A structural optimization method for double-chamber vial

Abstract

The present invention provides a structural optimization method of a double-chambered cillin bottle, belonging to the technical field of double-chambered cillin bottles, wherein the cillin bottle comprises a bottle mouth, a bottle body, a first sealing rubber plug, a second sealing rubber plug and a plastic cap; the bottle body comprises an upper chamber and a lower chamber, the upper chamber is used to store a solution, and the lower chamber is used to store a powdered medicine; the first sealing rubber plug is arranged at the bottle mouth, and the second sealing rubber plug is arranged between the upper chamber and the lower chamber; the plastic cap is installed outside the bottle mouth, and is used to press the first sealing rubber plug; when the plastic cap is pressed, the first sealing rubber plug moves downward and is squeezed and deformed, so that the pressure in the upper chamber increases, and the second sealing rubber plug is pushed downward and falls into the lower chamber, so that the liquid in the upper chamber flows into the lower chamber to dissolve the powder. The method comprises establishing a group of motion equations and optimizing an objective function, determining the shapes and sizes of the first sealing rubber plug and the second sealing rubber plug, and solving the problem that there is a risk of rubber plug debris falling off in the existing cillin bottle.

Description

Technical Field

[0001] The invention belongs to the technical field of double-chamber vials, and in particular relates to a structure optimization method for a double-chamber vial. Background Art

[0002] In the pharmaceutical industry, injections are an important and widely used dosage form. Traditional injections are usually divided into two forms: liquid and powder. Many drugs need to be stored in powder form due to stability issues and then mixed with solvents before use. In this case, medical staff need to prepare liquid medicine, a process that presents many potential risks and challenges.

[0003] First of all, the preparation process of the drug solution needs to be carried out in a professional clean environment to ensure sterility and safety. The "Guidelines for the Construction and Management of Intravenous Drug Preparation Centers (Trial)" issued by the General Office of the National Health Commission clearly states that medical institutions need to establish independent clean rooms for preparing drug solutions. Although this requirement helps to ensure drug safety and reduce occupational exposure, it also places higher hardware requirements on medical institutions and increases medical costs.

[0004] Secondly, the traditional dispensing process involves multiple puncture operations. Medical staff need to use a syringe to extract liquid from a solvent bottle and then inject the liquid into a vial containing drug powder. This process has several potential problems:

[0005] 1. Rubber stopper debris contamination: According to relevant research, multiple punctures of the vial stopper will increase the risk of rubber stopper debris falling off. These tiny debris may mix into the drug solution, affecting the quality and safety of the drug.

[0006] 2. Occupational exposure risk: During repeated punctures, there is a risk of accidental needle puncture of the operator, which may cause medical staff to be exposed to harmful drugs or infectious substances.

[0007] 3. Environmental pollution: Certain drugs may produce aerosols during the preparation process, which will be emitted into the air and cause environmental pollution, posing a health threat to people around.

[0008] 4. Operational complexity: The multi-step dispensing process increases operational complexity and may lead to human errors, such as inaccurate dosage or insufficient mixing. Summary of the invention

[0009] In view of this, the present invention provides a structural optimization method for a double-chamber vial, which can solve the technical problem that multiple punctures of the vial stopper of the existing vial will increase the risk of the stopper debris falling off.

[0010] The present invention is achieved in that:

[0011] The present invention provides a structural optimization method for a double-chamber vial for optimizing a double-chamber vial, wherein the double-chamber vial comprises: a bottle mouth, a bottle body, a first sealing rubber plug, a second sealing rubber plug and a plastic cap; the bottle body comprises an upper chamber and a lower chamber, the upper chamber is used to store a solution, and the lower chamber is used to store a powder medicine; the first sealing rubber plug is arranged at the bottle mouth, and the second sealing rubber plug is arranged between the upper chamber and the lower chamber; the plastic cap is installed outside the bottle mouth and is used to press the first sealing rubber plug; when the plastic cap is pressed, the first sealing rubber plug moves downward and is squeezed and deformed, so that the pressure in the upper chamber is increased, and the second sealing rubber plug is pushed to move downward and fall into the lower chamber, so that the liquid in the upper chamber flows into the lower chamber to dissolve the powder.

[0012] Wherein, the bottle body is made of a borosilicate glass tube.

[0013] The pressure generated by the extrusion and deformation of the first sealing rubber plug is greater than the pressure required for the second sealing rubber plug to move downward after being pressed.

[0014] When the plastic cap is pressed, it can drive the first sealing rubber plug to move downward, causing the first sealing rubber plug to be squeezed and deformed, increasing the pressure in the upper chamber, thereby pushing the second sealing rubber plug to move downward and fall into the lower chamber.

[0015] The lower chamber is used to store medicines in the form of freeze-dried powders; and the upper chamber is used to store aseptically filled liquid solvents.

[0016] Among them, the method of using the double-chamber vial includes: pressing the plastic cap to allow the liquid in the upper chamber to flow into the lower chamber and mix with the powder, without the need to use a syringe to puncture and extract the liquid and inject it into the powder bottle, thereby avoiding contamination by rubber stopper chips, accidental punctures and aerosol contamination of the drug solution.

[0017] The present invention provides a method for optimizing the structure of a double-chamber vial, which is used to optimize the structure of the double-chamber vial, specifically to optimize the shapes and sizes of the first sealing rubber plug and the second sealing rubber plug, so that when the plastic cap is pressed, the first sealing rubber plug can be driven to move downward, so that the first sealing rubber plug is squeezed and deformed, and the pressure in the upper chamber is increased, thereby pushing the second sealing rubber plug to move downward and fall into the lower chamber, and preventing the second sealing rubber plug from getting stuck or tilted during the falling process. The method comprises the following steps:

[0018] S10, establishing a group of motion equations, including a first sealing rubber plug motion equation, an upper chamber pressure change equation, a second sealing rubber plug motion equation, a friction force function, a lower chamber pressure change equation, and a liquid flow equation;

[0019] S20. Determine various parameters in the equations through experimental measurement and theoretical calculation, including mass, elastic coefficient, damping coefficient, friction coefficient, viscosity, surface tension, gas constant, specific heat ratio, flow coefficient, and density;

[0020] S30, establishing an objective function: establishing a comprehensive objective function including multiple performance indicators according to system performance requirements;

[0021] S40, according to actual engineering limitations and safety requirements, setting the value range of each parameter as a constraint condition;

[0022] S50, optimizing and solving the comprehensive objective function, wherein a genetic algorithm is used for global search and a simulated annealing algorithm is used for local optimization;

[0023] S60, numerically solve the system of motion equations, simulate the dynamic process of the system, and evaluate the objective function value in each iteration;

[0024] S70. Determine the optimal shape and size parameters of the first sealing rubber plug and the second sealing rubber plug according to the optimization result, and perform actual sample production and verification testing.

[0025] Furthermore, the motion equations are specifically described as follows:

[0026] 1. The first sealing plug motion equation:

[0027] ;

[0028] In the formula, is the mass of the first sealing rubber plug (kg); is the displacement of the first sealing plug (m); is time(s); is the damping coefficient (N·s / m); is the elastic modulus (N / m); Pressure applied to the plastic cap (N); is the upper chamber pressure (Pa); is the effective area of ​​the first sealing plug (m²).

[0029] 2. Upper chamber pressure change equation:

[0030] ;

[0031] In the formula, is the specific heat ratio of gases; is the gas constant (J / (mol·K)); is temperature (K); is the volume of the upper chamber (m³), , is the initial volume.

[0032] 3. The second sealing plug motion equation:

[0033] ;

[0034] In the formula, is the mass of the second sealing rubber plug (kg); is the displacement of the second sealing plug (m); is the damping coefficient (N·s / m); is the friction function (N); is the effective area of ​​the second sealing rubber plug (m²); is the lower chamber pressure (Pa).

[0035] 4. Friction function:

[0036] ;

[0037] In the formula, is the friction coefficient; is the positive pressure (N); is the friction attenuation coefficient (1 / m); is the maximum static friction (N); is the speed influence coefficient (s / m).

[0038] 5. Lower chamber pressure change equation:

[0039] ;

[0040] In the formula, is the volume of the lower chamber (m³), , is the initial volume.

[0041] 6. Liquid flow equation:

[0042] ;

[0043] In the formula, is the volume flow rate (m³ / s); is the flow coefficient; is the opening area (m²); is the density of the liquid (kg / m³).

[0044] Method for obtaining relevant parameters of the motion equations:

[0045] 1. , , , : Obtained by precision balance measurement and precision caliper measurement.

[0046] 2. , , : Obtained through material dynamic mechanical analysis (DMA) experiment.

[0047] 3. , : Measured by friction tester.

[0048] 4. , : Obtained by fitting the experimental data.

[0049] 5. : Determined by fluid mechanics experiments.

[0050] 6. , : Obtained by measuring with a precision graduated cylinder.

[0051] The specific expression of the comprehensive objective function is as follows:

[0052] ;

[0053] In the formula, is the comprehensive objective function value; is the weight coefficient and satisfies ; are the normalized functions of each performance index respectively; is the falling time of the second sealing plug (s); is the system pressure change (Pa); is the liquid flow rate (m³ / s); is the mixing uniformity (dimensionless).

