Preparation method of tetanus human immune globulin

Abstract

The invention relates to the technical field of biological pharmacy, and discloses a tetanus human immune globulin preparation method, which comprises: S1, plasma pretreatment: taking anticoagulant plasma with a tetanus antibody titer of more than or equal to 10 IU / mL, and carrying out filtration treatment on the anticoagulant plasma; an improved self-adaptive algorithm is adopted to determine various parameters in the extraction process, S3, composite chromatographic purification, S4, collaborative virus inactivation, and S5, preparation preparation. According to the method, through linkage of an improved adaptive particle swarm-response surface coupling algorithm, first, 40 groups of initial sample sets are constructed by Latin hypercube sampling, a double-response surface model (R2gt; 0.95) is fitted by using a quadratic polynomial, and then a particle swarm depends on the model to predict fitness and dynamically adjust inertia weight balance optimization. By means of the linkage, the TT-IgG extraction rate is increased by 13-15%, the impurity protein removal rate is increased by 14-16%, RSD of three parallel experiments is smaller than or equal to 3%, and it is guaranteed that parameters are accurate and repeated.

Description

Technical Field

[0001] This invention relates to the field of biopharmaceutical technology, specifically to a method for preparing tetanus immunoglobulin. Background Technology

[0002] Tetanus immunoglobulin (TT-IgG) is a specific antibody preparation extracted from human plasma. It is mainly used for the prevention and treatment of tetanus, and is especially suitable for patients who are allergic to tetanus antitoxin. Its preparation process requires key steps such as plasma pretreatment, extraction, purification, virus inactivation and preparation. Among them, the low-temperature ethanol extraction step plays a decisive role in the product yield and purity.

[0003] In existing technologies, the optimization of low-temperature ethanol extraction parameters for tetanus immunoglobulin often employs single-factor experiments or orthogonal experimental methods. By fixing other variables and adjusting individual parameters such as ethanol concentration, system temperature, and pH one by one, the optimal parameter range is determined by combining indicators such as extraction rate and removal rate of impurities. Some processes introduce response surface methodology for limited multi-parameter fitting to assist in screening parameter combinations.

[0004] The most critical shortcoming of the existing technology is that traditional optimization methods are difficult to achieve synergistic optimization of multiple parameters and cannot accurately explore the interaction between ethanol concentration, temperature and pH, resulting in unsatisfactory extraction efficiency and removal of impurities and proteins. In addition, the parameters have poor repeatability, making it difficult to meet the requirements of high yield and high purity for large-scale production. In view of this, we propose a method for preparing tetanus immunoglobulin. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for preparing tetanus immunoglobulin, which solves the problems of poor extraction efficiency and insufficient reproducibility caused by the difficulty in coordinating and optimizing multiple parameters in traditional methods.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for preparing tetanus immunoglobulin, comprising the following steps: S1 Plasma Pretreatment: Take anticoagulated plasma with a tetanus antibody titer ≥10 IU / mL, filter it through a filter cloth and then through a microfiltration membrane to remove impurities, and obtain pretreated plasma; S2 Low-Temperature Ethanol Co-extraction: Based on the pretreated plasma obtained in S1, parameters were determined using an improved adaptive algorithm. Ethanol was added to the pretreated plasma to adjust the final concentration to 15-25% (v / v), the pH of the system was adjusted to 5.0-6.0, the system temperature was lowered to -2~4℃, and after incubation and stirring, centrifugation was performed. The supernatant was collected as the crude extract. S3 composite chromatography purification: Based on the crude extract obtained from S2, the crude extract is first loaded onto an equilibrated weak anion exchange resin column. After rinsing with equilibration buffer, it is eluted with Tris-HCl buffer containing 0.1-0.2 mol / L NaCl at a flow rate of 1.0-1.5 BV / h and the elution peak is collected. Then, ammonium sulfate is added to the elution peak solution to adjust the concentration and pH. After adjusting the pH, the solution is loaded onto an equilibrated hydrophobic interaction chromatography column. After rinsing with equilibration buffer containing ammonium sulfate, it is eluted with equilibration buffer containing low concentration of ammonium sulfate at a flow rate of 1.0-1.5 BV / h and the elution peak is collected as the pure solution. S4 synergistic virus inactivation: Based on the pure solution obtained from S3, the pH of the pure solution was adjusted to 3.8-4.2 with acid solution, and the system temperature was controlled at 25-30℃ for 24-36h. After incubation, the solution was pretreated by microfiltration membrane and then filtered through a 20-30nm nanometer membrane. The filtrate was collected. Preparation of S5 formulation: Based on the filtrate obtained in S4, the filtrate is concentrated through an ultrafiltration membrane to a tetanus immunoglobulin concentration of 80-120 g / L. Sodium chloride is added to adjust the osmotic pressure, and after filtration and sterilization through a terminal filter membrane, it is dispensed into containers to obtain the finished tetanus immunoglobulin product.

[0007] Preferably, in the S1 plasma pretreatment, the anticoagulated plasma is anticoagulated with sodium citrate solution, and the mass-volume concentration of sodium citrate solution in the anticoagulated plasma is 0.35-0.40%; the mesh size of the filter cloth is 480-520 mesh; and the pore size of the microfiltration membrane used for filtration is 0.40-0.50 μm.

[0008] Preferably, in the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm optimizes parameters by constructing an initial sample set and a dual response surface model. The initial sample set uses ethanol concentration, system temperature, and system pH as input variables, and the dual response surface model correlates the input variables with the extraction efficiency index.

[0009] Preferably, in the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm includes particle swarm parameter settings, including particle number, initial value of inertia weight, learning factor and maximum number of iterations, with a comprehensive evaluation function as the fitness judgment criterion.

[0010] Preferably, in the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm achieves iterative optimization by dynamically adjusting the inertia weight, and imposes boundary constraints on the particle positions to ensure that the parameters are within the set range.

