Drug release system based on MEMS microfluidic anesthesia bomb

Abstract

The invention relates to the technical field of data regulation, and provides a drug release system based on an MEMS microfluidic anesthesia bomb, which solves the problem that the existing anesthesia bomb drug release system cannot timely discover the blockage of a drug release path, and comprises a data acquisition module, a model construction module, a data acquisition module, a drug release detection module, a detection result verification module and the like. Drug release task information is obtained and matched with a preset knowledge base, a random forest model is used for simulating the drug release process, drug release data is collected in real time and compared with a simulation result, the drug release path blockage situation is found and early warned in time, the drug release stability is improved, and the drug release efficiency is improved. The system can also verify whether the real-time drug release data exceeds the standard.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to a drug release system based on a MEMS microfluidic anesthetic bullet. Background Art

[0002] The microfluidic anesthetic bomb based on MEMS (MEMS stands for Micro-Electro-Mechanical System in English and Micro-Electro-Mechanical System in Chinese) is a medical device that integrates microfluidic chip technology. MEMS technology miniaturizes mechanical systems through semiconductor technology to form micro-electro-mechanical systems. Microfluidic technology uses this feature to construct functional components such as channels and reaction chambers that contain fluids at the micron scale, and manipulate the movement of micron-volume fluids in tiny spaces. The microfluidic anesthetic bomb based on MEMS integrates various functional units such as micro-reaction cells, micro-pumps, micro-valves, etc. through micro-machining technology to achieve precise control and release of anesthetic drugs.

[0003] The drug release process of the MEMS microfluidic anesthetic bullet is a controllable miniaturized process. The anesthetic drug is pre-loaded into the micro-liquid storage chamber in the microfluidic chip. The micropump and microvalve system driven by MEMS technology can accurately control the flow path and release rate of the drug according to the preset program or external instructions. The drug flows in the microchannel on demand and is finally accurately delivered to the target area in a trace, continuous or pulsed manner through a micro nozzle or release hole, realizing the timed, quantitative and fixed-point release of the anesthetic drug.

[0004] The drug release system based on MEMS microfluidic anesthetic bullets has the following technical pain points in actual use. Under complex and changeable physiological environments, biological contamination and blockage may occur in the drug release path of the anesthetic bullet. The existing drug release system of the anesthetic bullet cannot detect the blockage of the drug release path of the anesthetic bullet in time through effective data analysis, resulting in reduced safety of the drug release system of the anesthetic bullet. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a drug release system based on a MEMS microfluidic anesthetic bullet, which solves the problem that the existing drug release system of the anesthetic bullet cannot timely detect the blockage of the drug release path of the anesthetic bullet through effective data analysis.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: The present invention provides a drug release system based on a MEMS microfluidic anesthetic bullet, comprising: The data acquisition module is used to acquire drug release task information, match the drug release task information with a preset drug knowledge base of the anesthetic bomb, and obtain drug standard information of the anesthetic bomb, wherein the drug standard information of the anesthetic bomb includes drug standard concentration, drug standard flow rate, and drug standard release rate; A model building module is used to obtain historical data of the drug release system of the anesthetic bullet, train a random forest model using the historical data of the drug release system of the anesthetic bullet, and obtain a drug release simulation model of the anesthetic bullet; A data acquisition module is used to send drug release task information to the drug release terminal of the anesthetic bomb, and collect real-time drug release data when the drug release terminal of the anesthetic bomb performs the drug release task. The real-time drug release data includes real-time drug concentration, fluid flow rate in the real-time biochip microchannel, temperature difference between the real-time internal and external environments of the real-time biochip, real-time drug release rate, pressure distribution at different positions in the real-time microchannel, real-time drug molecular diffusion coefficient, pH value of the real-time internal and external environments of the real-time biochip, real-time ion concentration change value, real-time drug diffusion area, real-time drug effect value, and real-time change value of simulated biological hormones in the experimental environment; The drug release detection module is used to substitute the drug release task information into the drug release simulation model of the anesthetic bullet and output the drug release simulation results of the anesthetic bullet. The drug release simulation results of the anesthetic bullet include the drug simulation concentration, the fluid flow rate in the simulated biochip microchannel, the simulated temperature difference between the internal and external environments of the biochip, the drug release simulation rate, the pressure distribution at different positions in the simulated microchannel, the simulated drug molecular diffusion coefficient, the simulated pH value of the internal and external environments of the biochip, the simulated ion concentration change value, the simulated drug diffusion area, the simulated drug effect value and the simulated biological hormone simulation change value in the experimental environment. The drug release simulation results of the anesthetic bullet are compared with the real-time drug release data to obtain the drug release simulation results of the anesthetic bullet. The simulation result is compared with the real-time drug release data, and the comparison result includes whether the comparison result is within a preset error range and whether the comparison result is not within the preset error range. If the comparison result is within the preset error range, the real-time drug release data is transmitted to the detection result verification unit. If the comparison result is not within the preset error range, a drug release path detection task is generated, and the drug release path detection task is sent to the drug release terminal of the anesthetic bomb to obtain the drug release path detection result. The drug release path detection result is matched in a preset drug path detection result knowledge base to obtain the drug release path detection analysis result. The drug release path detection analysis result includes whether the drug release path is blocked and whether the drug release path is not blocked. When the drug release path is blocked, drug release path blockage warning information is generated; The test result verification unit is used to compare the real-time drug release data with the drug standard information of the anesthetic bullet. If the real-time drug release data exceeds the drug standard information of the anesthetic bullet in the comparison result of the real-time drug release data and the drug standard information of the anesthetic bullet, a drug release exceeding standard warning information is generated.

[0007] Furthermore, in the flow regulating system of the anesthetic bomb of the present invention, the data acquisition module is also used for: The drug release task information is parsed to obtain the parsed drug release task information, which includes: drug name, drug type, expected drug standard concentration, expected drug release rate, expected fluid flow rate, expected temperature difference between the internal and external environments of the biochip, expected pH value of the internal and external environments of the biochip, range of changes in simulated biological hormones in the experimental environment, expected pressure distribution at different positions in the microchannel, expected range of drug molecule diffusion coefficient, expected range of changes in ion concentration, expected drug diffusion area, and expected drug effect value.

[0008] Furthermore, in the flow regulating system of the anesthetic bomb of the present invention, the model building module is also used for: The historical data of the drug release system of the anesthetic bomb is extracted to obtain the characteristics of the drug release process. The characteristics of the drug release process include drug concentration characteristics, flow rate characteristics, temperature difference characteristics, pressure distribution characteristics, pH value characteristics and ion concentration characteristics. The drug release process characteristics are used as the input of the model. Initialize the random forest model parameters, including learning rate, number of iterations, and random seed; The characteristics of the drug release process were input into the selected random forest model, and the model parameters were adjusted by the gradient descent algorithm to minimize the prediction error, thus obtaining the drug release simulation model of the anesthetic bullet.

