Nanometer delivery device for gastric cancer targeted drug and use method of nanometer delivery device

Abstract

The invention discloses a nanometer delivery device for a gastric cancer targeted drug and a use method of the nanometer delivery device, and belongs to the technical field of drug targeted delivery. The device comprises a molecular recognition and optimization module which is responsible for accurately recognizing a tumor cell specific molecular marker and providing personalized treatment strategy recommendation; the nano-carrier design module is used for designing multifunctional lipid-polymer hybrid nano-particles and carrying out surface targeting ligand modification; the intelligent drug loading module is used for improving the stability and controllability of drug loading based on a pH / temperature sensitive release mechanism and effectively reducing the toxic influence of non-targeted tissues; the molecular imaging and monitoring module integrates a nanoprobe imaging technology and a quantum dot tracing technology, constructs a treatment-imaging integrated system, realizes real-time dynamic monitoring of a treatment process, and provides instant feedback of a molecular level; and the risk assessment module is used for establishing a safety database and providing dynamic risk assessment of the treatment process through a biological safety assessment system and long-term tracking management.

Description

Technical Field

[0001] The present application relates to the technical field of targeted drug delivery, and more specifically, to a nano-delivery device for gastric cancer targeted drugs and a method for using the same. Background Art

[0002] Gastric cancer is one of the malignant tumors with the highest morbidity and mortality rates worldwide. Traditional treatments mainly include surgical resection, chemotherapy, and radiotherapy, but these methods often have problems such as unstable efficacy, large side effects, and inability to accurately locate tumors, resulting in low survival rates for patients. In recent years, targeted drug therapy, as a new treatment strategy, has greatly improved the treatment effect and reduced damage to normal tissues by precisely targeting specific molecular targets of tumor cells. However, there are still significant challenges in the delivery efficiency and accuracy of targeted drugs in the body.

[0003] At present, nanotechnology is widely used in the field of drug delivery, which can effectively improve the bioavailability of drugs and optimize the targeting of drugs through the size and surface modification of nanocarriers. However, traditional nano drug delivery systems often face the following problems in practical applications: first, the drug loading capacity of nanocarriers is limited, which is difficult to meet the needs of large doses of drugs; second, the time and location of drug release are difficult to accurately control, which often leads to uneven distribution of drugs in the body and affects the therapeutic effect; third, there is a lack of real-time monitoring and adjustment mechanisms during drug delivery, and it is impossible to optimize the treatment plan in a timely manner according to the individual differences of patients.

[0004] In order to overcome these technical bottlenecks, research in recent years has begun to focus on the development of nano-delivery systems with high drug loading capacity, precise release, and controllable monitoring. Through intelligent design and biocompatibility optimization, it is expected to improve drug delivery efficiency while reducing side effects and achieving personalized treatment. Although some nano-drug delivery systems have been put into clinical application, how to solve their technical problems in precise targeting, drug loading and release regulation, real-time monitoring, etc., is still the focus and difficulty of current research.

[0005] In summary, how to achieve controlled release, real-time monitoring and personalized treatment of drugs while ensuring efficient targeted drug delivery has become a technical problem that needs to be solved urgently. Summary of the invention

[0006] In order to overcome a series of defects in the prior art, the purpose of this application is to provide a nano delivery device for gastric cancer targeted drugs, including the following modules:

[0007] The molecular recognition and optimization module is responsible for accurately identifying tumor cell-specific molecular markers and integrating clinical and genomic data to provide personalized treatment strategy recommendations;

[0008] Nanocarrier design module, which designs multifunctional lipid-polymer hybrid nanoparticles and performs surface targeting ligand modification to significantly improve drug delivery efficiency by optimizing the carrier's biocompatibility, degradability and nanoparticle size;

[0009] Intelligent drug loading module, based on pH / temperature sensitive release mechanism, improves the stability and controllability of drug loading and effectively reduces the toxic effects on non-target tissues;

[0010] Molecular imaging and monitoring module, integrating nanoprobe imaging technology and quantum dot tracing technology, constructing a treatment-imaging integrated system, realizing real-time dynamic monitoring of the treatment process, and providing instant feedback at the molecular level;

[0011] The risk assessment module establishes a safety database and provides dynamic risk assessment of the treatment process through a biosafety assessment system and long-term follow-up management.

[0012] Furthermore, the molecular recognition and optimization module includes the following components:

[0013] The data collection unit is responsible for collecting patients’ genomic data, clinical data, transcriptomic data, and other relevant cross-omics data;

[0014] The data preprocessing and fusion unit standardizes, cleans and fuses the collected multi-dimensional data to ensure the high quality and consistency of the data;

[0015] Feature extraction unit, which extracts molecular marker features specifically related to tumor cells from cross-omics data and screens out potential targeting molecules;

[0016] Molecular marker identification unit, which analyzes patient data in real time and accurately identifies specific molecular markers associated with tumor cells;

[0017] The personalized treatment strategy generation unit combines the patient's clinical data and genomic information to generate a tailored personalized treatment plan and recommend the best targeted drug or treatment strategy;

[0018] The Molecular Optimization and Simulation Unit performs molecular-level optimization and drug-target interaction simulation based on the identified molecular markers to ensure that the selected targets can effectively interact with the drugs.

[0019] Furthermore, potential targeting molecules were screened out by the following formula:

[0020]

[0021] Among them, X fusion is the fused data matrix, with dimension (n fusion , mfusion ), where n fusion is the number of features, m fusion is the sample size; Y tumor is the tumor sample label, with a dimension of (1, m fusion ); W is the regression coefficient; is the estimated value of W, that is, the best regression coefficient obtained by data fitting, which represents the relationship between the input features and tumor markers; ||W||1 is the L1 norm, which is used to select sparse features; λ is the regularization parameter;

[0022] A tailor-made, personalized treatment plan is generated using the following formula:

[0023]

[0024] Among them, H * represents the optimal personalized treatment plan generated; H represents the set of possible treatment plans; Cost(H, D) is the treatment cost of treatment plan H under given patient data D; δ is the weight coefficient for balancing the relationship between treatment cost and risk; Risk(H) is the risk brought by treatment plan H.