[0011] Preferably, in the S2 low-temperature ethanol co-extraction, the dual response surface model uses a quadratic polynomial fitting, and outputs the optimal parameters when the iteration reaches the termination condition. The termination condition includes the maximum number of iterations or a fitness value stability threshold.

[0012] Preferably, in the S2 low-temperature ethanol co-extraction, the ethanol used is an ethanol solution with a mass-volume concentration of 92-98%; the ethanol is added while stirring, with a stirring rate of 250-350 r / min; the temperature is maintained while stirring at a rate of 280-320 r / min for 0.8-1.2 h; the centrifugation operation temperature is 3-5℃, the rotation speed is 7500-8500 r / min, and the centrifugation time is 18-22 min.

[0013] Preferably, in the S3 composite chromatography purification, the weak anion exchange resin is DEAE-PSB resin with a crosslinking degree of 8-12% and a particle size of 50-80 μm; the equilibration buffer is 0.04-0.06 mol / L Tris-HCl buffer with a pH of 7.0-7.4; the crude extract loading volume is 23-27 mg tetanus immunoglobulin / mL resin; and rinsing is performed until the UV 280 nm absorbance is stable.

[0014] Preferably, in the S3 composite chromatography purification, the hydrophobic interaction chromatography column packing material is phenyl agarose; the final concentration after adding ammonium sulfate is 0.8-1.2 mol / L, and the pH after adjustment is 6.8-7.2; the equilibration solution is a 0.04-0.06 mol / L Tris-HCl buffer containing 0.8-1.2 mol / L ammonium sulfate, with a pH of 6.8-7.2; the concentration of the Tris-HCl buffer used for elution is 0.05 mol / L; and the concentration of ammonium sulfate in the low-concentration ammonium sulfate equilibration solution is 0.08-0.12 mol / L.

[0015] Preferably, in the S4 synergistic virus inactivation and S5 preparation of the agent, the acid solution used to adjust the pH is a 1 mol / L hydrochloric acid solution; the incubation process is stirred once every 6-8 hours at a stirring rate of 150-200 r / min; the microfiltration membrane used for pretreatment in S4 has a pore size of 0.20-0.24 μm; the nanomembrane is a hydrophilic polyethersulfone membrane, the operating pressure is 0.10-0.15 MPa, and the temperature is 18-25℃; the ultrafiltration membrane has a molecular weight cutoff of 28-32 kDa; the amount of sodium chloride added is such that its mass-volume concentration in the solution reaches 0.8-1.0%; the pore size of the terminal filter membrane is 0.20-0.24 μm; and the container is a vial with a specification of 8-12 mL.

[0016] This invention provides a method for preparing human tetanus immunoglobulin. It has the following beneficial effects: 1. This invention utilizes an improved adaptive particle swarm optimization-response surface coupling algorithm. First, 40 initial sample sets are constructed using Latin hypercube sampling. Then, a quadratic polynomial is used to fit the dual response surface model (R²). 2(>0.95), then the particle swarm optimization relies on the model to predict fitness, dynamically adjusting the inertia weights to achieve optimal balance. This linkage increases the TT-IgG extraction rate by 13-15 percentage points, the removal rate of impurity proteins by 14-16 percentage points, and the RSD of three parallel experiments is ≤3%, ensuring parameter accuracy and repeatability.

[0017] 2. This invention proposes a novel DEAE-PSB weak anion exchange resin (adsorption capacity 25 mg / mL) combined with hydrophobic interaction chromatography in the purification step. The eluent is optimized to be a Tris-HCl buffer containing 0.1-0.2 mol / L NaCl (flow rate 1.2 BV / h). Compared with traditional DEAE-Sepharose resin and single chromatography, the removal rate of impurities is increased by 3.5-8.2 percentage points, the product purity reaches over 99.4%, and the antibody titer is indirectly improved. This reduces the impurity load for subsequent processes and ensures the quality of the final product.

[0018] 3. This invention proposes a synergistic method of "low pH incubation + nano-membrane filtration" in the virus inactivation process. After adjusting the pH to 3.8-4.2 and incubating at 25-30℃ for 24-36 hours, the virus is filtered through a 20-30nm polyethersulfone membrane. Compared with low pH incubation alone, the virus inactivation titer is increased from 4.7log to over 7.0log (meeting the ≥6log standard), and the antibody activity retention rate reaches over 91.5%. This improves the safety of virus inactivation while minimizing the impact on antibody activity, thus balancing safety and efficacy. Attached Figure Description

[0019] Figure 1 This is a perspective view of the present invention. Detailed Implementation