[0009] Furthermore, in the flow regulating system of the anesthetic bomb of the present invention, the data acquisition module is also used for: The drug release task information is sent to the drug release terminal of the anesthetic bomb, and the concentration change of the drug during the release process is monitored in real time by chemical sensors. The real-time flow rate of the fluid in the microchannel is measured by a flow meter or a flow sensor. The real-time temperature of the internal and external environments of the biochip is measured by a temperature sensor, and the temperature difference is calculated. The drug release rate is calculated in real time by monitoring the working status of the drug release device. The pressure sensor is used to measure the pressure at different positions of the microchannel to obtain a real-time pressure distribution diagram. By observing the diffusion behavior of drug molecules in the medium, the diffusion coefficient is calculated in real time using a diffusion model. The pH sensor is used to monitor the pH value of the internal and external environments of the biochip in real time. The concentration change of ions in the solution is monitored in real time by an ion selective electrode or an ion chromatograph. The diffusion area of ​​the drug in the medium is measured in real time by image processing technology or direct observation. The real-time effect of the drug on the experimental subject is monitored by biosensors or physiological indicators.

[0010] Furthermore, the flow regulating system of the anesthetic bomb of the present invention, the drug release detection module is also used for: Receive drug release task information from the data acquisition module, parse the drug release task information, extract drug release task parameters, and obtain drug type, concentration requirements, release rate, and environmental conditions; Load the pre-trained anesthetic bullet drug release simulation model, initialize the model parameters, substitute the parsed drug release task information as input parameters into the simulation model, and receive and set the model's boundary conditions and initial conditions; Start the drug release simulation model of the anesthetic bullet and begin to simulate the drug release process; The drug release simulation model of the anesthetic bullet calculates and outputs the simulation results of the drug release process based on the input parameters and internal algorithms; Simulation results of drug release process, including: Drug simulation concentration: simulated drug concentration changes during the release process; Simulate the flow rate of the fluid in the microchannel of the biochip: simulate the flow rate distribution of the fluid in the microchannel; Simulate the temperature difference between the inside and outside of the biochip: simulate the temperature difference between the inside and outside of the biochip; Drug release simulation rate: the simulated drug release rate changes over time; Simulate the pressure distribution at different positions in the microchannel: the pressure value of each point in the microchannel obtained by simulation; Simulated drug molecule diffusion coefficient: simulated diffusion coefficient of drug molecules in the medium; Simulate the pH value of the internal and external environment of the biochip: simulate the pH value of the internal and external environment of the biochip; Simulated ion concentration change value: the concentration change of ions in the simulated solution; Simulated drug diffusion area: the simulated drug diffusion area in the medium; Simulated drug effect value: the expected effect of the drug on the experimental subject predicted according to the simulated conditions; Simulated changes in biohormones in the experimental environment: If the model contains this function, the simulated changes in biohormones are obtained.

[0011] Furthermore, the flow regulating system of the anesthetic bomb of the present invention, the drug release detection module is also used for: The drug release simulation result and the real-time drug release data of the anesthetic bullet are aligned based on time, so as to obtain the aligned drug release simulation result and the real-time drug release data of the anesthetic bullet; The drug release simulation results of the aligned anesthetic bullet and each index in the real-time drug release data are used to calculate the error between the simulation results and the real-time data; The error between the simulation result and the real-time data includes absolute error and relative error. The absolute error is the difference between the simulation value and the real-time value, and the relative error is the difference between the simulation value and the real-time value divided by the real-time value. Compare the calculated error with a preset error range, where the preset error range is a pre-accepted error range; If the errors of all indicators are within the preset error range, the comparison result is judged to be within the preset error range; If the error of any one or more indicators exceeds the preset error range, the comparison result is judged to be outside the preset error range; If the comparison result is within the preset error range, the simulation result is consistent with the real-time data, and the real-time drug release data is transmitted to the test result verification unit; If the comparison result is not within the preset error range, there is a difference between the simulation result and the real-time data.

[0012] Furthermore, the flow regulating system of the anesthetic bomb of the present invention, the drug release detection module is also used for: Comparing the drug release simulation result of the anesthetic bullet with the real-time drug release data, an error index comparison result is obtained, and the error index comparison result includes an index of an error exceeding a preset range; Based on the comparison results of the error indicators, matching is performed in the preset knowledge base of generated drug release paths, and the indicators whose errors exceed the preset range are used as the matching basis to obtain the drug release path detection task; The drug release path detection task includes the specific path to be detected and the expected detection indicators; Encapsulate the information of the drug release path detection task into a standard task instruction, which includes the detection path, detection index and detection time, send the encapsulated task instruction to the drug release terminal of the anesthetic bomb, monitor the execution of the task instruction by the drug release terminal, and receive the detection result of the drug release path from the drug release terminal, which should include the flow rate, pressure and temperature on the detection path; The received test results are matched with a preset drug path test result knowledge base, and based on the matching results, it is determined whether the drug release path is blocked.

[0013] Beneficial effects of the present invention: The present invention matches the drug release task information with the preset drug knowledge base through the data acquisition module, obtains the drug standard information, and obtains the concentration, flow rate and rate of drug release parameters that meet the standard requirements. The drug release simulation model constructed using the random forest model can predict the changes in various parameters during the drug release process and improve the prediction accuracy of drug release.

[0014] Data from the drug release process is collected in real time, and compared with the simulation results through the drug release detection module to promptly detect and correct deviations. If the drug release path is found to be blocked, the system will generate an early warning message to remind the user or system administrator to take appropriate measures to avoid potential safety issues. The high-precision sensors and advanced monitoring technology of the data acquisition module can continuously optimize the drug release strategy and improve the stability and consistency of drug release through comparative verification of simulation and real-time data. The system can automatically record and analyze historical data during the drug release process to provide data support for subsequent model training and optimization. Through intelligent data analysis and management, the system can continuously learn and improve the efficiency of drug release.

[0015] In summary, the drug release system based on MEMS microfluidic anesthetic bullets has brought significant progress to the medical field by improving the accuracy of drug release, enhancing the safety of the system, improving the reliability of the system, supporting intelligent management and optimization, and promoting the development of medical technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0017] Figure 1 A schematic diagram of a unit module of a drug release system based on a MEMS microfluidic anesthetic bomb provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0019] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0020] The present invention provides a drug release system based on a MEMS microfluidic anesthetic bullet, comprising: The data acquisition module is used to acquire drug release task information, match the drug release task information with a preset drug knowledge base of the anesthetic bomb, and obtain drug standard information of the anesthetic bomb, wherein the drug standard information of the anesthetic bomb includes drug standard concentration, drug standard flow rate, and drug standard release rate; The data acquisition module is responsible for acquiring the drug release task information and matching it with the preset anesthetic bullet drug knowledge base to obtain the drug standard information of the anesthetic bullet.

[0021] The data acquisition module first receives drug release task information from the user or the system, which usually includes the drug name, drug type, expected drug concentration, expected drug release rate, expected fluid flow rate, expected temperature difference between the internal and external environments of the biochip, pH value, range of changes in simulated biological hormones in the experimental environment, expected pressure distribution at different positions in the microchannel, expected range of drug molecule diffusion coefficient, expected range of changes in ion concentration, expected drug diffusion area, and expected drug effect value, etc.

[0022] The data acquisition module matches the drug release task information with the preset anesthetic bullet drug knowledge base. The drug knowledge base is a pre-built and stored database that contains standard information of various anesthetic bullet drugs, such as standard drug concentration, standard drug flow rate, standard drug release rate, etc.

