Preparation method of external vesicle drug and biomarker loading system

Abstract

The invention provides a preparation method of an external vesicle drug and biomarker loading system.The preparation method comprises the steps that firstly, external vesicles are separated and purified through differential centrifugation and ultracentrifugation, and polyethylene glycol is adopted for modification to improve stability; the preparation method comprises the following steps: screening external vesicles with proper particle sizes by a dynamic light scattering method, endowing the external vesicles with targeting ability through ligand modification, carrying out drug and biomarker loading by adopting an electroporation method, carrying out quantitative optimization based on a system equilibrium equation set and a multi-dimensional index vector in the loading process, and finally carrying out freeze drying to prepare a finished product. And the performance of the preparation is ensured by controlling the crystallinity. And a complete mathematical description system and a multi-dimensional parameter optimization method are established. Accurate control over the loading process is achieved by solving a system balance equation set; through construction of multi-dimensional index vectors, quantitative optimization of loading parameters is achieved, and the technical problem that in the prior art, an external vesicle drug and biomarker loading system lacks and is difficult to achieve quantitative optimization is solved.

Description

Technical Field

[0001] This invention belongs to the technical field of exovesicular drug and biomarker loading systems, and more specifically, relates to a method for preparing an exovesicular drug and biomarker loading system. Background Technology

[0002] Exovesicles hold great promise as novel drug and biomarker delivery carriers in the biomedical field. Their natural biocompatibility and targeted delivery capabilities make them ideal nanoscale drug and biomarker delivery systems. Traditional methods for loading drugs and biomarkers onto exovesicles mainly include physical methods such as electroporation, sonication, and freeze-thaw cycles, as well as chemical methods such as surface modification and membrane fusion. While these methods have demonstrated the feasibility of exovesicles as drug and biomarker carriers in practical applications, significant limitations remain in the controllability and optimization of the loading process. In particular, the lack of systematic parameter optimization methods and quantitative characterization techniques during drug and biomarker loading leads to problems such as low loading efficiency, large batch-to-batch variations, and unstable preparation processes.

[0003] Currently, exovesicle drug and biomarker loading systems face several technical bottlenecks in practical applications. First, existing loading methods lack precise control over the loading process; the selection of loading parameters often relies on empirical judgment, making it difficult to establish a quantitative relationship between loading conditions and loading effects. Second, the heterogeneity and complex membrane structure of exoves themselves make the distribution behavior of drugs and biomarkers during loading unpredictable and uncontrollable, directly affecting loading efficiency and the uniformity of drugs and biomarkers. Third, existing technologies lack systematic mathematical models to describe and optimize the loading process, hindering theoretical guidance and optimized design of loading parameters. This severely restricts the large-scale production and clinical application of exovesicle drug and biomarker loading systems.

[0004] In the development of exovesicular drug and biomarker loading systems, achieving precise control and quantitative optimization of the loading process has always been a core challenge. Existing technologies generally employ single-parameter optimization or empirical judgment methods, lacking systematic theoretical guidance and mathematical model support, and thus failing to effectively address the multi-parameter coupling and dynamic equilibrium control issues during the loading process. These technical limitations result in low preparation efficiency and unreliable product quality for exovesicular drug and biomarker loading systems, severely hindering their promotion and development in clinical applications. In summary, existing technologies for exovesicular drug and biomarker loading systems suffer from a lack of technical expertise that hinders quantitative optimization. Summary of the Invention

[0005] In view of this, the present invention provides a method for preparing an external vesicle drug and biomarker loading system, which can solve the technical problem in the prior art that there is a lack of external vesicle drug and biomarker loading systems and it is difficult to achieve quantitative optimization.

[0006] This invention is achieved as follows: A method for preparing an extravesicular drug and biomarker loading system includes the following steps: collecting human cell culture medium, removing cell debris and large particles by differential centrifugation, and filtering the supernatant through a 0.22-micron filter membrane; separating extravesicular vesicles by ultracentrifugation; adding 1% to 3% polyethylene glycol to the resuspended extravesicular vesicle solution and measuring the surface potential of the extravesicular vesicles; determining the particle size distribution and surface area of ​​the extravesicular vesicles using dynamic light scattering, and selecting extravesicular vesicles with a particle size range of 30 to 150 nanometers; adding a targeting ligand to the modified extravesicular vesicle solution; dissolving the drug and biomarker to be loaded in dimethyl sulfoxide to prepare a solution with a concentration of 1 to 5 mg / mL; and based on electroporation... An optimization function for loading parameters was established using a set of pore loading parameters, and the optimal combination of electroporation parameters was solved using dynamic programming. The loading rate and encapsulation efficiency of the drug and biomarkers were calculated using a system of equilibrium equations for the external vesicle drug and biomarker system, which included a drug and biomarker distribution equilibrium equation, a membrane flux equilibrium equation, and a mass conservation equation. Unloaded free drugs and biomarkers were removed using an ultrafiltration centrifuge tube based on the system's drug and biomarker distribution function. The prepared external vesicle drug and biomarker loading system was freeze-dried to obtain a lyophilized powder. The crystallinity of the formulation was determined using differential scanning calorimetry and X-ray diffraction, and formulations with a crystallinity in the range of 10% to 30% were selected.

[0007] Specifically, the differential centrifugation method involves centrifuging at 300g for 10 minutes at 4 degrees Celsius to remove intact cells, collecting the supernatant, centrifuging at 2000g for 20 minutes to remove cell debris, and then centrifuging at 10000g for 30 minutes to remove large particles.

[0008] Specifically, the step of separating the outer vesicles by ultracentrifugation involves centrifuging at 100,000 rpm for 120 minutes at 4 degrees Celsius. After centrifugation, pre-cooled phosphate buffer is added to the precipitate for resuspending, and the resuspending volume is 1 / 10 of the original culture medium volume.

[0009] In the equilibrium equation set of the external vesicle drug and biomarker system, the drug and biomarker distribution equilibrium equation uses parameters such as external phase drug and biomarker concentration, internal phase drug and biomarker concentration, and membrane surface charge density, and outputs a membrane drug and biomarker concentration distribution function; the membrane flux equilibrium equation uses parameters such as transmembrane concentration difference, membrane porosity, reaction temperature, and external vesicle number, and outputs a drug and biomarker transmembrane flux; the mass conservation equation uses parameters such as total system volume, loading time, and external vesicle volume fraction, and outputs a system drug and biomarker distribution function.

[0010] Specifically, the loading parameter optimization function is a two-dimensional discrete data set consisting of voltage and time value points, with the voltage range being 150 to 300 volts and the pulse time range being 10 to 20 milliseconds.

[0011] The target ligand to the extravesicular protein is in a mass ratio of 1:50 to 1:100, and the reaction is carried out at 25 degrees Celsius for 60 minutes.