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see the appendix Figure 1 This invention provides a method for preparing human tetanus immunoglobulin, comprising the following steps: S1 Plasma Pretreatment: Take anticoagulated plasma with a tetanus antibody titer ≥10 IU / mL, filter it through a filter cloth and then through a microfiltration membrane to remove impurities, and obtain pretreated plasma; In the S1 plasma pretreatment, the anticoagulated plasma is anticoagulated using sodium citrate solution, with a mass-volume concentration of 0.35-0.40% in the anticoagulated plasma; the filter cloth has a mesh size of 480-520 mesh; and the microfiltration membrane used for filtration has a pore size of 0.40-0.50 μm. S2 Low-Temperature Ethanol Co-extraction: Based on the pretreated plasma obtained in S1, parameters were determined using an improved adaptive algorithm. Ethanol was added to the pretreated plasma to adjust the final concentration to 15-25% (v / v), the pH of the system was adjusted to 5.0-6.0, the system temperature was lowered to -2~4℃, and after incubation and stirring, centrifugation was performed. The supernatant was collected as the crude extract. In the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm optimizes parameters by constructing an initial sample set and a dual response surface model. The initial sample set uses ethanol concentration, system temperature, and system pH as input variables. The dual response surface model correlates the input variables with the extraction efficiency index. In the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm includes particle swarm parameter settings, including particle number, initial inertia weight, learning factor, and maximum iteration count. A comprehensive evaluation function is used as the fitness criterion. In the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm achieves iterative optimization by dynamically adjusting the inertia weight and constrains particle positions to ensure parameters remain within a set range. In the S2 low-temperature ethanol co-extraction, the dual response surface model uses quadratic polynomial fitting. When the iteration reaches a termination condition, the optimal parameters are output. The termination condition includes the maximum number of iterations or a fitness value stabilization threshold. The algorithm includes the following: The first step was to construct an initial sample set, using ethanol concentration X1 (in % (v / v), representing the volume percentage of ethanol in the plasma system), system temperature X2 (in °C, representing the temperature of the reaction system during extraction), and system pH X3 (unitless, representing the acidity or alkalinity of the reaction system) as input variables. Each variable had 5 levels (X1: 15%, 18%, 21%, 24%, 25%; X2: -2℃, 0℃, 2℃, 3℃, 4℃; X3: 5.0, 5.3, 5.5, 5.7, 6). 0), using Latin hypercube sampling to generate 40 initial samples (each sample corresponds to a set of (X1, X2, X3) parameter combinations), and performing extraction experiments on each sample according to step S2, measuring and recording the extraction rate Y1 of tetanus immunoglobulin in the crude extract (in %, i.e. the percentage of tetanus immunoglobulin extracted relative to the initial total amount in plasma) and the removal rate of impurities Y2 (in %, i.e. the percentage of removed impurities relative to the initial total amount of impurities in plasma), which will serve as the basis for subsequent modeling; The second step is to establish a response surface model. Based on the 40 sets of data (X1, X2, X3, Y1, Y2) obtained in the first step, a quadratic polynomial is used to fit the relationship between Y1 and (X1, X2, X3) and Y2 and (X1, X2, X3) respectively, resulting in a dual response surface model. Its general formula is: , Where Y is the response value (Y=Y1 when fitting Y1, Y=Y2 when fitting Y2), a0 is the constant term (the baseline value obtained from the fitting), a i Let a be the coefficient of the linear term (i=1,2,3, corresponding to the linear influence coefficients of X1, X2, and X3, respectively). ii The coefficients of the quadratic term (i=1,2,3, respectively corresponding to...) (nonlinear influence coefficient), a ij The coefficients of the interaction term (1≤i<j≤3, corresponding to X) i X j The interaction coefficients were obtained by fitting the sample data using the least squares method. This model is used to quantitatively describe the impact of input variables on the extraction efficiency index and to provide a predictive basis for subsequent particle swarm optimization. The third step initializes the particle swarm parameters, setting the particle number N=30 (each particle represents a set of parameter combinations to be optimized (X1, X2, X3)), the initial value of the inertia weight ω0=0.9 (controlling the degree to which particles inherit their previous velocity), the learning factors c1=c2=2 (c1 is the individual learning factor, controlling the degree to which particles learn towards their own historical best position; c2 is the social learning factor, controlling the degree to which particles learn towards the global best position of the population), and the maximum number of iterations K=50 (the maximum number of iterations at which the algorithm terminates). Simultaneously, the fitness function F=0.6Y1+0.4Y2 is defined (where Y1 and Y2 are predicted by the response surface model in the second step, and the weights 0.6 and 0.4 reflect the importance of the extraction rate and removal rate, respectively; a larger F value indicates a better parameter combination). The position of each particle is then randomly initialized. (K=1 represents the first iteration, i=1,2,…,30 represents the i-th particle) and velocity (The velocity components correspond to the rates of change of X1, X2, and X3, respectively), where the initial position value is randomly generated within the range of variable values, and the initial velocity value is within [-v... max v max Randomly generated within (v) max For the maximum speed, take 2096 of the variable range; The fourth step is to perform adaptive iterative optimization. First, for each particle i in the k-th iteration, its position is calculated using the response surface model from the second step. The corresponding Y1 and Y2 are then substituted into the fitness function in the third step. Obtain the fitness value, and then update the individual optimal position of each particle. (like If the fitness is greater than the particle's historical best fitness, then (otherwise remain unchanged) and the population's global optimal position gbest k (Retrieve all) (The position with the highest fitness); then calculate the velocity for the (k+1)th iteration according to the velocity update formula: in The inertial weight of particle i in the k-th iteration is adjusted according to the adaptive strategy: if ( (where the average fitness of the population is in the k-th iteration) (rand() generates a random number between 0 and 1, making...) (Enhanced local search within the range of 0.4-0.6) like ,but (make (Between 0.7 and 0.9, enhance global search) (r1 and r2 are random numbers between 0 and 1) (increase search randomness); Update the formula by position. Calculate the new position and apply boundary constraints to it (if X1 exceeds 15-25%, force it to be set to the nearest boundary value; the same applies if X2 exceeds -2~4°C or X3 exceeds 5.0-6.0), ensuring that the parameters are within the valid range; repeat the above iterative process until the termination condition is met. The fifth step is to determine the optimal parameters. This is done when the number of iterations reaches the maximum number of iterations K=50 set in the third step, or when the global optimal fitness F is achieved in 5 consecutive iterations. gbest Change in F gbest,k+1 - F gbest,k When |≤0.001, stop iterating; at this point, the global optimal position of the population is gbest. k The corresponding parameter combination (X1, X2, X3) is the optimal extraction parameter for step S2. This parameter will be used to guide the actual low-temperature ethanol co-extraction operation, and its effectiveness will be verified by the linkage between the response surface model and particle swarm optimization (the particle swarm depends on the response surface model to predict fitness, and the prediction accuracy of the response surface model is guaranteed by the initial sample set). In the S2 low-temperature ethanol co-extraction, the ethanol used is an ethanol solution with a mass-volume concentration of 92-98%; the ethanol is added while stirring, with a stirring rate of 250-350 r / min; the stirring rate during heat preservation is 280-320 r / min, and the stirring time is 0.8-1.2 h; the centrifugation operation temperature is 3-5℃, the rotation speed is 7500-8500 r / min, and the centrifugation time is 18-22 min. Based on the improved adaptive algorithm described above, an experiment was conducted, and the experimental procedure is as follows: I. Plasma pretreatment: Take anticoagulated plasma with tetanus antibody titer ≥10 IU / mL (sodium citrate concentration 0.38%), filter it through a 500-mesh filter cloth, then filter it through a 0.45μm microfiltration membrane, and store it at 4℃ for later use.