[0054] The normalization functions are defined as follows:

[0055] ;

[0056] ;

[0057] ;

[0058] ;

[0059] ;

[0060] The specific expressions of the constraints are as follows:

[0061] 1. The first sealing plug size constraints:

[0062] ;

[0063] ;

[0064] 2. Second sealing plug size constraints:

[0065] ;

[0066] ;

[0067] 3. System pressure constraints:

[0068] ;

[0069] ;

[0070] 4. Material strength constraints:

[0071] ;

[0072] 5. Flow rate constraints:

[0073] ;

[0074] 6. Mixed time constraints:

[0075] ;

[0076] In the formula, are the diameter and height of the first sealing rubber plug respectively (m); are the diameter and height of the second sealing rubber plug respectively (m); are the pressures of the upper and lower chambers, respectively (Pa); is the maximum stress (Pa); is the material yield strength (Pa); is the mixing time (s). The subscripts min and max represent the minimum and maximum values ​​of the parameters, respectively.

[0077] Furthermore, the step S50 specifically includes:

[0078] 1. Improved genetic algorithm:

[0079] Initialize the population ,in is an individual (i.e., a set of values ​​for the optimization parameters).

[0080] Fitness function: ,in is the comprehensive objective function defined above.

[0081] Selection operation: Use roulette selection method to select probability .

[0082] Crossover operation: Adaptive crossover rate ,

[0083] ;

[0084] in, is the maximum fitness value in the population, is the average fitness value, is the larger fitness value of the two individuals involved in the crossover, is a constant, usually .

[0085] Mutation operation: Adopt adaptive mutation rate ,

[0086] ;

[0087] in, is the fitness value of the individual to be mutated, is a constant, usually .

[0088] 2. Simulated Annealing Algorithm:

[0089] For the local optimal solution obtained by genetic algorithm , and perform simulated annealing optimization.

[0090] New solution generation: ,in is a random number between [-1, 1], is the step length.

[0091] Acceptance criteria:

[0092] ;

[0093] in, , is the current temperature.

[0094] Cooling function: ,in is the temperature reduction coefficient, usually 0.95-0.99.

[0095] S60, use the fourth-order Runge-Kutta method to numerically solve the system equations, simulate the dynamic process of the system, and evaluate the objective function value in each iteration:

[0096] Assume that the motion equations can be expressed as:

[0097] ;

[0098] in, , including the first sealing plug position, speed, upper chamber pressure, the second sealing plug position, speed, lower chamber pressure, and liquid flow.

[0099] The iterative formula of the fourth-order Runge-Kutta method is:

[0100] ;

[0101] in,

[0102] ;

[0103] ;

[0104] ;

[0105] ;

[0106] is the time step, For the a point in time.

[0107] After each iteration, the objective function value is calculated:

[0108] ;

[0109] in, They are respectively the falling time of the second sealing plug, the system pressure change, the liquid flow rate, and the mixing uniformity in the current time step.

[0110] Furthermore, the multiple performance indicators include the falling time of the second sealing plug, the system pressure change, the liquid flow rate, and the mixing uniformity.

[0111] Furthermore, the method for optimizing and solving the comprehensive objective function is to use an improved genetic algorithm combined with a simulated annealing algorithm for optimization and solution.

[0112] Furthermore, the method for numerically solving the set of motion equations is the fourth-order Runge-Kutta method.

[0113] Specifically, step S10 includes:

[0114] Step 101, establishing a motion equation of the first sealing rubber plug, including the mass, displacement, time, damping coefficient, elastic coefficient, pressure applied by the plastic cap, upper chamber pressure, and effective area of ​​the first sealing rubber plug;

[0115] Step 102, establishing an upper chamber pressure change equation, including gas specific heat ratio, gas constant, temperature, upper chamber volume and upper chamber volume change rate;

[0116] Step 103, establishing a motion equation of the second sealing rubber plug, including the mass, displacement, time, damping coefficient, friction function, upper chamber pressure, lower chamber pressure and effective area of ​​the second sealing rubber plug;

[0117] Step 104, establishing a friction function, including friction coefficient, normal pressure, friction attenuation coefficient, maximum static friction and speed influence coefficient;

[0118] Step 105, establishing a lower chamber pressure change equation, including gas specific heat ratio, gas constant, temperature, lower chamber volume and lower chamber volume change rate;

[0119] Step 106: Establish a liquid flow equation, including volume flow rate, flow coefficient, opening area, upper chamber pressure, lower chamber pressure and liquid density.

[0120] Wherein, the step S20 specifically includes:

[0121] Step 201, measuring the mass of the first sealing rubber plug and the second sealing rubber plug by using a precision balance;

[0122] Step 202, measuring the effective area of ​​the first sealing rubber plug and the second sealing rubber plug by using a precision caliper;

[0123] Step 203, obtaining the damping coefficients of the first sealing rubber plug and the second sealing rubber plug and the elastic coefficient of the first sealing rubber plug through a material dynamic mechanical analysis experiment;

[0124] Step 204, measuring the friction coefficient and the maximum static friction force by a friction tester;

[0125] Step 205, obtaining the friction attenuation coefficient and the speed influence coefficient by fitting the experimental data;

[0126] Step 206, determining the flow coefficient through a fluid mechanics experiment;

[0127] Step 207: Measure the initial volumes of the upper chamber and the lower chamber using a precision measuring cylinder.

[0128] Wherein, the step S30 specifically includes:

[0129] Step 301, determining a normalized function of the drop time of the second sealing rubber plug, the function being expressed as the maximum drop time minus the actual drop time divided by the maximum drop time minus the minimum drop time;

[0130] Step 302, determine a normalized function of the system pressure change, which is expressed as the actual pressure change minus the minimum pressure change divided by the maximum pressure change minus the minimum pressure change;

[0131] Step 303, determining a normalized function of the liquid flow rate, the function being expressed as the actual flow rate minus the minimum flow rate divided by the maximum flow rate minus the minimum flow rate;

[0132] Step 304, determining a normalized function of mixing uniformity, the function being expressed as actual mixing uniformity minus minimum mixing uniformity divided by maximum mixing uniformity minus minimum mixing uniformity;

[0133] Step 305: Set the weight coefficients of each performance indicator and ensure that the sum of all weight coefficients is equal to 1;

[0134] Step 306: construct a comprehensive objective function according to each normalization function and weight coefficient.

[0135] Wherein, the step S40 specifically includes:

[0136] Step 401, setting the minimum and maximum values ​​of the diameter of the first sealing rubber plug to ensure that the diameter of the first sealing rubber plug is within the range;

[0137] Step 402, setting the minimum and maximum values ​​of the height of the first sealing rubber plug to ensure that the height of the first sealing rubber plug is within the range;

[0138] Step 403, setting the minimum and maximum values ​​of the diameter of the second sealing rubber plug to ensure that the diameter of the second sealing rubber plug is within the range;

[0139] Step 404, setting the minimum and maximum values ​​of the height of the second sealing rubber plug to ensure that the height of the second sealing rubber plug is within the range;

[0140] Step 405, setting the minimum and maximum values ​​of the pressures of the upper chamber and the lower chamber to ensure that the system pressure is within the range;

[0141] Step 406: Set material strength constraints to ensure that the maximum stress does not exceed the material yield strength;

[0142] Step 407, setting the minimum and maximum values ​​of the flow rate to ensure that the liquid flow rate is within the range;

[0143] Step 408: Set the maximum mixing time to ensure that the actual mixing time does not exceed this value.

[0144] Wherein, the step S50 specifically includes:

[0145] Step 501, initializing a genetic algorithm population, each individual representing a set of shape and size parameters of a first sealing rubber plug and a second sealing rubber plug;

[0146] Step 502: Calculate the fitness value of each individual, that is, the value of the comprehensive objective function;

[0147] Step 503: Perform a selection operation to retain individuals with higher fitness;

[0148] Step 504: Perform a crossover operation to generate a new individual;

[0149] Step 505: Perform mutation operation to increase population diversity;

[0150] Step 506, repeating steps 502 to 505 until the maximum number of iterations is reached or the convergence condition is met;

[0151] Step 507: Select the best individual as the global optimal solution;

[0152] Step 508: Using the global optimal solution as the initial solution, use the simulated annealing algorithm to perform local optimization to obtain the final optimization result.

[0153] Wherein, the step S60 specifically includes:

[0154] Step 601, substituting the optimized shape and size parameters of the first sealing rubber plug and the second sealing rubber plug into the motion equation group;

[0155] Step 602, setting initial conditions, including initial position, initial velocity and initial pressure;

[0156] Step 603, using the fourth-order Runge-Kutta method to numerically solve the system of motion equations;

[0157] Step 604, calculating the system state at each time step, including the first sealing plug position, the second sealing plug position, the upper chamber pressure, the lower chamber pressure and the liquid flow rate;

[0158] Step 605, evaluating various performance indicators according to the calculation results, including the falling time of the second sealing rubber plug, the system pressure change, the liquid flow rate and the mixing uniformity;

[0159] Step 606, calculating the comprehensive objective function value;

[0160] Step 607: Repeat steps 603 to 606 until a preset simulation time is reached or a termination condition is met.

[0161] Wherein, the step S70 specifically includes:

[0162] Step 701, determining the optimal diameter and height of the first sealing rubber plug according to the optimization result;

[0163] Step 702: determining the optimal diameter and height of the second sealing rubber plug according to the optimization result;

[0164] Step 703, determining the optimal material formula of the first sealing rubber plug and the second sealing rubber plug according to the optimization result;

[0165] Step 704: making actual samples according to the determined parameters;

[0166] Step 705, measuring the dimensions of the first sealing rubber plug and the second sealing rubber plug to ensure that they meet the design requirements;

[0167] Step 706: Conduct material performance tests, including hardness, elastic modulus, and friction coefficient;

[0168] Step 707, performing functional tests on the double-chamber vial, including sealing, pressure conduction, and mixing effects;

[0169] Step 708: Analyze the test results to verify the effectiveness of the optimization method.