[0012] The freeze-drying process includes three stages: pre-freezing, primary drying, and secondary drying. The pre-freezing stage is carried out at -40 degrees Celsius for 4 hours. The primary drying stage is carried out at -20 degrees Celsius with a vacuum of 20 Pa for 24 hours. The secondary drying stage is carried out at 20 degrees Celsius with a vacuum of 10 Pa for 12 hours.

[0013] The electroporation method is used to load drugs and biomarkers by performing 3 to 5 electroporation operations, with a time interval of 30 seconds between two adjacent electroporation operations.

[0014] The initial concentrations of the drug and biomarker solutions were determined by high performance liquid chromatography, and the molecular weights and membrane lipid-water partition coefficients of the drugs and biomarkers to be loaded were also determined.

[0015] The crystallinity was determined by differential scanning calorimetry under the following conditions: a heating rate of 10 degrees Celsius per minute and a scanning range of 25 to 200 degrees Celsius; the X-ray diffraction determination conditions included a Cu target, a tube voltage of 40 kV, a tube current of 30 mA, a scanning range of 5 to 40 degrees, and a scanning speed of 4 degrees per minute.

[0016] Compared with existing technologies, this invention provides a method for preparing an exovesicular drug and biomarker loading system. This invention proposes a method based on a system equilibrium equation set and multidimensional index vectors. By establishing a complete mathematical description system, precise control and quantitative optimization of the loading process are achieved. This method, for the first time, integrates key parameters in the exovesicular drug and biomarker loading process into participation index vectors, contribution index vectors, and gain index vectors, constructing a system equilibrium equation set including drug and biomarker distribution equilibrium equations, membrane flux equilibrium equations, and mass conservation equations, providing a theoretical basis for optimizing the loading process.

[0017] This invention effectively solves the problems existing in the prior art through several innovative designs. By establishing a set of electroporation loading parameters and an optimization function for loading parameters, precise control of loading conditions is achieved; by using a system equilibrium equation set to describe the distribution behavior of biomarker drugs in the exovesicle system, quantitative optimization of the loading process is achieved; and by constructing a multidimensional index vector, a quantitative relationship between loading parameters and loading effect is established, achieving standardization and controllability of the preparation process. Simultaneously, this invention also improves the stability and uniformity of exovesicles through polyethylene glycol modification and strict particle size screening, and enhances targeting ability through surface ligand modification.

[0018] This invention successfully solves the technical problem of quantitative optimization in existing exovesicular drug and biomarker loading systems, which lack sufficient quantity. Its core lies in establishing a complete mathematical description system and a multidimensional parameter optimization method. By solving the system equilibrium equations, precise control of the loading process is achieved; by constructing multidimensional index vectors, quantitative optimization of loading parameters is realized; and by precisely controlling process parameters, the repeatability of the preparation process and the uniformity of product quality are ensured. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method of the present invention.

[0020] Figure 2 This is a graph showing the trend of the surface potential of the outer vesicles in Example 2 as a function of polyethylene glycol modification time.

[0021] Figure 3 This is a diagram showing the particle size distribution of the external vesicles in Example 2.

[0022] Figure 4 Contour plot of optimized electroporation parameters in Example 2.

[0023] Figure 5 The in vitro release curves of the drugs and biomarkers in Example 2 are shown. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0025] like Figure 1 The diagram shown is a flowchart of a method for preparing an exovesicle drug and biomarker loading system provided by the present invention. This method includes the following steps:

[0026] S01. Collect human cell culture medium, remove cell debris and large particles by differential centrifugation, and filter the supernatant through a 0.22-micron filter membrane.

[0027] S02. The outer vesicles were separated by ultracentrifugation. The vesicles were centrifuged at 100,000 rpm for 120 minutes at 4 degrees Celsius. The precipitate was collected and resuspended in phosphate buffer.

[0028] S03. Add 1% to 3% polyethylene glycol by mass to the resuspended vesicle solution, stir at 4 degrees Celsius for 8 hours, and measure the surface potential of the vesicle.

[0029] S04. The particle size distribution and surface area of ​​the external vesicles were determined by dynamic light scattering method, and external vesicles with a particle size in the range of 30 to 150 nanometers were selected.

[0030] S05. Add the targeting ligand to the modified vesicle solution. The mass ratio of the ligand to the vesicle protein is 1:50 to 1:100. React at 25 degrees Celsius for 60 minutes.

[0031] S06. Dissolve the drug and biomarker to be loaded in dimethyl sulfoxide to prepare a drug and biomarker solution with a concentration of 1 to 5 mg / mL, determine the initial concentration of the drug and biomarker solution, and determine the molecular weight and membrane lipid-water partition coefficient of the drug and biomarker to be loaded.

[0032] S07. Electroporation is used to load drugs and biomarkers. The voltage range of 150 to 300 volts is divided into 10 voltage value points, and the pulse time of 10 to 20 milliseconds is divided into 10 time value points to construct an electroporation loading parameter set. Based on the electroporation loading parameter set, a loading parameter optimization function is established. The loading parameter optimization function uses the voltage value points and time value points as resource constraints, takes the drug loading amount as the objective function, and uses dynamic programming to solve for the optimal electroporation parameter combination. Electroporation operations are performed 3 to 5 times according to the optimal electroporation parameter combination, with a time interval of 30 seconds between two adjacent electroporation operations. The permeability coefficient and membrane thickness of the external vesicle membrane are measured.

[0033] S08. Calculate the loading rate and encapsulation efficiency of drugs and biomarkers using the equilibrium equations of the external vesicle drug and biomarker system. The equilibrium equations include a drug and biomarker distribution equilibrium equation, a membrane flux equilibrium equation, and a mass conservation equation. Specifically: the drug and biomarker distribution equilibrium equation describes the concentration balance of drugs and biomarkers across the external vesicle membrane; the membrane flux equilibrium equation characterizes the rate of transmembrane transport of drugs and biomarkers; and the mass conservation equation calculates the overall distribution of drugs and biomarkers within the system.

[0034] S09. Based on the system drug and biomarker distribution function output by the mass conservation equation, remove unloaded free drugs and biomarkers through an ultrafiltration centrifuge tube.

[0035] S10. The prepared external vesicle drug and biomarker loading system is freeze-dried to obtain freeze-dried powder;

[0036] S11. Differential scanning calorimetry and X-ray diffraction were used to determine the crystallinity of the formulation, and formulations with crystallinity in the range of 10% to 30% were selected.

[0037] The drug and biomarker distribution equilibrium equation uses the following parameters: external phase concentration, internal phase concentration, and membrane surface charge density, and the output is the membrane concentration distribution function.

[0038] The membrane flux balance equation uses the following parameters: transmembrane concentration gradient, membrane porosity, reaction temperature, and number of external vesicles, and outputs the transmembrane flux of drugs and biomarkers.

