Method for predicting or evaluating stability of mrna-LNP liquid preparation, and use thereof

Abstract

A method for predicting or evaluating the stability of an mRNA-LNP liquid preparation, and the use thereof. The method comprises the steps of: centrifuging an mRNA-LNP liquid preparation, then equilibrating same, then placing the preparation in a multifunctional protein stability analyzer to measure changes in the turbidity, hydraulic radius and intermolecular interactions of the mRNA-LNP liquid preparation with temperature, and calculating a stability evaluation temperature Tstability to obtain a comprehensive stability score Sstability on the basis of the measured data and Tstability, wherein a higher Sstability indicates that the stability of the mRNA-LNP liquid preparation is better.

Description

A method for predicting or evaluating the stability of mRNA-LNP liquid formulations and its application Technical Field

[0001] This invention belongs to the field of drug quality control technology, specifically relating to a method for predicting or evaluating the stability of mRNA-LNP liquid formulations and its application. Background Technology

[0002] Lipid nanoparticles (LNPs) are key delivery vectors in gene therapy and vaccine development, effectively encapsulating mRNA to prevent degradation in both in vivo and in vitro environments while facilitating its penetration through cell membranes into target cells, thus significantly improving the stability and efficacy of mRNA delivery in vivo. However, due to the inherent instability of mRNA molecules, they are highly susceptible to degradation by environmental factors such as enzymes, pH, and temperature. Variations in the physical properties of LNPs (such as particle size and surface charge) under different environmental conditions may further exacerbate this problem, thereby affecting the stability and delivery efficiency of mRNA-LNPs. Therefore, effectively assessing and predicting the stability of mRNA-LNPs has become a significant challenge in the current field of gene therapy and vaccine development.

[0003] Several technical solutions for LNP delivery systems have been disclosed in the prior art (such as Chinese patent documents with publication numbers CN117088820A and CN116514672A). These patents focus on improving the stability of LNPs in mRNA delivery by optimizing their composition and structure, thereby enhancing bioavailability. However, in terms of stability characterization, existing technologies still mainly rely on traditional methods, such as differential scanning calorimetry (DSC), accelerated stability assays, and fluorescence polarization assays. DSC is a classic thermal analysis method that assesses stability by measuring the heat absorption and release of a sample during temperature changes. However, DSC requires a large sample volume and is time-consuming, making it difficult to perform rapid high-throughput screening. Accelerated stability assays 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 assays infer stability by detecting changes in fluorescence of samples at different temperatures, but usually require sample labeling, increasing experimental complexity. Furthermore, the label may affect the native structure and function of the mRNA. The limitations of traditional detection methods are mainly that they are complex, require a large number of samples, are time-consuming, and some methods require chemical modification of the samples, which may affect the true stability of the samples.

[0004] Chinese patent document CN107255646A discloses a method for rapid quantitative prediction of drug stability. This invention establishes a model for the maximum single impurity and total impurities after drug crystal stabilization using XRD patterns combined with chemometrics, and uses this model to predict drug stability. However, this method still relies on accelerated stability experiments to obtain model training data during model building, and it is only applicable to drugs obtained through crystallization, not to mRNA-LNP drugs.

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

[0006] To address the shortcomings of existing technologies, this invention provides a method for predicting or evaluating the stability of mRNA-LNP liquid formulations. This method is applicable to formulation development and quality control in fields such as mRNA vaccines and gene therapy, thereby improving formulation stability and R&D efficiency.

[0007] The specific technical solution adopted is as follows:

[0008] A method for predicting or assessing the stability of mRNA-LNP liquid formulations includes: centrifuging the mRNA-LNP liquid formulation, equilibrating it, and then placing it in a multifunctional protein stability analyzer to test the changes in turbidity, hydrodynamic radius, and intermolecular interactions of the mRNA-LNP liquid formulation with temperature, and calculating the stability assessment temperature T. stability Based on the data obtained from the test and T stability The overall stability score S is obtained. stability S stability The higher the value, the better the stability of the mRNA-LNP liquid formulation.

[0009] Specifically, the mRNA-LNP liquid formulation contains lipid nanoparticles loaded with mRNA. The mRNA-LNP liquid formulation can be prepared in-house or commercially available products can be used directly.

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

[0011] Furthermore, microfluidic technology is used to mix an aqueous phase containing mRNA with an organic phase containing complex lipid materials; the liquid medium includes buffer solutions and may also contain preservatives and other additives.