[0025] Furthermore, the nanocarrier design module includes the following components:

[0026] The carrier material selection unit selects lipid and polymer materials according to drug properties and targeting requirements to ensure the stability, drug loading capacity and biocompatibility of the carrier;

[0027] The carrier synthesis unit fuses lipids and polymers to form multifunctional lipid-polymer hybrid nanoparticles, ensuring that the carrier has a stable structure and excellent drug loading capacity;

[0028] The surface modification unit connects the targeting ligand to the surface of the nanoparticle through chemical modification, ensuring that the carrier can accurately recognize and target tumor cells;

[0029] The particle size control unit adjusts the particle size range of nanoparticles to optimize particle distribution, cell penetration and drug delivery efficiency while avoiding immune responses caused by overly large particles;

[0030] The biocompatibility optimization unit is responsible for improving the biocompatibility of nanocarriers, reducing the recognition and clearance of the immune system, and prolonging the circulation time of the carriers in the body;

[0031] The degradability planning unit ensures that the carrier can be cleared through biodegradation pathways after drug release, reducing long-term toxicity and avoiding accumulation of carrier materials in the body.

[0032] Furthermore, the particle size range of the nanoparticles is adjusted by the following comprehensive optimization function: O(d) = w1·D(d) + w2·E(d) + w3·R(d) - w4·I(d), where O(d) is a comprehensive optimization function used to describe the optimization process of various factors considered when adjusting the particle size d of the nanoparticles; w1 is the importance of the particle distribution target; w2 is the optimization importance of cell permeability; w3 is the optimization importance of drug delivery efficiency; w4 is the optimization importance of immune response; D(d) represents the influence function of particle size d on particle distribution, and the formula is: k B is the Boltzmann constant; T is the temperature that affects the behavior of nanoparticles; η represents the drug loading efficiency of nanoparticles; E(d) represents the effect function of particle size d on cell permeability, and the formula is: d0 represents the initial particle size, that is, the initial size of the nanoparticles during synthesis; A is a constant coefficient related to material properties and drug release rate factors; B is a constant coefficient related to the stability of the carrier and cell absorption efficiency factors; R(d) represents the effect function of particle size d on drug delivery efficiency, and the formula is: α represents the regulatory factor related to particle size; C is a constant coefficient related to the immune response inhibition effect and carrier biocompatibility; I(d) represents the effect function of particle size d on immune response, and the formula is: C1 represents constant 1 in the particle size adjustment process; d1 represents the lower limit of the ideal particle size range, which is used to define the lower limit of the particle size in the optimization process; C2 represents constant 2 in the particle size optimization process.

[0033] Furthermore, the smart drug loading module includes the following components:

[0034] The drug release control unit regulates the release rate and extent of drugs in the tumor microenvironment based on the characteristics of pH / temperature sensitive materials, ensuring accurate drug release and reducing toxicity to non-target tissues;

[0035] The stability enhancement unit improves the stability of the drug load by optimizing the carrier surface structure and intermolecular interactions, thus preventing the drug from being released or cleared prematurely in the body;

[0036] Targeted release trigger unit, which activates the drug release mechanism through pH / temperature changes in the targeted tissue or tumor environment, ensuring that the drug works only in the target area and reduces the impact on healthy tissue;

[0037] Loading efficiency monitoring unit, which monitors the loading efficiency and release process of drugs in the carrier to ensure that the loading amount, stability and controllability of the drugs meet the treatment needs;

[0038] The side effect reduction unit reduces the systemic toxicity and side effects of drugs by precisely controlling the release time and concentration of drugs and reducing the exposure of drugs in non-target areas.

[0039] Furthermore, the molecular imaging and monitoring module includes the following components:

[0040] Nanoprobe design unit, which designs and synthesizes specific nanoprobes, combines imaging functions with drug carriers to ensure that they can be accurately positioned in the tumor area and provide high-resolution imaging signals;

[0041] The quantum dot tracing unit uses the fluorescence properties of quantum dots to perform highly sensitive tracing, tracking the distribution and dynamic changes of nanoparticles in the body in real time, and providing visual monitoring of drug delivery during treatment;

[0042] Imaging data acquisition unit, which collects imaging signals from nanoprobes and quantum dots, obtains tissue and drug distribution information during treatment in real time, and ensures accurate spatial positioning;

[0043] The image processing and analysis unit processes and analyzes the acquired imaging data to generate clear molecular images and extract key information about tumor areas and drug accumulation points;

[0044] Real-time dynamic monitoring unit, which monitors the delivery and release of drugs during treatment in real time, dynamically tracks the effect of tumor treatment, and provides feedback and adjustment to the treatment process;

[0045] The molecular feedback unit provides immediate feedback at the molecular level based on imaging results to help optimize treatment strategies.

[0046] Furthermore, the treatment process is feedback-regulated by the following formula:

[0047]

[0048]

[0049] in, is the derivative of drug concentration C(t) with time t, indicating the rate of change of drug concentration with time; dt is the time increment, which is used to describe the change of drug concentration in a small time interval; R0 is the initial drug delivery rate; α0 is the sensitivity parameter of feedback regulation, which determines the influence of feedback regulation on drug delivery rate; S tumor(t) is the tumor survival rate, which indicates the survival rate of tumor cells over time; S(t) is the drug release rate, which indicates the rate at which the drug is released from the treatment device or carrier into the body at a given time t; S0 is the initial tumor survival rate, which indicates the survival rate of tumor cells at the beginning of treatment; k is the efficacy parameter of the drug on tumor cells, which determines how the drug concentration affects the tumor survival rate; C(t) represents the concentration level of the drug in the body at a given time t; β is the sensitivity index of drug efficacy to concentration, which determines the nonlinear relationship between drug concentration and therapeutic effect.