[0022] II. Initial Sample Set Construction: 40 sets of parameters (X1, X2, X3) were generated by Latin hypercube sampling (X1: 15-25% ethanol concentration, X2: -2~4℃ temperature, X3: 5.0-6.0 pH). Each set of parameters corresponds to one extraction experiment.

[0023] III. Low-temperature ethanol extraction: Add 95% ethanol to 100 mL of pretreated plasma to adjust to X1, then adjust to X3 with 1 mol / L HCl / NaOH, cool to X2, stir at 300 r / min for 1 h, centrifuge at 4 °C and 8000 r / min for 20 min, and collect the supernatant.

[0024] IV. Index Determination: The concentration of tetanus immunoglobulin in the supernatant was determined by ultraviolet spectrophotometry (to calculate the extraction rate Y1), and the residual amount of impurities was determined by the Coomassie brilliant blue method (to calculate the removal rate Y2).

[0025] V. Response Surface Model Construction: A quadratic polynomial model was fitted using 40 sets of data (X1, X2, X3, Y1, Y2) to verify the model's significance (R²). 2 >0.95).

[0026] VI. Particle Swarm Optimization: Based on the response surface model, adaptive optimization is performed according to the initial parameters (number of particles 30, ω0=0.9, c1=c2=2, 50 iterations) to output the optimal parameters.

[0027] VII. Verification Experiment: Repeat the extraction experiment three times with the optimal parameters, calculate the average value and RSD (relative standard deviation) of Y1 and Y2, and verify the reliability of the algorithm.

[0028] Parameter table for the validation experiment of optimized parameters in step S2 of tetanus immunoglobulin preparation:

[0029] Note: 1. The optimal verification parameters are the optimal values ​​output by the "Improved Adaptive Particle Swarm Response Surface Coupling Algorithm"; 2. All assay methods comply with the relevant provisions of the "Tetanus Immunoglobulin" section in Part III of the Chinese Pharmacopoeia (2020 Edition); 3. Correlation indicators directly reflect the effectiveness of optimized parameters; RSD ≤ 5% indicates that the experimental results have good repeatability. Experimental conclusions Parameter optimization results: The optimal parameters for step S2 (final ethanol concentration 2096 (v / v), system temperature 0°C, system pH 5.5) obtained by the "improved adaptive particle swarm optimization-response surface optimization algorithm" can stably achieve an extraction rate of over 95% for tetanus immunoglobulin (TT-IgG) and a removal rate of over 90% for impurities. Compared with the traditional single-factor optimization method (extraction rate 80-82%, impurity removal rate 74-76%), the extraction rate is improved by 13-15 percentage points and the impurity removal rate is improved by 14-16 percentage points, effectively solving the pain points of "low extraction efficiency and incomplete removal of impurities" in traditional processes. Algorithm reliability and model validity: Coefficient of determination R of response surface model 2 >0.95 indicates that the model can accurately fit the relationship between ethanol concentration, temperature, pH and extraction efficiency; during particle swarm optimization, the change in global optimal fitness over 5 consecutive iterations is ≤0.001, proving that the algorithm converges and is stable; in 3 parallel verification experiments, the relative standard deviation (RSD) of extraction rate and impurity protein removal rate is ≤396, which is far below the set 5% threshold, indicating that the optimization parameters have good repeatability and practicality and can be used for large-scale production; Process stability: Under optimal parameters, plasma pretreatment (0.38% sodium citrate concentration, 0.45μm microfiltration membrane) and extraction (adding ethanol at 300r / min and stirring, centrifuging at 8000r / min for 20min) work synergistically to ensure the structural stability of TT-IgG in the supernatant (verified by SDS-PAGE electrophoresis, no obvious protein denaturation bands were observed), and the residual amount of impurities was ≤0.5g / L. This reduced the impurity load for the subsequent S3 complex chromatography purification step, indirectly improving the purity and antibody titer of the final product. S3 composite chromatography purification: Based on the crude extract obtained from S2, the crude extract is first loaded onto an equilibrated weak anion exchange resin column. After rinsing with equilibration buffer, it is eluted with Tris-HCl buffer containing 0.1-0.2 mol / L NaCl at a flow rate of 1.0-1.5 BV / h and the elution peak is collected. Then, ammonium sulfate is added to the elution peak solution to adjust the concentration and pH. After adjusting the pH, the solution is loaded onto an equilibrated hydrophobic interaction chromatography column. After rinsing with equilibration buffer containing ammonium sulfate, it is eluted with equilibration buffer containing low concentration of ammonium sulfate at a flow rate of 1.0-1.5 BV / h and the elution peak is collected as the pure solution. In the S3 composite chromatography purification, the weak anion exchange resin is DEAE-PSB resin with a crosslinking degree of 8-12% and a particle size of 50-80 μm; the equilibration buffer is 0.04-0.06 mol / L Tris-HCl buffer with a pH of 7.0-7.4; the crude extract loading volume is 23-27 mg tetanus immunoglobulin / mL resin; and the solution is washed until the UV absorbance at 280 nm is stable. In the S3 composite chromatography purification, the hydrophobic interaction chromatography column packing material is phenyl agarose; the final concentration after adding ammonium sulfate is 0.8-1.2 mol / L, and the pH is adjusted to 6.8-7.2; the equilibration buffer is a 0.04-0.06 mol / L Tris-HCl buffer containing 0.8-1.2 mol / L ammonium sulfate, with a pH of 6.8-7.2; the concentration of Tris-HCl buffer used for elution is 0.05 mol / L; the concentration of ammonium sulfate in the low-concentration ammonium sulfate equilibration solution is 0.08-0.12 mol / L. S4 synergistic virus inactivation: Based on the pure solution obtained from S3, the pH of the pure solution was adjusted to 3.8-4.2 with acid solution, and the system temperature was controlled at 25-30℃ for 24-36h. After incubation, the solution was pretreated by microfiltration membrane and then filtered through a 20-30nm nanometer membrane. The filtrate was collected. Preparation of S5 formulation: Based on the filtrate obtained in S4, the filtrate is concentrated through an ultrafiltration membrane to a tetanus immunoglobulin concentration of 80-120 g / L. Sodium chloride is added to adjust the osmotic pressure. After filtration and sterilization through a terminal filter membrane, the filtrate is dispensed into containers to obtain the finished tetanus immunoglobulin product. In the preparation of the S4 synergistic virus inactivation and S5 formulation, the acid solution used to adjust the pH is a 1 mol / L hydrochloric acid solution; the incubation process is stirred once every 6-8 hours at a stirring rate of 150-200 r / min; the microfiltration membrane used for pretreatment in S4 has a pore size of 0.20-0.24 μm; the nanomembrane is a hydrophilic polyethersulfone membrane, the operating pressure is 0.10-0.15 MPa, and the temperature is 18-25℃; the ultrafiltration membrane has a molecular weight cutoff of 28-32 kDa; the amount of sodium chloride added is such that its mass-volume concentration in the solution reaches 0.8-1.0%; the pore size of the terminal filter membrane is 0.20-0.24 μm; the container is a vial with a specification of 8-12 mL. Example 1:

[0030] S1 Plasma Pretreatment: Take anticoagulated plasma with a tetanus antibody titer of 12 IU / mL, and use sodium citrate solution for anticoagulation (the mass-volume concentration of sodium citrate solution in anticoagulated plasma is 0.38%). Filter the plasma through a 500-mesh filter cloth and a 0.45 μm microfiltration membrane to remove impurities, and then store it at 4℃ for later use.

[0031] S2 Low-Temperature Ethanol Co-extraction: Based on the pretreated plasma obtained in S1, parameters were determined using an improved adaptive algorithm. 95% ethanol was added to 100 mL of pretreated plasma while stirring (stirring rate 300 r / min) to adjust the final ethanol concentration to 18% (v / v). The pH of the system was adjusted to 5.5 using 1 mol / L HCl / NaOH. The system temperature was lowered to 0℃ and stirred at 300 r / min for 1.0 h. Afterward, the system was centrifuged at 4℃ and 8000 r / min for 20 min, and the supernatant was collected as the crude extract. The improved adaptive algorithm optimizes parameters by constructing an initial sample set and a dual response surface model. This includes setting particle swarm parameters (30 particles, initial inertia weight of 0.9, learning factors c1=c2=2, and maximum number of iterations of 50). The comprehensive evaluation function F=0.6Y1+0.4Y2 is used as the fitness criterion. Iterative optimization is achieved by dynamically adjusting the inertia weight. Boundary constraints are imposed on particle positions. The dual response surface model is fitted with a quadratic polynomial. The parameters are output when the iteration reaches the termination condition (the change in global optimal fitness is ≤0.001 after 5 consecutive iterations or after 50 iterations).

[0032] S3 composite chromatography purification: Based on the crude extract obtained in S2, the crude extract was first loaded onto an equilibrated weak anion exchange resin column (the weak anion exchange resin was DEAE-PSB resin, with a crosslinking degree of 10% and a particle size of 65 μm; the equilibration buffer was 0.05 mol / L Tris-HCl buffer, pH 7.2; the loading volume was 25 mg tetanus immunoglobulin / mL resin). After washing with the equilibration buffer until the absorbance at UV 280 nm stabilized, it was then purified by 0.05 mol / L Tris-HCl buffer containing 0.15 mol / L NaCl at a flow rate of 1.2 BV / h. The elution was rapidly eluted and the elution peak was collected. Ammonium sulfate was then added to the elution peak solution to adjust the final concentration to 1.0 mol / L. The pH was adjusted to 7.0, and the solution was loaded onto an equilibrated hydrophobic interaction chromatography column (the packing material was phenyl agarose; the equilibration buffer was 0.05 mol / L Tris-HCl buffer containing 1.0 mol / L ammonium sulfate, pH 7.0). After washing with equilibration buffer containing 1.0 mol / L ammonium sulfate, the solution was eluted with 0.05 mol / L Tris-HCl buffer containing 0.1 mol / L ammonium sulfate at a flow rate of 1.2 BV / h. The elution peak was collected as the pure solution.

[0033] S4 synergistic virus inactivation: Based on the pure solution obtained from S3, the pH of the pure solution was adjusted to 4.0 with 1 mol / L hydrochloric acid solution, and the system temperature was controlled at 28℃ for 30 h. During the incubation process, the solution was stirred once every 7 h at a rate of 180 r / min. After incubation, the solution was pretreated by a 0.22 μm microfiltration membrane and then filtered through a 25 nm hydrophilic polyethersulfone nanomembrane (operating pressure 0.12 MPa, temperature 22℃), and the filtrate was collected.

[0034] Preparation of S5 formulation: Based on the filtrate obtained in S4, the filtrate was concentrated to a tetanus immunoglobulin concentration of 100 g / L using an ultrafiltration membrane with a molecular weight cutoff of 30 kDa. Sodium chloride was added to adjust the osmotic pressure by making the sodium chloride mass-volume concentration in the solution reach 0.9%. After filtration and sterilization through a 0.22 μm terminal filter membrane, the solution was dispensed into 10 mL vials to obtain the finished tetanus immunoglobulin product. Example 2:

[0035] Compared with Example 1, only the system temperature in the S2 low-temperature ethanol co-extraction is different; all other steps and parameters are the same.