[0023] Through the matching process, the data acquisition module can extract the drug standard information corresponding to the current drug release task. The standard information provides an important reference for subsequent model construction, data collection, drug release detection and test result verification.

[0024] Drug standard information includes but is not limited to the following parameters: Standard drug concentration: refers to the standard concentration value that the anesthetic bullet should reach when releasing the drug.

[0025] Standard drug flow rate: refers to the standard flow rate of the drug in the anesthetic bullet during the release process.

[0026] Standard drug release rate: refers to the standard rate of release of anesthetic drugs, usually measured by the amount of drug released per unit time.

[0027] The data acquisition module provides accurate drug standard information for the entire drug release system by acquiring and matching drug release task information. By comparing real-time drug release data with drug standard information, the system can promptly detect and correct deviations, thereby avoiding problems such as blockage of the drug release path.

[0028] A model building module is used to obtain historical data of the drug release system of the anesthetic bullet, train a random forest model using the historical data of the drug release system of the anesthetic bullet, and obtain a drug release simulation model of the anesthetic bullet; The model building module is responsible for obtaining the historical data of the drug release system of the anesthetic bullet and using the data to train the random forest model to obtain the drug release simulation model of the anesthetic bullet. The drug release simulation model of the anesthetic bullet can predict and simulate various parameters and states in the drug release process.

[0029] The drug release simulation model of the anesthetic bullet first collects the historical data of the anesthetic bullet drug release system. The historical data of the anesthetic bullet drug release system includes various parameters and state information in the previous drug release process, such as drug concentration, flow rate, temperature difference, pressure distribution, pH value, ion concentration change value, etc.

[0030] The model building module extracts features from historical data to identify characteristic variables that are closely related to the drug release process. Characteristic variables usually include drug concentration features, flow rate features, temperature difference features, pressure distribution features, pH value features, and ion concentration features.

[0031] Initialize the parameters of the random forest model: Before building the model, you need to initialize the parameters of the random forest model. Parameters include learning rate, number of iterations, and random seed, which have an important impact on the training process and final performance of the model.

[0032] Training the random forest model: Using the extracted drug release process features as input, historical data is input into the random forest model for training. The model performance is gradually optimized by continuously adjusting the model parameters (e.g., using the gradient descent algorithm) with the goal of minimizing the prediction error.

[0033] Obtaining a simulation model for drug release from anesthesia bullets: After sufficient training, the model building module will obtain a stable simulation model for drug release from anesthesia bullets. This model can accurately simulate and predict various parameters and states in the drug release process.

[0034] The random forest model improves prediction accuracy by integrating multiple decision trees and is able to handle complex nonlinear relationships.

[0035] The random forest model has a good tolerance to noise and outliers and is not prone to overfitting. Although the random forest model is a black box model, the impact of each feature on the prediction result can be evaluated through indicators such as feature importance.

[0036] The model building module provides powerful prediction and simulation capabilities for the entire drug release system by building a simulation model for drug release from anesthetic bullets. This enables the system to more accurately predict various parameters and states in the drug release process, thereby promptly discovering and correcting deviations and improving the stability of drug release.

[0037] A data acquisition module is used to send drug release task information to the drug release terminal of the anesthetic bomb, and collect real-time drug release data when the drug release terminal of the anesthetic bomb performs the drug release task. The real-time drug release data includes real-time drug concentration, fluid flow rate in the real-time biochip microchannel, temperature difference between the real-time internal and external environments of the real-time biochip, real-time drug release rate, pressure distribution at different positions in the real-time microchannel, real-time drug molecular diffusion coefficient, pH value of the real-time internal and external environments of the real-time biochip, real-time ion concentration change value, real-time drug diffusion area, real-time drug effect value, and real-time change value of simulated biological hormones in the experimental environment; The data acquisition module is responsible for sending the drug release task information to the drug release terminal of the anesthetic bullet, and collecting various data of the terminal in real time when performing the drug release task.

[0038] Sending drug release task information: The data acquisition module first receives drug release task information from the system or user, which describes in detail the type, concentration, rate and other relevant parameters of the drug to be released. The data acquisition module sends the information to the drug release terminal of the anesthetic bomb to guide it to perform specific drug release operations.

[0039] During the process of the anesthetic bullet drug release terminal performing the drug release task, the data acquisition module begins to collect various data in real time, including but not limited to: Real-time drug concentration: Real-time monitoring of drug concentration changes during the release process through chemical sensors.

[0040] Real-time flow rate of fluid in biochip microchannels: Use a flow meter or flow sensor to measure the real-time flow rate of fluid in microchannels.

[0041] Real-time temperature difference between the inside and outside of the biochip: Use a temperature sensor to measure the real-time temperature of the inside and outside of the biochip and calculate the temperature difference.

[0042] Real-time drug release rate: By monitoring the working status of the drug release device, the drug release rate can be calculated in real time.

[0043] Real-time pressure distribution at different locations in the microchannel: Use a pressure sensor to measure the pressure at different locations in the microchannel to obtain a real-time pressure distribution diagram.

[0044] Real-time drug molecule diffusion coefficient: By observing the diffusion behavior of drug molecules in the medium, the diffusion coefficient is calculated in real time using the diffusion model.

[0045] Real-time pH value of the environment inside and outside the biochip: Use a pH sensor to monitor the pH value of the environment inside and outside the biochip in real time.

[0046] Real-time ion concentration change value: Real-time monitoring of ion concentration changes in the solution through ion selective electrodes or ion chromatographs.

[0047] Real-time drug diffusion area: Real-time measurement of the drug diffusion area in the medium through image processing technology or direct observation.

[0048] Real-time drug effect value: monitor the real-time effect of drugs on experimental subjects through biosensors or physiological indicators.

[0049] Real-time change values ​​of simulated biological hormones in the experimental environment: If the experimental environment contains settings for simulating changes in biological hormones, their change values ​​are monitored in real time.

[0050] The data acquisition module provides a solid foundation for subsequent simulation, testing and verification by collecting various data during the release process of anesthetic bullets in real time and accurately. It not only helps the system to control the drug release process more accurately, but also can promptly detect and correct possible deviation problems, such as blockage of the drug release path.

[0051] The drug release detection module is used to substitute the drug release task information into the drug release simulation model of the anesthetic bullet and output the drug release simulation results of the anesthetic bullet. The drug release simulation results of the anesthetic bullet include the drug simulation concentration, the fluid flow rate in the simulated biochip microchannel, the simulated temperature difference between the internal and external environments of the biochip, the drug release simulation rate, the pressure distribution at different positions in the simulated microchannel, the simulated drug molecular diffusion coefficient, the simulated pH value of the internal and external environments of the biochip, the simulated ion concentration change value, the simulated drug diffusion area, the simulated drug effect value and the simulated biological hormone simulation change value in the experimental environment. The drug release simulation results of the anesthetic bullet are compared with the real-time drug release data to obtain the drug release simulation results of the anesthetic bullet. The simulation result is compared with the real-time drug release data, and the comparison result includes whether the comparison result is within a preset error range and whether the comparison result is not within the preset error range. If the comparison result is within the preset error range, the real-time drug release data is transmitted to the detection result verification unit. If the comparison result is not within the preset error range, a drug release path detection task is generated, and the drug release path detection task is sent to the drug release terminal of the anesthetic bomb to obtain the drug release path detection result. The drug release path detection result is matched in a preset drug path detection result knowledge base to obtain the drug release path detection analysis result. The drug release path detection analysis result includes whether the drug release path is blocked and whether the drug release path is not blocked. When the drug release path is blocked, drug release path blockage warning information is generated; The drug release detection module is a component of the present invention, which is responsible for substituting the drug release task information into the drug release simulation model of the anesthetic bomb, outputting the simulation results, and comparing the simulation results with the real-time drug release data to determine whether the drug release process is normal. The following are the specific functions and operation procedures of the drug release detection module: The main function of the drug release detection module is to substitute the drug release task information into the pre-trained anesthetic bullet drug release simulation model, and obtain the simulation results of drug release through model calculation. Then, the simulation results are compared with the real-time collected drug release data, the difference between the two is analyzed, and the comparison results are used to determine whether there is a blockage in the drug release path.