[0170] Optionally, the method further comprises the following steps:

[0171] Step 801, establishing a three-dimensional model of the first sealing rubber plug and the second sealing rubber plug;

[0172] Step 802: meshing the three-dimensional model using finite element analysis software;

[0173] Step 803: Setting material properties, boundary conditions and loading conditions;

[0174] Step 804: Perform static analysis to obtain stress distribution and deformation;

[0175] Step 805: Perform dynamic analysis to simulate the movement of the first sealing rubber plug and the second sealing rubber plug;

[0176] Step 806: Perform fluid-structure coupling analysis to simulate the interaction between liquid flow and sealing plug deformation;

[0177] Step 807: further optimize the shapes and sizes of the first sealing rubber plug and the second sealing rubber plug according to the analysis results.

[0178] Optionally, the method further comprises the following steps:

[0179] Step 901, establishing a multi-scale model of the first sealing rubber plug and the second sealing rubber plug, including a molecular scale, a microscopic scale, and a macroscopic scale;

[0180] Step 902: Using molecular dynamics simulation method to study the microstructure and performance of the sealing plug material at the molecular scale;

[0181] Step 903: Using a representative volume element method to study the mechanical properties and deformation behavior of the material at a microscopic scale;

[0182] Step 904: On a macroscopic scale, use a continuum mechanics method to study the deformation and movement of the entire sealing plug;

[0183] Step 905: Establish an information transmission mechanism between different scales to achieve coupling of multi-scale models;

[0184] Step 906: Optimize the material composition and microstructure of the sealing rubber plug using a multi-scale model;

[0185] Step 907: Integrate the optimization results of the multi-scale model into the overall structural optimization method.

[0186] Compared with the prior art, the structural optimization method of a double-chamber vial provided by the present invention has the following beneficial effects:

[0187] 1. Simplify the dispensing process and improve operational safety: The double-chamber vial of the present invention pre-packs the solvent and the powder into different chambers of the same container. When in use, the two components can be automatically mixed by simply pressing the plastic cap, without the need for additional puncture and injection operations. This design greatly simplifies the dispensing process and reduces the number of manual operation steps, thereby significantly reducing the risk of operational errors and occupational exposure. Compared with traditional methods, the present invention can reduce at least one puncture operation, effectively reducing the probability of medical staff being accidentally stabbed.

[0188] 2. Reduce environmental requirements and improve ease of use: Since the double-chamber vial of the present invention does not require complex dispensing operations before use, it is no longer strictly dependent on a professional clean dispensing environment. This feature allows drugs to be used quickly and safely in more scenarios, such as emergency rooms, operating rooms, and even field rescue. This not only improves the flexibility and convenience of drug use, but also may reduce the investment cost of medical institutions in hardware facilities.

[0189] 3. Optimized sealing performance to ensure reliable activation: By optimizing the shape and size of the first and second sealing rubber plugs, the present invention ensures that the second sealing rubber plug can be reliably pushed down when pressed, avoiding the problem of getting stuck or tilting. This design not only improves the reliability of the product, but also ensures that the two components can be fully mixed, thereby ensuring the consistency of the efficacy.

[0190] 4. Simple structure and easy production: Compared with some complex double-chamber designs, the present invention adopts a relatively simple structure, which is mainly composed of a bottle body, two sealing rubber plugs and a plastic cap. This simplified design not only helps to reduce production costs, but also improves the stability and reliability of the product.

[0191] 5. Optimize user experience:

[0192] The simple push-to-activate method makes this product easy to use, and even non-professionals can quickly master the operation method. This user-friendly design helps improve the efficiency and safety of drug use. No extensive experience is required, and there is no risk of the stopper falling off due to multiple punctures of the vial stopper during the dispensing process.

[0193] In summary, the structural optimization method of the double-chamber vial of the present invention solves the technical problem that multiple punctures of the vial stopper of the existing vial increase the risk of the stopper debris falling off. BRIEF DESCRIPTION OF THE DRAWINGS

[0194] Figure 1 A schematic diagram of the structure of an optimized double-chamber vial provided by the present invention;

[0195] In the accompanying drawings, the components represented by the reference numerals are listed as follows:

[0196] 10. Bottle mouth; 20. Bottle body; 31. First sealing rubber plug; 32. Second sealing rubber plug; 33. Plastic cap; 41. Upper chamber; 42. Lower chamber. DETAILED DESCRIPTION

[0197] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0198] like Figure 1 As shown, it is a schematic diagram of the structure of a double-chambered syringe bottle optimized by the method of the present invention, comprising: a bottle mouth 10, a bottle body 20, a first sealing rubber plug 31, a second sealing rubber plug 32 and a plastic cap 33; the bottle body 20 comprises an upper chamber 41 and a lower chamber 42, the upper chamber 41 is used to store a solution, and the lower chamber 42 is used to store a powdered medicine; the first sealing rubber plug is arranged at the bottle mouth, and the second sealing rubber plug is arranged between the upper chamber and the lower chamber; the plastic cap is installed outside the bottle mouth, and is used to press the first sealing rubber plug; when the plastic cap is pressed, the first sealing rubber plug moves downward and is squeezed and deformed, so that the pressure in the upper chamber increases, and the second sealing rubber plug is pushed to move downward and fall into the lower chamber, so that the liquid in the upper chamber flows into the lower chamber to dissolve the powder.

[0199] When in use, the operator only needs to press the plastic cap hard. This action will push the first sealing plug downward and deform. Since liquid is basically incompressible, the downward pressure of the first sealing plug will cause the pressure in the upper chamber to increase rapidly. This pressure increase is transmitted to the second sealing plug through the liquid medium, pushing it downward and eventually out of its original position and falling into the lower chamber. This process allows the liquid in the upper chamber to flow into the lower chamber and be fully mixed with the powdered medicine.

[0200] The key to this specific implementation lies in the design of the first sealing rubber plug and the second sealing rubber plug. The deformation characteristics of the first sealing rubber plug need to be carefully controlled to ensure that sufficient pressure can be generated when pressed without causing liquid leakage. The design of the second sealing rubber plug needs to maintain good sealing while being able to fall smoothly under a certain pressure. This balance is achieved by accurately controlling the elastic modulus, surface roughness and contact area of ​​the rubber plug material with the bottle wall.

[0201] In order to better determine the parameters of the above-mentioned specific design, a structural optimization method of a double-chamber vial provided by the present invention is described in detail below, which is used to optimize the structure of the above-mentioned double-chamber vial, specifically to optimize the shapes and sizes of the first sealing rubber plug and the second sealing rubber plug, so that when the plastic cap is pressed, the first sealing rubber plug can be driven to move downward, so that the first sealing rubber plug is squeezed and deformed, and the pressure in the upper chamber is increased, thereby pushing the second sealing rubber plug to move downward and fall into the lower chamber, and preventing the second sealing rubber plug from getting stuck or tilted during the falling process. The method comprises the following steps:

[0202] S10, establishing a group of motion equations, including a first sealing rubber plug motion equation, an upper chamber pressure change equation, a second sealing rubber plug motion equation, a friction force function, a lower chamber pressure change equation, and a liquid flow equation;

[0203] S20. Determine various parameters in the equations through experimental measurement and theoretical calculation, including mass, elastic coefficient, damping coefficient, friction coefficient, viscosity, surface tension, gas constant, specific heat ratio, flow coefficient, and density;

[0204] S30, establishing an objective function: establishing a comprehensive objective function including multiple performance indicators according to system performance requirements;

[0205] S40, according to actual engineering limitations and safety requirements, setting the value range of each parameter as a constraint condition;

[0206] S50, optimizing and solving the comprehensive objective function, wherein a genetic algorithm is used for global search and a simulated annealing algorithm is used for local optimization;

[0207] S60, numerically solve the system of motion equations, simulate the dynamic process of the system, and evaluate the objective function value in each iteration;

[0208] S70. Determine the optimal shape and size parameters of the first sealing rubber plug and the second sealing rubber plug according to the optimization result, and perform actual sample production and verification testing.

[0209] The specific implementation methods of the above steps are described in detail below:

[0210] The specific implementation method of step S10 is to establish a set of motion equations. The purpose of this step is to construct a mathematical model to describe the motion state and interaction of each component in the dual-chamber vial system. The specific implementation process is as follows: First, establish the motion equation of the first sealing plug, considering its mass, elastic properties and damping effect. Then, establish the upper chamber pressure change equation, considering the effects of gas compression and volume change. Next, establish the motion equation of the second sealing plug, considering its force conditions and friction characteristics. After that, establish a friction function to describe the friction change between the second sealing plug and the bottle wall. Again, establish the lower chamber pressure change equation, considering the effect of volume change on pressure. Finally, establish a liquid flow equation to describe the liquid flow between the two chambers. This step is mainly based on basic physical principles such as Newton's laws of motion, the first law of thermodynamics and Bernoulli's equation. By establishing these equations, the dynamic behavior of the system can be fully described, laying the foundation for the subsequent optimization process.

[0211] Specifically, the motion equations are described as follows:

[0212] 1. The first sealing plug motion equation:

[0213] ;

[0214] In the formula, is the mass of the first sealing rubber plug (kg); is the displacement of the first sealing plug (m); is time(s); is the damping coefficient (N·s / m); is the elastic modulus (N / m); Pressure applied to the plastic cap (N); is the upper chamber pressure (Pa); is the effective area of ​​the first sealing plug (m²).

[0215] 2. Upper chamber pressure change equation:

[0216] ;

[0217] In the formula, is the specific heat ratio of gases; is the gas constant (J / (mol·K)); is temperature (K); is the volume of the upper chamber (m³), , is the initial volume.

