Transcutaneous electrical acupoint stimulation for regulating immune checkpoint system and method thereof

Abstract

The present application relates to the technical field of immunotherapy, in particular to a transcutaneous acupoint electrical stimulation regulation and control immune checkpoint system and method thereof, comprising six modules of electrical stimulation signal generation, immune metabolism fingerprint collection, data analysis processing, electrical stimulation control, drug control and immune memory enhancement, through 10Hz basic carrier and 65-75Hz high frequency micro-vibration oscillation complex waveform, accurately regulating and controlling immune checkpoint expression, real-time collecting T cell PD-1 expression, ATP content and IL-2 secretion, calculating immune metabolism coupling index, identifying PD-1 expression window period, dynamically adjusting electrical stimulation parameters accordingly, and triggering low-dose PD-1 inhibitor administration in the window period, realizing treatment effect optimization, at the same time, monitoring CD8+ memory T cell proportion and predicting immune memory durability. Only 1 / 3 of the conventional dose of PD-1 inhibitor can achieve better treatment effect, bringing innovation breakthrough to the field of immunotherapy.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of immunotherapy, in particular to transcutaneous acupoint electrical stimulation for regulating immune checkpoint system and method thereof, and more particularly to a technical solution of combining acupoint electrical stimulation with immune checkpoint inhibitors. BACKGROUND

[0002] Immune checkpoint inhibitor therapy is a major breakthrough in the field of tumor treatment. By breaking the tumor immune escape mechanism, it activates the patient's own immune system to attack tumor cells. Currently, immune checkpoint inhibitors represented by PD-1 / PD-L1 inhibitors have shown significant efficacy in the treatment of melanoma, lung cancer, renal cancer and other tumors. However, clinical data shows that the objective response rate of single drug therapy is only 20%-40%, and there are problems such as high treatment cost and immune-related adverse reactions.

[0003] In the prior art, CN 119656475 A discloses an electrical stimulation pulse physiotherapy instrument and an electrical stimulation pulse self-adaptive regulation method thereof. The method is mainly based on electromyographic signal analysis. By obtaining the electromyographic characteristics of different relaxation and contraction intervals, the cumulative deviation index and deviation contribution index are calculated, and then the propagation characteristic change degree and muscle activity index are determined, and finally the electrical stimulation pulse parameters are adjusted. This technology only focuses on the physical reaction of muscles and is mainly used for muscle rehabilitation and pain management, which has the following technical limitations:

[0004] 1. Only focusing on muscle physical reaction, ignoring the regulation effect of electrical stimulation on the immune system

[0005] 2. Lack of real-time biomarker detection and feedback integration mechanism;

[0006] 3. No consideration of the synergistic effect of electrical stimulation and drug therapy;

[0007] 4. Unable to adjust parameters for specific disease states (such as tumors);

[0008] 5. Lack of consideration and monitoring of cellular and molecular level effects;

[0009] Research has found that electrical stimulation of specific frequencies can affect T cell function through the neural-immune regulation pathway and regulate the expression of immune checkpoint molecules. However, the existing technology lacks a system that can precisely regulate the expression of T cell PD-1 and synergize with low-dose immune checkpoint inhibitors, and cannot maximize the effect of immunotherapy and minimize side effects. SUMMARY

[0010] The application aims to provide a transcutaneous acupoint electrical stimulation regulation immune checkpoint system and a method thereof, and solve the technical problems of the current immunotherapy lacking personalized and precise regulation, limited efficacy and significant side effects. The application integrates the transcutaneous acupoint electrical stimulation technology and the immune metabolism monitoring system, precisely regulates the T cell PD-1 expression level, creates the best immune checkpoint inhibitor intervention opportunity, and realizes the efficient application of low-dose immunotherapy drugs.

[0011] The application provides a transcutaneous acupoint electrical stimulation regulation immune checkpoint system, which comprises:

[0012] An immune checkpoint expression adaptive adjustment module is configured to generate an electrical stimulation signal with a specific frequency, wherein the specific frequency comprises a composite waveform of a 10 Hz base carrier and a 65-75 Hz high-frequency micro-oscillation superposition;

[0013] An immune metabolism fingerprint collection module is connected with the immune checkpoint expression adaptive adjustment module and is configured to collect the T cell surface PD-1 expression amount, the ATP content and the IL-2 secretion amount of a patient, and generate an immune metabolism state vector;

[0014] A data analysis processing module is connected with the immune metabolism fingerprint collection module and is configured to receive the immune metabolism state vector, calculate an immune metabolism coupling index, and identify a PD-1 expression window period;

[0015] An electrical stimulation control module is connected with the data analysis processing module and is configured to dynamically adjust electrical stimulation parameters according to the immune metabolism coupling index;

[0016] A drug administration control module is connected with the data analysis processing module and the electrical stimulation control module, and is configured to trigger low-dose PD-1 inhibitor administration when the PD-1 expression window period is detected;

[0017] An immune memory strengthening module is connected with the data analysis processing module and the drug administration control module, and is configured to monitor the proportion change of CD8+ memory T cells and generate immune memory persistence prediction data.

[0018] Preferably, the immune checkpoint expression adaptive adjustment module comprises:

[0019] An acupoint positioning unit is configured to determine the accurate coordinate positions of Guanyuan and Zusanli acupoints;

[0020] An electrical stimulation waveform generation unit is configured to generate the composite waveform of the 10 Hz base carrier and the 65-75 Hz high-frequency micro-oscillation superposition, and the pulse width of the composite waveform is 300 μs;

[0021] A stimulation timing control unit is configured to control the stimulation-rest ratio to be 2:1, wherein the stimulation phase is 40 seconds and the rest phase is 20 seconds.

[0022] As preferred, the immune metabolism fingerprint collection module comprises:

[0023] a micro-sampling unit for automatically collecting 50 μL of peripheral blood every 2-6 hours through a microneedle array;

[0024] a microfluidic detection unit for receiving the peripheral blood sample and detecting the expression level of PD-1 on the surface of T cells through fluorescence resonance energy transfer technology;

[0025] an ATP bioluminescence detection unit for detecting the mitochondrial ATP content of T cells in the peripheral blood;

[0026] an IL-2 fluorescence immunoassay unit for detecting the IL-2 secretion level in the peripheral blood.

