Method for predicting or evaluating stability of mRNA-LNP liquid preparation and application thereof

Abstract

The invention discloses a method for predicting or evaluating the stability of an mRNA-LNP liquid preparation and application of the method, and belongs to the technical field of medicine quality control, and the method comprises the following steps: centrifuging the mRNA-LNP liquid preparation, balancing, putting the mRNA-LNP liquid preparation into a multifunctional protein stability analyzer, and analyzing the stability of the mRNA-LNP liquid preparation. According to the method, the change of the turbidity, the hydraulic radius and the intermolecular interaction of the mRNA-LNP liquid preparation along with the temperature is tested, the stability evaluation temperature Tstability is calculated, the comprehensive stability score Sstability is obtained according to the data obtained through the test and the Tstability, and the higher the Sstability is, 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, gene therapy and the like, is efficient, label-free and good in accuracy, and can be used for improving the stability and research and development efficiency of the preparation.

Description

Technical Field

[0001] The present invention belongs to the technical field of drug quality control, and in particular relates to a method for predicting or evaluating the stability of an mRNA-LNP liquid preparation and an application thereof. Background Art

[0002] Lipid nanoparticles (LNPs) are key delivery vectors in gene therapy and vaccine development. They can effectively encapsulate mRNA to prevent its degradation in vivo and in vitro environments, while helping it penetrate cell membranes and enter target cells, thereby significantly improving the stability and effectiveness of mRNA delivery in vivo. However, since mRNA molecules themselves are highly unstable and are easily degraded by environmental factors (such as enzymes, pH, temperature, etc.), changes in the physical properties of LNPs (such as particle size, surface charge) under different environmental conditions may further aggravate 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 current field of gene drug and vaccine development.

[0003] The prior art discloses a number of technical solutions for LNPs delivery systems (such as Chinese patent documents with publication numbers CN117088820A and CN116514672A, etc.), which focus on optimizing the composition and structure of LNPs to improve their stability in delivering mRNA, thereby improving 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, and fluorescence polarization. DSC is a classic thermal analysis method that evaluates the stability of a sample by measuring the heat absorption and heat release of the sample during temperature changes. However, DSC requires a large amount of sample, and the experimental process is time-consuming, making it difficult to quickly perform high-throughput screening. Accelerated stability experiments infer long-term stability by storing samples at higher temperatures to accelerate their degradation process. This method is time-consuming and its accuracy is affected by the assumed conditions. Fluorescence polarization can infer the stability of a sample by detecting the fluorescence changes of the sample at different temperatures, but it usually requires the sample to be labeled, which increases the complexity of the experiment, and the marker may affect the natural structure and function of the mRNA. The limitations of traditional detection methods mainly lie in the complexity of the experiments, the need for more samples, the long time it takes, and some methods require chemical modification of the samples, which may affect the actual stability of the samples.

[0004] A Chinese patent document with publication number CN107255646A discloses a method for rapid quantitative prediction of drug stability. The invention uses XRD spectra combined with chemometric methods to establish a model of the maximum single impurity and total impurity after drug crystal stabilization, and uses this model to predict drug stability. In the process of model establishment, this method still obtains model training data through accelerated stability experiments, and this method is only applicable to drugs obtained by crystallization, not to mRNA-LNP drugs.

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

[0006] In order to address the deficiencies in the prior art, the present invention provides a method for predicting or evaluating the stability of mRNA-LNP liquid preparations, which is suitable for preparation development and quality control in the fields of mRNA vaccines and gene therapy, and is used to improve the stability and R&D efficiency of the preparations.

[0007] The specific technical solutions adopted are as follows:

[0008] A method for predicting or evaluating the stability of an mRNA-LNP liquid preparation comprises: centrifuging the mRNA-LNP liquid preparation, balancing it, and then placing it in a multifunctional protein stability analyzer to test the turbidity, hydrodynamic radius and molecular interaction of the mRNA-LNP liquid preparation as a function of temperature, and calculating 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 the value, the better the stability of the mRNA-LNP liquid formulation.

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

[0010] Optionally, the preparation method of the mRNA-LNP liquid preparation includes: 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.

[0011] Furthermore, microfluidic technology is used to mix the aqueous phase containing mRNA and the organic phase containing the composite lipid material; the liquid medium includes a buffer and may also contain auxiliary agents such as preservatives.

