. The precise drug mixing system based on intelligent proportioning as claimed in claim 7, It is characterized in that The system comprises: After completing the initial recovery of microfluidic mixing, add the drug profile to the database; Blockchain technology is used to perform distributed management of drug files added to the database, and compliance verification of the microfluidic mixing process of drop-type drug proportions is automatically performed based on the first dosage standard and the second dosage standard.

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