[0218] 3. The second sealing plug motion equation:

[0219] ;

[0220] In the formula, is the mass of the second sealing rubber plug (kg); is the displacement of the second sealing plug (m); is the damping coefficient (N·s / m); is the friction function (N); is the effective area of ​​the second sealing rubber plug (m²); is the lower chamber pressure (Pa).

[0221] 4. Friction function:

[0222] ;

[0223] In the formula, is the friction coefficient; is the positive pressure (N); is the friction attenuation coefficient (1 / m); is the maximum static friction (N); is the speed influence coefficient (s / m).

[0224] 5. Lower chamber pressure change equation:

[0225] ;

[0226] In the formula, is the volume of the lower chamber (m³), , is the initial volume.

[0227] 6. Liquid flow equation:

[0228] ;

[0229] In the formula, is the volume flow rate (m³ / s); is the flow coefficient; is the opening area (m²); is the density of the liquid (kg / m³).

[0230] Method for obtaining relevant parameters of the motion equations:

[0231] 1. , , , : Obtained by precision balance measurement and precision caliper measurement.

[0232] 2. , , : Obtained through material dynamic mechanical analysis (DMA) experiment.

[0233] 3. , : Measured by friction tester.

[0234] 4. , : Obtained by fitting the experimental data.

[0235] 5. : Determined by fluid mechanics experiments.

[0236] 6. , : Obtained by measuring with a precision graduated cylinder.

[0237] The specific implementation method of step S20 is to determine the various parameters in the equation group through experimental measurement and theoretical calculation. The purpose of this step is to obtain accurate system parameters to ensure the accuracy of subsequent optimization calculations. The specific implementation process is as follows: First, use a precision balance and a caliper to measure the mass and size of the first sealing plug and the second sealing plug. Then, the elastic coefficient and damping coefficient of the plug are determined by a material dynamic mechanical analysis (DMA) experiment. Next, a friction tester is used to measure the friction coefficient between the plug and the bottle wall. After that, the flow coefficient is determined by a fluid mechanics experiment. Again, a viscometer is used to measure the viscosity of the liquid. Finally, parameters such as gas constants and specific heat ratios are obtained by theoretical calculation or table lookup. This step is mainly based on the principles of experimental mechanics and material science. Through precise experimental measurements and theoretical calculations, the key parameters of the system can be obtained, providing reliable data support for the subsequent optimization process.

[0238] The specific implementation method of step S30 is to establish a comprehensive objective function containing multiple performance indicators. The purpose of this step is to integrate the multiple performance requirements of the system into a mathematical expression for subsequent overall optimization. The specific implementation process is as follows: First, determine the performance indicators that need to be considered, including the falling time of the second sealing plug, the system pressure change, the liquid flow rate and the mixing uniformity. Then, establish a separate objective function for each performance indicator, which should be able to quantify the quality of each indicator. Next, introduce a weight coefficient to adjust the importance of each performance indicator in the overall optimization. After that, combine each individual objective function into a comprehensive objective function by weighted summation. Finally, normalize the comprehensive objective function so that its value range is between 0 and 1. This step is mainly based on the theory of multi-objective optimization. By establishing a comprehensive objective function, multiple performance requirements can be converted into a quantifiable optimization target, providing a clear optimization direction for the subsequent optimization process.

[0239] The specific implementation method of step S40 is to set the value range of each parameter as a constraint condition according to the actual engineering limitations and safety requirements. The purpose of this step is to ensure that the optimization results meet the needs and safety standards of practical applications. The specific implementation process is as follows: First, according to the physical properties of the material and the processing technology limitations, the size range of the first sealing plug and the second sealing plug is set. Then, based on system safety considerations, the maximum allowable pressure of the upper and lower chambers is set. Next, according to the material strength requirements, the maximum allowable stress is set. After that, considering the drug dissolution rate requirements, the range of liquid flow rate is set. Finally, according to the efficacy requirements, the maximum allowable mixing time is set. These constraints can be expressed in the form of inequalities or equations. For example, the diameter range of the first sealing plug can be set to 20 mm ≤ D1 ≤ 22 mm, and the maximum allowable pressure of the system can be set to P ≤ 300 kPa. This step is mainly based on engineering practice and safety standards. By setting reasonable constraints, it can be ensured that the optimization results are not only theoretically feasible, but also meet the needs of practical applications.

[0240] Specifically, the specific expression of the comprehensive objective function is as follows:

[0241] ;

[0242] In the formula, is the comprehensive objective function value; is the weight coefficient and satisfies ; are the normalized functions of each performance index respectively; is the falling time of the second sealing plug (s); is the system pressure change (Pa); is the liquid flow rate (m³ / s); is the mixing uniformity (dimensionless).

[0243] The normalization functions are defined as follows:

[0244] ;

[0245] ;

[0246] ;

[0247] ;

[0248] ;

[0249] The specific expressions of the constraints are as follows:

[0250] 1. The first sealing plug size constraints:

[0251] ;

[0252] ;

[0253] 2. Second sealing plug size constraints:

[0254] ;

[0255] ;

[0256] 3. System pressure constraints:

[0257] ;

[0258] ;

[0259] 4. Material strength constraints:

[0260] ;

[0261] 5. Flow rate constraints:

[0262] ;

[0263] 6. Mixed time constraints:

[0264] ;

[0265] In the formula, are the diameter and height of the first sealing rubber plug respectively (m); are the diameter and height of the second sealing rubber plug respectively (m); are the pressures of the upper and lower chambers, respectively (Pa); is the maximum stress (Pa); is the material yield strength (Pa); is the mixing time (s). The subscripts min and max represent the minimum and maximum values ​​of the parameters, respectively.

[0266] The specific implementation method of step S50 is to optimize and solve the comprehensive objective function. The purpose of this step is to find a parameter combination that can make the objective function obtain the optimal value. The specific implementation process is as follows: First, select an appropriate optimization algorithm. Considering the complexity and nonlinear characteristics of the problem, this method uses an improved genetic algorithm combined with a simulated annealing algorithm for optimization and solution. The genetic algorithm is used for global search, and the simulated annealing algorithm is used for local optimization. Then, the parameter population is initialized, and each individual represents a set of possible parameter values. Next, the fitness of each individual is evaluated, that is, the objective function value is calculated. After that, selection, crossover and mutation operations are performed to generate a new population. In this process, a simulated annealing mechanism is introduced to accept suboptimal solutions with a certain probability to avoid falling into local optimality. Repeat this process until the termination condition is reached, such as reaching the maximum number of iterations or there is no significant improvement in the optimal solution for multiple generations in a row. Finally, the optimal solution is output as the optimization result. In practical applications, the population size can be set to 100, the maximum number of iterations to 1000, the crossover probability to 0.8, the mutation probability to 0.1, the initial temperature to 100, and the cooling coefficient to 0.98. This step is mainly based on evolutionary computing and stochastic optimization theory. By combining the advantages of genetic algorithms and simulated annealing algorithms, the optimal solution can be efficiently searched in a complex solution space, thereby obtaining the optimal parameter combination of the double-chamber vial structure.

[0267] Specifically, the step S50 includes:

[0268] 1. Improved genetic algorithm:

[0269] Initialize the population ,in is an individual (i.e., a set of values ​​for the optimization parameters).

[0270] Fitness function: ,in is the comprehensive objective function defined above.

[0271] Selection operation: Use roulette selection method to select probability .

[0272] Crossover operation: Adaptive crossover rate ,

[0273] ;

[0274] in, is the maximum fitness value in the population, is the average fitness value, is the larger fitness value of the two individuals involved in the crossover, is a constant, usually .

[0275] Mutation operation: Adopt adaptive mutation rate ,

[0276] ;

[0277] in, is the fitness value of the individual to be mutated, is a constant, usually .

[0278] 2. Simulated Annealing Algorithm:

[0279] For the local optimal solution obtained by genetic algorithm , and perform simulated annealing optimization.

[0280] New solution generation: ,in is a random number between [-1, 1], is the step length.

[0281] Acceptance criteria:

[0282] ;

[0283] in, , is the current temperature.

[0284] Cooling function: ,in is the temperature reduction coefficient, usually 0.95-0.99.

[0285] S60, use the fourth-order Runge-Kutta method to numerically solve the system equations, simulate the dynamic process of the system, and evaluate the objective function value in each iteration:

[0286] Assume that the motion equations can be expressed as:

[0287] ;

[0288] in, , including the first sealing plug position, speed, upper chamber pressure, the second sealing plug position, speed, lower chamber pressure, and liquid flow.

[0289] The iterative formula of the fourth-order Runge-Kutta method is:

[0290] ;

[0291] in,

[0292] ;

[0293] ;

[0294] ;

[0295] ;

[0296] is the time step, For the a point in time.

[0297] After each iteration, the objective function value is calculated:

[0298] ;

[0299] in, They are respectively the falling time of the second sealing plug, the system pressure change, the liquid flow rate, and the mixing uniformity in the current time step.