[0027] As preferred, the data analysis processing module comprises:

[0028] an immune metabolism state vector construction unit for constructing a three-dimensional immune metabolism state vector of the patient, the vector comprising the expression level of PD-1, the ATP content, and the IL-2 secretion level;

[0029] a coupling index calculation unit for calculating an immune metabolism coupling index IMCI, the IMCI being calculated by the formula , wherein is a dynamic weight coefficient based on the type of tumor of the patient, PD1_ratio is the ratio of the expression level of PD-1 on the surface of T cells to the baseline value, ATP_ratio is the ratio of the mitochondrial ATP content of T cells to the baseline value, and IL2_ratio is the ratio of the IL-2 secretion level to the baseline value;

[0030] an expression window period identification unit for identifying the optimal treatment window period when the expression level of PD-1 reaches 130%-140% of the baseline.

[0031] As preferred, the electrical stimulation control module comprises:

[0032] a parameter optimization engine for dynamically adjusting the electrical stimulation parameters based on the immune metabolism coupling index through a pre-trained Q-learning model;

[0033] an impedance monitoring unit for monitoring the changes in tissue impedance in the acupoint area in real time and providing feedback data to the parameter optimization engine;

[0034] a waveform modulation unit for adjusting the frequency and pulse width of the electrical stimulation complex waveform according to the output of the parameter optimization engine.

[0035] As preferred, the drug administration control module is configured to:

[0036] triggering the PD-1 inhibitor administration when the PD-1 expression reaches 135±5% of the baseline;

[0037] The dose of the PD-1 inhibitor is 1 / 3 of the conventional therapeutic dose.

[0038] As preferred, the immune memory strengthening module comprises:

[0039] a memory T cell detection unit for monitoring the proportion of CD8+CD45RO+CD62L+ memory T cells;

[0040] a periodic training plan unit for generating a 21-day / cycle electrostimulation-drug synergistic intervention scheme;

[0041] an immune memory persistence prediction unit for predicting the immune memory persistence period based on the change in the proportion of CD8+ memory T cells.

[0042] As preferred, the data analysis processing module is further used for:

[0043] constructing an optimal trajectory of the immune metabolic state space, and a target state region of the optimal trajectory is defined as {PD1: 135±5%, ATP: >200%, IL2: >150%};

[0044] calculating a deviation vector of the current immune metabolic state and the target state region.

[0045] As preferred, the system further comprises:

[0046] a treatment effect evaluation module connected with the data analysis processing module, for generating a treatment effect evaluation report based on the change trend of the immune metabolic coupling index;

[0047] a remote monitoring module connected with the data analysis processing module, for transmitting the patient immune metabolic state data to a doctor terminal and receiving the doctor's treatment scheme adjustment instruction.

[0048] A percutaneous acupoint electrostimulation method for regulating immune checkpoints, applied to the system, comprising the following steps:

[0049] collecting the patient's peripheral blood, detecting the CD8+ T cell PD-1 basal expression level and IL-2 secretion capacity, and establishing a patient immune metabolic baseline index set;

[0050] selecting an acupoint combination based on the patient's constitution and tumor type, and implementing a composite waveform electrostimulation of a 10Hz basic carrier wave superimposed with a 65-75Hz high-frequency micro-vibration on the Guanyuan and Zusanli acupoints;

[0051] Peripheral blood of the patient is collected every 2 hours, real-time monitoring of T cell PD-1 expression change, ATP content and IL-2 secretion level, and the immune metabolism state vector is constructed;

[0052] The immune metabolism coupling index is calculated, and the PD-1 expression window period is identified;

[0053] When the PD-1 expression amount reaches 135±5% of the baseline, the PD-1 inhibitor with a conventional dose of 1 / 3 is given;

[0054] The change of the proportion of CD8+ memory T cells is monitored, and the persistence of immune memory is evaluated;

[0055] Based on the change of the immune metabolism coupling index and the proportion of memory T cells, the electric stimulation parameters and the treatment scheme are dynamically adjusted.

[0056] The beneficial effects of the present application include:

[0057] 1. The immune checkpoint expression window period is created, and the PD-1 inhibitor with a conventional dose of 1 / 3 can achieve better treatment effect.

[0058] 2. The objective response rate (ORR) is increased to 54%, which is increased by 28.6% compared with simple immunotherapy (42%).

[0059] 3. The incidence of immune-related adverse reactions is reduced by 65%, and the treatment cost is reduced by 53%.

[0060] 4. An immune metabolism evaluation system that can be monitored in real time is established, and individualized precision treatment is realized.

[0061] 5. Through the immune memory strengthening mechanism, the treatment persistence and the progression-free survival period are significantly prolonged. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 It is a whole structure schematic diagram of the transcutaneous acupoint electrical stimulation regulation and control immune checkpoint system of the present application;

[0063] Figure 2 It is a structure schematic diagram of the immune checkpoint expression adaptive regulation module of the present application;

[0064] Figure 3 It is a structure schematic diagram of the immune metabolism fingerprint collection module of the present application;

[0065] Figure 4 It is a structure schematic diagram of the data analysis processing module of the present application;

[0066] Figure 5 It is a structure schematic diagram of the electric stimulation control module of the present application;

[0067] Figure 6 It is a structure schematic diagram of the drug administration control module of the present application;

[0068] Figure 7 This is a schematic diagram of the immune memory enhancement module structure of the present invention;

[0069] Figure 8 A flow chart showing the enhanced functionality of the data analysis and processing module of the present invention;

[0070] Figure 9 This is a schematic diagram of the structures of the treatment effect evaluation module and the remote monitoring module of the present invention;

[0071] Figure 10 This is a flow chart of the method for regulating immune checkpoints through transcutaneous electrical acupoint stimulation of the present invention. DETAILED DESCRIPTION

[0072] Please refer to the attached Figures 1-10 , the specific implementation of the present invention is further described in detail below with reference to the accompanying drawings.

[0073] like Figure 1 As shown, the transcutaneous acupoint electrical stimulation immune checkpoint regulation system provided by the present invention includes an immune checkpoint expression adaptive regulation module 1, an immune metabolic fingerprint acquisition module 2, a data analysis and processing module 3, an electrical stimulation control module 4, a drug administration control module 5 and an immune memory enhancement module 6.

[0074] Immune Checkpoint Expression Adaptive Regulation Module 1 generates an electrical stimulation signal at a specific frequency, consisting of a composite waveform composed of a 10Hz base carrier wave and a 65-75Hz high-frequency micro-oscillation. This module precisely stimulates acupoints such as Guanyuan and Zusanli, providing electrical stimulation with specific parameters at different stages to regulate the expression of PD-1 molecules on the surface of T cells.

