A method for predicting or evaluating the stability of mRNA-lnp liquid formulations and applications thereof

Abstract

The application discloses a method for predicting or evaluating the stability of mRNA-LNP liquid preparation and application thereof, and belongs to the technical field of drug quality control, and the method steps comprise the following: after centrifugation of mRNA-LNP liquid preparation, balance, and then place the mRNA-LNP liquid preparation in a multifunctional protein stability analyzer, test the turbidity, hydrodynamic radius and intermolecular interaction of the mRNA-LNP liquid preparation with the change of temperature, calculate the stability evaluation temperature T stability , according to the data obtained by testing and T stability , obtain a comprehensive stability score S stability , the higher S stability , the better the stability of the mRNA-LNP liquid preparation is. The method is suitable for preparation development and quality control in the fields of mRNA vaccines and gene therapy, is efficient, marker-free and accurate, and can be used for improving the stability and research and development efficiency of the preparation.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of pharmaceutical quality control, and specifically relates to a method for predicting or evaluating the stability of mRNA-LNP liquid preparation and application thereof. BACKGROUND

[0002] Lipid nanoparticles (LNPs) are key delivery carriers in gene therapy and vaccine development, which can effectively encapsulate mRNA, avoid its degradation in in vitro and in vivo environments, and help it penetrate the cell membrane into target cells, thereby significantly improving the stability and effectiveness of mRNA delivery in vivo. However, due to the high instability of mRNA molecules themselves, they are easily affected by environmental factors (such as enzymes, pH, temperature, etc.) and degraded, and the changes in the physical properties (such as particle size, surface charge) of LNPs under different environmental conditions may further exacerbate this problem, thereby affecting the stability and delivery efficiency of mRNA-LNP. Therefore, how to effectively evaluate and predict the stability of mRNA-LNP has become an important challenge in the field of current gene drugs and vaccine development.

[0003] There are many technical solutions about LNP delivery system in the prior art (such as Chinese patent documents with publication numbers CN117088820A and CN116514672A). These patents focus on optimizing the composition and structure of LNPs to improve their stability in delivering mRNA, thereby improving the bioavailability. However, in terms of stability characterization, the prior art still mainly relies on traditional methods such as differential scanning calorimetry (DSC), accelerated stability testing method and fluorescence polarization method. DSC is a classic thermal analysis method that evaluates the stability of samples by measuring their heat absorption and heat release during temperature changes. However, DSC requires a large amount of sample and the experimental process is time-consuming, making it difficult to perform high-throughput screening quickly. Accelerated stability experiments store samples at higher temperatures to accelerate their degradation process to predict long-term stability. This method is time-consuming and its accuracy is affected by the assumption conditions. Fluorescence polarization method can detect the fluorescence changes of samples at different temperatures to predict their stability, but it usually requires labeling of samples, which increases the complexity of experiments, and the label may affect the natural structure and function of mRNA. The limitations of traditional detection methods mainly lie in the complexity of experiments, the need for more samples, the long time-consuming, and the need for chemical modification of samples in some methods, which may affect the true stability of the samples.

[0004] The Chinese patent document with the publication number CN107255646A discloses a method for quickly quantitatively predicting drug stability. The invention is to establish a model of maximum single impurity after drug crystal stabilization and total impurity after stabilization by combining XRD pattern and chemometrics method, so as to predict drug stability by the model. In the process of establishing the model, the model training data is still obtained by accelerated stability test, and the method is only applicable to drugs obtained by crystallization, and is not applicable to mRNA-LNP drugs.

[0005] Therefore, it is of great significance to develop a more efficient, more convenient and sample modification-free method for predicting or evaluating the stability of mRNA-LNP liquid preparation. SUMMARY

[0006] In order to solve the problems existing in the prior art, the present application provides a method for predicting or evaluating the stability of mRNA-LNP liquid preparation, which is suitable for the development and quality control of preparations in the fields of mRNA vaccines and gene therapy, so as to improve the stability and research and development efficiency of the preparation.

[0007] The specific technical solutions are as follows:

[0008] A method for predicting or evaluating the stability of mRNA-LNP liquid preparation, comprising: after centrifugation of the mRNA-LNP liquid preparation, balancing, and then placing it in a multifunctional protein stability analyzer, testing the turbidity, hydrodynamic radius and intermolecular interaction of the mRNA-LNP liquid preparation with temperature, calculating the stability evaluation temperature T stability , according to the data obtained by testing and T stability , obtaining a comprehensive stability score S stability , the higher S stability , the better the stability of the mRNA-LNP liquid preparation.