[0039] The mass conservation equation uses the following parameters: total system volume, loading time, and external vesicle volume fraction, and outputs the distribution function of system drugs and biomarkers.

[0040] The participation index vector is specifically a three-dimensional vector composed of the surface potential of the external vesicle, the lipid-water partition coefficient, and the membrane permeability coefficient.

[0041] The contribution index vector is specifically a three-dimensional vector composed of transmembrane flux of drugs and biomarkers, intramembrane drug and biomarker concentration distribution function, and system drug and biomarker distribution function.

[0042] The gain index vector is specifically a three-dimensional vector composed of drug and biomarker loading rate, drug and biomarker encapsulation rate, and formulation crystallinity.

[0043] The electroporation loading parameter set is specifically a two-dimensional discrete data set composed of voltage value points and time value points;

[0044] The loading parameter optimization function is specifically a mathematical function that maps voltage and time values ​​to the loading amount of drugs and biomarkers.

[0045] The exovesicle drug and biomarker loading system has the following technical features: polyethylene glycol modification and strict particle size screening concentrate the exovesicle particle size distribution, thereby improving the uniformity of drug and biomarker loading; the loading parameters are optimized through the system's equilibrium equations to make the loading process controllable and maximize efficiency; freeze-drying is used to protect the exovesicle membrane structure and ensure the stability of the formulation during storage; a drug and biomarker distribution equilibrium equation is used to achieve a reasonable distribution of drugs and biomarkers inside and outside the exovesicle membrane and improve loading efficiency; a membrane flux balance equation is used to control the transmembrane process of drugs and biomarkers to avoid leakage; a mass conservation equation is used to achieve a balanced distribution of drugs and biomarkers within the system to ensure the uniformity of formulation quality; ligand modification provides targeting ability and improves the selectivity of drugs and biomarkers; and crystallinity is controlled within the range of 10% to 30% to ensure the formulation's dissolution performance and bioavailability.

[0046] The present invention relates to an exovesicle drug and biomarker loading system, specifically a nanoscale delivery system based on exovesicles as drug and biomarker carriers. The stability of the exovesicles is improved by polyethylene glycol modification. Therapeutic drugs and biomarkers are loaded into the exovesicles using electroporation. Loading conditions are optimized using the system's equilibrium equations. Targeted delivery of drugs and biomarkers is achieved by combining surface ligand modification. This exovesicle drug and biomarker loading system is used to improve bioavailability, reduce side effects, and enhance efficacy.

[0047] The specific implementation of the above steps is described in detail below. Step S01 involves first separating and collecting extravesicles from the human cell culture medium, and then pre-treating them using differential centrifugation. This technique is based on the principle that particles of different sizes have different sedimentation rates under centrifugal force. Cell debris and large particles are removed through multiple centrifugations at different speeds. Specifically, at 4 degrees Celsius, the cells are first centrifuged at 300g for 10 minutes to remove intact cells. After collecting the supernatant, the cells are centrifuged at 2000g for 20 minutes to remove cell debris, followed by centrifugation at 10000g for 30 minutes to remove large particles. Finally, the obtained supernatant is filtered through a 0.22-micron pore size polyurethane membrane using a constant pressure filtration mode, controlling the transmembrane pressure difference within the range of 0.02 to 0.05 MPa, and the filtration rate at 1 to 2 ml per minute. The purpose of this step is to obtain a pure extravesicle solution, providing a good foundation for subsequent separation.

[0048] The specific implementation of step S02 involves separating the exovesicles using ultracentrifugation. This method is based on the centrifugal sedimentation effect caused by the density difference between the exovesicles and the solution. High-speed centrifugation separates the exovesicles from the solution. Specifically, the pretreated supernatant is transferred to a polypropylene centrifuge tube and centrifuged at 100,000 rpm for 120 minutes at 4 degrees Celsius. During centrifugation, the temperature fluctuation is controlled within ±1 degree Celsius. After centrifugation, the supernatant is carefully removed, and pre-cooled phosphate buffer (pH 7.4, ionic strength 0.15 mol / L) is added to the precipitate. The precipitate is slowly resuspended at a volume of 1 / 10 of the original culture medium volume. Air bubbles are avoided during resuspending. This step aims to obtain high-purity exovesicles, providing a material basis for subsequent modification.

[0049] The specific implementation of step S03 involves adding 1% to 3% polyethylene glycol (PEG) by mass to the resuspended vesicle solution for surface modification. PEG with a molecular weight of 2000 Daltons is selected, and the modification is performed using a covalent bonding method. Specifically, the PEG solution is slowly added dropwise at 4 degrees Celsius, with a stirring rate controlled at 200 rpm for 8 hours. During the modification process, samples are taken every hour to measure the surface potential of the vesicles using laser Doppler microelectrophoresis at 25 degrees Celsius. The vesicle concentration is diluted to 0.1 mg / mL, and each sample is measured three times. The zeta potential value is recorded. This step improves the stability of the vesicles and reduces in vivo clearance through PEG modification.

[0050] The specific implementation of step S04 involves using dynamic light scattering to determine the particle size distribution and surface area of ​​the external vesicles. This method is based on the Brownian motion principle and calculates the particle size distribution by analyzing the time correlation function of the scattered light intensity. Specifically, the external vesicle sample is diluted to an appropriate concentration, and a helium-neon laser with a wavelength of 633 nm is used. The scattering angle is 90 degrees and the temperature is 25 degrees Celsius. Each sample is measured 5 times to obtain the particle size distribution curve. The number-average particle size, volume-average particle size, and polydispersity index are calculated. The specific surface area is estimated using a spherical model. External vesicles with a particle size distribution in the range of 30 to 150 nm and a polydispersity index of less than 0.3 are selected. This step aims to obtain external vesicles with uniform particle size to ensure the uniformity of subsequent loading.

[0051] The specific implementation of step S05 involves adding a targeting ligand to the modified vesicle solution and using an azide click chemistry reaction to achieve covalent binding between the ligand and the surface protein of the vesicle. The mass ratio of the ligand to the vesicle protein is controlled within the range of 1:50 to 1:100. Specifically, the ligand is dissolved in dimethyl sulfoxide to prepare a solution with a concentration of 1 mg / mL, which is then slowly added dropwise to the vesicle solution at 25°C for 60 minutes. During the reaction, the particle size change is monitored in real time using dynamic light scattering to ensure that the modification process does not affect the structural integrity of the vesicle. After the reaction, unreacted ligand is removed by ultrafiltration and centrifugation. This step endows the vesicle with targeting ability through surface modification, thereby improving the selectivity of delivery.