[0075] The immune metabolic fingerprint acquisition module 2 is connected to the immune checkpoint expression adaptive regulation module 1 to collect real-time immune metabolic indicators such as PD-1 expression on the patient's T cell surface, ATP content, and IL-2 secretion, generating a three-dimensional immune metabolic state vector. This module uses microfluidics and fluorescence detection technologies to achieve high-precision detection of trace samples.

[0076] Data Analysis and Processing Module 3 is connected to Immunometabolism Fingerprint Acquisition Module 2 to receive the immunometabolism state vector, calculate the immunometabolism coupling index, and identify the PD-1 expression window. This module is the core decision-making center of the system, using complex data analysis algorithms to transform multidimensional biomarker data into a basis for treatment decisions.

[0077] The electrical stimulation control module 4 is connected to the data analysis and processing module 3 and is used to dynamically adjust the electrical stimulation parameters based on the immune metabolic coupling index. This module accurately converts data analysis results into electrical stimulation parameters, ensuring that electrical stimulation achieves optimal results at different stages.

[0078] The drug administration control module 5 is connected with the data analysis processing module 3 and the electrical stimulation control module 4, and is used to trigger low-dose PD-1 inhibitor administration when the PD-1 expression window period is detected. This module ensures the precise timing of drug administration, maximizes drug effects while minimizing adverse reactions.

[0079] The immune memory enhancement module 6 is connected with the data analysis processing module 3 and the drug administration control module 5, and is used to monitor changes in the proportion of CD8+ memory T cells and generate immune memory persistence prediction data. This module focuses on the long-term effects of treatment, enhances immune memory formation through specific strategies, and prolongs treatment persistence.

[0080] A complete data closed loop is formed between the modules: the immune checkpoint expression adaptive adjustment module 1 generates electrical stimulation signals that act on the patient's acupoints; the immune metabolism fingerprint collection module 2 detects changes in immune metabolism after electrical stimulation; the data analysis processing module 3 analyzes these changes and generates decisions; the electrical stimulation control module 4 and the drug administration control module 5 execute adjustments according to the decisions; and finally the immune memory enhancement module 6 evaluates the long-term effects and feeds back to the system, achieving closed-loop control throughout the process.

[0081] As shown in Figure 2 The immune checkpoint expression adaptive adjustment module 1 includes an acupoint positioning unit 11, an electrical stimulation waveform generation unit 12, and a stimulation timing control unit 13.

[0082] The acupoint positioning unit 11 is used to determine the precise coordinate position of Guanyuan and Zusanli acupoints. This unit uses optical positioning technology combined with anatomical databases to achieve precise positioning of acupoints. Preferably, this unit is also equipped with a pressure sensor that can detect the touch pressure response in the acupoint area, improving positioning accuracy. The positioning accuracy of the acupoint positioning unit 11 reaches ±2 mm, ensuring that electrical stimulation always acts on the core area of the target acupoint.

[0083] The electrical stimulation waveform generation unit 12 is used to generate a composite waveform of a 10Hz base carrier superimposed with a 65-75Hz high-frequency micro-oscillation, with a pulse width of 300μs. This unit uses digital signal processing technology to generate accurate composite waveforms through a microprocessor-controlled D / A converter. Preferably, the base carrier uses a square wave form with a duty cycle of 50% and an amplitude of 2-5mA; the high-frequency micro-oscillation uses a sine wave form with an amplitude of 15%-20% of the base wave amplitude. This composite waveform design can simultaneously activate different types of receptors in the acupoint area, producing the best immune regulation effect.

[0084] The stimulation timing control unit 13 is used to control the stimulation-rest ratio of 2:1, with a stimulation phase of 40 seconds and a rest phase of 20 seconds. This unit is responsible for controlling the time pattern of electrical stimulation, avoiding tissue adaptation, and maintaining the effect of stimulation. Preferably, this unit also has an adaptive adjustment function, which automatically fine-tunes the stimulation timing according to changes in tissue impedance, ensuring the stability of the electrical stimulation effect. In each treatment cycle, the stimulation timing control unit 13 is also responsible for controlling the total stimulation time of 30 minutes, twice a day.

[0085] The information flow between the three units is as follows: the acupoint positioning unit 11 first transmits the precise coordinate information of the acupoint to the electrical stimulation waveform generation unit 12, which generates an electrical stimulation waveform suitable for the specific characteristics of the acupoint; then the stimulation timing control unit 13 receives the waveform information and controls the output timing of the electrical stimulation, forming a complete electrical stimulation program.

[0086] As shown in Figure 3 The immune metabolism fingerprint collection module 2 includes a micro-sampling unit 21, a microfluidic detection unit 22, an ATP bioluminescence detection unit 23, and an IL-2 fluorescent immunoassay unit 24.

[0087] The micro-sampling unit 21 is used to automatically collect 50 μL of peripheral blood every 2-6 hours through a microneedle array. This unit uses painless microneedle technology, and the array is made of biocompatible materials. Microneedles with a diameter of less than 100 μm can reach the capillary layer and avoid nerve endings, achieving painless sampling. Preferably, the microneedle surface is coated with a hydrophilic material to improve blood collection efficiency. The sampling process is controlled by a precision motor to ensure the accuracy and consistency of the sampling amount each time.

[0088] The microfluidic detection unit 22 is used to receive peripheral blood samples and detect the expression level of PD-1 on the surface of T cells through fluorescence resonance energy transfer technology. This unit contains a microfluidic chip, and the chip surface is fixed with anti-PD-1 antibodies and corresponding fluorescent probes. When blood samples containing different concentrations of PD-1 molecules pass through the chip, the fluorescence signal intensity is proportional to the expression level of PD-1. Preferably, this unit uses a confocal fluorescence detection system with a detection limit of 5 ng / mL and a dynamic range of 5-500 ng / mL, which can accurately capture the small changes in the expression level of PD-1.

[0089] The ATP bioluminescence detection unit 23 is used to detect the mitochondrial ATP content of T cells in peripheral blood. This unit uses the luciferase bioluminescence principle, and through specific cleavage of T cells, it releases intracellular ATP and reacts with luciferase reagents to produce light signals. Preferably, this unit uses a photomultiplier tube to detect weak light signals with a sensitivity of 10-18 mol, which can accurately reflect the energy metabolism status of T cells.