[0050] Furthermore, the risk assessment module includes the following components:

[0051] The biosafety assessment unit evaluates the potential hazards and safety of nanocarriers and drugs to the human body through comprehensive analysis of their toxicity, immunogenicity and biocompatibility;

[0052] Clinical data monitoring unit, which collects and analyzes patients’ clinical data during treatment in real time, including physiological indicators, drug reactions and side effects;

[0053] Long-term follow-up management unit, to establish and maintain long-term health records for patients, track the effects of late-stage drug treatment, and ensure that safety changes over time are continuously monitored;

[0054] Safety database construction unit, integrating clinical data, drug reactions and biosafety test results to build a safety database;

[0055] Dynamic risk assessment unit, which dynamically assesses potential risks during treatment based on the treatment progress and real-time patient responses, and adjusts treatment plans in a timely manner based on changes;

[0056] The risk optimization and adjustment unit optimizes treatment strategies and drug delivery plans through a feedback mechanism, reduces possible risks during treatment, and ensures patient safety and treatment outcomes.

[0057] Furthermore, based on the treatment progress and the patient's real-time response, the potential risks during the treatment process are dynamically evaluated, and the treatment plan is adjusted in a timely manner according to the changes, including the following steps:

[0058] According to the patient's treatment goals, calculate the treatment effect index E τ , the formula is: Where, ΔV tumor represents the change in tumor volume, Δτ is the time interval;

[0059] Calculate the patient's comprehensive risk value R, the formula is: Among them, x j is the jth risk factor; f j (x j) is x j The risk function of j is the weight of the jth risk factor; n is the total number of risk factors;

[0060] According to the risk assessment results, calculate the new treatment parameter value P new , the formula is: Among them, P old is the current parameter; T R is the safety threshold of risk.

[0061] The purpose of the present application is also to provide a method for using a nano-delivery device for gastric cancer targeted drugs, comprising the following steps:

[0062] Integrate patients' genomic data, clinical information and multi-omics data to accurately identify specific molecular markers of tumor cells, develop personalized treatment plans and recommend the best targeted drugs;

[0063] Design lipid-polymer hybrid nanoparticles to significantly improve their targeting ability to tumor cells through surface targeting ligand modification, particle size regulation, and biocompatibility optimization;

[0064] Load targeted drugs into nanoparticles and use pH and temperature sensitive release mechanisms to achieve drug stability and controllability;

[0065] Deliver nanocarriers to the tumor area through blood circulation, and use high-resolution imaging technology to monitor the distribution and dynamic changes of nanoparticles in the body in real time, while recording drug delivery and release to provide immediate feedback on the treatment effect;

[0066] The patient's physiological indicators and drug response data are collected in real time, and dynamic risk assessment is performed in combination with the safety database. Based on the monitoring results, drug delivery parameters and treatment strategies are adaptively adjusted to optimize efficacy and ensure patient safety.

[0067] Compared with the prior art, this application has the following beneficial effects:

[0068] This application achieves efficient targeted drug delivery and real-time treatment process monitoring by combining genomic data with clinical information, and dynamically optimizes treatment plans through an intelligent feedback mechanism, thereby significantly improving treatment outcomes and reducing side effects and risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a schematic diagram of the structure of a nano-delivery device for gastric cancer targeted drugs disclosed in an embodiment of the present application. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical scheme and advantages of the implementation of the present invention clearer, the technical scheme in the embodiment of the present invention will be described in more detail below in conjunction with the drawings in the embodiment of the present invention. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of the present invention, not all of the embodiments.

[0071] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0072] The embodiments and directional terms described below with reference to the accompanying drawings are exemplary and intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0073] like Figure 1 As shown, a nano delivery device for gastric cancer targeted drugs includes the following modules:

[0074] The molecular recognition and optimization module is responsible for accurately identifying tumor cell-specific molecular markers and integrating clinical and genomic data to provide personalized treatment strategy recommendations;

[0075] Nanocarrier design module, which designs multifunctional lipid-polymer hybrid nanoparticles and performs surface targeting ligand modification to significantly improve drug delivery efficiency by optimizing the carrier's biocompatibility, degradability and nanoparticle size;

[0076] Intelligent drug loading module, based on pH / temperature sensitive release mechanism, improves the stability and controllability of drug loading and effectively reduces the toxic effects on non-target tissues;

[0077] Molecular imaging and monitoring module, integrating nanoprobe imaging technology and quantum dot tracing technology, constructing a treatment-imaging integrated system, realizing real-time dynamic monitoring of the treatment process, and providing instant feedback at the molecular level;

[0078] The risk assessment module establishes a safety database and provides dynamic risk assessment of the treatment process through a biosafety assessment system and long-term follow-up management.

[0079] In this embodiment, the molecular recognition and optimization module is a key component of the gastric cancer targeted drug nano-delivery device, which is responsible for accurately identifying specific molecular markers of tumor cells. This module combines clinical data and genomic data to provide personalized treatment strategies. It uses high-precision biomarker screening technology to ensure that drugs can interact directly with tumor cells without unnecessary reactions with normal cells. This process is based on molecular features unique to the surface of tumor cells, such as specific receptors or mutation markers, such as HER2, EGFR, etc., to ensure the selectivity and efficiency of targeted drugs. By integrating clinical data and genomic data, it is also possible to customize and recommend the most suitable treatment plan based on individual differences of patients, thereby maximizing the efficacy. Accurate molecular recognition not only reduces the toxic effects on normal cells, but also enables effective personalized treatment in different subtypes of gastric cancer, thereby providing technical support for precision medicine.

[0080] In this embodiment, the nanocarrier design module is an important component to ensure the efficient delivery of targeted drugs. When designing multifunctional lipid-polymer hybrid nanoparticles, the module takes into account the biocompatibility, degradability and particle size control of the carrier by optimizing the combination mode of lipids and polymers. The design of lipid-polymer hybrid materials ensures the stability and sustained release ability of the drug in the body, and at the same time enables the carrier to modify the targeted ligand by adjusting the surface properties, thereby achieving accurate identification of tumor cells. By optimizing the particle size, the nanocarrier can effectively penetrate the vascular wall of the tumor tissue, enter the tumor cell interior, and improve the drug delivery efficiency. This carrier can not only carry high concentrations of drug molecules, avoiding the common problems of premature release of drugs or failure to reach the target in traditional drug delivery systems, but also its biodegradability ensures that after the drug is released, the carrier can be discharged from the body non-toxic and harmless.