[0009] Specifically, the mRNA-LNP liquid preparation contains lipid nanoparticles loaded with mRNA. The mRNA-LNP liquid preparation can be prepared by itself, or a commercially available product can be directly used.

[0010] Optionally, the preparation method of the mRNA-LNP liquid preparation comprises: mixing the aqueous phase containing mRNA and the organic phase containing complex lipid material to obtain mRNA-LNP nanoparticles, and further mixing with a liquid medium to obtain the mRNA-LNP liquid preparation.

[0011] Further, the aqueous phase containing mRNA and the organic phase containing complex lipid material are mixed by using microfluidic technology; the liquid medium includes a buffer, and can also contain preservatives and other auxiliaries.

[0012] Preferably, the centrifugal speed is 10000-15000 rpm, the centrifugal time is 15-30 minutes, and the centrifugal temperature is 3.5-4.5℃. The centrifugation removes large particle impurities or aggregates in the mRNA-LNP liquid preparation, ensures the purity of the sample, and further improves the accuracy of subsequent analysis.

[0013] Preferably, the sample is equilibrated at 20-25℃ for 20-30 minutes. The equilibration process can ensure that the mRNA-LNP liquid preparation sample is consistent with the ambient temperature, reaches thermal equilibrium, and avoids the influence of temperature fluctuations on experimental results.

[0014] Further, in the multifunctional protein stability analyzer, the turbidity is detected based on the back reflection module, the hydrodynamic radius is detected based on the dynamic light scattering technology, and the intermolecular interaction is detected based on the static light scattering technology.

[0015] Specifically, the stability evaluation temperature T stability is calculated as follows:

[0016]

[0017] wherein T turbidity , T rH , and T Scattering respectively represent the temperature T parameter at which the turbidity, the hydrodynamic radius, and the intermolecular interaction parameter change by 10% during the test temperature change. parameter If the change of a parameter does not exceed 10% within the test temperature change range, then T max is the highest test temperature.

[0018] Preferably, T max is 98℃.

[0019] Specifically, the calculation method of the comprehensive stability score S stability is as follows:

[0020]

[0021] wherein Δ Turbidity represents the change amount of the turbidity with temperature, Δ rH represents the change amount of the hydrodynamic radius with temperature, and Δ Scattering represents the change amount of the intermolecular interaction with temperature.

[0022] The stability performance of the mRNA-LNP liquid preparation in the long-term storage process is verified by the accelerated stability experiment to determine the prediction or evaluation accuracy of the method, specifically, the accelerated stability experiment process is that the mRNA-LNP liquid preparation is stored in a 40 DEG C biological stability box for 6 weeks and 12 weeks, after 6 weeks and 12 weeks, the changes of particle size, polydispersity index (PDI), Zeta potential and encapsulation rate are measured to evaluate the long-term stability, and the results prove that the method has good accuracy, is consistent with the accelerated stability experiment result, and greatly shortens the detection period.

[0023] The application further provides application of the method for predicting or evaluating the stability of the mRNA-LNP liquid preparation in mRNA-LNP vaccine quality control or mRNA-LNP vaccine research and development.

[0024] Compared with the prior art, the application has the beneficial effects that:

[0025] (1) The method provided by the application uses multiple detection modules of the multifunctional protein stability analyzer, provides a high-efficiency, label-free and accurate method for predicting or evaluating the stability of the mRNA-LNP liquid preparation, can perform label-free and non-destructive detection on the mRNA-LNP liquid preparation under different environmental conditions (such as temperature, pH and preservatives), and at the same time avoids the potential influence of chemical modification in the traditional method on the stability of the sample, the comprehensive stability score S stability provided by the application is calculated by the formula, the changes of various detection parameters are quantified, a comprehensive and objective stability evaluation index is provided, and the evaluation result is more real and reliable.

[0026] (2) The multifunctional protein stability analyzer is used to perform multiple-parameter joint detection on the mRNA-LNP liquid preparation in the application, subtle changes of the mRNA-loaded lipid nanoparticles are captured, and the accuracy and reliability of the prediction result are improved.