[0090] The IL-2 fluorescence immunoassay unit 24 is used to detect the IL-2 secretion level in peripheral blood. The unit uses fluorescence immunoassay technology, combined with specific anti-IL-2 antibody and quantum dot fluorescence labeling, to realize rapid quantitative detection of IL-2. Preferably, the detection limit of the unit reaches 5 pg / mL, the linear range is 5-2000 pg / mL, and the T cell activation state can be accurately reflected.

[0091] The information flow between the four units is as follows: the peripheral blood sample collected by the microsampling unit 21 is simultaneously distributed to the microfluidic detection unit 22, the ATP bioluminescence detection unit 23 and the IL-2 fluorescence immunoassay unit 24, the three detection units process the sample in parallel and generate respective detection data, and finally integrate into complete immune metabolism fingerprint data, which is transmitted to the data analysis processing module 3.

[0092] As shown in Figure 4 , the data analysis processing module 3 includes an immune metabolism state vector construction unit 31, a coupling index calculation unit 32 and an expression window period identification unit 33.

[0093] The immune metabolism state vector construction unit 31 is used to construct a three-dimensional immune metabolism state vector of the patient, which includes PD-1 expression amount, ATP content and IL-2 secretion amount. The unit receives the original detection data from the immune metabolism fingerprint collection module 2, and constructs a three-dimensional state vector after standardization processing. Preferably, the vector is represented in the following form:

[0094] ,

[0095] Among them, represents the PD-1 expression amount at time point , represents the baseline PD-1 expression amount; represents the ATP content at time point , represents the baseline ATP content; represents the IIL-2 secretion amount at time point , represents the baseline IL-2 secretion amount; the superscript represents the vector transpose.

[0096] The coupling index calculation unit 32 is used to calculate the immune metabolism coupling index IMCI, which is calculated by the formula , wherein PD1_ratio is the ratio of PD-1 expression on T cell surface to the baseline value, and the calculation formula is PD1(t) / PD1_0, where PD1(t) represents the PD-1 expression at time point t, and PD1_0 represents the baseline PD-1 expression. ATP_ratio is the ratio of T cell mitochondrial ATP content to the baseline value, and the calculation formula is ATP(t) / ATP_0, where ATP(t) represents the ATP content at time point t, and ATP_0 represents the baseline ATP content; IL2_ratio is the ratio of IL-2 secretion to the baseline value, and the calculation formula is IL2(t) / IL2_0, where IL2(t) represents the IL-2 secretion at time point t, and IL2_0 represents the baseline IL-2 secretion. The sum of the three coefficients a, b, and g is equal to 1, ensuring the balance and comparability of the IMCI index in calculation.

[0097] The unit generates a single immune metabolic coupling index by comprehensively evaluating the three indicators of PD-1 expression, ATP content, and IL-2 secretion, as the core basis for treatment decision-making. Preferably, the dynamic weight coefficient is determined according to the immune metabolic characteristics of different tumor types:

[0098] Melanoma: ;

[0099] Lung cancer: ;

[0100] Renal cell carcinoma: ;

[0101] The expression window period identification unit 33 is used to identify the optimal treatment window period when the PD-1 expression reaches 130% to 140% of the baseline. The unit identifies the time point when the PD-1 expression reaches the ideal treatment window period by analyzing the dynamic change curve of PD-1 expression, providing accurate timing for drug administration. Preferably, the unit uses a sliding window algorithm, and when the PD-1 expression of the continuous 3 sampling points is within the target interval (130% to 140%), it is confirmed to enter the treatment window period. At the same time, the unit also monitors the PD-1 expression change rate to ensure that the expression level is in a relatively stable state.

[0102] The information flow between the three units is as follows: the immune metabolic state vector construction unit 31 first receives the original detection data and constructs the state vector, and then transmits the vector to the coupling index calculation unit 32 for IMCI calculation; at the same time, the PD-1 expression component in the state vector is transmitted to the expression window period identification unit 33 for window period analysis; finally, the IMCI index and window period information are integrated and transmitted to the electrical stimulation control module 4 and the drug administration control module 5, guiding subsequent treatment adjustment.

[0103] As Figure 5As shown, the electrical stimulation control module 4 includes a parameter optimization engine 41 , an impedance monitoring unit 42 and a waveform modulation unit 43 .

[0104] The parameter optimization engine 41 is used to dynamically adjust electrical stimulation parameters based on the immunometabolism coupling index using a pre-trained Q-learning model. This engine includes a pre-trained model library containing Q-learning models pre-trained based on extensive clinical and experimental data, categorized by tumor type, patient constitution, and baseline immune status; a transfer learning module for rapidly adapting pre-trained models to individual patient characteristics; a hybrid optimization algorithm combining Q-learning and Bayesian optimization to accelerate parameter convergence; and a treatment decision support system that provides real-time parameter recommendations and predictive effect evaluation. The system utilizes a Q-learning model library trained over 10,000 simulation cycles, covering parameter mappings for common tumor types (melanoma, lung cancer, renal cancer, etc.). The model is built using offline training data (including historical patient data and animal model data), resulting in a stable state-action value function Q(s,a).

[0105] The engine uses the principle of reinforcement learning, treating the transition of immune metabolic state as a reward function of specific electrical stimulation parameters, and finding the optimal parameter combination through continuous trial and learning. Preferably, the Q value update formula of the parameter optimization engine 41 is:

[0106] ,

[0107] In this formula, Indicates status Take action The value function of is the corresponding state-action value function in the pre-trained model, is the pre-training knowledge transfer coefficient (value range 0 , is the learning rate, usually set to 0.1-0.3, Represents instant reward (determined by the change in IMCI), is the discount factor (usually set to 0.8-0.9), Indicates the maximum value of the next state.

[0108] in, is the Q value of the pre-trained model, and λ represents the degree of individualized learning: initially λ = 0.1, and gradually adjusted to a maximum of 0.3 as the treatment progresses according to the patient's response, ensuring that the parameters are mainly based on existing knowledge rather than online learning.

[0109] A hybrid optimizer is constructed by combining Bayesian optimization algorithm, and a probability model of IMCI and electrical stimulation parameters is established by Gaussian process regression to achieve exploration-exploitation balance and reach a local optimal solution within 10-15 parameter adjustments without complete convergence to obtain good treatment effect.

[0110] Before each actual parameter adjustment, the system performs 100 Monte Carlo simulations based on the current immune metabolic state of the patient to predict the risk and benefit of potential parameter adjustments, and only parameter changes with a predicted improvement probability of >85% are used.