[0081] In this embodiment, the core advantage of the intelligent drug loading module is that it regulates the loading stability and release process of the drug through a pH / temperature sensitive release mechanism. The design of this mechanism utilizes the special properties of the tumor microenvironment, such as low pH and high temperature, to promote the precise release of drugs in the tumor area. In normal tissues, the drug carrier remains stable, avoiding premature release of the drug, thereby reducing the toxic effects on healthy tissues. In the low pH environment of tumor tissue, the drug release mechanism of the nanocarrier is activated, and the drug is rapidly released to the targeted area to achieve targeted treatment of tumor cells. This intelligent drug loading mechanism not only enhances the therapeutic effect of the drug, but also minimizes the toxic effects on non-targeted tissues through an optimized release pattern. This precise control strategy, combined with the environmentally sensitive characteristics of pH / temperature, helps to improve the bioavailability of the drug, reduce the side effects of the drug, and provide a safer and more effective treatment plan for gastric cancer patients.

[0082] In this embodiment, the molecular imaging and monitoring module combines nanoprobe imaging technology and quantum dot tracing technology to form an integrated treatment-imaging system. The core of this module is to provide instant feedback at the molecular level by real-time monitoring of drug delivery and tumor treatment processes. Nanoprobes and quantum dots can be accurately imaged in vivo by combining with drug carriers, helping doctors observe the distribution of drugs in tumor tissues and evaluate the therapeutic effect in real time. In addition, molecular imaging technology can also reveal the response of tumor cells to drugs and determine whether the drugs effectively reach the target and work. The introduction of this module not only enhances the visualization ability of drug treatment, but also provides higher clinical diagnostic accuracy, which helps to optimize treatment plans and improve the success rate of targeted treatment for gastric cancer. Real-time dynamic monitoring enables the treatment process to be adjusted more flexibly and provide patients with personalized treatment plans.

[0083] In this embodiment, the risk assessment module establishes a comprehensive safety database through a biosafety assessment system and long-term tracking management to provide dynamic risk assessment for the treatment process. This module helps doctors to promptly discover and deal with potential safety issues by real-time monitoring of possible side effects and risks during the patient's treatment. In addition, the risk assessment module combines factors such as individual differences, drug reactions, and immune system status of patients to provide a scientific basis for the adjustment of treatment plans and reduce unforeseen risks during the treatment process. Through continuous biosafety assessment and long-term tracking data analysis, the safety database can be dynamically updated to ensure the adaptability and safety of treatment plans at different stages. The introduction of this module enhances the safety and accuracy of drug therapy, making gastric cancer treatment not only efficient, but also risk-controlled, and improving the overall safety guarantee during the treatment process.

[0084] In summary, the nano-delivery device for targeted gastric cancer drugs disclosed in this embodiment achieves precise, personalized and safe treatment effects through the cooperation of multiple highly integrated modules. The molecular recognition and optimization module provides precise targeted recognition, the nano-carrier design module optimizes the drug delivery efficiency, the intelligent drug loading module ensures the stability and controllable release of the drug, the molecular imaging and monitoring module provides real-time dynamic monitoring, and the risk assessment module provides risk management during treatment through biosafety assessment. The advantages of the nano-delivery device for targeted gastric cancer drugs lie in its comprehensiveness, intelligence and personalization, which provides a safer and more efficient treatment method for gastric cancer patients, greatly improving the effect and safety of targeted drug therapy.

[0085] Furthermore, the molecular recognition and optimization module includes the following components:

[0086] The data collection unit is responsible for collecting patients’ genomic data, clinical data, transcriptomic data, and other relevant cross-omics data;

[0087] The data preprocessing and fusion unit standardizes, cleans and fuses the collected multi-dimensional data to ensure the high quality and consistency of the data;

[0088] Feature extraction unit, which extracts molecular marker features specifically related to tumor cells from cross-omics data and screens out potential targeting molecules;

[0089] Molecular marker identification unit, which analyzes patient data in real time and accurately identifies specific molecular markers associated with tumor cells;

[0090] The personalized treatment strategy generation unit combines the patient's clinical data and genomic information to generate a tailored personalized treatment plan and recommend the best targeted drug or treatment strategy;

[0091] The Molecular Optimization and Simulation Unit performs molecular-level optimization and drug-target interaction simulation based on the identified molecular markers to ensure that the selected targets can effectively interact with the drugs.

[0092] In summary, the molecular recognition and optimization module plays a vital role in targeted drug therapy for gastric cancer. The data acquisition unit collects multidimensional data of patients, providing a comprehensive basis for subsequent analysis; the data preprocessing and fusion unit ensures the consistency and high quality of data; the feature extraction unit identifies key molecular markers from complex cross-omics data; the molecular marker recognition unit accurately identifies tumor-specific markers through real-time analysis; the personalized treatment strategy generation unit formulates a tailored treatment plan based on the specific situation of the patient; the molecular optimization and simulation unit improves the targeting and efficacy of drugs through simulation optimization of drugs and targets. This module not only improves the accuracy of gastric cancer treatment, but also provides strong data support and technical guarantee for personalized treatment, providing patients with safer and more effective treatment plans.

[0093] Furthermore, potential targeting molecules were screened out by the following formula:

[0094]

[0095] Among them, X fusion is the fused data matrix, with dimension (n fusion , m fusion ), where n fusion is the number of features, m fusion is the sample size; Y tumor is the tumor sample label, with a dimension of (1, m fusion ); W is the regression coefficient; is the estimated value of W, that is, the best regression coefficient obtained by data fitting, which represents the relationship between the input features and tumor markers; ||W||1 is the L1 norm, which is used to select sparse features; λ is the regularization parameter;

[0096] A tailor-made, personalized treatment plan is generated using the following formula:

[0097]

[0098] Among them, H * represents the optimal personalized treatment plan generated; H represents the set of possible treatment plans; Cost(H, D) is the treatment cost of treatment plan H under given patient data D; δ is the weight coefficient for balancing the relationship between treatment cost and risk; Risk(H) is the risk brought by treatment plan H.