[0012] Preferably, the centrifugal speed is 10,000-15,000 rpm, the centrifugal time is 15-30 minutes, and the centrifugal temperature is 3.5-4.5° C. Centrifugation removes large particle impurities or aggregates in the mRNA-LNP liquid preparation to ensure sample purity, thereby improving the accuracy of subsequent analysis.

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

[0014] Furthermore, 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.

[0015] Specifically, the stability evaluation temperature T stability The calculation method is:

[0016]

[0017] Among them, T turbidity , T rH , T Scattering Respectively represent the temperature T when turbidity, hydrodynamic radius, and intermolecular interaction parameters change by 10% with the test temperature during the test parameter If a parameter changes by no more than 10% within the test temperature range, then T parameter At the highest test temperature T max count.

[0018] Preferably, T max is 98°C.

[0019] Specifically, the comprehensive stability score S stability The calculation method is:

[0020]

[0021] Among them, Δ Turbidity Indicates the change of turbidity with temperature, Δ rH represents the change of hydraulic radius with temperature, Δ Scattering It indicates the change of intermolecular interaction with temperature.

[0022] The stability performance of the mRNA-LNP liquid preparation during long-term storage was verified by an accelerated stability experiment to determine the prediction or evaluation accuracy of the method of the present invention. Specifically, the accelerated stability experiment process is: the mRNA-LNP liquid preparation is stored in a 40°C bio-stabilization box for 6 weeks and 12 weeks. After 6 weeks and 12 weeks, the changes in its particle size, polydispersity index (PDI), Zeta potential and encapsulation efficiency are measured to evaluate its long-term stability. The results show that the method of the present invention has good accuracy, which is consistent with the results of the accelerated stability experiment and greatly shortens the detection cycle.

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

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] (1) The present invention uses a variety of detection modules of a multifunctional protein stability analyzer to provide an efficient, label-free and accurate method for predicting or evaluating the stability of mRNA-LNP liquid preparations. It can perform label-free and non-destructive detection of mRNA-LNP liquid preparations under different environmental conditions (such as temperature, pH, preservatives), while avoiding the potential impact of chemical modification on sample stability in traditional methods. The comprehensive stability score S provided by the present invention is stability The calculation formula provides a comprehensive and objective stability evaluation index by quantifying the changes in various test parameters, making the evaluation results more real and reliable.

[0026] (2) The present invention uses a multi-parameter combined detection of mRNA-LNP liquid preparations through a multifunctional protein stability analyzer to capture subtle changes in lipid nanoparticles loaded with mRNA, thereby improving the accuracy and reliability of the prediction results.

[0027] (3) Traditional stability assessment methods usually require a long storage period to observe changes in the preparation. However, the present invention can predict or evaluate the long-term stability of mRNA-LNP liquid preparations in a shorter time by real-time analysis of key parameters and quantitative calculation of indicators, thereby improving R&D efficiency and greatly shortening the detection cycle.

[0028] (4) The method of the present invention performs detection without destroying the sample, thereby preserving the integrity of the sample. It is particularly suitable for the development of high-cost mRNA-LNP liquid preparations and helps to reduce research and development costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1This is a curve diagram of parameter changes of mRNA-LNP liquid preparations with different prescriptions (Groups F, G, and H) in Example 1 during the test process.

[0030] Figure 2 This is a curve diagram of parameter changes of mRNA-LNP liquid preparations with different prescriptions (Groups A, I, and J) in Example 2 during the test process.

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

[0032] Figure 4 Statistical diagram of the change in particle size dispersion coefficient of mRNA-LNP nanoparticles in groups F, G, and H after storage at 40°C for 6 and 12 weeks in Example 3 (mean ± SD, n = 3)

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

[0034] Figure 6 This is a statistical graph of the Zata potential changes of mRNA-LNP nanoparticles in groups F, G, and H stored at 40° C. for 6 weeks and 12 weeks in Example 3 (mean ± SD, n = 3).

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

[0036] Figure 8 This is a statistical diagram of the change in particle size dispersion coefficient of mRNA-LNP nanoparticles in groups A, I, and J after storage at 40° C. for 6 weeks and 12 weeks in Example 4 (mean ± SD, n = 3).