[0111] This hybrid strategy not only maintains the theoretical basis of Q-learning algorithm, but also solves the practical problems of sample size and time limit in clinical application, so that the algorithm can play an effective role in a single patient treatment cycle.

[0112] The impedance monitoring unit 42 is used to monitor the impedance changes of the acupoint area in real time and provide feedback data to the parameter optimization engine 41. This unit reflects the physiological state changes of the acupoint area by measuring the impedance value between the electrode and the tissue. Preferably, this unit uses the four-electrode method to measure tissue impedance, with a frequency of 1 kHz, a measurement range of 100Ω-10kΩ, and an accuracy of ±5%. Impedance data is collected every second and transmitted to the parameter optimization engine 41 after filtering.

[0113] The waveform modulation unit 43 is used to adjust the frequency and pulse width of the electrical stimulation complex waveform according to the output of the parameter optimization engine 41. This unit receives the optimized parameter instructions and accurately adjusts the parameters of the output waveform. Preferably, the waveform modulation unit 43 can adjust the parameters within the following ranges:

[0114] Fundamental frequency: 8-12Hz, step 0.5Hz;

[0115] Micro-oscillation frequency: 60-80Hz, step 5Hz;

[0116] Pulse width: 200-400μs, step 20μs;

[0117] Amplitude: 1-10mA, step 0.5mA;

[0118] The information flow between the three units is as follows: the impedance monitoring unit 42 collects acupoint area impedance data in real time and transmits it to the parameter optimization engine 41; the parameter optimization engine 41 combines impedance data and immune metabolic coupling index to generate optimized parameters through Q-learning algorithm; the waveform modulation unit 43 receives the optimized parameters and adjusts the electrical stimulation output waveform to act on the patient's acupoint, forming a closed-loop control.

[0119] As Figure 6As shown, the drug administration control module 5 is configured to trigger the administration of the PD-1 inhibitor when it is detected that the PD-1 expression level reaches 135±5% of the baseline, and the dosage of the PD-1 inhibitor is 1 / 3 of the conventional treatment dosage.

[0120] The medication control module 5 includes a window period monitoring unit 51 , a dosage calculation unit 52 and a medication execution unit 53 .

[0121] The window period monitoring unit 51 is used to receive PD-1 expression window period information from the data analysis and processing module 3 and continuously monitor whether the patient's PD-1 expression level reaches the dosing window. Preferably, this unit adopts a dual-threshold judgment mechanism. When the PD-1 expression level reaches 130% of the baseline for the first time, it enters the warning state. When the expression level stabilizes in the range of 135±5% for more than 30 minutes, it is confirmed that the optimal dosing window has been entered.

[0122] The dose calculation unit 52 is used to calculate the precise dose of the PD-1 inhibitor based on the patient's weight, tumor type, and immune metabolic coupling index. Preferably, the unit uses the following formula to calculate the dose:

[0123] ,

[0124] Wherein, Dose represents the calculated dose; represents the standard dose (mg / kg); represents the patient's weight (kg); represents the fine-tuning coefficient based on IMCI, ranging from 0.8 to 1.2.

[0125] The drug administration execution unit 53 is used to control the precise administration of the PD-1 inhibitor according to the dosage calculation results. Preferably, the unit supports two administration modes:

[0126] 1. Automatic drug delivery mode: connect to the infusion pump to precisely control the drug delivery rate and dosage;

[0127] 2. Assisted medication administration mode: Generates detailed medication instructions to assist medical staff in completing manual medication administration;

[0128] Information flows between the three units as follows: Window period monitoring unit 51 continuously monitors PD-1 expression levels and sends a signal to dose calculation unit 52 when the dosing window is reached. Dose calculation unit 52 combines patient information and the IMCI index to calculate the precise dose. Dosing execution unit 53 receives the dose information and executes the dosing operation. The entire process automates the entire process from biomarker monitoring to precise drug delivery.

[0129] like Figure 7 As shown, the immune memory strengthening module 6 includes a memory T cell detection unit 61 , a periodic training plan unit 62 and an immune memory persistence prediction unit 63 .

[0130] The memory T cell detection unit 61 is used to monitor the proportion of CD8+CD45RO+CD62L+ memory T cells. This unit detects the change in the proportion of memory T cells in peripheral blood by flow cytometry technology. Preferably, this unit uses a microfluidic chip combined with fluorescently labeled antibodies to achieve accurate analysis of CD8+CD45RO+CD62L+ central memory T cells and CD8+CD45RO+CD62L- effector memory T cells. The detection frequency is once a week, and the sample size is 2 mL of peripheral blood.

[0131] The periodic training plan unit 62 is used to generate a 21-day / cycle electrical stimulation-drug synergistic intervention scheme. This unit automatically generates an individualized periodic training plan based on the memory T cell detection results. Preferably, a complete training cycle includes:

[0132] Electrical stimulation phase: 1-14 days, 2 times a day, 30 minutes each time;

[0133] Drug administration: single administration at the peak of the electrical stimulation effect (usually on the 10th-12th day);

[0134] Recovery phase: 15-21 days, no intervention, observe the consolidation of immune memory;

[0135] The immune memory durability prediction unit 63 is used to predict the duration of immune memory based on the change in the proportion of CD8+ memory T cells. This unit predicts the durability of immune memory by analyzing the dynamic changes in the proportion of memory T cells after multiple cycles of training. Preferably, this unit uses the following prediction model:

[0136] ,

[0137] where, represents the predicted duration of immune memory; represents the base duration (constant, usually 3 months); represents the disease-specific coefficient, ranging from 1.5 to 2.5; represents the increase in the proportion of memory T cells relative to the baseline.

[0138] The information flow between the three units is as follows: the memory T cell detection unit 61 regularly collects and analyzes memory T cell data, which is transmitted to the periodic training plan unit 62 and the immune memory durability prediction unit 63; the periodic training plan unit 62 generates the next cycle training plan based on the cell data; the immune memory durability prediction unit 63 predicts the durability of immune memory in combination with historical data, which is fed back to the system for long-term treatment planning.

[0139] As Figure 8As shown, the data analysis processing module 3 is also used to construct the optimal trajectory of immune metabolic state space, and the target state region of the optimal trajectory is defined as {PD1: 135±5%, ATP: >200%, IL2: >150%}; the deviation vector of the current immune metabolic state and the target state region is calculated.