[0052] The specific implementation of step S06 involves first dissolving the drug and biomarker to be loaded in dimethyl sulfoxide to prepare a solution with a concentration of 1 to 5 mg / mL. The initial concentration of the drug and biomarker solution is determined using high-performance liquid chromatography (HPLC). Chromatographic conditions include mobile phase composition, flow rate, and detection wavelength. The relative standard deviation of the measurement results is controlled within 2%. Simultaneously, the molecular weight and membrane lipid-water partition coefficient of the drug and biomarker to be loaded are determined. The molecular weight is determined by mass spectrometry, and the membrane lipid-water partition coefficient is determined by an oscillation method. Specifically, the drug and biomarker solution is mixed with n-octanol and oscillated at 25°C for 24 hours to reach partition equilibrium. The concentrations of the drug and biomarker in the two phases are determined by HPLC, and the partition coefficient is calculated. This step aims to obtain the physicochemical parameters of the drug and biomarker, providing a basis for the subsequent loading process.

[0053] The specific implementation of step S07 involves loading drugs and biomarkers using electroporation. This method is based on the principle of reversibly perforating cell membranes with an applied electric field. Efficient loading of drugs and biomarkers is achieved by optimizing the electric field parameters. Specifically, the voltage range of 150 to 300 volts is divided into 10 equal voltage value points, and the pulse time of 10 to 20 milliseconds is divided into 10 equal time value points, constructing an electroporation loading parameter set containing 100 parameter combinations. Based on this parameter set, a loading parameter optimization function is established. This function uses a polynomial fitting method to optimize the voltage values. Points and time values ​​are mapped to drug and biomarker loading amounts. The optimal parameter combination is solved using a dynamic programming algorithm. The objective function of the algorithm is to maximize the drug and biomarker loading amounts. Constraints include voltage limits and time limits. The optimal parameter combination obtained is used to perform 3 to 5 electroporation operations, with each operation spaced 30 seconds apart and the operating temperature controlled at 4 degrees Celsius. At the same time, the permeability coefficient and membrane thickness of the outer vesicle membrane are measured. The permeability coefficient is determined by the tracer method, and the membrane thickness is observed by transmission electron microscopy. This step achieves efficient loading of drugs and biomarkers through parameter optimization.

[0054] The specific implementation of step S08 involves calculating the loading rate and encapsulation efficiency of drugs and biomarkers through a set of equilibrium equations for the external vesicle drug and biomarker system. This set of equations includes a drug and biomarker distribution equilibrium equation, a membrane flux equilibrium equation, and a mass conservation equation. The drug and biomarker distribution equilibrium equation uses a Langmuir adsorption model based on thermodynamic equilibrium, considering factors such as the concentration of drugs and biomarkers in the external phase, the concentration of drugs and biomarkers in the internal phase, and the membrane surface charge density to calculate the concentration distribution function of drugs and biomarkers within the membrane. The membrane flux equilibrium equation is based on Fick's diffusion law, using parameters such as transmembrane concentration difference, membrane porosity, reaction temperature, and the number of external vesicles to calculate the transmembrane flux of drugs and biomarkers. The mass conservation equation considers parameters such as the total system volume, loading time, and volume fraction of external vesicles to calculate the distribution function of drugs and biomarkers in the system. By solving this set of equations, the distribution of drugs and biomarkers in each phase of the system is obtained. This step aims to achieve a quantitative description and optimization of the loading process.

[0055] The specific implementation of step S09 involves using ultrafiltration centrifugation to remove unloaded free drugs and biomarkers based on the system drug and biomarker distribution function output by the mass conservation equation. Specifically, the loaded mixture is transferred to an ultrafiltration centrifuge tube with a molecular weight cutoff of 100 kilodaltons, centrifuged at 5000g for 30 minutes at 4 degrees Celsius, the retentate is collected, and the ultrafiltration process is repeated twice. The concentration of free drugs and biomarkers in the filtrate is determined by high performance liquid chromatography, and the drug and biomarker loading rate is calculated. This step aims to obtain a pure exovesicle drug and biomarker loading system.

[0056] The specific implementation of step S10 involves freeze-drying the prepared exovesicle drug and biomarker loading system using a programmed cooling freeze-drying process, which includes three stages: pre-freezing, primary drying, and secondary drying. The pre-freezing stage is carried out at -40 degrees Celsius for 4 hours. The primary drying stage is carried out at -20 degrees Celsius under a vacuum of 20 Pa for 24 hours. The secondary drying stage is carried out at 20 degrees Celsius under a vacuum of 10 Pa for 12 hours. Throughout the process, the temperature difference between the rack and the product is controlled within 10 degrees Celsius. This step aims to obtain a stable freeze-dried formulation.

[0057] The specific implementation of step S11 involves determining the crystallinity of the formulation using differential scanning calorimetry (DSC) and X-ray diffraction (XRD). The DSC conditions include a heating rate of 10 degrees Celsius per minute, a scanning range of 25 to 200 degrees Celsius, recording the enthalpy value, and calculating the crystallinity. The XRD conditions include a Cu target, a tube voltage of 40 kV, a tube current of 30 mA, a scanning range of 5 to 40 degrees Celsius, and a scanning speed of 4 degrees Celsius per minute. The crystallinity is calculated using the diffraction peak area. Formulations with an average crystallinity between 10% and 30% determined by both methods are selected. This step aims to ensure that the formulation has good dissolution properties and bioavailability.

[0058] The formulas or calculation processes involved in this invention are described in detail below.

[0059] 1. The first step is the determination of the surface potential of the external vesicles in step S03:

[0060] The formula for calculating the surface potential of the external vesicle is as follows:

[0061]

[0062] In the formula, ζ is the surface potential of the outer vesicle, in mV; η is the solution viscosity, in Pa·s; and μ is the electrophoretic mobility, in m³ / s. 2 / (V·s); ε0 is the vacuum permittivity; ε r is the relative permittivity of the medium.

[0063] The parameter acquisition method is as follows:

[0064] μ was obtained by laser Doppler microelectrophoresis; η was determined by capillary viscometer at 25 degrees Celsius; ε r The relative permittivity of the water is 78.5.

[0065] 2. The dynamic light scattering measurement process in step S04:

[0066] The particle size distribution function is specifically expressed as follows:

[0067]

[0068] In the formula, G(τ) is the autocorrelation function; τ is the delay time, in seconds; R h D is the hydrodynamic radius, in nm; D is the diffusion coefficient, in m. 2 / s; q is the scattering vector, in meters. -1 g(R) h ) is the particle size distribution function.

[0069] The formula for calculating the scattering vector is:

[0070]

[0071] In the formula, n is the refractive index of the medium; λ is the incident light wavelength in nm; and θ is the scattering angle.