[0012] Preferably, the centrifugation speed is 10,000-15,000 rpm, the centrifugation time is 15-30 minutes, and the centrifugation temperature is 3.5-4.5℃. Centrifugation removes large particulate impurities or aggregates from the mRNA-LNP liquid preparation, ensuring sample purity and thus improving the accuracy of subsequent analyses.

[0013] Preferably, the equilibration process is carried out at 20-25℃ for 20-30 minutes. This equilibration process ensures that the mRNA-LNP liquid formulation sample is at the same temperature as the environment, achieving thermal equilibrium and avoiding 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 dynamic light scattering technology, and intermolecular interactions are detected based on static light scattering technology.

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

[0016] Among them, T turbidity T rH T Scattering These represent the temperatures T corresponding to a 10% change in turbidity, hydrodynamic radius, and intermolecular interaction parameters during the test, respectively. parameter If, within the test temperature range, a certain parameter changes by no more than 10%, then T parameter At the highest test temperature T max count.

[0017] Preferred, T max It is 98℃.

[0018] Specifically, the overall stability score S stability The calculation method is as follows:

[0019] Where, Δ Turbidity Δ represents the change in turbidity with temperature. rH Δ represents the change in hydraulic radius with temperature. Scattering This indicates the change in intermolecular interactions with temperature.

[0020] Accelerated stability experiments were conducted to verify the stability of the mRNA-LNP liquid formulation during long-term storage, thereby assessing the accuracy of the prediction or evaluation method of this invention. Specifically, the accelerated stability experiment involved storing the mRNA-LNP liquid formulation in a 40°C biostability chamber for 6 and 12 weeks. After 6 and 12 weeks, changes in particle size, polydispersity index (PDI), zeta potential, and encapsulation efficiency were measured to evaluate its long-term stability. The results demonstrated that the method of this invention is accurate and consistent with the results of the accelerated stability experiment, significantly shortening the detection cycle.

[0021] This invention also provides the application of the method for predicting or evaluating the stability of mRNA-LNP liquid formulations in the quality control of mRNA-LNP vaccines or in the development of mRNA-LNP vaccines.

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0023] (1) This invention utilizes multiple 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 formulations. It enables label-free and non-destructive detection of mRNA-LNP liquid formulations under different environmental conditions (such as temperature, pH, and preservatives), while avoiding the potential impact of chemical modifications on sample stability in traditional methods. The comprehensive stability score S provided by this invention... stability The calculation formula, by quantifying the changes in various detection parameters, provides a comprehensive and objective stability evaluation index, making the evaluation results more realistic and reliable.

[0024] (2) This invention uses a multi-parameter joint detection of mRNA-LNP liquid formulations by a multi-functional protein stability analyzer to capture subtle changes in lipid nanoparticles loaded with mRNA, thereby improving the accuracy and reliability of the prediction results.

[0025] (3) Traditional stability assessment methods usually require a long storage period to observe changes in the formulation. However, this invention can predict or assess the long-term stability of mRNA-LNP liquid formulations in a short time by analyzing key parameters in real time and performing quantitative calculations on indicators, thereby improving R&D efficiency and greatly shortening the testing cycle.

[0026] (4) The method of the present invention can perform detection without damaging the sample and preserve the integrity of the sample. It is particularly suitable for the development of high-cost mRNA-LNP liquid formulations and helps to reduce R&D costs. Attached Figure Description

[0027] Figure 1 shows the parameter changes of different formulations (F, G, H groups) of mRNA-LNP liquid preparations in Example 1 during the testing process.

[0028] Figure 2 shows the parameter changes of different formulations (groups A, I, and J) of mRNA-LNP liquid preparations in Example 2 during the testing process.

[0029] Figure 3 shows the average particle size changes 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).

[0030] Figure 4 shows the statistical changes in the particle size distribution 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).

[0031] Figure 5 shows the encapsulation efficiency 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).

[0032] Figure 6 shows the Zata potential changes 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 7 shows the average particle size change 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).

[0034] Figure 8 shows the changes in particle size dispersion coefficient 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).

[0035] Figure 9 shows the encapsulation efficiency 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 10 shows the Zata potential 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). Detailed Implementation

[0037] To make the objectives, features, and advantages of this invention more apparent and understandable, a detailed description is provided below through specific embodiments. Many specific details are set forth in the following description to provide a thorough understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below. Technical features in various embodiments of the invention can be combined appropriately without mutual conflict.