[0052] The information is substituted into the drug release simulation model of the anesthetic bomb. The model calculates and outputs the simulation results of drug release according to the input task information and internal algorithms. The simulation results include drug simulation concentration, fluid flow rate in the simulated biochip microchannel, simulated temperature difference between the internal and external environments of the biochip, drug release simulation rate, pressure distribution at different positions in the simulated microchannel, simulated drug molecular diffusion coefficient, simulated pH value of the internal and external environments of the biochip, simulated ion concentration change value, simulated drug diffusion area, simulated drug effect value, and simulated biological hormone simulation change value in the experimental environment.

[0053] The drug release detection module simultaneously receives the real-time drug release data from the data acquisition module, and compares the simulation results with the real-time data, and the content of the comparison includes the real-time data items corresponding to all the above simulation results.

[0054] The comparison results are divided into two situations: the comparison results are within the preset error range and the comparison results are not within the preset error range. The preset error range is set in advance according to system requirements and actual application scenarios to determine whether the deviation between the simulation results and the actual data is within an acceptable range.

[0055] If the comparison result is within the preset error range, it means that the simulation result is consistent with the real-time data and the drug release process is normal. At this time, the drug release detection module transmits the real-time drug release data to the detection result verification unit for further verification.

[0056] If the comparison result is not within the preset error range, it means that there is a difference between the simulation result and the real-time data, and there may be problems such as drug release path blockage. At this time, the drug release detection module will generate a drug release path detection task.

[0057] The drug release detection task includes information such as the specific detection path and the expected detection indicators.

[0058] The mission information is encapsulated into standard mission instructions and sent to the drug release terminal of the anesthetic bullet.

[0059] Monitor the execution of task instructions by the drug release terminal and receive the detection results of the drug release path from the terminal.

[0060] Analyze the test results and generate warning information: The received test results are matched and analyzed with the preset drug pathway test result knowledge base.

[0061] Based on the matching results, determine whether there are problems such as blockage in the drug release path.

[0062] If there is a blockage problem, an early warning message of drug release path blockage will be generated, and relevant personnel will be notified in time to handle it.

[0063] By comparing simulation results with real-time data, the drug release detection module can promptly identify possible problems in the drug release process, such as blockage of the drug release path, etc., which helps to improve the safety of the drug release system and enable the drug to be accurately delivered to the target area in the predetermined manner and dosage, thereby achieving better therapeutic effects. At the same time, the module can also provide data support for further optimization and improvement of the system.

[0064] The test result verification unit is used to compare the real-time drug release data with the drug standard information of the anesthetic bullet. If the real-time drug release data exceeds the drug standard information of the anesthetic bullet in the comparison result of the real-time drug release data and the drug standard information of the anesthetic bullet, a drug release exceeding standard warning information is generated.

[0065] The test result verification unit is responsible for comparing and verifying the real-time collected drug release data with the preset anesthetic bullet drug standard information. If it is found that the real-time data exceeds the range specified by the standard information, the system will automatically generate a drug release excess warning information to prompt the operator or the system to automatically take corresponding measures.

[0066] The test result verification unit first receives the real-time drug release data from the data acquisition module, including multiple indicators such as real-time drug concentration, real-time fluid flow rate in the microchannel of the biochip, real-time temperature difference between the inside and outside of the biochip, and real-time drug release rate.

[0067] Next, the test result verification unit will obtain the drug standard information corresponding to the current drug release task from the preset anesthetic bullet drug knowledge base. The standard information usually includes the drug standard concentration, drug standard flow rate, drug standard release rate, etc.

[0068] The real-time drug release data is compared with the standard information of the anesthetic bullet one by one. During the comparison process, the system will check whether each indicator is within the range specified by the standard information.

[0069] If any real-time drug release data is found to exceed the corresponding drug standard information, the test result verification unit will determine that the drug release exceeds the standard.

[0070] In this case, the system will automatically generate an early warning message for drug release exceeding the limit. This early warning message will clearly indicate which indicators have exceeded the limit and the degree of the exceedance, so that the operator can quickly understand the problem and take appropriate corrective measures.

[0071] The setting of the test result verification unit improves the stability of the drug release process. Through real-time comparison and verification, the system can promptly detect and warn of potential over-standard conditions, thereby avoiding the risks that may be caused by improper drug release. This is of great significance for improving the reliability of medical equipment and ensuring the safety of patients. At the same time, the unit also provides strong data support for the continuous optimization and improvement of the system.

[0072] Specifically, the flow regulation system of the anesthetic bomb of the present invention, the data acquisition module is also used for: The drug release task information is parsed to obtain the parsed drug release task information, which includes: drug name, drug type, expected drug standard concentration, expected drug release rate, expected fluid flow rate, expected temperature difference between the internal and external environments of the biochip, expected pH value of the internal and external environments of the biochip, range of changes in simulated biological hormones in the experimental environment, expected pressure distribution at different positions in the microchannel, expected range of drug molecule diffusion coefficient, expected range of changes in ion concentration, expected drug diffusion area, and expected drug effect value.

[0073] The data acquisition module comprehensively analyzes the received drug release task information and extracts more detailed and specific parameters so that subsequent modules can perform related operations more accurately.

[0074] The data acquisition module first receives the drug release task information from the user or the system upper module, which usually exists in a structured or unstructured form and contains the basic instructions required to perform the drug release task.

[0075] Next, the data acquisition module will conduct in-depth analysis of the received task information. This analysis process aims to convert the task information into a format that can be understood and processed by the system.

[0076] During the parsing process, the data acquisition module extracts the following parameters: Drug Name: Clearly indicate the type of drug to be released.

[0077] Drug type: describes the chemical or biological classification of a drug, which helps the system understand the characteristics of the drug.

[0078] Desired drug concentration: Set the target concentration range that should be maintained during drug release.

[0079] Expected Drug Release Rate: Specifies the speed or rate at which the drug is released from the anesthetic cartridge.

[0080] Expected fluid flow rate: The velocity that the fluid flowing in the microchannel should reach.

[0081] Expected temperature difference between the inside and outside environment of the biochip: Set the ideal temperature difference between the inside and outside environment of the biochip.

[0082] Expected pH value of the environment inside and outside the biochip: Specifies the pH range of the environment inside and outside the biochip.