[0072] 3. Optimization function for electroporation loading parameters in step S07:

[0073] The loading parameter optimization function is specifically expressed as follows:

[0074]

[0075] In the formula, L(V, t) represents the drug and biomarker loading amount, in μg / mg; V represents the voltage value, in V; t represents the pulse duration, in ms; a ij λ represents the elements in the polynomial coefficient matrix A; β, γ, δ, λ are the fitting parameters; V0 is the optimal voltage threshold; ∈ represents the random error term; n, m are the highest degree of the polynomial.

[0076] The polynomial coefficient matrix A is specifically represented as follows:

[0077]

[0078] In the formula, a ij The fitting coefficients are obtained using the least squares method.

[0079] 4. The equilibrium equations for the extravesicular drug and biomarker system in step S08:

[0080] Drug distribution equilibrium equation:

[0081]

[0082] In the formula, C m Intramembrane drug and biomarker concentrations, in mg / mL; C o The concentrations of exogenous drugs and biomarkers are expressed in mg / mL; C i This represents the concentration of the drug and biomarker in the internal phase, in mg / mL; K p q is the allocation coefficient; s The surface charge density of the membrane is expressed in C / m³. 2 α is the charge influence factor.

[0083] Membrane flux balance equation:

[0084]

[0085] In the formula, J is the transmembrane flux, with units of mol / (m²). 2 ·s); D m The diffusion coefficient within the membrane is expressed in m.2 / s; ε is membrane porosity; z is the charge number of the drug and biomarker; F is Faraday constant; R is gas constant; T is absolute temperature in K; ψ is electric potential in V; x is the coordinate in the membrane thickness direction in m.

[0086] mass conservation equation:

[0087]

[0088] In the formula, φ v t represents the volume fraction of the external vesicles; t represents time, in seconds. For the Laplace operator.

[0089] 5. Crystallinity calculation in step S11:

[0090] The specific formula for calculating crystallinity is as follows:

[0091]

[0092] In the formula, X c Crystallinity; ΔH m ΔH is the enthalpy of fusion, expressed in J / g. c It is the enthalpy of crystallization, expressed in J / g; The theoretical enthalpy of fusion for a fully crystalline sample is given in J / g.

[0093] The vectors or parameters involved in this invention are explained in detail below.

[0094] 1. The participation index vector mentioned in step S07:

[0095] The participation index vector is specifically represented as follows:

[0096]

[0097] In the formula, ζ is the participation index vector; ζ is the surface potential of the outer vesicle, in mV; logP is the logarithm of the lipid-water partition coefficient; P m The membrane permeability coefficient is expressed in cm / s; where,

[0098] In the formula, is the unit orthogonal basis vector; p1, p2, and p3 are the normalized values ​​of surface potential, distribution coefficient, and permeability coefficient, respectively.

[0099] 2. The contribution index vector mentioned in step S07:

[0100] The contribution index vector is specifically represented as follows:

[0101]

[0102] In the formula, The contribution index vector; J represents the transmembrane flux of drugs and biomarkers, in mol / (m²). 2 ·s); C m (x) is the intracellular drug and biomarker concentration distribution function; C(x,t) is the systemic drug and biomarker distribution function.

[0103] 3. The gain exponent vector mentioned in step S07:

[0104] The gain exponent vector is specifically represented as follows:

[0105]

[0106] In the formula, L is the gain exponent vector; r E represents the loading rate of drugs and biomarkers, expressed as a percentage. r X represents the encapsulation efficiency of drugs and biomarkers, expressed as a percentage (%). c Crystallinity of the formulation, expressed as a percentage.

[0107] 4. The set of electroporation loading parameters mentioned in step S07:

[0108] The specific set of electroporation loading parameters is represented as follows:

[0109] Ω={(V i , t j )|V i =V min +iΔV,t j =t min +jΔt,i,j=0,1,…,9};

[0110] In the formula, Ω is the set of parameters; V i The voltage value is within the range of 150-300V; t j The time value is 10-20 ms; ΔV is the voltage interval; Δt is the time interval; V min The minimum voltage value is 150V; t min The minimum time value is 10ms.

[0111] Specifically, the principle of this invention is based on the physicochemical properties and mass transfer kinetics of the exovesicle drug and biomarker loading system. First, reversible nanopores are formed on the exovesicle membrane using electroporation, providing channels for the transmembrane transport of drugs and biomarkers. During electroporation, the precise control of the applied electric field strength and pulse duration determines the size and number of membrane pores, thus affecting the loading efficiency of drugs and biomarkers. This invention establishes a loading parameter optimization function, establishing a quantitative relationship between voltage and time values ​​and the loading amount of drugs and biomarkers, thereby achieving precise control of loading conditions.

[0112] During drug loading, complex multiphase equilibrium relationships exist within the system. The drug and biomarker partitioning equilibrium equation describes the concentration distribution of drugs and biomarkers across the outer vesicle membrane, considering the influence of surface charge density on drug and biomarker partitioning. The membrane flux equilibrium equation, based on Fick's diffusion law and the Nernst-Planck equation, describes the transmembrane transport kinetics of drugs and biomarkers. The mass conservation equation describes the overall distribution of drugs and biomarkers within the system. This set of system equilibrium equations provides a theoretical foundation for the quantitative description and optimization of the loading process.

[0113] By constructing a multidimensional index vector, this invention establishes a quantitative relationship between loading parameters and loading effect. The participation index vector reflects the physicochemical properties of the external vesicles, drugs, and biomarkers; the contribution index vector describes the key kinetic parameters in the loading process; and the gain index vector characterizes the multidimensional evaluation index of the loading effect. This multidimensional parameter optimization method makes the control of the loading process more precise and scientific.

[0114] The following provides a specific embodiment 1 of the present invention, and the specific implementation of each step in this embodiment 1 is described in detail below.

[0115] The specific implementation of step S01 involves first separating and collecting extravesicles from the human cell culture medium, and pretreating them using differential centrifugation. This technique is based on the principle that particles of different sizes have different sedimentation rates under centrifugal force. Cell debris and large particles are removed through multiple centrifugations at different speeds. Specifically, at 4 degrees Celsius, the cells are first removed by centrifugation at 300g for 10 minutes. After collecting the supernatant, the cells are removed by centrifugation at 2000g for 20 minutes, followed by centrifugation at 10000g for 30 minutes to remove large particles. Finally, the obtained supernatant is filtered through a polyurethane membrane with a pore size of 0.22 micrometers using a constant pressure filtration mode, controlling the transmembrane pressure difference within the range of 0.02 to 0.05 MPa, and the filtration rate is controlled at 1 to 2 ml per minute. This filtration process follows standard operating procedures to ensure the uniformity and repeatability of filtration. The purpose of this step is to obtain a pure extravesicle solution, providing a good foundation for subsequent separation.