[0140] The enhanced functions of the data analysis processing module 3 include an optimal trajectory planning unit 34 and a deviation calculation unit 35.

[0141] The optimal trajectory planning unit 34 is used to construct the optimal trajectory from the current state to the target state region in the three-dimensional immune metabolic state space. This unit adopts a dynamic programming algorithm, considers the biological feasibility of system state transition, and plans a state transition path with the minimum energy consumption and the best treatment effect. Preferably, the target state region is defined as:

[0142] PD-1 expression: 135±5% of baseline;

[0143] ATP content: >200% of baseline;

[0144] IL-2 secretion: >150% of baseline;

[0145] This state combination represents that the T cells have both appropriate levels of PD-1 expression (favorable for low-dose drug to play a role) and sufficient energy supply (high level of ATP) and activation ability (high level of IL-2).

[0146] The deviation calculation unit 35 is used to calculate the deviation vector of the current immune metabolic state and the target state region. This unit quantifies the treatment process by calculating the Euclidean distance between the current state vector and the center point of the target region. Preferably, the deviation vector calculation formula is:

[0147] ,

[0148] wherein, represents the deviation vector at time point ; represents the state vector at time point ; represents the target state vector .

[0149] The information flow between the two units is as follows: the optimal trajectory planning unit 34 first constructs the optimal trajectory according to the initial state of the patient and the target state region; then the deviation calculation unit 35 calculates the deviation vector of the current state and the target state in real time; the deviation information and the trajectory planning are fed back to the electrical stimulation control module 4, guiding the dynamic adjustment of the electrical stimulation parameters, ensuring that the immune metabolic state of the patient converges to the target region along the optimal trajectory.

[0150] As shown in Figure 9 The system of the present application further comprises a treatment effect evaluation module 7 connected with the data analysis processing module 3, for generating a treatment effect evaluation report based on the change trend of the immune metabolism coupling index; a remote monitoring module 8 connected with the data analysis processing module 3, for transmitting the patient's immune metabolism state data to the doctor's terminal and receiving the doctor's treatment scheme adjustment instruction.

[0151] The treatment effect evaluation module 7 comprises a short-term effect evaluation unit 71 and a long-term therapeutic effect prediction unit 72.

[0152] The short-term effect evaluation unit 71 is used to analyze the dynamic change of the immune metabolism coupling index during treatment and evaluate the immediate effect of treatment. Preferably, this unit adopts the following evaluation criteria:

[0153] IMCI rises by >30%: good treatment response;

[0154] IMCI rises by 10%-30%: treatment is effective;

[0155] IMCI rises by <10%: limited treatment effect;

[0156] IMCI decreases: treatment is ineffective and needs to be adjusted;

[0157] The long-term therapeutic effect prediction unit 72 is used to predict the long-term treatment effect according to the change trend of the immune metabolism coupling index and the proportion of memory T cells. Preferably, this unit adopts a machine learning algorithm combined with a historical patient database to predict the disease progression-free survival and overall survival, providing a basis for treatment scheme adjustment.

[0158] The remote monitoring module 8 comprises a data transmission unit 81 and a scheme adjustment unit 82.

[0159] The data transmission unit 81 is used to transmit the patient's immune metabolism state data in real time to the doctor's workstation through an encrypted network connection. Preferably, this unit adopts a medical-grade data encryption protocol to ensure data transmission security; at the same time, it realizes the function of local data caching to ensure data integrity in case of network interruption.

[0160] The scheme adjustment unit 82 is used to receive the treatment scheme adjustment instruction sent by the doctor through the remote terminal and convert it into a parameter setting executable by the system. Preferably, this unit provides a graphical interface, allowing the doctor to intuitively view the changes in the patient's immune metabolism state and adjust the treatment parameters through simple operations.

[0161] The information flow between the two modules is as follows: the data analysis and processing module 3 transmits the immune metabolism data to the treatment effect evaluation module 7 and the remote monitoring module 8 at the same time; the evaluation report generated by the treatment effect evaluation module 7 is transmitted to the doctor terminal through the remote monitoring module 8; the adjustment instructions sent by the doctor through the remote monitoring module 8 are fed back to each functional module of the system, realizing remote monitoring and adjustment.

[0162] As shown in Figure 10 The transcutaneous acupoint electrical stimulation method for regulating immune checkpoints provided by the present application comprises the following steps:

[0163] Step S1: Collecting peripheral blood of the patient, detecting the PD-1 basic expression level and IL-2 secretion capacity of CD8+ T cells, and establishing a set of immune metabolism baseline indicators of the patient.

[0164] In this step, first, 5 mL of peripheral blood of the patient is collected, the PD-1 expression level on the surface of CD8+ T cells is detected by flow cytometry, the IL-2 secretion level is detected by ELISA method, and the ATP content is detected by luciferase method. The measurement results are used as the baseline values of the patient, which are used for the calculation of the subsequent relative changes. Preferably, the baseline data collection is carried out continuously for 3 days before the treatment starts, and the mean value is taken as the final baseline value to eliminate the influence of physiological fluctuations.

[0165] Step S2: Selecting an acupoint combination based on the patient's constitution and tumor type, and implementing compound waveform electrical stimulation with superposition of 10Hz basic carrier and 65-75Hz high-frequency micro-oscillation on Guanyuan acupoint and Zusanli acupoint.

[0166] In this step, the best acupoint combination is selected from the acupoint database according to the patient's constitution and tumor type. For most solid tumor patients, the combination of Guanyuan acupoint and Zusanli acupoint is preferred; for hematological tumor patients, Xuehai acupoint can be added; for liver cancer patients, Taichong acupoint can be added. The electrical stimulation adopts a compound waveform with superposition of 10Hz basic carrier and 65-75Hz high-frequency micro-oscillation, the pulse width is 300us, the amplitude is initially set to 3mA, the stimulation-rest ratio is 2:1 (stimulation phase 40 seconds, rest phase 20 seconds), each stimulation is 30 minutes, and the stimulation is carried out twice a day.

[0167] Step S3: Collecting peripheral blood of the patient every 2-6 hours, real-time monitoring of T cell PD-1 expression change, ATP content and IL-2 secretion level, and constructing an immune metabolism state vector.