[0027] (3) The traditional stability evaluation method usually needs a long storage time to observe the changes of the preparation, and the method provided by the application can predict or evaluate the long-term stability of the mRNA-LNP liquid preparation in a short time by analyzing the key parameters in real time and quantitatively calculating the indexes, improves the research and development efficiency, and greatly shortens the detection period.

[0028] (4) The method provided by the application detects without destroying the sample, retains the integrity of the sample, is particularly suitable for the development of high-cost mRNA-LNP liquid preparations, and helps to reduce the research and development cost. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1Figure 1. Changes in parameters of mRNA-LNP liquid formulations of different formulations (F, G, H groups) in Example 1 during the test process.

[0030] Figure 2 Figure 2. Changes in parameters of mRNA-LNP liquid formulations of different formulations (A, I, J groups) in Example 2 during the test process.

[0031] Figure 3 Figure 3. Changes in average particle size of mRNA-LNP nanoparticles of F, G, H groups in Example 3 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3).

[0032] Figure 4 Figure 4. Changes in polydispersity index of mRNA-LNP nanoparticles of F, G, H groups in Example 3 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3).

[0033] Figure 5 Figure 5. Changes in encapsulation efficiency of mRNA-LNP nanoparticles of F, G, H groups in Example 3 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3).

[0034] Figure 6 Figure 6. Changes in Zata potential of mRNA-LNP nanoparticles of F, G, H groups in Example 3 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3).

[0035] Figure 7 Figure 7. Changes in average particle size of mRNA-LNP nanoparticles of A, I, J groups in Example 4 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3).

[0036] Figure 8 Figure 8. Changes in polydispersity index of mRNA-LNP nanoparticles of A, I, J groups in Example 4 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3).

[0037] Figure 9 Figure 9. Changes in encapsulation efficiency of mRNA-LNP nanoparticles of A, I, J groups in Example 4 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3).

[0038] Figure 10 Figure 10. Changes in Zata potential of mRNA-LNP nanoparticles of A, I, J groups in Example 4 after storage at 40°C for 6 weeks, 12 weeks, (mean ± SD, n = 3). DETAILED DESCRIPTION

[0039] For the purpose of making the objectives, characteristics and advantages of the present application more apparent and comprehensible, specific embodiments are described in detail below. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be practiced in a large number of other ways different from those described herein, and one skilled in the art can make similar improvements without departing from the spirit of the present application, and therefore the present application is not limited by the specific examples disclosed below. The technical features in each embodiment of the present application can be combined accordingly without mutual conflict.

[0040] The operation methods not specified in the following examples are generally carried out according to the conventional conditions, or according to the conditions recommended by the manufacturers. The contents not described in detail in the specification belong to the prior art known to those skilled in the art. The experimental materials used in the following examples can be purchased from conventional biochemical reagent companies, unless otherwise specified.

[0041] First, mRNA-LNP liquid formulations were prepared:

[0042] (1) mRNA aqueous phase preparation:

[0043] mRNA aqueous phase: mRNA sample aqueous solution with a final concentration of 0.17 mg / mL.

[0044] Preparation: The mRNA solution was diluted to 0.17 mg / mL with a 0.1 M sodium citrate, pH 4.0 solution.

[0045] (2) Organic phase preparation:

[0046] The composition of the organic phase includes SM102 cationic lipid, cholesterol, DSPC (1,2-dodecyl-sn-glycero-3-phosphocholine) and DMG-PEG 2000 (dimethylglycero-polyethylene glycol 2000) with a molar percentage of 50 / 38.5 / 10 / 1.5, respectively, and a total lipid concentration of 18.5 mM, supplemented with anhydrous ethanol as a solvent.

[0047] (3) Preparation of mRNA-LNP liquid formulations

[0048] The organic phase and the mRNA aqueous phase were mixed by microfluidization at a flow rate ratio of 1:3, and the total flow rate was also 12 ml / min. After ultrafiltration and concentration, a solution containing mRNA-LNP nanoparticles was obtained. After mixing with different buffers and different types of preservatives, different mRNA-LNP liquid formulations were prepared. The specific formulations are shown in the following table:

[0049] Table 1 Composition of different mRNA-LNP liquid formulations

[0050] Prescription Name Sucrose Buffer Preservative A 12％ 10 mM Tris-Hcl buffer, pH 7.4 / F 12％ 10 mM PB buffer, pH 7.8 / G 12％ 10 mM PB buffer, pH 8.0 / H 12％ 10 mM PB buffer, pH 6.8 / I 12％ 10 mM Tris-Hcl buffer, pH 7.4 16 mM m-cresol J 12％ 10 mM Tris-Hcl buffer, pH 7.4 0.9% benzyl alcohol

[0051] Example 1

[0052] The mRNA-LNP liquid formulation samples of different prescriptions prepared in the above steps (F, G, H groups) were added to ep tubes, and the samples were centrifuged at 15000 rpm for 15 minutes at 4±0.5°C using a high-speed refrigerated centrifuge. After centrifugation, the samples were equilibrated at 25°C for 30 minutes. Each sample (N=3) was loaded into a capillary using a Nano DSF dedicated capillary, the capillary was filled with the sample, and the capillary was placed on the back reflection sample loading table of the Nano Temper Panta multifunctional protein stability analyzer. After the sample was loaded into the instrument, the detection parameter settings were performed. The concentration, buffer system and dynamic viscosity of each sample were input in the Prometheus&Control software. The instrument was set to start at 25°C, with a temperature rise rate of 1°C / min, and the final temperature (T max ) was set to 98°C. The instrument will record the aggregation and denaturation of mRNA-LNPs at each temperature change; the turbidity, hydrodynamic radius and intermolecular interaction of the mRNA-LNP liquid formulation were tested as the temperature changed, and the stability evaluation temperature T stability and the comprehensive stability score S stability were calculated, and the results are shown in Table 2.

[0053] Table 2 mRNA-LNP liquid formulation stability test related data

[0054]

[0055] In this example, the stability of mRNA-LNP liquid formulations under different pH conditions was evaluated. The results showed that when the temperature was raised to above 90°C, the intermolecular interaction and turbidity of each group of mRNA-LNP liquid formulations changed significantly, especially the increase in hydrodynamic radius and turbidity, indicating that the particles aggregated in this temperature range. Specifically, the particle size of group H increased the most under high temperature conditions, the turbidity increased significantly, and the comprehensive stability score (S stability ) value was the smallest. All the above results indicate that its stability under high temperature conditions is poor. Figure 1

[0056] Example 2

[0057] ​The mRNA-LNP liquid formulation samples of different formulations prepared in the above steps (groups A, I, J) were added to ep tubes, and the samples were centrifuged at 15000 rpm for 30 minutes at 4±0.5°C using a high-speed refrigerated centrifuge. After centrifugation, the samples were equilibrated at 25°C for 30 minutes. Each sample (N=3) was loaded into a capillary using a Nano DSF dedicated capillary, the capillary was filled with the sample, and the capillary was placed on the back reflection sample loading table of the Nano Temper Panta multifunctional protein stability analyzer. After the sample was loaded into the instrument, the detection parameter settings were performed. The concentration of each sample, the buffer system and the dynamic viscosity were input in the Prometheus & Control software. The instrument was set to start at 25°C, with a temperature ramp of 1°C / min, and end at (T max ) 98°C, and the instrument would record the aggregation and denaturation of mRNA-LNP at varying temperatures. The turbidity, hydrodynamic radius and intermolecular interaction of the mRNA-LNP liquid formulation were tested as a function of temperature, and the stability evaluation temperature T stability and the comprehensive stability score S stability were calculated, and the results are shown in Table 3.

[0058] Table 3 mRNA-LNP liquid formulation stability test related data

[0059]

[0060] The results show that when the temperature is increased to 60-90°C, the intermolecular interaction and turbidity of the mRNA-LNP nanoparticles in each group change significantly. Among them, the turbidity of group J increases rapidly near 60°C, and the S stability value is the smallest, indicating that the stability of group J is poor. The intermolecular interaction and hydrodynamic radius of group A change relatively little, and the S stability value is the largest, showing good stability. Figure 2

[0061] Example 3

[0062] To verify the experimental results predicted by the method in Example 1. Different formulations of mRNA-LNP liquid formulations (F, G, H groups) were placed in a 40°C biological stability box for accelerated stability experiments (6 weeks, 12 weeks), and were taken out for testing at the specified time.