[0099] In summary, by introducing regression analysis and L1 norm feature selection technology, the screening process of potential target molecules can accurately identify important tumor-related molecular markers from large-scale genomic and transcriptomic data. This process not only improves the efficiency of targeted drug research and development, but also enhances the accuracy of treatment, ensuring the scientificity and effectiveness of treatment targets. In terms of generating personalized treatment plans, by weighing the cost and risk of treatment, a tailored treatment plan can be generated according to the specific situation of the patient, ensuring the maximization of the treatment effect while reducing the risk of side effects and treatment failure.

[0100] Furthermore, the nanocarrier design module includes the following components:

[0101] The carrier material selection unit selects lipid and polymer materials according to drug properties and targeting requirements to ensure the stability, drug loading capacity and biocompatibility of the carrier;

[0102] The carrier synthesis unit fuses lipids and polymers to form multifunctional lipid-polymer hybrid nanoparticles, ensuring that the carrier has a stable structure and excellent drug loading capacity;

[0103] The surface modification unit connects the targeting ligand to the surface of the nanoparticle through chemical modification, ensuring that the carrier can accurately recognize and target tumor cells;

[0104] The particle size control unit adjusts the particle size range of nanoparticles to optimize particle distribution, cell penetration and drug delivery efficiency while avoiding immune responses caused by overly large particles;

[0105] The biocompatibility optimization unit is responsible for improving the biocompatibility of nanocarriers, reducing the recognition and clearance of the immune system, and prolonging the circulation time of the carriers in the body;

[0106] The degradability planning unit ensures that the carrier can be cleared through biodegradation pathways after drug release, reducing long-term toxicity and avoiding accumulation of carrier materials in the body.

[0107] In summary, the nanocarrier design module provides strong support for drug delivery through the synergistic effect of multiple units. The carrier material selection unit ensures the stability, drug loading capacity and biocompatibility of the carrier; the carrier synthesis unit combines lipids and polymers to form an efficient carrier structure; the surface modification unit achieves precise targeting through chemical modification of targeting ligands; the particle size control unit optimizes the distribution and cell permeability of nanoparticles; the biocompatibility optimization unit increases the circulation time of the carrier in the body by reducing the immune response; and the degradability planning unit ensures that the carrier can be cleared through biodegradation after drug release. Through the combination and optimization of these technologies, the nanocarrier design module can improve the efficiency and safety of drug delivery and ensure that nanomedicines achieve the best effect in clinical applications.

[0108] Furthermore, the particle size range of the nanoparticles is adjusted by the following comprehensive optimization function: O(d) = w1·D(d) + w2·E(d) + w3·R(d) - w4·I(d), where O(d) is a comprehensive optimization function used to describe the optimization process of various factors considered when adjusting the particle size d of the nanoparticles; w1 is the importance of the particle distribution target; w2 is the optimization importance of cell permeability; w3 is the optimization importance of drug delivery efficiency; w4 is the optimization importance of immune response; D(d) represents the influence function of particle size d on particle distribution, and the formula is: k B is the Boltzmann constant; T is the temperature that affects the behavior of nanoparticles; η represents the drug loading efficiency of nanoparticles; E(d) represents the effect function of particle size d on cell permeability, and the formula is: d0 represents the initial particle size, that is, the initial size of the nanoparticles during synthesis; A is a constant coefficient related to material properties and drug release rate factors; B is a constant coefficient related to the stability of the carrier and cell absorption efficiency factors; R(d) represents the effect function of particle size d on drug delivery efficiency, and the formula is: α represents the regulatory factor related to particle size; C is a constant coefficient related to the immune response inhibition effect and carrier biocompatibility; I(d) represents the effect function of particle size d on immune response, and the formula is: C1 represents constant 1 in the particle size adjustment process; d1 represents the lower limit of the ideal particle size range, which is used to define the lower limit of the particle size in the optimization process; C2 represents constant 2 in the particle size optimization process.

[0109] Furthermore, the smart drug loading module includes the following components:

[0110] The drug release control unit regulates the release rate and extent of drugs in the tumor microenvironment based on the characteristics of pH / temperature sensitive materials, ensuring accurate drug release and reducing toxicity to non-target tissues;

[0111] The stability enhancement unit improves the stability of the drug load by optimizing the carrier surface structure and intermolecular interactions, thus preventing the drug from being released or cleared prematurely in the body;

[0112] Targeted release trigger unit, which activates the drug release mechanism through pH / temperature changes in the targeted tissue or tumor environment, ensuring that the drug works only in the target area and reduces the impact on healthy tissue;

[0113] Loading efficiency monitoring unit, which monitors the loading efficiency and release process of drugs in the carrier to ensure that the loading amount, stability and controllability of the drugs meet the treatment needs;

[0114] The side effect reduction unit reduces the systemic toxicity and side effects of drugs by precisely controlling the release time and concentration of drugs and reducing the exposure of drugs in non-target areas.

[0115] In summary, the smart drug loading module achieves precise drug release and therapeutic specificity through the collaborative work of multiple technical units. The drug release regulation unit ensures the precise release of drugs in the tumor microenvironment based on the characteristics of pH / temperature sensitive materials; the stability enhancement unit improves the loading stability of the drug by optimizing the carrier structure; the targeted release trigger unit ensures that the drug is only released in the tumor area to reduce toxicity to healthy tissues; the loading efficiency monitoring unit monitors the drug loading and release process in real time to ensure the therapeutic effect; the side effect reduction unit reduces the systemic side effects of the drug by precisely controlling the release time and concentration. Through the precise design of these technical units, the smart drug loading module not only improves the therapeutic effect of the drug, but also significantly reduces side effects, promoting the development of precision medicine and targeted therapy.