[0083] Range of simulated biohormone variation in experimental settings: The expected range of variation of biohormones under simulated experimental conditions.

[0084] Expected pressure distribution at different locations in the microchannel: Expected pressure distribution at different locations in the microchannel.

[0085] Expected range of drug molecule diffusion coefficients: The expected range of rates or coefficients for drug molecules to diffuse in a medium.

[0086] Expected range of variation in ion concentration: The expected range of variation in ion concentration in a solution.

[0087] Expected drug diffusion area: The area over which the drug is expected to diffuse in the medium.

[0088] Expected drug effect value: the effect or degree of action that a drug is expected to produce on the experimental subjects.

[0089] Through in-depth analysis of drug release task information, the data acquisition module provides the system with more detailed and comprehensive parameter support. The parameters not only help the system to simulate the drug release process more accurately, but also provide important references for subsequent data collection, model building, and test result verification. At the same time, this also improves the flexibility and adaptability of the system, enabling it to cope with drug release tasks of different types and specifications.

[0090] Specifically, in the flow regulating system of the anesthetic bomb of the present invention, the model building module is also used for: The historical data of the drug release system of the anesthetic bomb is extracted to obtain the characteristics of the drug release process. The characteristics of the drug release process include drug concentration characteristics, flow rate characteristics, temperature difference characteristics, pressure distribution characteristics, pH value characteristics and ion concentration characteristics. The drug release process characteristics are used as the input of the model. Initialize the random forest model parameters, including learning rate, number of iterations, and random seed; The characteristics of the drug release process were input into the selected random forest model, and the model parameters were adjusted by the gradient descent algorithm to minimize the prediction error, thus obtaining the drug release simulation model of the anesthetic bullet.

[0091] In the drug release system based on MEMS microfluidic anesthetic bullet, it is responsible for using historical data to train and optimize the drug release simulation model. The following is a detailed description of the specific functions and operations of the model building module: The model building module is mainly responsible for extracting features from the historical data of the drug release system of the anesthetic bullet, and using the features to build and train the random forest model to achieve accurate simulation of the drug release process.

[0092] Feature extraction: The model building module will conduct an in-depth analysis of the historical data of the drug release system of the anesthetic bomb and extract the features that are closely related to the drug release process. Features include but are not limited to drug concentration features, flow rate features, temperature difference features, pressure distribution features, pH value features, and ion concentration features.

[0093] The extracted features are designed to comprehensively reflect the various physical, chemical, and biological changes during drug release and provide rich input information for the construction of subsequent models.

[0094] Model initialization: The model building module initializes the parameters of the random forest model. Parameters are crucial to the performance of the model, including learning rate, number of iterations, and random seed. The learning rate determines the step size of the model parameter update during training, the number of iterations controls the number of rounds of model training, and the random seed is used to ensure the repeatability of model training.

[0095] Model training: The extracted drug release process features were used as input into the selected random forest model.

[0096] Through optimization methods such as gradient descent algorithm, the model parameters are continuously adjusted to minimize the prediction error and train the model. After multiple iterations and optimizations, a simulation model of anesthetic bullet drug release that can accurately simulate the drug release process is finally obtained.

[0097] The operation of the model building module is of great significance to improving the safety of the drug release system. By using historical data to train and optimize the model, the system can more accurately predict various changes in the drug release process, thereby providing more precise guidance for subsequent drug release tasks.

[0098] Specifically, the flow regulation system of the anesthetic bomb of the present invention, the data acquisition module is also used for: The drug release task information is sent to the drug release terminal of the anesthetic bomb, and the concentration change of the drug during the release process is monitored in real time by chemical sensors. The real-time flow rate of the fluid in the microchannel is measured by a flow meter or a flow sensor. The real-time temperature of the internal and external environments of the biochip is measured by a temperature sensor, and the temperature difference is calculated. The drug release rate is calculated in real time by monitoring the working status of the drug release device. The pressure sensor is used to measure the pressure at different positions of the microchannel to obtain a real-time pressure distribution diagram. By observing the diffusion behavior of drug molecules in the medium, the diffusion coefficient is calculated in real time using a diffusion model. The pH sensor is used to monitor the pH value of the internal and external environments of the biochip in real time. The concentration change of ions in the solution is monitored in real time by an ion selective electrode or an ion chromatograph. The diffusion area of ​​the drug in the medium is measured in real time by image processing technology or direct observation. The real-time effect of the drug on the experimental subject is monitored by biosensors or physiological indicators.

[0099] In the drug release system based on MEMS microfluidic anesthetic bullet, it is responsible for sending the drug release task information to the drug release terminal of the anesthetic bullet, and also undertakes the task of real-time collection and monitoring of various data. The following is a description of the detailed functions of the data acquisition module: The data acquisition module integrates a variety of high-precision sensors and advanced monitoring technologies to collect various data in the process of drug release from anesthetic bullets in real time, including but not limited to drug concentration, fluid flow rate, ambient temperature, drug release rate, pressure distribution, drug molecular diffusion coefficient, pH value, ion concentration, drug diffusion area, and drug effect, etc. The data provides a solid foundation for precise control of the system and subsequent analysis.

[0100] Sending drug release task information, the data acquisition module first receives the drug release task information from other modules of the system, and sends the information to the drug release terminal of the anesthetic bomb to guide the terminal to perform specific drug release operations.

[0101] Real-time monitoring of drug concentration: Chemical sensors are used to monitor drug concentration changes during the release process in real time to ensure that the drug can be released at the predetermined concentration.

[0102] Measuring fluid flow rate: Use a flow meter or flow sensor to accurately measure the real-time flow rate of the fluid in the microchannel to monitor the speed and stability of drug flow.

[0103] Monitor ambient temperature and calculate temperature difference: Use temperature sensors to measure the real-time temperature of the environment inside and outside the biochip and calculate the temperature difference to evaluate the impact of ambient temperature on the drug release process.

[0104] Calculate drug release rate: By monitoring the working status of the drug release device, calculate the drug release rate in real time to ensure that the drug can be released at the predetermined rate.

[0105] Measuring pressure distribution: Use pressure sensors to measure pressure at different locations in the microchannel to obtain real-time pressure distribution maps to monitor pressure changes during drug flow.

[0106] Calculate the diffusion coefficient of drug molecules: By observing the diffusion behavior of drug molecules in the medium, the diffusion coefficient is calculated in real time using the diffusion model to evaluate the diffusion ability and stability of the drug.

[0107] Monitor pH value: Use pH sensor to monitor the pH value inside and outside the biochip in real time to ensure that the drug is released within the appropriate pH range.

[0108] Monitoring changes in ion concentration: The concentration changes of ions in the solution can be monitored in real time by ion selective electrodes or ion chromatographs to evaluate the changes in ion balance during drug release.

[0109] Measuring drug diffusion area: Through image processing technology or direct observation, the drug diffusion area in the medium is measured in real time to evaluate the drug coverage and release effect.

[0110] Monitoring drug effects: Monitor the real-time effects of drugs on experimental subjects through biosensors or physiological indicators to evaluate the efficacy and safety of drugs.

[0111] The operation of the data acquisition module is crucial to achieve precise control and real-time monitoring of the drug release system based on MEMS microfluidic anesthetic bombs. By comprehensively collecting and monitoring various data during the drug release process, the system can promptly detect and adjust abnormal conditions so that the drug can be accurately released according to the predetermined plan, which not only improves the reliability and safety of the system, but also provides valuable data support for subsequent drug development and optimization.