[0038] Unless otherwise specified, the operating methods in the following examples are generally performed under conventional conditions or as recommended by the manufacturer. Contents not described in detail in this specification are prior art known to those skilled in the art. Unless otherwise specified, the experimental materials used in the examples below can be purchased from conventional biochemical reagent companies.

[0039] First, prepare the mRNA-LNP liquid formulation:

[0040] (1) Aqueous phase preparation of mRNA:

[0041] mRNA aqueous phase: an aqueous solution of mRNA sample with a final concentration of 0.17 mg / mL.

[0042] Preparation: Dilute the mRNA solution to 0.17 mg / mL using 0.1 M sodium citrate solution, pH 4.0.

[0043] (2) Organic phase preparation:

[0044] The organic phase consisted of SM102 cationic lipids, cholesterol, DSPC (1,2-eicosyl-sn-glycerol-3-phosphocholine) and DMG-PEG 2000 (dimethylglycerol-based polyethylene glycol 2000), with molar percentages of 50 / 38.5 / 10 / 1.5, and a total lipid concentration of 18.5 mM. Anhydrous ethanol was used as the solvent for replenishment.

[0045] (3) Preparation of mRNA-LNP liquid formulation

[0046] The organic phase and the aqueous phase containing mRNA were injected and mixed using a microfluidic device at a flow rate ratio of 1:3, with a total flow rate of 12 ml / min. After ultrafiltration and concentration, a solution containing mRNA-LNP nanoparticles was obtained. This solution was then mixed with different buffer solutions and different types of preservatives to prepare mRNA-LNP liquid formulations with different formulations. Specific formulations are shown in the table below.

[0047] Table 1 Composition of different mRNA-LNP liquid formulations

[0048] Example 1

[0049] The mRNA-LNP liquid formulations (groups F, G, and H) prepared in the above steps were added to ep tubes and centrifuged at 15,000 rpm for 15 minutes at 4 ± 0.5 °C. After centrifugation, the samples were equilibrated at 25 °C for 30 minutes. Each sample (N=3) was loaded into a Nano DSF capillary tube from Noptane, ensuring the capillary was full. The capillary tube was then placed on the back-reflection sample loading stage of the Nano Temper Panta multifunctional protein stability analyzer. After sample loading, the detection parameters were set. The concentration, buffer system, and dynamic viscosity of each sample were entered into the Prometheus & Control software. The instrument's initial temperature was set to 25 °C, the heating rate to 1 °C / min, and the termination temperature (T0) to 25 °C. max The instrument will record the aggregation and denaturation of mRNA-LNPs at each temperature change, with a set temperature of 98℃. It will also test the changes in turbidity, hydrodynamic radius, and intermolecular interactions of the mRNA-LNP liquid formulation with temperature, and calculate the stability assessment temperature T. stability and overall stability score S stability The results are shown in Table 2.

[0050] Table 2. Data related to the stability test of mRNA-LNP liquid formulation.

[0051] In this embodiment, the stability of mRNA-LNP liquid formulations under different pH conditions was evaluated. The results showed that when the temperature increased above 90°C, the intermolecular interactions and turbidity of each group of mRNA-LNP liquid formulations changed significantly, especially the increase in hydrodynamic radius and turbidity, indicating particle aggregation within this temperature range. Specifically, group H showed the largest increase in particle size and a significant increase in turbidity under high-temperature conditions, and its overall stability score (S) was also the lowest. stability The value is the smallest, and all the above results indicate that its stability under high temperature conditions is poor (Figure 1).

[0052] Example 2

[0053] The mRNA-LNP liquid formulations (groups A, I, and J) prepared in the above steps were added to ep tubes and centrifuged at 15,000 rpm for 30 minutes at 4 ± 0.5 °C. After centrifugation, the samples were equilibrated at 25 °C for 30 minutes. Each sample (N=3) was loaded into a Noptane Nano DSF capillary tube, ensuring the capillary was full. The capillary tube was then placed on the back-reflection sample loading stage of the Nano Temper Panta multifunctional protein stability analyzer. After sample loading, the detection parameters were set. The concentration, buffer system, and dynamic viscosity of each sample were entered into the Prometheus & Control software. The instrument's initial temperature was set to 25 °C, the heating rate to 1 °C / min, and the final temperature (T0) was set to [missing value]. max At 98℃, the instrument will record the aggregation and denaturation of mRNA-LNP under temperature changes. The instrument will also test the changes in turbidity, hydrodynamic radius, and intermolecular interactions of the mRNA-LNP liquid formulation with temperature, and calculate the stability assessment temperature T. stability and overall stability score S stability The results are shown in Table 3.