[0300] The specific implementation method of step S60 is to numerically solve the set of motion equations and simulate the dynamic process of the system. The purpose of this step is to verify the validity of the optimization results and to analyze the dynamic behavior of the system in detail. The specific implementation process is as follows: First, select a suitable numerical solution method. Considering the rigidity and nonlinear characteristics of the set of equations, this method uses the fourth-order Runge-Kutta method for solution. Then, set the initial conditions and boundary conditions, including initial pressure, initial position, etc. Next, discretize the time domain and select a suitable time step, such as 0.001 seconds. After that, iterate and calculate each time step to update the system state. In each iteration, first calculate the position and velocity of the first sealing plug, then calculate the upper chamber pressure, then calculate the position and velocity of the second sealing plug, then calculate the lower chamber pressure, and finally calculate the liquid flow rate. Repeat this process until the specified simulation time is reached. In the solution process, special attention should be paid to the numerical stability problem, and an adaptive step strategy can be used to improve the calculation efficiency and accuracy. Finally, the simulation results are post-processed, such as drawing time-position curves, pressure change curves, etc. This step is mainly based on numerical analysis and computational fluid dynamics theory. Through numerical simulation, we can understand the dynamic behavior of the system in detail, verify the feasibility of the optimization results, and provide a basis for further improvement.

[0301] The specific implementation method of step S70 is to determine the optimal shape and size parameters of the first sealing plug and the second sealing plug according to the optimization results, and to make actual samples and verify the test. The purpose of this step is to convert the theoretical optimization results into actual products and verify their performance through experiments. The specific implementation process is as follows: First, according to the optimization results, the specific size and shape parameters of the first sealing plug and the second sealing plug are determined. For example, the diameter of the first sealing plug may be optimized to 21.2 mm and the height is 7.8 mm; the diameter of the second sealing plug may be optimized to 20.6 mm and the height is 5.9 mm. Then, the specific structure of the plug is designed, such as whether to add detailed features such as flanges and grooves. Next, select suitable materials and manufacturing processes, such as injection molding or compression molding. After that, make samples and perform size and appearance inspections to ensure that they meet the design requirements. Again, perform functional tests, including sealing tests, pressure tests, and mixing effect tests. In the sealing test, the pressurization method or vacuum method can be used, and the test pressure should not be less than 300 kPa. In the pressure test, simulate the actual use and record the pressure change curve. In the mixing effect test, the tracer method can be used to evaluate the mixing uniformity. Finally, necessary adjustments and optimizations are made based on the test results, such as fine-tuning the plug size or improving the material formula. This step is mainly based on engineering design and quality control theory. Through actual sample preparation and verification testing, it can ensure that the optimization results can achieve the expected effect in actual applications and lay the foundation for mass production of products.

[0302] Specifically, the principle of the present invention is:

[0303] 1. Pressure transmission principle: The core mechanism of the present invention is to use the pressure transmission principle to achieve mixing of the contents of the two chambers. When the plastic cap is pressed, the first sealing rubber plug is first pushed downward. Since the liquid is basically incompressible, the downward pressure of the first sealing rubber plug will cause the pressure in the upper chamber to increase rapidly. This pressure increase is transmitted to the second sealing rubber plug through the liquid medium, pushing it downward and eventually out of its original position and falling into the lower chamber. This process conforms to Pascal's law, that is, the pressure change in the closed container will be evenly transmitted to all parts of the liquid.

[0304] 2. Material deformation and sealing: The design of the first sealing rubber plug utilizes the elastic deformation characteristics of the material. When subjected to pressure, the rubber plug will deform to a certain extent. On the one hand, this deformation increases the sealing with the bottle wall to prevent liquid leakage; on the other hand, the volume of the rubber plug decreases during the deformation process, further increasing the pressure in the upper chamber. This design cleverly utilizes the elastic characteristics of the material, which not only ensures the sealing of the system, but also enhances the pressure transmission effect.

[0305] 3. Fluid dynamics design: The shape and size of the second sealing plug are optimized to take fluid dynamics into consideration. When the second sealing plug starts to move, its shape ensures that the surrounding liquid can flow evenly, avoiding problems such as jamming or tilting caused by eddy currents or uneven flow. This design is based on the streamline principle in fluid mechanics, which minimizes flow resistance and ensures the smooth fall of the plug.

[0306] 4. Friction control: The friction design between the second sealing rubber plug and the bottle wall is also the key to the present invention. The friction needs to be large enough to maintain the seal under normal conditions, but not too large to prevent the rubber plug from falling. This balance is achieved by precisely controlling the elastic coefficient, surface roughness and contact area with the bottle wall of the rubber plug material. The friction design follows Coulomb's friction law to find the best balance between static friction and dynamic friction.

[0307] 5. Pressure balance and mixing: When the second sealing plug falls into the lower chamber, the pressure of the upper and lower chambers will be quickly balanced. During this process, the liquid will flow into the lower chamber at a high speed and fully mix with the powder medicine. This high-speed flow helps the powder to dissolve quickly and disperse evenly. The design of the mixing process takes into account the turbulent mixing theory in fluid mechanics, ensuring the full dissolution and uniformity of the medicine.

[0308] 6. Structural mechanics optimization: The structural design of the entire double-chamber vial takes mechanical balance into consideration. The bottle body is made of borosilicate glass, which has good mechanical strength and chemical stability. The thickness and shape of the bottle body are calculated to withstand internal pressure changes without breaking or deforming. This structural optimization is based on the principles of material mechanics and structural mechanics, ensuring the safety and reliability of the product during use.

[0309] 7. System dynamics model: The entire working process of the present invention can be described by a series of differential equations, including the rubber plug motion equation, pressure change equation and fluid flow equation. This dynamic model takes into account the interaction between the various components in the system, so that the entire process can be accurately controlled and predicted. The establishment and solution of the model are based on classical mechanics and fluid mechanics theory, providing a theoretical basis for the optimal design of the product.

[0310] In summary, the dual-chamber vial solution of the present invention is a comprehensive design that crosses multiple disciplines, involving knowledge in multiple fields such as fluid mechanics, material mechanics, mechanical design, chemistry, and pharmacy. The design of each component and the operation of the overall system are based on rigorous scientific principles and engineering practices. This design based on scientific principles ensures that the present invention can effectively solve the problems in the prior art and provide a safe, reliable, and easy-to-use drug packaging solution.

[0311] In order to better understand and implement the structural optimization method of a dual-chamber vial of the present invention, a specific embodiment 1 of the structural optimization method of a dual-chamber vial is provided below. The specific steps of this embodiment 1 are described in detail as follows:

[0312] Step S10: Establishing the equations of motion

[0313] 1. The first sealing plug motion equation:

[0314]

[0315] in:

[0316] : Mass of the first sealing rubber plug (kg)

[0317] : Displacement of the first sealing plug (m)

[0318] : time (s)

[0319] : Damping coefficient of the first sealing rubber plug (N·s / m)

[0320] : Elastic coefficient of the first sealing rubber plug (N / m)

[0321] : Pressure applied by the plastic cap (N)

[0322] : Upper chamber pressure (Pa)

[0323] :Effective area of ​​the first sealing plug (m²)

[0324] 2. Upper chamber pressure change equation:

[0325]

[0326] in:

[0327] : ratio of specific heats of gases (dimensionless)

[0328] : Gas constant (J / (mol·K))

[0329] : Temperature (K)

[0330] : Volume of upper chamber (m³),

[0331] : Initial volume of upper chamber (m³)

[0332] 3. The second sealing plug motion equation:

[0333]

[0334] in:

[0335] : Mass of the second sealing rubber plug (kg)

[0336] : Displacement of the second sealing plug (m)

[0337] : Damping coefficient of the second sealing rubber plug (N·s / m)

[0338] : Friction force function (N)

[0339] : Effective area of ​​the second sealing plug (m²)

[0340] : Lower chamber pressure (Pa)

[0341] 4. Friction function:

[0342]

[0343] in:

[0344] : Friction coefficient (dimensionless)

[0345] : Positive pressure (N)

[0346] : Friction attenuation coefficient (1 / m)

[0347] : Maximum static friction (N)

[0348] : Speed ​​influence coefficient (s / m)

[0349] 5. Lower chamber pressure change equation:

[0350]

[0351] in:

[0352] : Volume of lower chamber (m³),

[0353] : Initial volume of lower chamber (m³)

[0354] 6. Liquid flow equation:

[0355]

[0356] in:

[0357] : Volume flow rate (m³ / s)

[0358] : Flow coefficient (dimensionless)

[0359] : Opening area (m²)

[0360] : Liquid density (kg / m³)

[0361] Step S20: Determine the parameters in the equation group

[0362] This step mainly involves experimental measurements and theoretical calculations and does not require additional formula explanations.

[0363] Step S30: Establishing the objective function

[0364] The expression of the comprehensive objective function is as follows:

[0365]

[0366] in:

[0367] : Comprehensive objective function value (dimensionless)

[0368] : Weight coefficient, and satisfy

[0369] : Normalization function of each performance index

[0370] : Second sealing plug drop time (s)

[0371] : System pressure change (Pa)

[0372] : Liquid flow rate (m³ / s)

[0373] : Mixing uniformity (dimensionless)

[0374] The normalization functions are defined as follows:

[0375] 1.

[0376] 2.

[0377] 3.

[0378] 4.

[0379] The subscripts max and min represent the maximum and minimum values ​​of the parameter, respectively.

[0380] Step S40: Setting constraints

[0381] The specific expressions of the constraints are as follows:

[0382] 1. The first sealing plug size constraints:

[0383]

[0384]

[0385] 2. Second sealing plug size constraints:

[0386]

[0387]

[0388] 3. System pressure constraints:

[0389]

[0390]

[0391] 4. Material strength constraints:

[0392]

[0393] 5. Flow rate constraints:

[0394]

[0395] 6. Mixed time constraints:

[0396]

[0397] in:

[0398] : Diameter and height of the first sealing plug (m)

[0399] : Diameter and height of the second sealing plug (m)

[0400] : Maximum stress (Pa)

[0401] : Material yield strength (Pa)

[0402] : Mixing time (s)

[0403] Step S50: Optimization solution

[0404] In this step, an improved genetic algorithm combined with a simulated annealing algorithm is used for optimization.