[0036] S2 Low-Temperature Ethanol Co-extraction: The system temperature was adjusted to 2°C, the final ethanol concentration remained at 18% (v / v), the system pH remained at 5.5, and other operations and algorithm parameters were the same as in Example 1. Example 3:

[0037] Compared with Example 1, only the pH of the system in the S2 low-temperature ethanol co-extraction is different; all other steps and parameters are the same.

[0038] S2 Low-Temperature Ethanol Co-extraction: The system pH was adjusted to 5.3, the final ethanol concentration remained at 18% (v / v), the system temperature remained at 0℃, and other operations and algorithm parameters were the same as in Example 1. Example 4:

[0039] Compared with Example 1, the only difference is the concentration of ammonium sulfate related to the hydrophobic interaction column in the S3 composite chromatography purification; all other steps and parameters are the same.

[0040] S3 composite chromatography purification: The final concentration of ammonium sulfate added to the elution peak solution of the weak anion exchange resin column was 0.9 mol / L, and the pH was adjusted to 7.0. The equilibration solution of the hydrophobic interaction chromatography column was 0.05 mol / L Tris-HCl buffer containing 0.9 mol / L ammonium sulfate (pH 7.0). During elution, elution was performed with 0.05 mol / L Tris-HCl buffer containing 0.09 mol / L ammonium sulfate at a flow rate of 1.2 BV / h. Other operations and parameters were the same as in Example 1.

[0041] Comparative Example 1: Traditional Single-Factor Optimization of S2 Parameters S1 Plasma Pretreatment: Same as in Example 1, i.e., take anticoagulated plasma with a tetanus antibody titer of 12 IU / mL, sodium citrate concentration of 0.38% (w / v), filter with a 500-mesh filter cloth, filter with a 0.45 μm microfiltration membrane, and store at 4°C for later use.

[0042] S2 Low-Temperature Ethanol Co-extraction: Parameters were determined through single-factor trial and error without employing an improved adaptive algorithm. 95% ethanol was added to 100 mL of pretreated plasma while stirring (280 rpm) until the final ethanol concentration reached 22% (v / v). The pH was adjusted to 5.8 using 1 mol / L HCl / NaOH. The system temperature was lowered to 2°C and stirred at 300 rpm for 1.2 h. The mixture was then centrifuged at 4°C and 7500 rpm for 20 min, and the supernatant was collected as the crude extract.

[0043] S3 composite chromatography purification, S4 synergistic virus inactivation, and S5 preparation of the formulation are all the same as in Example 1.

[0044] Comparative Example 2: S3 using traditional anion exchange resin S1 Plasma pretreatment, S2 Low-temperature ethanol synergistic extraction: Same as in Example 1.

[0045] S3 composite chromatography purification: The weak anion exchange resin was replaced with traditional DEAE-Sepharose resin (6% crosslinking, 100 μm particle size); the equilibration buffer remained 0.05 mol / L Tris-HCl buffer (pH 7.2); the crude extract was loaded at a rate of 18 mg tetanus immunoglobulin / mL resin; after rinsing with the equilibration buffer until the UV absorbance at 280 nm stabilized, elution was performed with 0.05 mol / L Tris-HCl buffer containing 0.15 mol / L NaCl at a flow rate of 1.2 BV / h and the elution peak was collected; subsequently, ammonium sulfate was added to the elution peak solution to adjust the final concentration to 1.0 mol / L and the pH to 7.0, and the loading and elution procedures were the same as in Example 1.

[0046] S4 synergistic virus inactivation and S5 preparation: are the same as in Example 1.

[0047] Comparative Example 3: S3 using only single anion chromatography S1 Plasma pretreatment, S2 Low-temperature ethanol synergistic extraction: Same as in Example 1.

[0048] S3 composite chromatography purification: Only the weak anion exchange chromatography step is retained, omitting the hydrophobic interaction chromatography step. The crude extract is loaded onto a DEAE-PSB resin column (parameters are the same as in Example 1), washed with equilibration buffer until the UV absorbance at 280 nm stabilizes, and then eluted with a 0.05 mol / L Tris-HCl buffer containing 0.15 mol / L NaCl at a flow rate of 1.2 BV / h. The elution peak is collected directly as the pure solution.

[0049] S4 synergistic virus inactivation and S5 preparation: are the same as in Example 1.

[0050] Comparative Example 4: S4 was incubated with low pH only. S1 Plasma pretreatment, S2 Low-temperature ethanol synergistic extraction, S3 Composite chromatography purification: Same as in Example 1.

[0051] S4 Synergistic Virus Inactivation: Based on the pure solution obtained from S3, the pH of the pure solution was adjusted to 4.0 with 1 mol / L hydrochloric acid solution, and the system temperature was controlled at 28℃ for 30 h. During the incubation process, the solution was stirred once every 7 h at a rate of 180 r / min. After incubation, the solution was directly filtered through a 0.22 μm microfiltration membrane, and the filtrate was collected, eliminating the need for the 25 nm hydrophilic polyethersulfone nanofiltration step.

[0052] Preparation of S5 formulation: Same as in Example 1.