[0112] Specifically, the flow regulating system of the anesthetic bomb of the present invention, the drug release detection module is also used for: Receive drug release task information from the data acquisition module, parse the drug release task information, extract drug release task parameters, and obtain drug type, concentration requirements, release rate, and environmental conditions; Load the pre-trained anesthetic bullet drug release simulation model, initialize the model parameters, substitute the parsed drug release task information as input parameters into the simulation model, and receive and set the model's boundary conditions and initial conditions; Start the drug release simulation model of the anesthetic bullet and begin to simulate the drug release process; The drug release simulation model of the anesthetic bullet calculates and outputs the simulation results of the drug release process based on the input parameters and internal algorithms; Simulation results of drug release process, including: Drug simulation concentration: simulated drug concentration changes during the release process; Simulate the flow rate of the fluid in the microchannel of the biochip: simulate the flow rate distribution of the fluid in the microchannel; Simulate the temperature difference between the inside and outside of the biochip: simulate the temperature difference between the inside and outside of the biochip; Drug release simulation rate: the simulated drug release rate changes over time; Simulate the pressure distribution at different positions in the microchannel: the pressure value of each point in the microchannel obtained by simulation; Simulated drug molecule diffusion coefficient: simulated diffusion coefficient of drug molecules in the medium; Simulate the pH value of the internal and external environment of the biochip: simulate the pH value of the internal and external environment of the biochip; Simulated ion concentration change value: the concentration change of ions in the simulated solution; Simulated drug diffusion area: the simulated drug diffusion area in the medium; Simulated drug effect value: the expected effect of the drug on the experimental subject predicted according to the simulated conditions; Simulated changes in biohormones in the experimental environment: If the model contains this function, the simulated changes in biohormones are obtained.

[0113] In the drug release system based on MEMS microfluidic anesthetic bomb, it is responsible for verifying and comparing the actual drug release data with the simulated prediction data to improve the accuracy of drug release. The following is a detailed description of the specific functions of the drug release detection module: The drug release detection module receives drug release task information, parses and extracts parameters, then uses a pre-trained simulation model to simulate the drug release process and compares the simulation results with the real-time collected drug release data, thereby achieving real-time monitoring and evaluation of the drug release process.

[0114] The drug release detection module first receives the drug release task information from the data acquisition module, which includes the drug name, drug type, expected drug standard concentration, expected drug release rate, expected fluid flow rate, expected temperature difference between the internal and external environments of the biochip, expected pH value, etc.

[0115] The module parses the information and extracts the drug release task parameters, such as drug type, concentration requirements, release rate, and environmental conditions.

[0116] The drug release detection module loads a pre-trained anesthetic bullet drug release simulation model. This model is based on the historical data of the drug release system of the anesthetic bullet and is trained through machine learning techniques such as the random forest algorithm. It can simulate various changes in the drug release process. Initialize the parameters of the simulation model, including the learning rate, number of iterations, random seeds, etc., to ensure that the model is in the best working state.

[0117] The parsed drug release task information is substituted into the simulation model as input parameters, and the boundary conditions and initial conditions of the model are set, such as the geometry of the microchannel and the physical properties of the fluid.

[0118] Start the drug release simulation model of the anesthetic bullet and start simulating the drug release process. The model will calculate and output various simulation results in the drug release process based on the input parameters and internal algorithms.

[0119] The drug release simulation model of the anesthetic bullet can simulate various parameters in the drug release process, including drug simulation concentration, fluid flow rate in the simulated biochip microchannel, temperature difference between the internal and external environments of the simulated biochip, drug release simulation rate, pressure distribution at different positions in the simulated microchannel, diffusion coefficient of simulated drug molecules, pH value of the simulated internal and external environments of the biochip, change value of simulated ion concentration, simulated drug diffusion area, simulated drug effect value and simulated change value of simulated biological hormones in the experimental environment.

[0120] The operation of the drug release detection module is of great significance to ensure the accuracy and safety of the drug release system based on MEMS microfluidic anesthetic bombs. By simulating the drug release process and comparing it with real-time data, the system can promptly detect and correct possible deviations or anomalies, thereby optimizing the drug release strategy, improving the treatment effect, and reducing potential risks. In addition, the module also provides strong support for drug research and development and optimization, which helps to promote the advancement and development of medical technology.

[0121] Specifically, the flow regulating system of the anesthetic bomb of the present invention, the drug release detection module is also used for: The drug release simulation result and the real-time drug release data of the anesthetic bullet are aligned based on time, so as to obtain the aligned drug release simulation result and the real-time drug release data of the anesthetic bullet; The drug release simulation results of the aligned anesthetic bullet and each index in the real-time drug release data are used to calculate the error between the simulation results and the real-time data; The error between the simulation result and the real-time data includes absolute error and relative error. The absolute error is the difference between the simulation value and the real-time value, and the relative error is the difference between the simulation value and the real-time value divided by the real-time value. Compare the calculated error with a preset error range, where the preset error range is a pre-accepted error range; If the errors of all indicators are within the preset error range, the comparison result is judged to be within the preset error range; If the error of any one or more indicators exceeds the preset error range, the comparison result is judged to be outside the preset error range; If the comparison result is within the preset error range, the simulation result is consistent with the real-time data, and the real-time drug release data is transmitted to the test result verification unit; If the comparison result is not within the preset error range, there is a difference between the simulation result and the real-time data.

[0122] In the drug release system based on MEMS microfluidic anesthetic bullet, the drug release simulation results of the anesthetic bullet are compared and verified with the real-time drug release data. The following is a detailed explanation of this function: Time Alignment,The drug release detection module first aligns the drug release simulation results of the anesthetic bullet with the real-time drug release data based on time.,This is because the simulation results and real-time data may be collected at different time points.,In order to accurately compare, it is necessary to ensure that they are compared at the same or similar time points.

[0123] Error calculation, after alignment, the module will calculate the error of each indicator in the drug release simulation results of the aligned anesthetic bomb and the real-time drug release data. The indicators include drug concentration, fluid flow rate, temperature difference, drug release rate, pressure distribution, drug molecular diffusion coefficient, pH value, ion concentration change value, drug diffusion area, drug effect value, and simulated biological hormone change value in the experimental environment. Error calculation includes absolute error and relative error. The absolute error is the difference between the simulated value and the real-time value, while the relative error is the percentage obtained by dividing the absolute error by the real-time value.

[0124] Error range comparison, compare the calculated error with the preset error range. This preset error range is pre-set by the system to determine whether the difference between the simulation result and the real-time data is within an acceptable range.

[0125] If the errors of all indicators are within the preset error range, then the comparison result is judged to be within the preset error range, which means that the simulation result is basically consistent with the real-time data.

[0126] If the error of any one or more indicators exceeds the preset error range, the comparison result is judged to be outside the preset error range, indicating that there is a difference between the simulation result and the real-time data.

[0127] Result processing: If the comparison result is within the preset error range, the drug release detection module transmits the real-time drug release data to the detection result verification unit for further verification.