[0037] Fig. 9 This is a statistical diagram of the changes in the encapsulation efficiency of mRNA-LNP nanoparticles in groups A, I, and J after storage at 40° C. for 6 weeks and 12 weeks in Example 4 (mean ± SD, n = 3).

[0038] Fig.10 This is a statistical graph of the Zata potential changes of mRNA-LNP nanoparticles in groups A, I, and J stored at 40° C. for 6 weeks and 12 weeks in Example 4 (mean ± SD, n = 3). DETAILED DESCRIPTION

[0039] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the following is a detailed description through specific embodiments. In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below. The technical features in each embodiment of the present invention can be combined accordingly without conflicting with each other.

[0040] The operating methods in the following examples without specifying specific conditions are usually carried out under conventional conditions or according to the conditions recommended by the manufacturer. The contents not described in detail in this specification belong to the prior art known to professionals in the field. The experimental materials used in the following examples, unless otherwise specified, can be purchased from conventional biochemical reagent companies.

[0041] First, prepare the mRNA-LNP liquid preparation:

[0042] (1) Preparation of mRNA aqueous phase:

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

[0044] Preparation: Dilute the mRNA solution to 0.17 mg / mL using 0.1 M sodium citrate, pH 4.0 solution.

[0045] (2) Preparation of organic phase:

[0046] The composition of the organic phase included SM102 cationic lipid, cholesterol, DSPC (1,2-eicosyl-sn-glycero-3-phosphocholine) and DMG-PEG 2000 (dimethylglycerol polyethylene glycol 2000), with molar percentages of 50 / 38.5 / 10 / 1.5, respectively, and a total lipid concentration of 18.5 mM. Anhydrous ethanol was used as the solvent supplement.

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

[0048] The organic phase and the mRNA aqueous phase were mixed by injection using a microfluidic device 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; the solution was mixed with different buffers and different types of preservatives to prepare mRNA-LNP liquid preparations with different prescriptions. The specific prescriptions are shown in the following table:

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

[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 16mM m-cresol J 12％ 10 mM Tris-HCl buffer, pH 7.4 0.9% Benzyl alcohol

[0051] Example 1

[0052] The mRNA-LNP liquid preparation samples (Groups F, G, and H) of different prescriptions prepared in the above steps were added to the ep tube, and the samples were centrifuged at 15,000 rpm at 4±0.5°C using a high-speed refrigerated centrifuge for 15 minutes. After centrifugation, the samples were balanced at 25°C for 30 minutes. Each sample (N=3) was loaded using a Nano DSF dedicated capillary from Noptan, so that the sample filled the capillary, and the capillary was placed on the back reflection sample loading station of the Nano Temper Panta multifunctional protein stability analyzer. After the sample was placed in the chamber, the detection parameters were set. The concentration, buffer system, and dynamic viscosity of each sample were entered into the Prometheus&Control software. The instrument start temperature was set to 25°C, the heating rate to 1°C / min, and the end temperature (T max ) is 98°C, and the instrument will record the aggregation and denaturation of mRNA-LNPs at each temperature change; test the changes in turbidity, hydrodynamic radius and intermolecular interaction of mRNA-LNP liquid preparations with temperature, and calculate the stability evaluation temperature T stability and comprehensive stability score S stability , the results are shown in Table 2;

[0053] Table 2 Data related to stability test of mRNA-LNP liquid preparation

[0054]

[0055] In this example, the stability of mRNA-LNP liquid preparations under different pH conditions was evaluated. The results showed that when the temperature was raised to above 90°C, the molecular interactions and turbidity of each group of mRNA-LNP liquid preparations 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 its comprehensive stability score (S stability ) value is the smallest. All the above results show that its stability under high temperature conditions is poor ( Figure 1 ).

[0056] Example 2

[0057] The mRNA-LNP liquid preparation samples (Groups A, I, and J) of different prescriptions prepared in the above steps were added to the ep tube, and the samples were centrifuged at 15,000 rpm at 4±0.5°C using a high-speed refrigerated centrifuge for 30 minutes. After centrifugation, the samples were balanced at 25°C for 30 minutes. Each sample (N=3) was loaded using a Nano DSF dedicated capillary from Noptan, so that the sample filled the capillary, and the capillary was placed on the back reflection sample loading station of the Nano Temper Panta multifunctional protein stability analyzer. After the sample was placed in the chamber, the detection parameters were set. The concentration, buffer system, and dynamic viscosity of each sample were entered into the Prometheus&Control software. The instrument start temperature was set to 25°C, the heating rate to 1°C / min, and the end temperature (T max )98℃, the instrument will record the aggregation and denaturation of mRNA-LNP under temperature changes. Test the turbidity, hydrodynamic radius and molecular interaction of mRNA-LNP liquid preparations with temperature changes, and calculate the stability evaluation temperature T stability and comprehensive stability score S stability , the results are shown in Table 3;