[0063] ​The physicochemical properties of LNPs are one of the important factors affecting their delivery efficiency and safety. The particle size and distribution of LNPs are important parameters affecting their stability. Ideally, the particle size of LNPs is controlled between 20 to 200 nanometers, which is beneficial to enhance the stability of LNPs, ensure their uniform dispersion in the physiological environment, and reduce the possibility of sedimentation or aggregation. DLS technology for measuring particle size has become a routine characterization method for nanoparticles. When using a laser particle size analyzer to analyze nanoparticles, the nanoparticles produce scattered light on the incident laser light, and the scattered light intensity is detected by a detector to calculate the particle size distribution. After DLS measurement, two sets of data can be obtained, namely the average particle size and the particle size dispersion coefficient (PDI) of the nanoparticle particle size. PDI reflects the uniformity of the particle size of LNPs, and is an important indicator of particle size characterization. PDI ranges from 0 to 1, which is considered to be a more uniform distribution of LNPs.

[0064] The surface adsorption properties of LNPs, i.e. Zeta potential, are another important parameter affecting their stability. The size of the Zeta potential directly affects the adsorption properties between nanoparticles, thereby affecting their dispersion and stability in solution.

[0065] Encapsulation efficiency reflects the degree and efficiency of LNPs in encapsulating effective ingredients (such as mRNA). High encapsulation efficiency means that the effective ingredients are more effectively encapsulated inside the LNPs, protected from in vivo enzyme degradation and other external factors, thereby improving the stability of the effective ingredients in vivo.

[0066] Particle size and potential detection: mRNA-LNP liquid formulations were diluted to 0.8-1.6 ng / μL total mRNA in pH 7.4 phosphate buffered saline (PBS) and transferred to a polystyrene cuvette, and the particle size and polydispersity were measured by DLS (Malvern Nano ZS Zetasizer) with a refractive index (RI) of 1.590, an absorption of 0.010 in PBS at 25°C, a viscosity of 0.9073 (cP), and an RI of 1.332. A running duration of 10 seconds was used for measurement, and the number of runs was automatically determined. Each measurement had a fixed position of 4.65 mm in the cuvette with automatic attenuation selection. The diameter was reported as z-average. The same system was also used for potential detection. Figure 3 、 Figure 4 and Figure 6 The results show that the LNPs in groups F, G, and H have similar average particle sizes and potential sizes at the end of preparation (0h). After 12 weeks of storage in a 40°C biological stability box, the average particle size and particle size dispersion coefficient of each group increased, and the average particle size and PDI of group H increased significantly, and the potential was lower. These results suggest that group H has the worst stability. This is consistent with the prediction results of Example 1.

[0067] Encapsulation efficiency: RNA encapsulation efficiency and concentration were determined by Quant-iT RiboGreen assay (Life Technologies). Quantification of RNA in mRNA-LNP liquid formulations was performed using a standard curve generated from dilutions of the respective RNA. Standards and samples were diluted with lx Tris-EDTA (TE) buffer (pH 8.0). Sample concentrations reached 0.1 ng / µL in polystyrene cuvettes. Fluorescence was measured using a fluorescence spectrophotometer (Varian Cary Eclipse) set at 500 nm excitation and 525 nm emission. Standard curves were calculated by linear regression analysis of the plotted fluorescence intensity versus standard concentration. RNA encapsulation of LNP samples was determined by comparing the signal of the RNA-binding fluorescent dye RiboGreen in the absence and presence of a detergent (0.1% Triton X-100). Figure 5 The results show that the encapsulation efficiency of group H decreased most significantly after 12 weeks in the 40°C biological stability box, further verifying that the stability of the liquid formulation of group H is poor.

[0068] Example 4

[0069] To verify the experimental results predicted by the method in Example 2. Different prescription mRNA-LNP liquid formulations (groups A, I, J) were placed in a 40°C biological stability box for accelerated stability experiments (6 weeks, 12 weeks), and were taken out at the specified time for testing.

[0070] Particle size and potential changes: mRNA-LNP liquid formulations were diluted to 0.8-1.6 ng / µL total mRNA in pH 7.4 phosphate buffered saline (PBS) and transferred to polystyrene cuvettes. Particle size and polydispersity were measured by DLS (Malvern ZS Zetasizer) using a refractive index (RI) of 1.590, an absorbance of 0.010 in PBS at 25°C with a viscosity of 0.9073 (cP) and an RI of 1.332. Measurements were taken using a run duration of 10 seconds with automatic run number determination. Each measurement had a fixed position in the cuvette of 4.65 mm with automatic attenuation selection. Diameter was reported as z-average. The same system was also used to measure potential. Figure 7 、 Figure 8 and Figure 10 The results show that the average particle size and PDI of group J increased most significantly after 12 weeks of storage in the 40°C biological stability box, and the potential was close to zero, indicating that its stability during long-term storage is poor, while the average particle size of groups A and I changed relatively small, showing good stability. This is consistent with the prediction results of Nano Temper.