[0116] Furthermore, the molecular imaging and monitoring module includes the following components:

[0117] Nanoprobe design unit, which designs and synthesizes specific nanoprobes, combines imaging functions with drug carriers to ensure that they can be accurately positioned in the tumor area and provide high-resolution imaging signals;

[0118] The quantum dot tracing unit uses the fluorescence properties of quantum dots to perform highly sensitive tracing, tracking the distribution and dynamic changes of nanoparticles in the body in real time, and providing visual monitoring of drug delivery during treatment;

[0119] Imaging data acquisition unit, which collects imaging signals from nanoprobes and quantum dots, obtains tissue and drug distribution information during treatment in real time, and ensures accurate spatial positioning;

[0120] The image processing and analysis unit processes and analyzes the acquired imaging data to generate clear molecular images and extract key information about tumor areas and drug accumulation points;

[0121] Real-time dynamic monitoring unit, which monitors the delivery and release of drugs during treatment in real time, dynamically tracks the effect of tumor treatment, and provides feedback and adjustment to the treatment process;

[0122] The molecular feedback unit provides immediate feedback at the molecular level based on imaging results to help optimize treatment strategies.

[0123] In summary, the molecular imaging and monitoring module provides real-time, precise treatment monitoring and feedback mechanisms through the collaborative work of multiple high-precision technical units. The nanoprobe design unit ensures that the drug can be accurately positioned and provides high-resolution imaging signals. The quantum dot tracer unit achieves high-sensitivity dynamic tracking through fluorescence characteristics. The imaging data acquisition unit provides precise spatial positioning data. The image processing and analysis unit generates clear molecular images and extracts key information. The real-time dynamic monitoring unit tracks drug delivery and release in real time, and the molecular-level feedback unit optimizes treatment strategies based on imaging data. The technical implementation of this module has greatly improved the accuracy and personalization of tumor treatment, helping doctors make scientific decisions based on real-time data, and ultimately promoting the development of targeted therapy and precision medicine.

[0124] Furthermore, the treatment process is feedback-regulated by the following formula:

[0125]

[0126]

[0127] in, is the derivative of drug concentration C(t) with time t, indicating the rate of change of drug concentration with time; dt is the time increment, which is used to describe the change of drug concentration in a small time interval; R0 is the initial drug delivery rate; α0 is the sensitivity parameter of feedback regulation, which determines the influence of feedback regulation on drug delivery rate; S tumor (t) is the tumor survival rate, which indicates the survival rate of tumor cells over time; S(t) is the drug release rate, which indicates the rate at which the drug is released from the treatment device or carrier into the body at a given time t; S0 is the initial tumor survival rate, which indicates the survival rate of tumor cells at the beginning of treatment; k is the efficacy parameter of the drug on tumor cells, which determines how the drug concentration affects the tumor survival rate; C(t) represents the concentration level of the drug in the body at a given time t; β is the sensitivity index of drug efficacy to concentration, which determines the nonlinear relationship between drug concentration and therapeutic effect.

[0128] Furthermore, the risk assessment module includes the following components:

[0129] The biosafety assessment unit evaluates the potential hazards and safety of nanocarriers and drugs to the human body through comprehensive analysis of their toxicity, immunogenicity and biocompatibility;

[0130] Clinical data monitoring unit, which collects and analyzes patients’ clinical data during treatment in real time, including physiological indicators, drug reactions and side effects;

[0131] Long-term follow-up management unit, to establish and maintain long-term health records for patients, track the effects of late-stage drug treatment, and ensure that safety changes over time are continuously monitored;

[0132] Safety database construction unit, integrating clinical data, drug reactions and biosafety test results to build a safety database;

[0133] Dynamic risk assessment unit, which dynamically assesses potential risks during treatment based on the treatment progress and real-time patient responses, and adjusts treatment plans in a timely manner based on changes;

[0134] The risk optimization and adjustment unit optimizes treatment strategies and drug delivery plans through a feedback mechanism, reduces possible risks during treatment, and ensures patient safety and treatment outcomes.

[0135] In summary, the risk assessment module constitutes a complete and dynamic treatment safety assurance system through the close collaboration of six technical units. The biosafety assessment unit ensures the biocompatibility and non-toxicity of the drug in the body, the clinical data monitoring unit collects the patient's treatment data in real time and evaluates the drug response, the long-term tracking management unit provides patients with health monitoring throughout their life cycle, the safety database construction unit provides historical data support, the dynamic risk assessment unit evaluates the risks during the treatment process in real time, and the risk optimization and adjustment unit adjusts the treatment plan based on real-time feedback to maximize the patient's treatment effect and safety. Through the implementation of this module, the safety of the treatment process can be significantly improved, adverse drug reactions and risks can be reduced, and the maximum benefit of patients in treatment can be ensured.

[0136] Furthermore, based on the treatment progress and the patient's real-time response, the potential risks during the treatment process are dynamically evaluated, and the treatment plan is adjusted in a timely manner according to the changes, including the following steps:

[0137] According to the patient's treatment goals, calculate the treatment effect index E τ , the formula is: Where, ΔV tumor represents the change in tumor volume, Δτ is the time interval;

[0138] Calculate the patient's comprehensive risk value R, the formula is: Among them, x j is the jth risk factor; f j (x j ) is x j The risk function of j is the weight of the jth risk factor; n is the total number of risk factors;

[0139] According to the risk assessment results, calculate the new treatment parameter value P new , the formula is: Among them, P old is the current parameter; T R is the safety threshold of risk.

[0140] The purpose of the present application is also to provide a method for using a nano-delivery device for gastric cancer targeted drugs, comprising the following steps:

[0141] Integrate patients' genomic data, clinical information and multi-omics data to accurately identify specific molecular markers of tumor cells, develop personalized treatment plans and recommend the best targeted drugs;

[0142] Design lipid-polymer hybrid nanoparticles to significantly improve their targeting ability to tumor cells through surface targeting ligand modification, particle size regulation, and biocompatibility optimization;

[0143] Load targeted drugs into nanoparticles and use pH and temperature sensitive release mechanisms to achieve drug stability and controllability;

[0144] Deliver nanocarriers to the tumor area through blood circulation, and use high-resolution imaging technology to monitor the distribution and dynamic changes of nanoparticles in the body in real time, while recording drug delivery and release to provide immediate feedback on the treatment effect;

[0145] The patient's physiological indicators and drug response data are collected in real time, and dynamic risk assessment is performed in combination with the safety database. Based on the monitoring results, drug delivery parameters and treatment strategies are adaptively adjusted to optimize efficacy and ensure patient safety.