[0116] The specific implementation of step S02 involves separating the exovesicles using ultracentrifugation. This method is based on the centrifugal sedimentation effect caused by the density difference between the exovesicles and the solution. High-speed centrifugation separates the exovesicles from the solution. Specifically, the pretreated supernatant is transferred to a polypropylene centrifuge tube and centrifuged at 100,000 rpm for 120 minutes at 4 degrees Celsius, with temperature fluctuations controlled within ±1 degree Celsius during centrifugation. After centrifugation, the supernatant is carefully removed, and pre-cooled phosphate buffer (pH 7.4, ionic strength 0.15 mol / L) is added to the precipitate. The precipitate is slowly resuspended at 1 / 10 of the original culture volume, avoiding the generation of air bubbles. Gentle mixing is performed using a mechanical shaker at 100 rpm for 10 minutes. This step aims to obtain high-purity exovesicles, providing a material basis for subsequent modification.

[0117] The specific implementation of step S03 involves adding 1% to 3% (by mass) of polyethylene glycol to the resuspended vesicle solution for surface modification. Polyethylene glycol with a molecular weight of 2000 Daltons is selected, and the modification is performed using a covalent bonding method. Specifically, the polyethylene glycol solution is slowly added dropwise at 4 degrees Celsius, with a stirring rate controlled at 200 rpm for 8 hours. During the modification process, samples are taken every hour to measure the surface potential of the vesicles using laser Doppler microelectrophoresis. The formula for calculating the surface potential of the vesicles is as follows: In the formula, ζ is the surface potential of the outer vesicle in mV, η is the solution viscosity in Pa·s, and μ is the electrophoretic mobility in m³ / s. 2 / (V·s), where ε₀ is the vacuum permittivity, ε rThe relative permittivity of the medium was used, the measurement temperature was 25 degrees Celsius, the concentration of the outer vesicles was diluted to 0.1 mg / mL, and each sample was measured 3 times. The zeta potential value was recorded. This step improved the stability of the outer vesicles and reduced the in vivo clearance rate by modifying them with polyethylene glycol.

[0118] The specific implementation of step S04 involves determining the particle size distribution and surface area of ​​the outer vesicles using a dynamic light scattering method. This method is based on the Brownian motion principle and calculates the particle size distribution by analyzing the time correlation function of the scattered light intensity. The particle size distribution function is... In the formula, G(τ) is the autocorrelation function, τ is the delay time in seconds, and R... h D is the hydrodynamic radius, in nm, and D is the diffusion coefficient, in m. 2 / s, where q is the scattering vector in meters. -1 ,g(R h Let be the particle size distribution function, and the formula for calculating the scattering vector is: In the formula, n is the refractive index of the medium, λ is the incident light wavelength in nm, and θ is the scattering angle. Specifically, the outer vesicle sample is diluted to an appropriate concentration, and a helium-neon laser with a wavelength of 633 nm is used. The scattering angle is 90 degrees and the temperature is 25 degrees Celsius. Each sample is measured 5 times to obtain the particle size distribution curve. The number-average particle size, volume-average particle size, and polydispersity index are calculated. The specific surface area is estimated by using a spherical model. Outer vesicles with a particle size distribution in the range of 30 to 150 nm and a polydispersity index of less than 0.3 are selected. This step aims to obtain outer vesicles with uniform particle size to ensure the uniformity of subsequent drug loading.

[0119] The specific implementation of step S05 involves adding a targeting ligand to the modified vesicle solution. Azid click chemistry is used to achieve covalent binding between the ligand and the surface protein of the vesicle. The mass ratio of ligand to vesicle protein is controlled within the range of 1:50 to 1:100. The ligand modification process is based on complete reaction kinetic calculations, and real-time monitoring technology is used to ensure the controllability of the modification degree. Specifically, the ligand is dissolved in dimethyl sulfoxide to prepare a solution with a concentration of 1 mg / mL, which is then slowly added dropwise to the vesicle solution at 25°C for 60 minutes. During the reaction, dynamic light scattering is used to monitor particle size changes in real time, and the uniformity of modification is ensured by calculating the quantum yield of polyethylene glycol modification. This step endows the vesicles with targeting ability through surface modification, improving the selectivity of drug delivery.

[0120] The specific implementation of step S06 is as follows: First, the drug and biomarker to be loaded are dissolved in dimethyl sulfoxide to prepare a drug and biomarker solution with a concentration of 1 to 5 mg / mL. An appropriate concentration range is selected according to the physicochemical properties of the drug and biomarker. The initial concentration of the drug and biomarker solution is determined by high performance liquid chromatography (HPLC). At the same time, the molecular weight and membrane lipid-water partition coefficient of the drug and biomarker to be loaded are determined. Combining the loading capacity of the system with the physicochemical properties of the drug and biomarker, a correlation model between loading parameters and molecular characteristics of drug and biomarker is established. The partition behavior of drug and biomarker in different phases is obtained through partition coefficient determination experiments. The determination is carried out by shaking at 25 degrees Celsius for 24 hours to reach partition equilibrium. The concentration of drug and biomarker in the two phases is determined by HPLC, and the partition coefficient is calculated.

[0121] The specific implementation of step S07 involves loading drugs and biomarkers using electroporation, wherein the loading parameter optimization function is: In the formula, L(V, t) represents the drug and biomarker loading amount in μg / mg, V is the voltage value in V, t is the pulse duration in ms, and a ij Let Ω be the polynomial coefficient matrix, β, γ, δ, λ be the fitting parameters, V0 be the optimal voltage threshold, ∈ be the random error term, and n, m be the highest degree of the polynomial. The electroporation loading parameter set is Ω = {(V...} i , t j )|V i =V min +iΔV,t j =t min The optimal parameter combination is determined by dynamic programming algorithm for the electroporation operation with an interval of 30 seconds between each operation and a temperature control of 4 degrees Celsius.

[0122] The specific implementation of step S08 involves calculating the loading rate and encapsulation efficiency of drugs and biomarkers using a system of equilibrium equations for the distribution of drugs and biomarkers in exovesicles. The equilibrium equations for drug and biomarker distribution are as follows: In the formula C m The concentration of drugs and biomarkers within the membrane is expressed in mg / mL, C. o The concentrations of exogenous drugs and biomarkers are expressed in mg / mL, C. i This represents the concentration of the drug and biomarker in the internal phase, in mg / mL, K. p q is the allocation coefficient. s The surface charge density of the membrane is expressed in C / m³. 2 α is the charge influence factor; the membrane flux balance equation is: In the formula, J represents the transmembrane flux, with units of mol / (m²).2 ·s), D m The diffusion coefficient within the membrane is expressed in m. 2 / s, ε is the membrane porosity, z is the charge number of the drug and biomarker, F is the Faraday constant, R is the gas constant, T is the absolute temperature in K, ψ is the electric potential in V, x is the coordinate of the membrane thickness direction in m; the mass conservation equation is: In the formula φ v The value represents the volume fraction of the external vesicles, where t is time, expressed in seconds. The Laplace operator is used to determine the distribution of the drug within the system through this set of equations.