[0071] Encapsulation efficiency: RNA encapsulation efficiency and concentration were determined by Quant-iT Ribo Green assay (Life Technologies). Quantification of RNA in mRNA-LNP liquid formulations was performed using a standard curve generated from dilutions of the respective RNA. Standards and samples were diluted with 1 x Tris-EDTA (TE) buffer (pH 8.0). Sample concentrations reached 0.1 ng / μL in polystyrene cuvettes. Fluorescence was measured using a fluorescence spectrophotometer (Varian Cary Eclipse) set at 500 nm excitation and 525 nm emission. Standard curves were calculated by linear regression analysis of the plotted fluorescence intensity versus standard concentration. RNA encapsulation of LNP samples was determined by comparing the signal of the RNA-binding fluorescent dye Ribo Green in the absence and presence of a detergent (0.1% Triton X-100). Figure 9 The results of the middle experiment showed that the encapsulation efficiency of group J decreased most significantly after 12 weeks of storage, indicating that it had poor stability during long-term storage, while the encapsulation efficiency of groups A and I was relatively stable, showing good storage stability. Further confirming the accuracy of the prediction results of Nano Temper.

[0072] The above embodiments are used to describe the technical solutions of the present application in detail. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the present application. Any modification, supplement or similar replacement within the principle range of the present application should be included in the protection scope of the present application.

Claims

1. A method for predicting or evaluating the stability of an mRNA-LNP liquid formulation, characterized in that: include: After centrifugation and balancing, the mRNA-LNP liquid preparation was placed in a multifunctional protein stability analyzer to test the changes in turbidity, hydrodynamic radius and intermolecular interaction of the mRNA-LNP liquid preparation with temperature, and calculate the stability evaluation temperature. T stability , according to the test data and T stability Get the comprehensive stability score S stability , S stability The higher it is, the better the stability of the mRNA-LNP liquid formulation; Stability evaluation temperature T stability The calculation method is: ； in, , , Respectively represent the temperature T when turbidity, hydrodynamic radius, and intermolecular interaction parameters change by 10% with the test temperature during the test process. parameter If a parameter does not change by more than 10% within the test temperature range, then T parameter At the highest test temperature T max count; Comprehensive stability score S stability The calculation method is: ； in, It represents the change of turbidity with temperature. represents the change of hydraulic radius with temperature, It represents the change of intermolecular interaction with temperature.

2. The method for predicting or evaluating the stability of an mRNA-LNP liquid formulation according to claim 1, wherein The mRNA-LNP liquid preparation contains lipid nanoparticles loaded with mRNA.

3. The method for predicting or evaluating the stability of an mRNA-LNP liquid formulation according to claim 2, wherein: The preparation method of the mRNA-LNP liquid preparation comprises: mixing an aqueous phase containing mRNA and an organic phase containing a composite lipid material to obtain mRNA-LNP nanoparticles, and further mixing with a liquid medium to obtain the mRNA-LNP liquid preparation.

4. The method for predicting or evaluating the stability of an mRNA-LNP liquid formulation according to claim 1, wherein The centrifugal speed is 10000-15000 rpm, the centrifugal time is 15-30 minutes, and the centrifugal temperature is 3.5-4.5°C.

5. The method for predicting or evaluating the stability of an mRNA-LNP liquid formulation according to claim 1, wherein Equilibrate at 20-25°C for 20-30 minutes.

6. The method for predicting or evaluating the stability of an mRNA-LNP liquid formulation according to claim 1, wherein In the multifunctional protein stability analyzer, turbidity is detected based on the back reflection module, the hydrodynamic radius is detected based on the dynamic light scattering technology, and the intermolecular interaction is detected based on the static light scattering technology.

7. Application of the method for predicting or evaluating the stability of an mRNA-LNP liquid formulation according to any one of claims 1 to 6 in mRNA-LNP vaccine quality control or mRNA-LNP vaccine research and development.

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