[0405] 1. Genetic Algorithm (GA)

[0406] The main steps of the genetic algorithm include:

[0407] a) Initialize the population:

[0408]

[0409] in, represents a possible solution, is the population size.

[0410] b) Calculate fitness:

[0411] ,in is the objective function.

[0412] c) Select an operation:

[0413] Using the roulette wheel selection method, the selection probability is:

[0414]

[0415] d) Crossover operation:

[0416] For the selected parent individual and , generating offspring and :

[0417]

[0418]

[0419] in, is a random number, .

[0420] e) Mutation operation:

[0421] For the selected individuals , perform Gaussian mutation:

[0422]

[0423] in, The mean is 0 and the variance is The normal distribution of .

[0424] 2. Simulated Annealing Algorithm (SA)

[0425] The main steps of the simulated annealing algorithm include:

[0426] a) Initialization:

[0427] Select initial solution and initial temperature .

[0428] b) Generate new solution:

[0429]

[0430] in, is a random disturbance.

[0431] c) Calculate the energy difference:

[0432]

[0433] d) Acceptance criteria:

[0434] if , then accept the new solution;

[0435] Otherwise, with probability Accept new interpretations.

[0436] e) Cooling:

[0437]

[0438] in, is the temperature drop coefficient, .

[0439] The optimization algorithm process combining GA and SA is as follows:

[0440] 1. Use GA to perform global search and get a better solution .

[0441] 2. For the initial solution, SA is used for local optimization.

[0442] 3. Repeat steps 1 and 2 until the termination condition is met.

[0443] Step S60: Numerical solution

[0444] In this step, the fourth-order Runge-Kutta method is used to numerically solve the system of equations of motion. For general ordinary differential equations:

[0445]

[0446] The calculation formula of the fourth-order Runge-Kutta method is:

[0447]

[0448] in:

[0449]

[0450]

[0451]

[0452]

[0453] is the step length, For the a point in time.

[0454] For the system of motion equations, it is necessary to transform them into a system of first-order ordinary differential equations:

[0455]

[0456]

[0457]

[0458]

[0459]

[0460]

[0461] This system of equations can then be solved using the fourth-order Runge-Kutta method.

[0462] Step S70: Result analysis and verification

[0463] In this step, the optimization results need to be analyzed and verified. This mainly includes the following aspects:

[0464] 1. Sensitivity analysis:

[0465] Calculate the partial derivatives of the objective function with respect to each design variable to assess the importance of each parameter:

[0466]

[0467] in, For the The sensitivity coefficients of the design variables are For the design variables.

[0468] 2. Stability analysis:

[0469] The stability of the system is evaluated by calculating the eigenvalues ​​of the system. For the linearized system:

[0470]

[0471] in, is the system matrix. If the real parts of all eigenvalues ​​are negative, the system is stable.

[0472] 3. Monte Carlo simulation:

[0473] The reliability of the system is evaluated through multiple random sampling. Define the probability of system failure:

[0474]

[0475] in, is the limit state function, is a vector of random variables.

[0476] 4. Experimental verification:

[0477] Calculate the root mean square error (RMSE) between the experimental results and the theoretical predictions:

[0478]

[0479] in, is the experimental observation value, is the theoretical prediction value, is the sample size.

[0480] In addition, the following aspects can be considered to further optimize and analyze the system:

[0481] 1. Multi-objective optimization:

[0482] In some cases, you may need to consider multiple objective functions. In this case, the Pareto optimization method can be used. For two objective functions and , we can define the Pareto optimal solution set:

[0483]

[0484] 2. Response surface methodology:

[0485] In order to reduce the computational complexity, the response surface method can be used to approximate the objective function. The commonly used quadratic response surface model is:

[0486]

[0487] in, are unknown coefficients and can be solved by the least squares method.

[0488] 3. Multi-scale modeling:

[0489] To consider multi-scale effects from the molecular scale to the macroscopic scale, a multi-scale simultaneous simulation method can be used:

[0490]

[0491]

[0492] in, and represent macro and micro variables respectively, is a small parameter.

[0493] 4. Improvements to optimization algorithms:

[0494] You can consider using more advanced optimization algorithms, such as the particle swarm optimization (PSO) algorithm. The speed and position update formula of PSO is:

[0495]

[0496]

[0497] in, is the inertia weight, and is the learning factor, and is a random number, is the optimal position of an individual, is the global optimal position.

[0498] In order to better understand and implement the double-chamber vial provided by the present invention, the following provides Example 2 of a specific application scenario of a double-chamber vial that needs to adopt the method of the present invention: This Example 2 describes a double-chamber vial for storing and mixing antibiotic powder and solvent. The double-chamber vial is made of borosilicate glass, including a bottle mouth, a bottle body, a first sealing rubber plug, a second sealing rubber plug and a plastic cap. The bottle body is divided into an upper chamber and a lower chamber, the upper chamber is used to store the solvent, and the lower chamber is used to store the antibiotic powder.

[0499] 1. Bottle design:

[0500] The bottle is made of transparent borosilicate glass material, with a total height of 100 mm and an outer diameter of 30 mm. The upper chamber volume is 10 ml and the lower chamber volume is 5 ml. The wall thickness of the bottle is 1.5 mm to ensure sufficient strength and pressure resistance. The inner diameter of the bottle mouth is 13 mm, the outer diameter is 20 mm, and the height is 7 mm. The inner wall of the bottle has been specially treated with extremely low adsorption to prevent the drug ingredients from being adsorbed.

[0501] 2. The first sealing plug:

[0502] The first sealing plug is made of bromobutyl rubber material, with a diameter of 13 mm and a height of 8 mm. The top of the plug is designed with a groove to facilitate the fixing of the plastic cap. The bottom of the plug is designed to be conical to improve the sealing performance. The hardness of the plug is 55 Shore A, with good elasticity and sealing performance. The surface of the plug is treated with polytetrafluoroethylene coating to reduce the interaction with the liquid medicine.

[0503] 3. Second sealing plug:

[0504] The second sealing rubber plug is also made of bromobutyl rubber material, with a diameter of 28 mm and a height of 5 mm. The rubber plug is designed in the shape of a double convex lens, thin in the middle and thick at both ends to ensure good sealing performance and easy compression deformation. The hardness of the rubber plug is 50 Shore A, slightly softer than the first sealing rubber plug, so that it can be deformed and moved under pressure. The edge of the rubber plug is designed with a raised lip structure to enhance the sealing effect with the bottle wall.

[0505] 4. Plastic cap:

[0506] The plastic cap is made of high-density polyethylene (HDPE) and is white and opaque. The inner diameter of the cap is 20 mm, which matches the outer diameter of the bottle mouth. The cap is 15 mm high and 2 mm thick at the top. The cap is designed with a raised structure inside to press the first sealing plug. The outside of the cap is designed with anti-slip texture for easy operation. The bottom of the cap is designed with an anti-tampering mark to ensure the safety of the drug.

[0507] 5. Upper chamber:

[0508] The upper chamber is used to store 10 ml of sterile water for injection. The inner wall of the chamber is siliconized to reduce the surface tension of the liquid and facilitate complete emptying. A 5 mm air chamber is left at the top of the upper chamber to buffer the pressure.

[0509] 6. Lower chamber:

[0510] The lower chamber is used to store 1 gram of antibiotics in freeze-dried powder form. The bottom of the chamber is designed to be arc-shaped to reduce dead corners and facilitate the full dissolution of the drug. The volume of the lower chamber is slightly larger than the volume of the powder, leaving enough space for liquid to enter and mix.

[0511] 7. Separation area design:

[0512] The partition between the upper and lower chambers is designed to be funnel-shaped with a slope of 30 degrees. This design helps the second sealing plug to fall smoothly under pressure and guides the liquid to flow quickly into the lower chamber. The inner wall of the partition is polished with a surface roughness Ra value of less than 0.2 microns to reduce friction.

[0513] 8. Sterility assurance:

[0514] The entire double-chamber vial is assembled under sterile conditions. The glass vial is sterilized at high temperature (250°C, 30 minutes). The sealing rubber stopper and plastic cap are sterilized by ethylene oxide gas. The filling and sealing process is carried out in a Class 100 clean room.

[0515] 9. How to use:

[0516] a) Remove the dust cover (if any).

[0517] b) Wipe the surface of the plastic cap with a 75% alcohol cotton pad.

[0518] c) Use your thumb to press firmly on the center of the plastic cap until you hear a "click".

[0519] d) Invert the vial 5-10 times to ensure that the powder is completely dissolved.

[0520] e) Let stand for 1 minute to allow air bubbles to dissipate.

[0521] f) Remove the plastic cap and the first sealing rubber plug.

[0522] g) Use a syringe to draw out the required dose of liquid medicine.

[0523] 10. Performance indicators:

[0524] a) Sealing performance: No leakage within 24 hours at 1.5 atmospheres.

[0525] b) Second sealing rubber plug falling time: falling within 0.5 seconds after being pressed.

[0526] c) Dissolution time: More than 90% of the samples were dissolved within 30 seconds.

[0527] d) Residual volume: The residual volume after emptying is less than 1%.

[0528] e) Particle contamination: The number of insoluble particles larger than 10 microns per milliliter of solution shall not exceed 300.

[0529] 11. Stability test:

[0530] Accelerated stability test was conducted at 25℃ / 60%RH and 40℃ / 75%RH for 6 months. Test indicators include:

[0531] a) Appearance: No obvious discoloration, turbidity or precipitation.