[0053] Experimental Results Recording Table (Comparison of Core Indicators between Example and Comparative Examples) Group S2 key variable parameters S3 Key Variable Parameters S4 Key Operations TT-IgG extraction rate (%) Protein removal rate (%) Product purity (%) Virus inactivation titer (log) Antibody activity retention rate (%) RSD (%, n=3) Example 1 18% ethanol, 0°C, pH 5.5 HIC ammonium sulfate 1.0 mol / L, elution 0.1 mol / L Low pH + 25nm membrane filtration 95.3 90.8 99.6 7.1 92.3 2.1 Example 2 18% ethanol, 2°C, pH 5.5 HIC ammonium sulfate 1.0 mol / L, elution 0.1 mol / L Low pH + 25nm membrane filtration 93.1 88.5 99.5 7.0 91.8 2.3 Example 3 18% ethanol, 0°C, pH 5.3 HIC ammonium sulfate 1.0 mol / L, elution 0.1 mol / L Low pH + 25nm membrane filtration 94.2 89.7 99.5 7.0 92.0 2.2 Example 4 18% ethanol, 0°C, pH 5.5 HIC ammonium sulfate 0.9 mol / L, elution 0.09 mol / L Low pH + 25nm membrane filtration 95.1 90.2 99.4 7.1 91.5 2.4 Comparative Example 1 Ethanol 22%, temperature 2℃, pH 5.8 (single-factor optimization) HIC ammonium sulfate 1.0 mol / L, elution 0.1 mol / L Low pH + 25nm membrane filtration 81.5 75.2 97.1 7.0 90.9 4.8 Comparative Example 2 18% ethanol, 0°C, pH 5.5 The resin used was DEAE-Sepharose, and the loading concentration was 18 mg / mL. Low pH + 25nm membrane filtration 95.0 87.3 98.2 7.1 92.1 2.5 Comparative Example 3 18% ethanol, 0°C, pH 5.5 Anion chromatography only (without HIC) Low pH + 25nm membrane filtration 95.2 82.6 98.0 7.0 91.7 2.6 Comparative Example 4 18% ethanol, 0°C, pH 5.5 HIC ammonium sulfate 1.0 mol / L, elution 0.1 mol / L Low pH incubation only (without membrane filtration) 95.4 90.5 99.5 4.7 92.2 2.3

[0054] Note: 1. Methods for determining indicators: TT-IgG extraction rate / impurity protein removal rate (UV spectrophotometry + Coomassie brilliant blue method), product purity (SDS-PAGE electrophoresis), virus inactivation titer (quantitative PCR for HBV), antibody activity retention rate (ELISA). 2. RSD is the relative standard deviation of three parallel experiments; Experimental conclusions 1. Conclusion on the effectiveness of parameter optimization in the example The impact of S2 parameters on core indicators: The TT-IgG extraction rate (95.3%) and the removal rate of impurities (90.8%) in Example 1 (optimal combination of S2 variables: 18% ethanol, 0℃ temperature, pH 5.5) were higher than those in Example 2 (temperature deviated to 2℃, extraction rate 93.1%, removal rate 88.5%) and Example 3 (pH deviated to 5.3, extraction rate 94.2%, removal rate 89.7%). This demonstrates that the synergistic optimization of ethanol concentration, temperature, and pH in S2 is the key to improving extraction efficiency. Furthermore, 0℃ temperature and 5.5 pH are more suitable for 18% ethanol concentration, which can reduce protein denaturation and impurity residue.

[0055] The effect of S3 parameter on purity: The purity of the product in Example 4 (HIC ammonium sulfate concentration reduced to 0.9 mol / L) (99.4%) was slightly lower than that in Example 1 (99.6%), but it still remained at a high level. This indicates that the HIC ammonium sulfate concentration in the range of 0.9-1.0 mol / L can effectively remove residual proteins. The process parameters have a certain degree of tolerance, providing room for parameter fine-tuning in large-scale production.

[0056] 2. Conclusions regarding differences from comparative techniques Algorithm optimization advantages: The TT-IgG extraction rate (81.5%) and impurity protein removal rate (75.2%) of Comparative Example 1 (traditional single-factor optimization S2) are much lower than those of Example 1, and the RSD (4.8%) is higher than that of Example 1 (2.1%). This proves that the "improved adaptive particle swarm optimization-response surface coupling algorithm" of this scheme can accurately explore the synergistic effect of multiple parameters. Compared with the single-factor trial and error method, the extraction efficiency is improved by 13.8 percentage points and the impurity protein removal rate is improved by 15.6 percentage points, while enhancing the experimental repeatability.

[0057] Advantages of resin selection: The removal rate of impurity proteins (87.3%) and the product purity (98.2%) of Comparative Example 2 (conventional DEAE-Sepharose resin) were lower than those of Example 1. This is because the traditional resin has a low adsorption capacity (18 mg / mL vs. 25 mg / mL in Example 1) and poor selectivity for impurity proteins. This proves that DEAE-PSB resin can effectively improve the purification effect, increasing the removal rate of impurity proteins by 3.5 percentage points and the product purity by 1.4 percentage points.

[0058] Advantages of composite chromatography: The removal rate of contaminant proteins in Comparative Example 3 (single chromatography only) (82.6%) and the product purity (98.0%) were significantly lower than those in Example 1, indicating that the composite chromatography of "anion exchange + hydrophobic interaction" can synergistically remove contaminant proteins with similar charges and different hydrophobic properties. Compared with single chromatography, the removal rate of contaminant proteins is increased by 8.2 percentage points and the product purity is increased by 1.6 percentage points.

[0059] Synergistic inactivation advantages: The virus inactivation titer of Comparative Example 4 (low pH incubation only) (4.7 log) was much lower than that of Example 1 (7.1 log), failing to meet the safety standard of ≥6 log in the Chinese Pharmacopoeia. This demonstrates that the synergistic inactivation of "low pH incubation + nanomembrane filtration" can completely retain residual virus, while maintaining antibody activity (92.2% vs. 92.3% in Example 1) and improving the safety of virus inactivation by 2.4 log.

[0060] 3. Conclusion on overall process stability The RSD of all embodiments was ≤2.4%, and the core indicators (extraction rate ≥93%, purity ≥99.4%, viral titer ≥7.0 log, activity retention rate ≥91.5%) were all better than those of the comparative examples. This proves that the parameters of the whole process of "pretreatment-extraction-purification-inactivation-formulation" of this solution are highly synergistic and the process is highly stable, which can meet the requirements of "high efficiency, high purity and high safety" for the large-scale production of tetanus immunoglobulin.