[0123] The specific implementation of step S09 involves using ultrafiltration centrifugation to remove unloaded free drugs and biomarkers based on the system drug and biomarker distribution function output from the mass conservation equation. Specifically, the loaded mixture is transferred to an ultrafiltration centrifuge tube with a molecular weight cutoff of 100 kilodaltons, centrifuged at 5000g for 30 minutes at 4 degrees Celsius, the retentate is collected, and the ultrafiltration process is repeated twice. The loading rate is calculated using the participation index vector. In the formula, ζ is the surface potential of the outer vesicle, in mV, logP is the logarithm of the membrane lipid-water partition coefficient, and P m The membrane permeability coefficient is expressed in cm / s; the contribution index vector is also shown. In the formula, J represents the transmembrane flux of drugs and biomarkers, in mol / (m²). 2 ·s), C m (x) represents the intramembrane drug and biomarker concentration distribution function, C(x,t) represents the system drug and biomarker distribution function; gain exponent vector In the formula L r Drug and biomarker loading rates, in % E r Encapsulation efficiency of drugs and biomarkers, in % X c The crystallinity of the formulation is expressed as a percentage. The concentrations of free drugs and biomarkers in the filtrate are determined by high performance liquid chromatography (HPLC), and the drug and biomarker loading rates are calculated. This step aims to obtain a pure exovesicle drug and biomarker loading system.

[0124] The specific implementation of step S10 involves freeze-drying the prepared exovesicle drug and biomarker loading system using a programmed cooling freeze-drying process, specifically including three stages: pre-freezing, primary drying, and secondary drying. The pre-freezing stage is carried out at -40 degrees Celsius for 4 hours, with thermocouples used to monitor the product temperature in real time to ensure temperature uniformity. The primary drying stage is carried out at -20 degrees Celsius under a vacuum of 20 Pa for 24 hours, with a capacitive sensor monitoring the drying endpoint during the drying process. The secondary drying stage is carried out at 20 degrees Celsius under a vacuum of 10 Pa for 12 hours. Throughout the process, the temperature difference between the rack and the product is controlled within 10 degrees Celsius. Residual moisture is monitored using online NIR spectroscopy to ensure that the final moisture content is below 3%. This step aims to obtain a stable freeze-dried formulation.

[0125] The specific implementation of step S11 involves determining the crystallinity of the formulation using differential scanning calorimetry and X-ray diffraction. The formula for calculating the crystallinity is as follows: In the formula X c For crystallinity, ΔH m ΔH is the enthalpy of fusion, expressed in J / g. c It is the enthalpy of crystallization, expressed in J / g. The theoretical enthalpy of fusion for fully crystalline samples, expressed in J / g, was determined using differential scanning calorimetry (DSC) under the following conditions: a heating rate of 10°C per minute and a scanning range of 25 to 200°C. The enthalpy value was recorded and the crystallinity was calculated. X-ray diffraction (XRD) was performed using a Cu target, a tube voltage of 40 kV, a tube current of 30 mA, a scanning range of 5 to 40 degrees, and a scanning speed of 4 degrees per minute. The crystallinity was calculated using the diffraction peak area. Formulations with an average crystallinity between 10% and 30% were selected to ensure good dissolution performance and bioavailability. This step, through strict control of the crystallinity range, optimizes the formulation's performance.

[0126] To better understand and implement this invention, the following is a specific application scenario of the invention, Example 2: When developing an anti-tumor drug carrier system, researchers designed and implemented the following experimental scheme based on the technical solution of this invention. First, HEK293T cell culture supernatant was collected, and differential centrifugation was used to separate and purify the outer vesicles. Specific centrifugation parameters are shown in Table 1.

[0127] Table 1. Parameters of Differential Centrifugation

[0128] Centrifugation stage Centrifugal force (g) Centrifugation time (min) Temperature (°C) Purpose Phase 1 300 10 4 Remove intact cells Phase Two 2000 20 4 Remove cell debris Phase Three 10000 30 4 Removal of large particles Phase 4 100000 120 4 Collecting external vesicles

[0129] The supernatant was filtered using a 0.22-micron polyethersulfone membrane, with the transmembrane pressure differential controlled at 0.035 MPa and a filtration rate of 1.5 mL / min. The collected exovesicle precipitate was resuspended in phosphate buffer (pH 7.4) at 1 / 10 of the original culture volume. 2% (w / w) polyethylene glycol (molecular weight 2000 Daltons) was added to the resuspended exovesicle solution for surface modification. The mixture was stirred at 4°C for 8 hours, and the surface potential of the exovesicles was measured every hour. The results are shown in Table 2.

[0130] Table 2. Changes in surface potential of external vesicles over time.

[0131] Time (h) Zeta potential (mV) Standard deviation (mV) 0 -15.3 0.8 1 -12.8 0.6 2 -10.5 0.7 4 -8.9 0.5 6 -8.2 0.4 8 -8.0 0.3

[0132] Figure 2 The variation trend of the surface potential of the outer vesicles with polyethylene glycol modification time is shown, including error bars to indicate measurement uncertainties. The particle size distribution of the outer vesicles was determined using dynamic light scattering, employing a helium-neon laser with a wavelength of 633 nm, a scattering angle of 90 degrees, and a measurement temperature of 25 degrees Celsius. The main parameters of the particle size distribution are shown in Table 3.

[0133] Table 3. External vesicle particle size distribution parameters

[0134] Parameter type numerical values unit Number average particle size 82.5 nm Volume average particle size 95.3 nm Multi-dispersion index 0.156 - Specific surface area 145.8 <![CDATA[m 2 / g]]>

[0135] Figure 3 The particle size distribution of the outer vesicles is shown. CD44 monoclonal antibody was selected as the targeting ligand and modified using an azide click chemistry reaction. The mass ratio of ligand to outer vesicle protein was 1:75. Doxorubicin was used as a model drug, prepared into a solution with a concentration of 2.5 mg / mL, and loaded using electroporation. The optimization process of the electroporation parameters is shown in Table 4.

[0136] Table 4 Results of Electroporation Parameter Optimization

[0137] Voltage (V) Pulse duration (ms) Loading weight (μg / mg) Loading efficiency (%) 150 10 45.3 18.1 200 15 78.6 31.4 250 15 156.2 62.5 300 15 142.8 57.1 250 20 148.9 59.6

[0138] Figure 4 The contour plots for optimizing electroporation parameters illustrate the effects of voltage and pulse time on loading. Based on the optimization results, a voltage of 250V and a pulse time of 15ms were selected as the optimal parameter combination, and three consecutive electroporation operations were performed with a 30-second interval between operations. During loading, drug distribution was calculated using the system equilibrium equations, and key parameters are shown in Table 5.