[0532] b) pH value: the change shall not exceed ±0.5.

[0533] c) Content: not less than 95% of the labeled amount.

[0534] d) Sterility: Maintain sterile conditions.

[0535] e) Osmotic pressure: change shall not exceed ±10%.

[0536] 12.Production process:

[0537] a) Glass bottle cleaning: Use purified water and ultrasonic cleaning, then dry with dust-free hot air.

[0538] b) Glass bottle sterilization: dry heat sterilization, 250℃ for 30 minutes.

[0539] c) Rubber stopper cleaning: Use purified water and surfactant to clean, then rinse with purified water.

[0540] d) Sterilization of rubber stoppers: Sterilization with ethylene oxide gas at a concentration of 600 mg / L, a temperature of 54°C, a relative humidity of 60%, and a time of 4 hours.

[0541] e) Powder filling: carried out in a Class 100 clean room, using a precision balance to ensure that the filling accuracy is within ±1%.

[0542] f) Second sealing rubber plug assembly: Use automated equipment to accurately place the second sealing rubber plug at the designated location.

[0543] g) Solvent filling: Use a validated aseptic filling system with a filling accuracy within ±2%.

[0544] h) Assembly of the first sealing rubber plug: Use automated equipment to press the first sealing rubber plug into the bottle mouth.

[0545] i) Plastic cap assembly: Put the plastic cap on the bottle mouth and make sure it fits tightly against the bottle body.

[0546] j) Labeling: Use an automatic labeling machine to stick the labels and ensure that the information is clear and readable.

[0547] k) Packaging: Put the vials into inner boxes and then into outer boxes.

[0548] l) Quality inspection: Each batch of products is sampled and inspected, including appearance, sealing, sterility and other indicators.

[0549] Through the above detailed design and strict quality control, the double-chamber vial of Example 2 can effectively ensure the stability and safety of the drug, and provide convenience and protection for clinical drug use.

[0550] Example 3: This example 3 describes a specific method for optimizing the structure of the double-chamber vial in Example 2. The optimization objectives are to improve the drop reliability of the second sealing rubber plug, reduce liquid residue, and shorten the mixing time.

[0551] Specific implementation of step S10:

[0552] The equations of motion are established, including the following equations:

[0553] 1. The first sealing plug motion equation:

[0554]

[0555] in:

[0556] : Mass of the first sealing rubber plug, in kg

[0557] : Displacement of the first sealing plug, in m

[0558] : time, in seconds

[0559] : Damping coefficient, unit is N·s / m

[0560] : Elastic modulus, unit is N / m

[0561] : The pressure applied by the plastic cap, in N

[0562] : Upper chamber pressure, in Pa

[0563] : The effective area of ​​the first sealing plug, in m²

[0564] 2. Upper chamber pressure change equation:

[0565]

[0566] in:

[0567] : ratio of specific heats of gases, dimensionless

[0568] : Gas constant, unit is J / (mol·K)

[0569] : Temperature, in K

[0570] : The volume of the upper chamber, in m³,

[0571] : Initial volume, in m³

[0572] 3. The motion equation of the second sealing plug:

[0573]

[0574] in:

[0575] : Mass of the second sealing rubber plug, in kg

[0576] : Displacement of the second sealing plug, in m

[0577] : Damping coefficient, unit is N·s / m

[0578] : Friction force function, unit is N

[0579] : The effective area of ​​the second sealing plug, in m²

[0580] : Lower chamber pressure, in Pa

[0581] 4. Friction function:

[0582]

[0583] in:

[0584] : Friction coefficient, dimensionless

[0585] : Positive pressure, unit is N

[0586] : Friction attenuation coefficient, unit is 1 / m

[0587] : Maximum static friction, in N

[0588] : Speed ​​influence coefficient, unit is s / m

[0589] 5. The pressure change equation of the lower chamber:

[0590]

[0591] in:

[0592] : Volume of the lower chamber, in m³,

[0593] : Initial volume, in m³

[0594] 6. Liquid flow equation:

[0595]

[0596] in:

[0597] : Volume flow rate, in m³ / s

[0598] : Flow coefficient, dimensionless

[0599] : Opening area, in m²

[0600] : Liquid density, in kg / m³

[0601] Specific implementation of step S20:

[0602] The parameters in the equations are determined through experimental measurements and theoretical calculations:

[0603] 1. Quality measurement:

[0604] Use a precision electronic balance (accuracy 0.0001g) to measure the mass of the first sealing plug g.

[0605] Measuring the quality of the second sealing plug g.

[0606] 2. Geometric dimension measurement:

[0607] Use a precision caliper (accuracy 0.01mm) to measure the effective area of ​​the first sealing plug m².

[0608] Measure the effective area of ​​the second sealing plug m².

[0609] 3. Material dynamic mechanical analysis (DMA) experiment:

[0610] A TA Instruments Q800 dynamic mechanical analyzer was used.

[0611] Test conditions: frequency range 0.1-100 Hz, temperature 25°C, strain amplitude 0.1%.

[0612] Measure the elastic coefficient of the first sealing plug N / m.

[0613] Measure the damping coefficient of the first sealing rubber plug N·s / m.

[0614] The damping coefficient of the second sealing rubber plug is measured N·s / m.

[0615] 4. Friction test:

[0616] An Anton Paar Friction Tester was used.

[0617] Test conditions: normal force 1N, sliding speed 0.1-10mm / s, temperature 25℃.

[0618] Measured friction coefficient .

[0619] Measured maximum static friction N.

[0620] 5. Data fitting:

[0621] Use the MATLAB Curve Fitting Toolbox.

[0622] By fitting the experimental data, the friction attenuation coefficient is obtained m⁻¹.

[0623] Get the speed influence coefficient s / m.

[0624] 6. Fluid mechanics experiment:

[0625] A homemade flow test device was used.

[0626] Test conditions: differential pressure range 0.1-1 bar, temperature 25°C.

[0627] Measured flow coefficient .

[0628] 7. Volume measurement:

[0629] Use a precision measuring cylinder (accuracy 0.1 mL) to measure the initial volume of the upper chamber. mL.

[0630] Measure the initial volume of the lower chamber mL.

[0631] 8. Other parameters:

[0632] Gas specific heat ratio (Air).

[0633] Gas constant J / (mol·K).

[0634] Room temperature K.

[0635] Liquid Density kg / m³ (water, 25°C).

[0636] Specific implementation of step S30:

[0637] According to the system performance requirements, a comprehensive objective function including multiple performance indicators is established:

[0638]

[0639] in:

[0640] : comprehensive objective function value, dimensionless

[0641] : Weight coefficient, dimensionless, and satisfies

[0642] : Normalized function of each performance index, dimensionless

[0643] : The second sealing plug falling time, in seconds

[0644] : System pressure change, unit is Pa

[0645] : Liquid flow rate, in m³ / s

[0646] : Mixing uniformity, dimensionless

[0647] The normalization functions are defined as follows:

[0648]

[0649]

[0650]

[0651]

[0652] Determine the weight coefficient based on expert evaluation and user demand analysis:

[0653] , , ,

[0654] Specific implementation of step S40:

[0655] According to actual engineering limitations and safety requirements, the value range of each parameter is set as a constraint condition:

[0656] 1. Size constraints of the first sealing plug:

[0657]

[0658]

[0659] 2. Size constraints of the second sealing plug:

[0660]

[0661]

[0662] 3. System pressure constraints:

[0663]

[0664]

[0665] 4. Material strength constraints:

[0666] (Yield Strength of Bromobutyl Rubber)

[0667] 5. Flow rate constraints:

[0668]

[0669] 6. Mixed time constraints:

[0670]

[0671] in:

[0672] : The diameter and height of the first sealing plug, in mm

[0673] : The diameter and height of the second sealing plug, in mm

[0674] : Pressure of the upper and lower chambers, in bar

[0675] : Maximum stress, in MPa

[0676] : Flow rate, in mL / s

[0677] : Mixing time, in seconds

[0678] Specific implementation of step S50:

[0679] The comprehensive objective function is optimized and solved by using an improved genetic algorithm combined with a simulated annealing algorithm. The specific steps are as follows:

[0680] 1. Initialization parameters:

[0681] - Population size: 100

[0682] - Chromosome length: 20 (each design variable is encoded with 5 bits)

[0683] - Crossover probability: 0.8

[0684] - Mutation probability: 0.01

[0685] - Maximum number of iterations: 1000

[0686] - Initial temperature: 100

[0687] - Cooling coefficient: 0.95

[0688] 2. Coding:

[0689] The design variables (geometric parameters of the first sealing rubber plug and the second sealing rubber plug) are encoded as binary strings.

[0690] 3. Initial population generation:

[0691] Randomly generate an initial population that satisfies the constraints.

[0692] 4. Fitness evaluation:

[0693] Calculate the objective function value of each individual and convert it into a fitness value.

[0694] 5. Select an operation:

[0695] Roulette wheel selection method is used to select outstanding individuals.

[0696] 6. Crossover operation:

[0697] The crossover operation is performed using the single-point crossover method.

[0698] 7. Mutation operation:

[0699] The uniform mutation method is used for mutation operation.

[0700] 8. Local search:

[0701] Perform simulated annealing local search for the best individual in the population.

[0702] Randomly generate new solutions near the current solution.

[0703] Calculate the energy difference .

[0704] if , accept the new interpretation.

[0705] Otherwise, with probability Accept new interpretations.

[0706] Update Temperature: .

[0707] 9. Repeat steps 4-8 until the maximum number of iterations is reached or the convergence condition is met.

[0708] 10. Decode the optimal individual and obtain the optimized design parameters.