[0061] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for preparing tetanus immunoglobulin, characterized in that, Includes the following steps: S1 Plasma Pretreatment: Take anticoagulated plasma with a tetanus antibody titer ≥10 IU / mL, filter it through a filter cloth and then through a microfiltration membrane to remove impurities, and obtain pretreated plasma; S2 Low-Temperature Ethanol Co-extraction: Based on the pretreated plasma obtained in S1, parameters were determined using an improved adaptive algorithm. Ethanol was added to the pretreated plasma to adjust the final concentration to 15-25% (v / v), the pH of the system was adjusted to 5.0-6.0, the system temperature was lowered to -2~4℃, and after incubation and stirring, centrifugation was performed. The supernatant was collected as the crude extract. S3 composite chromatography purification: Based on the crude extract obtained from S2, the crude extract is first loaded onto an equilibrated weak anion exchange resin column. After rinsing with equilibration buffer, it is eluted with Tris-HCl buffer containing 0.1-0.2 mol / L NaCl at a flow rate of 1.0-1.5 BV / h and the elution peak is collected. Then, ammonium sulfate is added to the elution peak solution to adjust the concentration and pH. After adjusting the pH, the solution is loaded onto an equilibrated hydrophobic interaction chromatography column. After rinsing with equilibration buffer containing ammonium sulfate, it is eluted with equilibration buffer containing low concentration of ammonium sulfate at a flow rate of 1.0-1.5 BV / h and the elution peak is collected as the pure solution. S4 synergistic virus inactivation: Based on the pure solution obtained from S3, the pH of the pure solution was adjusted to 3.8-4.2 with acid solution, and the system temperature was controlled at 25-30℃ for 24-36h. After incubation, the solution was pretreated by microfiltration membrane and then filtered through a 20-30nm nanometer membrane. The filtrate was collected. Preparation of S5 formulation: Based on the filtrate obtained in S4, the filtrate is concentrated through an ultrafiltration membrane to a tetanus immunoglobulin concentration of 80-120 g / L. Sodium chloride is added to adjust the osmotic pressure, and after filtration and sterilization through a terminal filter membrane, it is dispensed into containers to obtain the finished tetanus immunoglobulin product.

2. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the S1 plasma pretreatment, the anticoagulated plasma is anticoagulated using sodium citrate solution, with a mass-volume concentration of 0.35-0.40% in the anticoagulated plasma; the filter cloth has a mesh size of 480-520 mesh; and the microfiltration membrane used for filtration has a pore size of 0.40-0.50 μm.

3. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm optimizes parameters by constructing an initial sample set and a dual response surface model. The initial sample set uses ethanol concentration, system temperature, and system pH as input variables, and the dual response surface model correlates the input variables with the extraction efficiency index.

4. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm includes particle swarm parameter settings, which include the number of particles, the initial value of the inertia weight, the learning factor, and the maximum number of iterations, with a comprehensive evaluation function as the fitness judgment criterion.

5. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the S2 low-temperature ethanol co-extraction, the improved adaptive algorithm achieves iterative optimization by dynamically adjusting the inertia weight and imposes boundary constraints on the particle positions to ensure that the parameters are within the set range.

6. The method for preparing tetanus immunoglobulin according to claim 3, characterized in that, In the S2 low-temperature ethanol co-extraction, the dual response surface model uses a quadratic polynomial fitting, and outputs the optimal parameters when the iteration reaches the termination condition. The termination condition includes the maximum number of iterations or the fitness value stability threshold.

7. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the S2 low-temperature ethanol co-extraction, the ethanol used is an ethanol solution with a mass-volume concentration of 92-98%; when adding ethanol, it is added while stirring, with a stirring rate of 250-350 r / min; the stirring rate during heat preservation is 280-320 r / min, and the stirring time is 0.8-1.2 h; the centrifugation operation temperature is 3-5℃, the rotation speed is 7500-8500 r / min, and the centrifugation time is 18-22 min.

8. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the S3 composite chromatography purification, the weak anion exchange resin is DEAE-PSB resin with a crosslinking degree of 8-12% and a particle size of 50-80 μm; the equilibration buffer is 0.04-0.06 mol / L Tris-HCl buffer with a pH of 7.0-7.4; the crude extract loading volume is 23-27 mg tetanus immunoglobulin / mL resin; and the solution is washed until the UV absorbance at 280 nm is stable.

9. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the S3 composite chromatography purification, the hydrophobic interaction chromatography column packing material is phenyl agarose; the final concentration after adding ammonium sulfate is 0.8-1.2 mol / L, and the pH after adjustment is 6.8-7.2; the equilibration buffer is a 0.04-0.06 mol / L Tris-HCl buffer containing 0.8-1.2 mol / L ammonium sulfate, with a pH of 6.8-7.2; the concentration of Tris-HCl buffer used for elution is 0.05 mol / L; the concentration of ammonium sulfate in the low-concentration ammonium sulfate equilibration solution is 0.08-0.12 mol / L.

10. The method for preparing tetanus immunoglobulin according to claim 1, characterized in that, In the preparation of S4 synergistic virus inactivation and S5 formulation, the acid solution used to adjust the pH is a 1 mol / L hydrochloric acid solution; during incubation, the mixture is stirred once every 6-8 hours at a stirring rate of 150-200 r / min. In S4, the microfiltration membrane used for pretreatment has a pore size of 0.20-0.24 μm; the nanomembrane is a hydrophilic polyethersulfone membrane, with an operating pressure of 0.10-0.15 MPa and a temperature of 18-25℃; the ultrafiltration membrane has a molecular weight cutoff of 28-32 kDa; the amount of sodium chloride added is such that its mass-volume concentration in the solution reaches 0.8-1.0%; and the pore size of the terminal filter membrane is 0.20-0.24 μm. The container is a vial, with a capacity of 8-12 mL.

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