[0168] In this step, 50ul of peripheral blood is automatically collected every 2-6 hours through a microneedle array, and the T cell PD-1 expression amount, ATP content and IL-2 secretion level are separated and detected through a microfluidic chip. The detection results are standardized and constructed into a three-dimensional immune metabolism state vector The state vector is transmitted to the data analysis processing module in real time for subsequent calculation and decision-making. We will adopt a hierarchical adaptive sampling strategy to dynamically adjust the sampling frequency according to different stages of treatment. Specifically, in the baseline establishment stage, sampling is performed every 4 hours, in the initial response stage of electrical stimulation (1-2 days), sampling is performed every 2 hours, in the window period monitoring stage, sampling is performed every 1 hour, and after entering the stable period, the sampling frequency is reduced to every 4-6 hours. At the same time, the single sampling volume can be reduced to 30 μL, ensuring that the total daily sampling volume is much lower than the conventional venous blood examination volume, and minimizing the burden on patients.

[0169] To make up for the lack of data density that may be caused by the reduction of actual sampling frequency, we will use a time series deep learning model combined with a physiological kinetic model to achieve high-precision data interpolation prediction. By constructing a continuous change curve with limited actual sampling points, we can achieve virtual 15-minute granularity monitoring. The prediction model is based on the existing immunotherapy biomarker kinetic rules, which can greatly reduce the actual blood sampling frequency while ensuring accuracy.

[0170] In addition, we will also integrate non-invasive monitoring methods as a supplement, such as transcutaneous immune activity monitoring based on spectral technology and acupoint area microdialysis technology, to further reduce the dependence on microneedle blood sampling and improve the overall practicality and patient acceptance of the system.

[0171] The system is also equipped with patient biological load monitoring function to assess the impact of sampling on patients in real time and automatically adjust the sampling strategy when abnormalities are detected to ensure safety.

[0172] Step S4: Calculate the immune metabolism coupling index to identify the PD-1 expression window period.

[0173] In this step, based on the immune metabolism state vector, the immune metabolism coupling index is calculated, where is a dynamic weight coefficient based on the patient's tumor type, PD1_ratio is the ratio of T cell surface PD-1 expression to baseline value, ATP_ratio is the ratio of T cell mitochondrial ATP content to baseline value, and IL2_ratio is the ratio of IL-2 secretion to baseline value. At the same time, the change of PD-1 expression relative to the baseline is monitored, and when it reaches 135±5% and remains stable (fluctuation <3% for 3 consecutive measurements), it is identified as the PD-1 expression window period. The IMCI index and window period information are used to guide the subsequent electrical stimulation parameter adjustment and drug administration timing.

[0174] Step S5: When the PD-1 expression reaches 135±5% of the baseline, give the patient 1 / 3 of the regular dose of PD-1 inhibitor.

[0175] In this step, once PD-1 expression reaches the target window period (135 ± 5% of baseline), the PD-1 inhibitor is administered at 1 / 3 of the regular dose. Preferably, for different PD-1 inhibitors, the dose administered is: 70 mg of pembrolizumab (35% of the regular 200 mg) or 80 mg of nivolumab (33% of the regular 240 mg). The administration method follows the requirements of the drug instructions, usually intravenous infusion for 30 minutes.

[0176] Step S6: Monitor the change in the proportion of CD8+ memory T cells and evaluate the durability of immune memory.

[0177] In this step, the proportion of CD8+CD45RO+CD62L+ central memory T cells and CD8+CD45RO+CD62L- effector memory T cells in peripheral blood is detected once a week by flow cytometry. According to the growth curve of the proportion of memory T cells, the durability of immune memory is predicted, and the long-term effect of treatment is evaluated. Preferably, when the proportion of CD8+ memory T cells reaches more than 200% of the baseline and remains stable for 3 consecutive weeks, it is determined that the immune memory is well formed.

[0178] Step S7: Dynamically adjust the electric stimulation parameters and treatment regimen based on the change in the immune metabolic coupling index and the proportion of memory T cells.

[0179] In this step, the electric stimulation parameters and treatment regimen are dynamically adjusted according to the IMCI index change trend and the proportion of memory T cells. Preferably, the adjustment strategy is as follows:

[0180] If the IMCI rises by <10%, increase the electric stimulation frequency to 12 Hz and extend the stimulation time to 40 minutes;

[0181] If the IMCI rises by 10%-30%, maintain the current parameters unchanged;

[0182] If the IMCI rises by >30%, consider reducing the stimulation frequency to once a day;

[0183] If the proportion of memory T cells increases by <50%, increase the electric stimulation-drug synergistic cycle to 42 days;

[0184] If the proportion of memory T cells increases by >200%, consider extending the treatment interval and performing intensive treatment once every 2-3 months;

[0185] Application case: application in melanoma patients

[0186] The following shows the actual effect of the present application through a specific application case.

[0187] The case selects 60 patients with advanced melanoma and divides them into three groups: 20 patients in group A receive only a conventional dose of PD-1 inhibitor treatment; 20 patients in group B receive percutaneous acupoint electrical stimulation combined with a conventional dose of PD-1 inhibitor treatment; and 20 patients in group C receive percutaneous acupoint electrical stimulation regulation of the immune checkpoint system treatment (electrical stimulation + low-dose PD-1 inhibitor). The patients in the three groups are balanced and comparable in terms of age, gender, disease stage and other baseline characteristics.

[0188] The treatment effect evaluation shows that:

[0189] 1. Objective response rate (ORR): 40% (8 / 20) in group A, 50% (10 / 20) in group B, and 55% (11 / 20) in group C;

[0190] 2. Disease control rate (DCR): 60% (12 / 20) in group A, 70% (14 / 20) in group B, and 75% (15 / 20) in group C;

[0191] 3. Median progression-free survival (PFS): 4.5 months in group A, 6.2 months in group B, and 7.1 months in group C;

[0192] 4. Immune-related adverse reactions (irAE): 45% (9 / 20) in group A, 40% (8 / 20) in group B, and 15% (3 / 20) in group C;

[0193] 5. Treatment cost: based on a three-month cycle, the average cost is 120,000 yuan in group A, 130,000 yuan in group B, and 56,000 yuan in group C;

[0194] Through comparative analysis, it can be seen that the percutaneous acupoint electrical stimulation regulation of the immune checkpoint system provided by the application not only has better or equivalent efficacy than conventional immunotherapy, but also significantly reduces the incidence of adverse reactions and treatment costs. In particular, in terms of immune memory persistence, 75% of patients in group C still maintain disease control status 3 months after treatment, which is significantly better than the 40% in group A and the 55% in group B.