[0709] Specific implementation of step S60:

[0710] The system of motion equations is numerically solved and the fourth-order Runge-Kutta method is used for numerical integration. The specific steps are as follows:

[0711] 1. Define state variables:

[0712]

[0713] in, , .

[0714] 2. Convert the differential equations into first-order ordinary differential equations:

[0715]

[0716] 3. Set initial conditions:

[0717]

[0718] in, and are the initial pressures of the upper and lower chambers, respectively.

[0719] 4. Choose the time step s, total simulation time s.

[0720] 5. For each time step arrive :

[0721] a) Calculate four increments:

[0722]

[0723]

[0724]

[0725]

[0726] b) Update state variables:

[0727]

[0728] c) Calculate liquid flow and mixing uniformity .

[0729] 6. Evaluate the objective function value at each iteration .

[0730] 7. Record changes in key parameters over time, including , , , and .

[0731] Specific implementation of step S70:

[0732] According to the optimization results, the optimal shape and size parameters of the first sealing rubber plug and the second sealing rubber plug are determined, and actual sample production and verification tests are carried out.

[0733] 1. Optimal design parameters:

[0734] First sealing plug:

[0735] diameter mm

[0736] high mm

[0737] Top groove depth mm

[0738] Bottom cone angle

[0739] Second sealing plug:

[0740] diameter mm

[0741] high mm

[0742] Center thickness mm

[0743] Edge lip height mm

[0744] 2. Sample production:

[0745] a) The first sealing rubber plug and the second sealing rubber plug are made of brominated butyl rubber using a precision mold.

[0746] b) Surface treatment of the rubber plug is performed by coating it with polytetrafluoroethylene.

[0747] c) According to the production process in Example 2, 100 optimized double-chamber vial samples were assembled.

[0748] 3. Verification test:

[0749] a) Sealing performance test:

[0750] - Detection using a helium mass spectrometer leak detector.

[0751] - Test conditions: internal helium pressure 1.5 bar, test time 30 minutes.

[0752] - Requirement: Leakage rate ≤ 1×10⁻ 7 Pa·m³ / s.

[0753] b) Second sealing plug drop time test:

[0754] - Use a high-speed camera (1000 frames / second) to record the falling process.

[0755] - Measure the time from the start of pressing to the time when the second sealing plug is completely inserted into the lower chamber.

[0756] - Requirements: Average falling time ≤ 0.5 seconds, and 100% of the samples can fall successfully.

[0757] c) Dissolution time test:

[0758] - Place 1 g of penicillin sodium powder in the lower chamber.

[0759] - Add 10 mL of water for injection into the upper chamber.

[0760] - After pressing, use a timer to measure the dissolution time.

[0761] - Requirement: More than 90% of the sample is completely dissolved within 30 seconds.

[0762] d) Residue test:

[0763] - Use a precision electronic balance (accuracy 0.0001g) to measure the weight difference before and after emptying.

[0764] - Calculate the residual rate = (weight after emptying - weight of empty bottle) / (weight before emptying - weight of empty bottle) × 100%.

[0765] - Requirements: Average residual rate ≤ 0.8%.

[0766] e) Particle contamination test:

[0767] - Measure insoluble particles in solution using an optical particle counter.

[0768] - Tested in accordance with the "Insoluble Particles Test Method" of Part IV of the 2020 edition of the Chinese Pharmacopoeia.

[0769] - Requirements: The number of particles ≥10μm is ≤300 / mL, and the number of particles ≥25μm is ≤20 / mL.

[0770] 4. Test result analysis:

[0771] a) Sealing performance: All 100 samples passed the test, with an average leakage rate of 5.2×10⁻ 8 Pa·m³ / s.

[0772] b) Drop time of the second sealing rubber plug: the average drop time was 0.42 seconds, the standard deviation was 0.05 seconds, and 100% of the samples dropped successfully.

[0773] c) Dissolution time: 95% of the samples were completely dissolved within 28 seconds, and the longest dissolution time was 33 seconds.

[0774] d) Residue: The average residual rate is 0.65% and the standard deviation is 0.12%.

[0775] e) Particle contamination: The average number of particles ≥10μm is 127 / mL, and the average number of particles ≥25μm is 8 / mL.

[0776] 5. Evaluation of optimization effect:

[0777] Compare the optimized dual chamber vial to the original design:

[0778] a) The second sealing plug drop time is shortened by 18%.

[0779] b) Dissolution time was reduced by 22%.

[0780] c) The residue amount was reduced by 35%.

[0781] d) Particle pollution levels were reduced by 42%.

[0782] The overall performance was improved by about 30%, achieving the optimization goal.

[0783] 6. Reliability analysis:

[0784] a) Monte Carlo simulation method is used to consider the manufacturing errors of various parameters and fluctuations in usage conditions.

[0785] b) Carry out 10,000 simulations and calculate the reliability of each performance indicator.

[0786] c) The results show that at a confidence level of 95%, all performance indicators of the optimized double-chamber vial can meet the requirements.

[0787] Through the above detailed implementation steps, this Example 3 successfully optimized the structure of the double-chamber vial of Example 2, significantly improved product performance, and laid a solid foundation for subsequent production, quality control and market promotion. This systematic optimization method is not only applicable to double-chamber vials, but can also be extended to the development of other similar medical device products.

[0788] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for optimizing the structure of a double-chamber vial, characterized in that: The method is used to optimize the structure of a double-chamber vial, specifically to optimize the shapes and sizes of a first sealing rubber plug and a second sealing rubber plug of a double-chamber vial, so that when a plastic cap is pressed, the first sealing rubber plug can be driven to move downward, so that the first sealing rubber plug is squeezed and deformed, and the pressure in the upper chamber is increased, thereby pushing the second sealing rubber plug to move downward and fall into the lower chamber, and preventing the second sealing rubber plug from getting stuck or tilted during the falling process. The method comprises the following steps: S10, establishing a group of motion equations, including a first sealing rubber plug motion equation, an upper chamber pressure change equation, a second sealing rubber plug motion equation, a friction force function, a lower chamber pressure change equation, and a liquid flow equation; S20. Determine various parameters in the equations through experimental measurement and theoretical calculation, including mass, elastic coefficient, damping coefficient, friction coefficient, viscosity, surface tension, gas constant, specific heat ratio, flow coefficient, and density; S30, establishing an objective function: establishing a comprehensive objective function including multiple performance indicators according to system performance requirements; S40, according to actual engineering limitations and safety requirements, setting the value range of each parameter as a constraint condition; S50, optimizing and solving the comprehensive objective function, wherein a genetic algorithm is used for global search and a simulated annealing algorithm is used for local optimization; S60, numerically solve the system of motion equations, simulate the dynamic process of the system, and evaluate the objective function value in each iteration; S70. Determine the optimal shape and size parameters of the first sealing rubber plug and the second sealing rubber plug according to the optimization result, and perform actual sample production and verification testing.

2. The structural optimization method of a double-chamber vial according to claim 1, characterized in that: The multiple performance indicators include the falling time of the second sealing plug, the system pressure change, the liquid flow rate, and the mixing uniformity.

3. The structural optimization method of a double-chamber vial according to claim 1, characterized in that: The method for optimizing and solving the comprehensive objective function is to use an improved genetic algorithm combined with a simulated annealing algorithm for optimization and solution.

4. The structural optimization method of a double-chamber vial according to claim 1, characterized in that: The method for numerically solving the set of motion equations is the fourth-order Runge-Kutta method.

5. A method for optimizing the structure of a double-chamber vial according to any one of claims 1 to 4, characterized in that: The double-chambered syringe bottle comprises: a bottle mouth, a bottle body, a first sealing rubber plug, a second sealing rubber plug and a plastic cap; the bottle body comprises an upper chamber and a lower chamber, the upper chamber is used to store a solution, and the lower chamber is used to store a powdered medicine; the first sealing rubber plug is arranged at the bottle mouth, and the second sealing rubber plug is arranged between the upper chamber and the lower chamber; the plastic cap is installed on the outside of the bottle mouth and is used to press the first sealing rubber plug; when the plastic cap is pressed, the first sealing rubber plug moves downward and is squeezed and deformed, so that the pressure in the upper chamber is increased, and the second sealing rubber plug is pushed downward and falls into the lower chamber, so that the liquid in the upper chamber flows into the lower chamber to dissolve the powder.

6. The method for structural optimization of a double-chamber vial according to claim 5, characterized in that: The bottle body is made of a borosilicate glass tube.

7. The method for structural optimization of a double-chamber vial according to claim 5, characterized in that: The pressure generated by the extrusion and deformation of the first sealing rubber plug is greater than the pressure required for the second sealing rubber plug to move downward after being pressed.

8. The method for structural optimization of a double-chamber vial according to claim 5, characterized in that: When the plastic cap is pressed, the first sealing rubber plug can be driven to move downward, so that the first sealing rubber plug is squeezed and deformed, and the pressure in the upper chamber is increased, thereby pushing the second sealing rubber plug to move downward and fall into the lower chamber.

9. The method for optimizing the structure of a double-chamber vial according to claim 5, characterized in that: The lower chamber is used to store medicines in the form of freeze-dried powders; the upper chamber is used to store aseptically filled liquid solvents.

10. The method for structural optimization of a double-chamber vial according to claim 5, characterized in that: The method for using the double-chamber vial includes: pressing the plastic cap to allow the liquid in the upper chamber to flow into the lower chamber to mix with the powder, without the need to use a syringe to puncture and extract the liquid and inject it into the powder bottle, thereby avoiding contamination by rubber stopper debris, accidental punctures and aerosol contamination of the drug solution.

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