[0146] The nano-delivery device for gastric cancer targeted drugs achieves precise, controllable and safe targeted therapy through the synergistic effect of multiple links. By integrating the patient's genomic data, clinical information and multi-omics data, it can accurately identify the molecular markers of tumor cells and formulate personalized treatment plans. The design optimization of lipid-polymer hybrid nanoparticles improves the drug's targeting ability, and the pH and temperature-sensitive release mechanism ensures the precise release of the drug in the tumor area. Combined with high-resolution imaging technology and real-time data acquisition, it can comprehensively monitor the drug delivery and treatment process, and make dynamic adjustments to optimize the efficacy. Through the comprehensive application of these technologies, the device can effectively improve the targeted treatment effect of gastric cancer and maximize the safety and treatment efficiency of patients.

[0147] Finally, it should be pointed out that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, a person skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A nano-delivery device for gastric cancer targeted drugs, characterized in that: Includes the following modules: The molecular recognition and optimization module is responsible for accurately identifying tumor cell-specific molecular markers and integrating clinical and genomic data to provide personalized treatment strategy recommendations; Nanocarrier design module, which designs multifunctional lipid-polymer hybrid nanoparticles and performs surface targeting ligand modification to significantly improve drug delivery efficiency by optimizing the carrier's biocompatibility, degradability and nanoparticle size; Intelligent drug loading module, based on pH / temperature sensitive release mechanism, improves the stability and controllability of drug loading and effectively reduces the toxic effects on non-target tissues; Molecular imaging and monitoring module, integrating nanoprobe imaging technology and quantum dot tracing technology, constructing a treatment-imaging integrated system, realizing real-time dynamic monitoring of the treatment process, and providing instant feedback at the molecular level; The risk assessment module establishes a safety database and provides dynamic risk assessment of the treatment process through a biosafety assessment system and long-term follow-up management.

2. A nano-delivery device for gastric cancer targeted drugs according to claim 1, characterized in that: The Molecular Recognition and Optimization Module includes the following components: The data collection unit is responsible for collecting patients’ genomic data, clinical data, transcriptomic data, and other relevant cross-omics data; The data preprocessing and fusion unit standardizes, cleans and fuses the collected multi-dimensional data to ensure the high quality and consistency of the data; Feature extraction unit, which extracts molecular marker features specifically related to tumor cells from cross-omics data and screens out potential targeting molecules; Molecular marker identification unit, which analyzes patient data in real time and accurately identifies specific molecular markers associated with tumor cells; The personalized treatment strategy generation unit combines the patient's clinical data and genomic information to generate a tailored personalized treatment plan and recommend the best targeted drug or treatment strategy; The Molecular Optimization and Simulation Unit performs molecular-level optimization and drug-target interaction simulation based on the identified molecular markers to ensure that the selected targets can effectively interact with the drugs.

3. A gastric cancer targeted drug nano-delivery device according to claim 2, characterized in that: Potential targeting molecules were screened by the following formula: Among them, X fusion is the fused data matrix, with dimension (n fusion ,m fusion ), where n fusion is the number of features, m fusion is the sample size; Y tumor is the tumor sample label, with a dimension of (1,m fusion ); W is the regression coefficient; is the estimated value of W, that is, the best regression coefficient obtained by data fitting, which represents the relationship between the input features and tumor markers; ‖W‖1 is the L1 norm, which is used to select sparse features; λ is the regularization parameter; A tailor-made, personalized treatment plan is generated using the following formula: Among them, H * represents the optimal personalized treatment plan generated; H represents the set of possible treatment plans; Cost(H,D) is the treatment cost of treatment plan H under given patient data D; δ is the weight coefficient for balancing the relationship between treatment cost and risk; Risk(H) is the risk brought by treatment plan H.

4. The nano-delivery device for gastric cancer targeted drugs according to claim 1, characterized in that: The Nanocarrier Design Module includes the following components: The carrier material selection unit selects lipid and polymer materials according to drug properties and targeting requirements to ensure the stability, drug loading capacity and biocompatibility of the carrier; The carrier synthesis unit fuses lipids and polymers to form multifunctional lipid-polymer hybrid nanoparticles, ensuring that the carrier has a stable structure and excellent drug loading capacity; The surface modification unit connects the targeting ligand to the surface of the nanoparticle through chemical modification, ensuring that the carrier can accurately recognize and target tumor cells; The particle size control unit adjusts the particle size range of nanoparticles to optimize particle distribution, cell penetration and drug delivery efficiency while avoiding immune responses caused by overly large particles; The biocompatibility optimization unit is responsible for improving the biocompatibility of nanocarriers, reducing the recognition and clearance of the immune system, and prolonging the circulation time of the carriers in the body; The degradability planning unit ensures that the carrier can be cleared through biodegradation pathways after drug release, reducing long-term toxicity and avoiding accumulation of carrier materials in the body.

5. The nano-delivery device for gastric cancer targeted drugs according to claim 4, characterized in that: The particle size range of nanoparticles is adjusted by the following comprehensive optimization function: O(d) = w1·D(d) + w2·E(d) + w3·R(d) - w4·I(d), where O(d) is a comprehensive optimization function used to describe the optimization process of various factors considered when adjusting the particle size d of nanoparticles; w1 is the importance of the particle distribution target; w2 is the optimization importance of cell permeability; w3 is the optimization importance of drug delivery efficiency; w4 is the optimization importance of immune response; D(d) represents the influence function of particle size d on particle distribution, and the formula is: k B is the Boltzmann constant; T is the temperature that affects the behavior of nanoparticles; η represents the drug loading efficiency of nanoparticles; E(d) represents the effect function of particle size d on cell permeability, and the formula is: d0 represents the initial particle size, that is, the initial size of the nanoparticles during synthesis; A is a constant coefficient related to material properties and drug release rate factors; B is a constant coefficient related to the stability of the carrier and cell absorption efficiency factors; R(d) represents the effect function of particle size d on drug delivery efficiency, and the formula is: α represents the regulatory factor related to particle size; C is a constant coefficient related to the immune response inhibition effect and carrier biocompatibility; I(d) represents the effect function of particle size d on immune response, and the formula is: C1 represents constant 1 in the particle size adjustment process; d1 represents the lower limit of the ideal particle size range, which is used to define the lower limit of the particle size in the optimization process; C2 represents constant 2 in the particle size optimization process.