[0058] Table 3 Data related to stability test of mRNA-LNP liquid preparation

[0059]

[0060] The results showed that when the temperature increased to 60-90°C, the molecular interactions and turbidity of each group of mRNA-LNP nanoparticles changed significantly. The turbidity of group J increased rapidly around 60°C and the turbidity of group S stability The smallest value indicates that group J has poor stability. However, the molecular interactions and hydrodynamic radius changes of group A are relatively small and S stability The 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, mRNA-LNP liquid preparations (Groups F, G, and H) with different prescriptions were placed in a 40°C biological stability chamber for accelerated stability tests (6 weeks and 12 weeks), and were taken out for testing within 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 and 200 nanometers, which is conducive to enhancing the stability of LNPs, ensuring their uniform dispersion in the physiological environment, and reducing the possibility of sedimentation or aggregation. DLS technology to measure particle size has become a conventional characterization method for nanoparticles. When using a laser particle size analyzer to analyze nanoparticles, the nanoparticles scatter light from the incident laser, and the detector is used to detect the intensity of the scattered light to calculate the particle size distribution of the particles. After measuring DLS, two sets of data can be obtained, namely the average particle size of the nanoparticles and the particle size dispersion index (PDI). PDI reflects the uniformity of the particle size of LNPs and is an important indicator for particle size characterization. A PDI range of 0-1 is considered to indicate that the LNPs are more evenly distributed.

[0064] The surface adsorption characteristics of LNPs, namely Zeta potential, is another important parameter affecting their stability. The magnitude of Zeta potential directly affects the adsorption characteristics between nanoparticles, thereby affecting their dispersion and stability in solution.

[0065] Encapsulation efficiency reflects the degree and efficiency of LNPs encapsulating active ingredients (such as mRNA). A high encapsulation efficiency means that the active ingredients are more effectively encapsulated inside LNPs, free from enzymatic degradation and other external factors in the body, thereby improving the stability of the active ingredients in the body.

[0066] Particle size potentiometric detection: The mRNA-LNP liquid formulation was diluted to 0.8-1.6 ng / μL total mRNA in phosphate buffered saline (PBS) at pH 7.4 and transferred to a polystyrene cuvette. Particle size and polydispersity were measured by DLS (Malvern Nano ZS Zetasizer) using a refractive index (RI) of 1.590, an absorbance of 0.010 in PBS at 25°C, a viscosity of 0.9073 (cP), and an RI of 1.332. Measurements were performed using a run duration of 10 seconds, 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 is reported as a z-average. The same system was also used for potentiometric detection. Figure 3 , Figure 4 and Figure 6 The results showed that the LNPs in groups F, G, and H had similar average particle sizes and potentials at the end of preparation (0h). After being placed in a 40°C biostability box for 12 weeks, the average particle size and particle size dispersion coefficient of each group increased, among which the average particle size and PDI of group H increased significantly, and the potential was lower. These results indicate that group H has the worst stability. This is consistent with the predicted results of Example 1.

[0067] Encapsulation efficiency: RNA encapsulation efficiency and concentration were determined by Quant-iT RiboGreen analysis (Life Technologies). Quantification of RNA in mRNA-LNP liquid formulations was performed using a standard curve generated from the corresponding RNA dilution. Standards and samples were diluted with 1xTris-EDTA (TE) buffer (pH 8.0). Sample concentrations reached 0.1 ng / μL in polystyrene cuvettes. Fluorescence was measured using a spectrofluorometer (Varian CaryEclipse) set at 500 nanometers for excitation and 525 nanometers for emission. The standard curve was calculated by linear regression analysis of the plotted fluorescence intensity and standard concentration. RNA encapsulation of LNPs samples was determined by comparing the signal of RNA binding to the fluorescent dye RiboGreen in the absence and presence of detergent (0.1% Triton X-100). Figure 5 The results showed that after being placed in a 40°C biostability chamber for 12 weeks, the encapsulation rate of group H decreased most significantly, further verifying that the stability of the liquid preparation of group H was poor.