[0139] Table 5 System Balance Parameters

[0140] Parameter type numerical values unit Intramembrane drug concentration 1.85 mg / mL Exogenous drug concentration 0.65 mg / mL Intraphase drug concentration 2.15 mg / mL transmembrane flux <![CDATA[3.26×10 -6 ]]> <![CDATA[mol / (m 2 ·s)]]> Membrane porosity 0.15 - Membrane permeability <![CDATA[2.8×10 -6 ]]> cm / s

[0141] After loading, free drug was removed by ultrafiltration centrifugation. The ultrafiltration parameters were 5000g, 30 minutes, 4 degrees Celsius, repeated twice. Formulation preparation was carried out using a programmed cooling lyophilization process. The lyophilization process parameters are shown in Table 6.

[0142] Table 6 Freeze-drying process parameters

[0143] stage Temperature (°C) Vacuum level (Pa) Time (h) Temperature difference on the rack (°C) Pre-freezing -40 - 4 5 One-time drying -20 20 24 8 Secondary drying 20 10 12 6

[0144] The key quality indicators of the final formulation are shown in Table 7:

[0145] Table 7. Preparation Quality Indicators

[0146] Indicator Type numerical values unit Drug loading rate 62.5 ％ Encapsulation rate 85.3 ％ Crystallinity 18.6 ％ residual moisture 2.1 ％ Particle size uniformity 0.142 PDI Release rate (24h) 76.8 ％

[0147] Figure 5 The in vitro release curve of the drug is shown, with light blue indicating the fluctuation range, ultimately achieving a confidence interval of approximately 95%. Compared to traditional exovesicle drug loading methods, this embodiment employs a systematic parameter optimization method that significantly improves loading efficiency. Traditional methods mainly rely on experience to select loading parameters, with loading efficiencies typically between 20% and 30%, and significant batch-to-batch variations. This embodiment establishes a loading parameter optimization function:

[0148]

[0149] Combining the system's equilibrium equations:

[0150]

[0151] Precise control of the loading process was achieved, increasing loading efficiency to 62.5% with a batch-to-batch relative standard deviation of less than 5%. Simultaneously, through the construction of a multi-dimensional index vector, the loading parameters were systematically optimized, ensuring the stability and uniformity of product quality. This method not only improves drug loading efficiency but also significantly enhances product quality controllability and batch-to-batch consistency, providing reliable technical support for the large-scale production of exovesicle drug loading systems.

[0152] It should be noted that the variables involved in this invention are explained in detail in Table 8 below.

[0153] Table 8. Variable Explanation Table

[0154]

[0155]

[0156] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for preparing an exovesicular drug and biomarker loading system, characterized by, The method comprises the following steps: Collecting human cell culture fluid, removing cell debris and large particles by differential centrifugation, filtering the supernatant through a 0.22 micron filter; separating exosomes by ultracentrifugation; adding 1% to 3% polyethylene glycol to the resuspended exosome solution; and measuring the surface potential of the exosomes; Measuring the particle size distribution and surface area of the exosomes by dynamic light scattering; selecting exosomes with a particle size in the range of 30 to 150 nanometers; adding a targeting ligand to the modified exosome solution; dissolving the drug and biomarker to be loaded in dimethyl sulfoxide to prepare a solution with a concentration of 1 to 5 milligrams per milliliter; establishing a loading parameter optimization function based on a set of electroporation loading parameters; using a dynamic programming method to solve the optimal electroporation parameter combination; calculating the drug and biomarker loading rate and encapsulation rate by a system of exosome drug and biomarker balance equations, which includes a drug and biomarker distribution balance equation, a membrane flux balance equation, and a mass conservation equation; removing unloaded free drugs and biomarkers by ultrafiltration centrifuge tubes according to the system drug and biomarker distribution function; freeze-drying the prepared exosome drug and biomarker loading system to obtain a freeze-dried powder; and measuring the crystallinity of the preparation by differential scanning calorimetry and X-ray diffraction, and selecting a preparation with a crystallinity in the range of 10% to 30%.

2. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by the steps of: The differential centrifugation method comprises the following steps: first, removing intact cells by centrifugation at 300g for 10 minutes at 4°C; collecting the supernatant and removing cell debris by centrifugation at 2000g for 20 minutes; and then removing large particles by centrifugation at 10000g for 30 minutes.

3. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by the steps of: The ultracentrifugation method for separating exosomes comprises the following steps: centrifuging at 100000 rpm for 120 minutes at 4°C; resuspending the precipitate with pre-cooled phosphate buffer after centrifugation; and resuspending the volume to 1 / 10 of the original culture solution.

4. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by, In the system of exosome drug and biomarker balance equations, the drug and biomarker distribution balance equation uses the concentration of the drug and biomarker in the outer phase, the concentration of the drug and biomarker in the inner phase, and the membrane surface charge density parameter, and outputs the drug and biomarker concentration distribution function in the membrane; the membrane flux balance equation uses the transmembrane concentration difference, membrane porosity, reaction temperature, and exosome number parameters, and outputs the drug and biomarker transmembrane flux; and the mass conservation equation uses the total volume of the system, loading time, and exosome volume fraction parameters, and outputs the system drug and biomarker distribution function.

5. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by the steps of: The loading parameter optimization function is a two-dimensional discrete data set composed of voltage value points and time value points, the voltage range is 150 to 300 volts, and the pulse time range is 10 to 20 milliseconds.

6. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by, The mass ratio of the targeting ligand to the exosome protein is 1:50 to 1:100, and the reaction is carried out at 25°C for 60 minutes.

7. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by the steps of: The freeze-drying step includes three stages of pre-freezing, primary drying and secondary drying, the pre-freezing stage is performed at minus 40 degrees Celsius, the freezing time is 4 hours, the primary drying stage is performed at minus 20 degrees Celsius, the vacuum degree is 20 Pa, and the drying time is 24 hours, and the secondary drying stage is performed at 20 degrees Celsius, the vacuum degree is 10 Pa, and the drying time is 12 hours.

8. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by, The electroporation method is performed 3 to 5 times of electroporation operations when loading drugs and biomarkers, and the time interval between adjacent two electroporation operations is 30 seconds.

9. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by, The initial concentration of the drug and biomarker solution is determined by high performance liquid chromatography, and the molecular weight and membrane lipid water partition coefficient of the drug and biomarker to be loaded are determined.

10. The method of claim 1, wherein the outer vesicular drug and biomarker loading system is prepared by, The crystallinity determination conditions by differential scanning calorimetry include a temperature rise rate of 10 degrees Celsius per minute and a scanning range of 25 to 200 degrees Celsius; the X-ray diffraction determination conditions include a Cu target, a tube voltage of 40 kilovolts, a tube current of 30 milliamperes, a scanning range of 5 to 40 degrees, and a scanning speed of 4 degrees per minute.

Images