[0195] Immune metabolism index analysis shows that patients in group C exhibit ideal immune metabolism characteristics during treatment: PD-1 expression reaches 130% to 140% of the baseline 7 to 10 days after electrical stimulation begins; ATP content is stably maintained at 220% to 250% of the baseline; and IL-2 secretion reaches 180% to 200% of the baseline. This combination of characteristics creates ideal conditions for low-dose PD-1 inhibitors to achieve optimal results.

[0196] In addition, the proportion of CD8+ memory T cells of the patients in group C reached 250% of the average of the baseline at the end of treatment, while that of group A was only 130% and that of group B was 160%. This shows that the immune memory enhancement effect of the application is significantly better than the conventional treatment, which provides a guarantee for long-term treatment effect.

[0197] The application case fully proves the significant advantages of the application in improving curative effect, reducing adverse reactions and reducing treatment cost, and has a broad clinical application prospect.

[0198] The above only describes the preferred embodiments of the application, and does not limit the patent protection scope of the application, and any equivalent structural transformation made under the inventive concept of the application, using the content of the specification and drawings, or directly / indirectly applied in other related technical fields, are also included in the patent protection scope of the application.

Claims

1. Transcutaneous acupoint electrical stimulation regulation of immune checkpoint system, characterized in that, Comprise: An immune checkpoint expression adaptive adjustment module for generating an electrical stimulation signal of a specific frequency, the specific frequency comprising a composite waveform of a 10 Hz base carrier wave superimposed with a 65-75 Hz high-frequency micro-oscillation; An immune metabolism fingerprint collection module connected with the immune checkpoint expression adaptive adjustment module for collecting the amount of PD-1 expression on the surface of T cells, the content of ATP, and the amount of IL-2 secretion of a patient, and generating an immune metabolism state vector; A data analysis processing module connected with the immune metabolism fingerprint collection module for receiving the immune metabolism state vector, calculating an immune metabolism coupling index, and identifying a PD-1 expression window period; An electrical stimulation control module connected with the data analysis processing module for dynamically adjusting electrical stimulation parameters according to the immune metabolism coupling index; A drug administration control module connected with the data analysis processing module and the electrical stimulation control module for triggering low-dose PD-1 inhibitor administration when the PD-1 expression window period is detected; An immune memory strengthening module connected with the data analysis processing module and the drug administration control module for monitoring changes in the proportion of CD8+ memory T cells and generating immune memory persistence prediction data; The data analysis processing module comprises: An immune metabolism state vector construction unit for constructing a three-dimensional immune metabolism state vector of a patient, the vector comprising the amount of PD-1 expression, the content of ATP, and the amount of IL-2 secretion; The coupling index calculation unit is used to calculate the immunometabolism coupling index IMCI, wherein the IMCI is calculated by the formula IMCI= a × PD1_ratio + β × ATP_ratio + γ × IL2_ratio Calculated, where is a dynamic weight coefficient based on the patient's tumor type, PD1_ratio is the ratio of PD-1 expression on the T cell surface relative to the baseline value, ATP_ratio is the ratio of ATP content in T cell mitochondria relative to the baseline value, and IL2_ratio is the ratio of IL-2 secretion relative to the baseline value; An expression window period identification unit for identifying an optimal treatment window period when the amount of PD-1 expression reaches 130%-140% of the baseline, identifying the time point when the amount of PD-1 expression reaches the ideal treatment window period by analyzing the dynamic change curve of the amount of PD-1 expression, providing a precise timing for drug administration, and adopting a sliding window algorithm to confirm entry into the treatment window period when the amount of PD-1 expression at three consecutive sampling points is within the target interval of 30%-140%; The electrical stimulation control module comprises: A parameter optimization engine for dynamically adjusting electrical stimulation parameters based on the immune metabolism coupling index through a pre-trained Q-learning model; An impedance monitoring unit for monitoring changes in tissue impedance in the acupoint area in real time and providing feedback data to the parameter optimization engine; A waveform modulation unit for adjusting the frequency and pulse width of the electrical stimulation composite waveform according to the output of the parameter optimization engine.

2. The system of claim 1, wherein, The immune checkpoint expression adaptive adjustment module comprises: An acupoint positioning unit for determining the precise coordinate positions of Guanyuan and Zusanli acupoints; An electrical stimulation waveform generation unit for generating the composite waveform of the 10 Hz base carrier wave superimposed with the 65-75 Hz high-frequency micro-oscillation, the pulse width of the composite waveform being 300 μs; A stimulation timing control unit for controlling a stimulation-rest ratio of 2:1, wherein the stimulation phase is 40 seconds and the rest phase is 20 seconds.

3. The system of claim 1, wherein, The immune metabolism fingerprint collection module comprises: A micro-sampling unit for automatically collecting 50 μL of peripheral blood every 2-6 hours through a microneedle array; a microfluidic detection unit configured to receive the peripheral blood sample and detect the expression level of PD-1 on the surface of T cells by fluorescence resonance energy transfer technology; an ATP bioluminescence detection unit configured to detect the content of mitochondrial ATP in the T cells in the peripheral blood; an IL-2 fluorescence immunoassay unit configured to detect the secretion level of IL-2 in the peripheral blood.

4. The system of claim 1, wherein, The administration control module is configured to: trigger administration of the PD-1 inhibitor when the expression level of PD-1 reaches 135±5% of the baseline; the dose of the PD-1 inhibitor is 1 / 3 of the conventional therapeutic dose.

5. The system of claim 1, wherein, The immune memory enhancement module includes: a memory T cell detection unit configured to monitor the proportion of CD8+CD45RO+CD62L+ memory T cells; a periodic training plan unit configured to generate an electrical stimulation-drug synergistic intervention scheme of 21 days / cycle; an immune memory persistence prediction unit configured to predict the duration of immune memory based on the change in the proportion of CD8+ memory T cells.

6. The system of claim 1, wherein, The data analysis processing module is further configured to: construct an optimal trajectory in the immune metabolic state space, and define a target state region of the optimal trajectory as {PD1: 135±5%, ATP: >200%, IL2: >150%}; calculate a deviation vector of the current immune metabolic state from the target state region.

7. The system of claim 1, wherein, The system further includes: a treatment effect evaluation module connected to the data analysis processing module and configured to generate a treatment effect evaluation report based on the change trend of the immune metabolic coupling index; a remote monitoring module connected to the data analysis processing module and configured to transmit the immune metabolic state data of the patient to a doctor terminal and receive the doctor's treatment scheme adjustment instruction.

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