6. The nano-delivery device for gastric cancer targeted drugs according to claim 1, characterized in that: The Smart Drug Load Module includes the following components: The drug release control unit regulates the release rate and extent of drugs in the tumor microenvironment based on the characteristics of pH / temperature sensitive materials, ensuring accurate drug release and reducing toxicity to non-target tissues; The stability enhancement unit improves the stability of the drug load by optimizing the carrier surface structure and intermolecular interactions, thus preventing the drug from being released or cleared prematurely in the body; Targeted release trigger unit, which activates the drug release mechanism through pH / temperature changes in the targeted tissue or tumor environment, ensuring that the drug works only in the target area and reduces the impact on healthy tissue; Loading efficiency monitoring unit, which monitors the loading efficiency and release process of drugs in the carrier to ensure that the loading amount, stability and controllability of the drugs meet the treatment needs; The side effect reduction unit reduces the systemic toxicity and side effects of drugs by precisely controlling the release time and concentration of drugs and reducing the exposure of drugs in non-target areas.

7. The nano-delivery device for gastric cancer targeted drugs according to claim 1, characterized in that: The Molecular Imaging and Monitoring Module includes the following components: Nanoprobe design unit, which designs and synthesizes specific nanoprobes, combines imaging functions with drug carriers to ensure that they can be accurately positioned in the tumor area and provide high-resolution imaging signals; The quantum dot tracing unit uses the fluorescence properties of quantum dots to perform highly sensitive tracing, tracking the distribution and dynamic changes of nanoparticles in the body in real time, and providing visual monitoring of drug delivery during treatment; Imaging data acquisition unit, which collects imaging signals from nanoprobes and quantum dots, obtains tissue and drug distribution information during treatment in real time, and ensures accurate spatial positioning; The image processing and analysis unit processes and analyzes the acquired imaging data to generate clear molecular images and extract key information about tumor areas and drug accumulation points; Real-time dynamic monitoring unit, which monitors the delivery and release of drugs during treatment in real time, dynamically tracks the effect of tumor treatment, and provides feedback and adjustment to the treatment process; The molecular feedback unit provides immediate feedback at the molecular level based on imaging results to help optimize treatment strategies.

8. The nano-delivery device for gastric cancer targeted drugs according to claim 7, characterized in that: The treatment process is feedback regulated by the following formula: in, is the derivative of drug concentration C(t) with time t, indicating the rate of change of drug concentration with time; dt is the time increment, which is used to describe the change of drug concentration in a small time interval; R0 is the initial drug delivery rate; α0 is the sensitivity parameter of feedback regulation, which determines the influence of feedback regulation on drug delivery rate; S tumor (t) is the tumor survival rate, which indicates the survival rate of tumor cells over time; S(t) is the drug release rate, which indicates the rate at which the drug is released from the treatment device or carrier into the body at a given time t; S0 is the initial tumor survival rate, which indicates the survival rate of tumor cells at the beginning of treatment; k is the efficacy parameter of the drug on tumor cells, which determines how the drug concentration affects the tumor survival rate; C(t) represents the concentration level of the drug in the body at a given time t; β is the sensitivity index of drug efficacy to concentration, which determines the nonlinear relationship between drug concentration and therapeutic effect.

9. The nano-delivery device for gastric cancer targeted drugs according to claim 1, characterized in that: The risk assessment module includes the following components: The biosafety assessment unit evaluates the potential hazards and safety of nanocarriers and drugs to the human body through comprehensive analysis of their toxicity, immunogenicity and biocompatibility; Clinical data monitoring unit, which collects and analyzes patients’ clinical data during treatment in real time, including physiological indicators, drug reactions and side effects; Long-term follow-up management unit, to establish and maintain long-term health records for patients, track the effects of late-stage drug treatment, and ensure that safety changes over time are continuously monitored; Safety database construction unit, integrating clinical data, drug reactions and biosafety test results to build a safety database; Dynamic risk assessment unit, which dynamically assesses potential risks during treatment based on the treatment progress and real-time patient responses, and adjusts treatment plans in a timely manner based on changes; The risk optimization and adjustment unit optimizes treatment strategies and drug delivery plans through a feedback mechanism, reduces possible risks during treatment, and ensures patient safety and treatment outcomes.

10. A method for using a nanometer delivery device for gastric cancer targeted drugs, based on the nanometer delivery device for gastric cancer targeted drugs according to any one of claims 1 to 9, characterized in that: The following steps are involved: Integrate patients' genomic data, clinical information and multi-omics data to accurately identify specific molecular markers of tumor cells, develop personalized treatment plans and recommend the best targeted drugs; Design lipid-polymer hybrid nanoparticles to significantly improve their targeting ability to tumor cells through surface targeting ligand modification, particle size regulation, and biocompatibility optimization; Load targeted drugs into nanoparticles and use pH and temperature sensitive release mechanisms to achieve drug stability and controllability; Deliver nanocarriers to the tumor area through blood circulation, and use high-resolution imaging technology to monitor the distribution and dynamic changes of nanoparticles in the body in real time, while recording drug delivery and release to provide immediate feedback on the treatment effect; The patient's physiological indicators and drug response data are collected in real time, and dynamic risk assessment is performed in combination with the safety database. Based on the monitoring results, drug delivery parameters and treatment strategies are adaptively adjusted to optimize efficacy and ensure patient safety.

Images