[0068] Example 4

[0069] To verify the experimental results predicted by the method in Example 2, mRNA-LNP liquid preparations (Groups A, I, and J) with different prescriptions were placed in a 40°C biological stability chamber for accelerated stability tests (6 weeks and 12 weeks), and were taken out for testing within the specified time.

[0070] Particle size potential changes: The mRNA-LNP liquid preparation was diluted to 0.8-1.6 ng / μL total mRNA in phosphate buffered saline (PBS) at pH 7.4 and transferred to a polystyrene cuvette. The particle size and polydispersity were measured by DLS (Malvern Nano ZS Zetasizer) using 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. The measurements were performed using a run duration of 10 seconds, 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 is reported as a z-average. The same system was also used to measure the potential. Figure 7 , Figure 8 and Fig.10 The results showed that after 12 weeks of biological stability storage at 40°C, the average particle size and PDI of group J increased most significantly, and the potential was the lowest and close to zero, indicating that its stability was poor during long-term storage, while the average particle size changes of groups A and I were relatively small, showing good stability. This is consistent with the Nano Temper prediction results.

[0071] Encapsulation efficiency: RNA encapsulation efficiency and concentration were determined by Quant-iT Ribo Green analysis (Life Technologies). Quantification of RNA in mRNA-LNP liquid preparations was performed using a standard curve generated from the corresponding RNA dilution. Standards and samples were diluted with 1x Tris-EDTA (TE) buffer (pH 8.0). Sample concentrations reached 0.1 ng / μL in polystyrene cuvettes. Fluorescence was measured using a spectrofluorometer (Varian Cary Eclipse) set at 500 nanometers for excitation and 525 nanometers for emission. The standard curve was calculated by linear regression analysis of the plotted fluorescence intensity and standard concentration. RNA encapsulation of LNPs samples was determined by comparing the signal of RNA binding to the fluorescent dye Ribo Green in the absence and presence of detergent (0.1% Triton X-100). Fig. 9 The experimental results showed that the encapsulation rate of group J decreased most significantly after 12 weeks of storage, indicating that its stability was poor during long-term storage, while the encapsulation rates of groups A and I were relatively stable, showing good storage stability. This further confirmed the accuracy of Nano Temper's prediction results.

[0072] The embodiments described above provide a detailed description of the technical solutions of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, supplements or similar substitutions made within the scope of the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting or evaluating the stability of a 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 molecular 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 the value, the better the stability of the mRNA-LNP liquid formulation.

2. The method for predicting or evaluating the stability of a mRNA-LNP liquid formulation according to claim 1, characterized in that: The mRNA-LNP liquid preparation contains lipid nanoparticles loaded with mRNA.

3. The method for predicting or evaluating the stability of a mRNA-LNP liquid formulation according to claim 2, characterized in that: 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 a mRNA-LNP liquid formulation according to claim 1, characterized in that: 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 mRNA-LNP liquid preparation according to claim 1, characterized in that: Equilibrate at 20-25°C for 20-30 minutes.

6. The method for predicting or evaluating the stability of a mRNA-LNP liquid formulation according to claim 1, characterized in that: 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. The method for predicting or evaluating the stability of a mRNA-LNP liquid formulation according to claim 1, characterized in that: Stability evaluation temperature T stability The calculation method is: Among them, T turbidity , T rH , T Scattering Respectively represent the temperature T when turbidity, hydrodynamic radius, and intermolecular interaction parameters change by 10% with the test temperature during the test parameter If a parameter changes by no more than 10% within the test temperature range, then T parameter At the highest test temperature T max count.

8. The method for predicting or evaluating the stability of a mRNA-LNP liquid formulation according to claim 7, characterized in that: Comprehensive stability score S stability The calculation method is: Among them, Δ Turbidity Indicates the change of turbidity with temperature, Δ rH represents the change of hydraulic radius with temperature, Δ Scattering It indicates the change of intermolecular interaction with temperature.

9. Application of the method for predicting or evaluating the stability of an mRNA-LNP liquid preparation according to any one of claims 1 to 8 in mRNA-LNP vaccine quality control or mRNA-LNP vaccine research and development.

Images