[0128] If the comparison result is not within the preset error range, the module will generate a drug release path detection task and send the task to the drug release terminal of the anesthetic bomb. The drug release terminal will perform the detection task and return the detection result of the drug release path. The drug release detection module will analyze the detection result to determine whether there is a blockage in the drug release path and generate corresponding warning information.

[0129] Specifically, the flow regulating system of the anesthetic bomb of the present invention, the drug release detection module is also used for: Comparing the drug release simulation result of the anesthetic bullet with the real-time drug release data, an error index comparison result is obtained, and the error index comparison result includes an index of an error exceeding a preset range; Based on the comparison results of the error indicators, matching is performed in the preset knowledge base of generated drug release paths, and the indicators whose errors exceed the preset range are used as the matching basis to obtain the drug release path detection task; The drug release path detection task includes the specific path to be detected and the expected detection indicators; Encapsulate the information of the drug release path detection task into a standard task instruction, which includes the detection path, detection index and detection time, send the encapsulated task instruction to the drug release terminal of the anesthetic bomb, monitor the execution of the task instruction by the drug release terminal, and receive the detection result of the drug release path from the drug release terminal, which should include the flow rate, pressure and temperature on the detection path; The received test results are matched with a preset drug path test result knowledge base, and based on the matching results, it is determined whether the drug release path is blocked.

[0130] In the drug release system based on MEMS microfluidic anesthetic bullets, the drug release detection module further processes the comparison results after comparing the drug release simulation results of the anesthetic bullet with the real-time drug release data to identify and respond to potential release path problems. The following is a specific description of the functions of the drug release detection module in this process: Error index comparison, the drug release detection module first compares the drug release simulation results of the anesthetic bomb with the real-time drug release data to obtain the error index comparison results. The results will clearly indicate which indicators (such as drug concentration, fluid flow rate, temperature difference, etc.) have errors that exceed the preset range.

[0131] Based on the error indicator comparison results, the module will match the preset generated drug release path knowledge base. This knowledge base contains the association information between various possible error indicators and the corresponding drug release path detection tasks. Through matching, the module generates specific drug release path detection tasks based on the indicators whose errors exceed the preset range. The task is designed to further diagnose possible problems through additional testing.

[0132] The generated drug release path detection task includes the specific detection path and the expected detection indicators. In order to ensure that the task can be correctly executed by the drug release terminal of the anesthetic bullet, the module will encapsulate the task information into standard task instructions. The standard task instructions contain information such as the detection path, detection indicators, and detection time to ensure the accuracy and executability of the task. The encapsulated task instructions will be sent to the drug release terminal of the anesthetic bullet. The drug release detection module will monitor the execution of the task instructions by the terminal to ensure that the task is carried out as expected.

[0133] Receive the test results of the drug release path from the drug release terminal of the anesthetic bomb. The results should include data such as flow rate, pressure and temperature on the test path. The drug release detection module will analyze the received test results and match them in the preset drug path test result knowledge base. This knowledge base contains the corresponding relationship between the test results and the status of the drug release path (such as whether there is blockage).

[0134] Based on the matching results, the module can determine whether there is a blockage in the drug release path. If there is a blockage, the module will generate a drug release path blockage warning message to remind the user or system administrator to take appropriate measures to solve the problem.

[0135] Through the above steps, the drug release detection module can effectively identify and respond to the path blockage problem that may exist in the release process of the anesthetic bullet, thereby ensuring the safety of the drug release system.

[0136] The technical solution of the present invention effectively solves the problem that the existing anesthetic bullet drug release system cannot timely detect the blockage of the drug release path by constructing a drug release system based on MEMS microfluidic anesthetic bullets. The specific solution is as follows: The data acquisition module first obtains the drug release task information and matches the information with the preset anesthetic bullet drug knowledge base to obtain the standard information of the drug (such as drug standard concentration, drug standard flow rate, drug standard release rate). The model construction module uses the historical data of the anesthetic bullet drug release system to train the random forest model to construct an anesthetic bullet drug release simulation model, which can simulate various parameters in the drug release process.

[0137] The data acquisition module sends the drug release task information to the anesthetic bullet drug release terminal and collects various data in the drug release process in real time (such as real-time drug concentration, fluid flow rate, temperature difference, pressure distribution, pH value, ion concentration change value, etc.). The drug release detection module substitutes the drug release task information into the anesthetic bullet drug release simulation model, outputs the simulation results, and compares the simulation results with the real-time collected data.

[0138] If the comparison result is within the preset error range, it means that the drug release process is normal, and the real-time data will be transmitted to the test result verification unit for further verification. If the comparison result exceeds the preset error range, it means that the drug release process may be abnormal. At this time, a drug release path detection task will be generated and sent to the anesthetic bullet drug release terminal for further detection.

[0139] The drug release path detection results will be matched in the preset drug path detection result knowledge base to determine whether the drug release path is blocked. If the test results show that the drug release path is blocked, the system will generate a drug release path blockage warning information so that timely measures can be taken. The test result verification unit compares the real-time drug release data with the drug standard information of the anesthetic bullet. If the real-time data exceeds the standard information, a drug release over-standard warning information will be generated.

[0140] Through the above technical scheme, the present invention can monitor various parameters in the process of drug release of anesthetic bullets in real time, and timely discover the blockage problem of the drug release path by comparing the simulation results with the real-time data, thereby improving the safety of the anesthetic bullet drug release system.

Claims

1. The drug release system based on MEMS microfluidic anesthetic bullet is characterized by: include: The data acquisition module is used to acquire drug release task information, match the drug release task information with a preset drug knowledge base of the anesthetic bomb, and obtain drug standard information of the anesthetic bomb, wherein the drug standard information of the anesthetic bomb includes drug standard concentration, drug standard flow rate, and drug standard release rate; A model building module is used to obtain historical data of the drug release system of the anesthetic bullet, train a random forest model using the historical data of the drug release system of the anesthetic bullet, and obtain a drug release simulation model of the anesthetic bullet; A data acquisition module is used to send drug release task information to the drug release terminal of the anesthetic bomb, and collect real-time drug release data when the drug release terminal of the anesthetic bomb performs the drug release task. The real-time drug release data includes real-time drug concentration, fluid flow rate in the real-time biochip microchannel, temperature difference between the real-time internal and external environments of the real-time biochip, real-time drug release rate, pressure distribution at different positions in the real-time microchannel, real-time drug molecular diffusion coefficient, pH value of the real-time internal and external environments of the real-time biochip, real-time ion concentration change value, real-time drug diffusion area, real-time drug effect value, and real-time change value of simulated biological hormones in the experimental environment; The drug release detection module is used to substitute the drug release task information into the drug release simulation model of the anesthetic bullet and output the drug release simulation results of the anesthetic bullet. The drug release simulation results of the anesthetic bullet include the drug simulation concentration, the fluid flow rate in the simulated biochip microchannel, the simulated temperature difference between the internal and external environments of the biochip, the drug release simulation rate, the pressure distribution at different positions in the simulated microchannel, the simulated drug molecular diffusion coefficient, the simulated pH value of the internal and external environments of the biochip, the simulated ion concentration change value, the simulated drug diffusion area, the simulated drug effect value and the simulated biological hormone simulation change value in the experimental environment. The drug release simulation results of the anesthetic bullet are compared with the real-time drug release data to obtain the drug release simulation results of the anesthetic bullet. The simulation result is compared with the real-time drug release data, and the comparison result includes whether the comparison result is within a preset error range and whether the comparison result is not within the preset error range. If the comparison result is within the preset error range, the real-time drug release data is transmitted to the detection result verification unit. If the comparison result is not within the preset error range, a drug release path detection task is generated, and the drug release path detection task is sent to the drug release terminal of the anesthetic bomb to obtain the drug release path detection result. The drug release path detection result is matched in a preset drug path detection result knowledge base to obtain the drug release path detection analysis result. The drug release path detection analysis result includes whether the drug release path is blocked and whether the drug release path is not blocked. When the drug release path is blocked, a drug release path blockage warning information is generated; The test result verification unit is used to compare the real-time drug release data with the drug standard information of the anesthetic bullet. If the real-time drug release data exceeds the drug standard information of the anesthetic bullet in the comparison result of the real-time drug release data and the drug standard information of the anesthetic bullet, a drug release exceeding standard warning information is generated.

2. The flow regulating system of the anesthetic bomb according to claim 1, characterized in that: The data acquisition module is further used for: The drug release task information is parsed to obtain the parsed drug release task information, which includes: drug name, drug type, expected drug standard concentration, expected drug release rate, expected fluid flow rate, expected temperature difference between the internal and external environments of the biochip, expected pH value of the internal and external environments of the biochip, range of changes in simulated biological hormones in the experimental environment, expected pressure distribution at different positions in the microchannel, expected range of drug molecule diffusion coefficient, expected range of changes in ion concentration, expected drug diffusion area, and expected drug effect value.

3. The flow regulating system of the anesthetic bomb according to claim 1, characterized in that: The model building module is also used to: The historical data of the drug release system of the anesthetic bomb is extracted to obtain the characteristics of the drug release process. The characteristics of the drug release process include drug concentration characteristics, flow rate characteristics, temperature difference characteristics, pressure distribution characteristics, pH value characteristics and ion concentration characteristics. The drug release process characteristics are used as the input of the model. Initialize the random forest model parameters, including learning rate, number of iterations, and random seed; The characteristics of the drug release process were input into the selected random forest model, and the model parameters were adjusted by the gradient descent algorithm to minimize the prediction error, thus obtaining the drug release simulation model of the anesthetic bullet.

4. The flow regulating system of the anesthetic bomb according to claim 1, characterized in that: The data acquisition module is also used for: The drug release task information is sent to the drug release terminal of the anesthetic bomb, and the concentration change of the drug during the release process is monitored in real time by chemical sensors. The real-time flow rate of the fluid in the microchannel is measured by a flow meter or a flow sensor. The real-time temperature of the internal and external environments of the biochip is measured by a temperature sensor, and the temperature difference is calculated. The drug release rate is calculated in real time by monitoring the working status of the drug release device. The pressure sensor is used to measure the pressure at different positions of the microchannel to obtain a real-time pressure distribution diagram. By observing the diffusion behavior of drug molecules in the medium, the diffusion coefficient is calculated in real time using a diffusion model. The pH sensor is used to monitor the pH value of the internal and external environments of the biochip in real time. The concentration change of ions in the solution is monitored in real time by an ion selective electrode or an ion chromatograph. The diffusion area of ​​the drug in the medium is measured in real time by image processing technology or direct observation. The real-time effect of the drug on the experimental subject is monitored by biosensors or physiological indicators.

5. The flow regulating system of the anesthetic bomb according to claim 1, characterized in that: The drug release detection module is also used for: Receive drug release task information from the data acquisition module, parse the drug release task information, extract drug release task parameters, and obtain drug type, concentration requirements, release rate, and environmental conditions; Load the pre-trained anesthetic bullet drug release simulation model, initialize the model parameters, substitute the parsed drug release task information as input parameters into the simulation model, and receive and set the model's boundary conditions and initial conditions; Start the drug release simulation model of the anesthetic bullet and begin to simulate the drug release process; The drug release simulation model of the anesthetic bullet calculates and outputs the simulation results of the drug release process based on the input parameters and internal algorithms; Simulation results of drug release process, including: Drug simulation concentration: simulated drug concentration changes during the release process; Simulate the flow rate of the fluid in the microchannel of the biochip: simulate the flow rate distribution of the fluid in the microchannel; Simulate the temperature difference between the inside and outside of the biochip: simulate the temperature difference between the inside and outside of the biochip; Drug release simulation rate: the simulated drug release rate changes over time; Simulate the pressure distribution at different positions in the microchannel: the pressure value of each point in the microchannel obtained by simulation; Simulated drug molecule diffusion coefficient: simulated diffusion coefficient of drug molecules in the medium; Simulate the pH value of the internal and external environment of the biochip: simulate the pH value of the internal and external environment of the biochip; Simulated ion concentration change value: the concentration change of ions in the simulated solution; Simulated drug diffusion area: the simulated drug diffusion area in the medium; Simulated drug effect value: the expected effect of the drug on the experimental subject predicted according to the simulated conditions; Simulated changes in biohormones in the experimental environment: If the model contains this function, the simulated changes in biohormones are obtained.

6. The flow regulating system of the anesthetic bomb according to claim 5, characterized in that: The drug release detection module is also used for: The drug release simulation result and the real-time drug release data of the anesthetic bullet are aligned based on time, so as to obtain the aligned drug release simulation result and the real-time drug release data of the anesthetic bullet; The drug release simulation results of the aligned anesthetic bullet and each index in the real-time drug release data are used to calculate the error between the simulation results and the real-time data; The error between the simulation result and the real-time data includes absolute error and relative error. The absolute error is the difference between the simulation value and the real-time value, and the relative error is the difference between the simulation value and the real-time value divided by the real-time value. Compare the calculated error with a preset error range, where the preset error range is a pre-accepted error range; If the errors of all indicators are within the preset error range, the comparison result is judged to be within the preset error range; If the error of any one or more indicators exceeds the preset error range, the comparison result is judged to be outside the preset error range; If the comparison result is within the preset error range, the simulation result is consistent with the real-time data, and the real-time drug release data is transmitted to the test result verification unit; If the comparison result is not within the preset error range, there is a difference between the simulation result and the real-time data.

7. The flow regulating system of the anesthetic bomb according to claim 6, characterized in that: The drug release detection module is also used for: Comparing the drug release simulation result of the anesthetic bullet with the real-time drug release data, an error index comparison result is obtained, and the error index comparison result includes an index of an error exceeding a preset range; Based on the comparison results of the error indicators, matching is performed in the preset knowledge base of generated drug release paths, and the indicators whose errors exceed the preset range are used as the matching basis to obtain the drug release path detection task; The drug release path detection task includes the specific path to be detected and the expected detection indicators; Encapsulate the information of the drug release path detection task into a standard task instruction, which includes the detection path, detection index and detection time, send the encapsulated task instruction to the drug release terminal of the anesthetic bomb, monitor the execution of the task instruction by the drug release terminal, and receive the detection result of the drug release path from the drug release terminal, which should include the flow rate, pressure and temperature on the detection path; The received test results are matched with a preset drug path test result knowledge base, and based on the matching results, it is determined whether the drug release path is blocked.

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