[0054] Table 3. Data related to the stability test of mRNA-LNP liquid formulation.

[0055] The results showed that when the temperature increased to 60-90℃, the intermolecular interactions and turbidity of the mRNA-LNP nanoparticles in each group changed significantly. Among them, the turbidity of group J increased rapidly near 60℃, and S... stability The smallest value indicates that group J has poor stability. Group A, on the other hand, has relatively small changes in intermolecular interactions and hydrodynamic radius, and S... stability The value is the largest, indicating good stability (Figure 2).

[0056] Example 3

[0057] To verify the experimental results predicted by the method in Example 1, mRNA-LNP liquid formulations with different formulations (groups F, G, and H) were placed in a 40°C biostability chamber for accelerated stability testing (6 weeks and 12 weeks), and were removed for testing at specified times.

[0058] The physicochemical properties of LNPs are among the important factors affecting their delivery efficiency and safety. The particle size and distribution of LNPs are crucial parameters influencing their stability. Ideally, LNP particle sizes should be controlled between 20 and 200 nanometers to enhance their stability, ensure uniform dispersion in physiological environments, and reduce the possibility of sedimentation or aggregation. Laser particle size analyzer (DLS) measurement has become a routine method for characterizing nanoparticles. When analyzing nanoparticles using a laser particle size analyzer, the nanoparticles scatter light from the incident laser. The intensity of the scattered light is detected by a detector to calculate the particle size distribution. After DLS measurement, two sets of data are obtained: the average particle size and the particle size distribution index (PDI). The PDI reflects the uniformity of LNP particle size and is an important indicator of particle size characterization. A PDI range of 0-1 is considered to indicate a relatively uniform LNP distribution.

[0059] The surface adsorption properties of LNPs, namely the zeta potential, are another important parameter affecting their stability. The magnitude of the zeta potential directly affects the adsorption interactions between nanoparticles, thereby influencing their dispersion and stability in solution.

[0060] Encapsulation efficiency reflects the degree and efficiency with which LNPs encapsulate active ingredients (such as mRNA). A high encapsulation efficiency means that the active ingredient is more effectively encapsulated within the LNP, protecting it from enzymatic degradation and other external factors in vivo, thereby improving the stability of the active ingredient in vivo.

[0061] Particle size and polydispersity 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 polystyrene cuvettes. Particle size and polydispersity were measured using a DLS (Malvin Nano ZS Zetasizer) with 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 10-second run duration, with the number of runs automatically determined. Each measurement was taken at a fixed position of 4.65 mm in the tube with automatic attenuation selection. Diameter was reported as the z-mean. The same system was also used for potential detection. Figures 3, 4, and 6 show that the LNPs in groups F, G, and H had similar average particle size and potential at the end of preparation (0 h). After being placed in a 40°C biostability chamber for 12 weeks, the average particle size and particle size distribution coefficient of each group increased. Among them, group H showed a significant increase in average particle size and PDI, and a lower potential, indicating that group H had the worst stability. This is consistent with the prediction results of Example 1.

[0062] Encapsulation efficiency: RNA encapsulation efficiency and concentration were determined using Quant-iT RiboGreen analysis (Life Technologies). RNA quantification in the mRNA-LNP liquid formulation was performed using standard curves generated from corresponding RNA dilutions. Standards and samples were diluted with 1x Tris-EDTA(TE) buffer (pH 8.0). Sample concentrations were brought to 0.1 ng / μL in polystyrene cuvettes. Fluorescence was measured using a fluorescence spectrophotometer (Varian Cary Eclipse) set to excitation at 500 nm and emission at 525 nm. Standard curves were calculated using linear regression analysis of fluorescence intensity against standard concentrations. RNA encapsulation in LNPs samples was determined by comparing the signal of the fluorescent dye RiboGreen binding with and without detergent (0.1% Triton X-100). Figure 5 shows that the encapsulation efficiency decreased most significantly in group H after 12 weeks in a 40°C biostability chamber, further validating the poor stability of the group H liquid formulation.

[0063] Example 4

[0064] To verify the experimental results predicted by the method in Example 2, mRNA-LNP liquid formulations of different formulations (groups A, I, and J) were placed in a 40°C biostability chamber for accelerated stability testing (6 weeks and 12 weeks), and were removed for testing at specified times.

[0065] Particle size and potential variation: 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 polystyrene cuvettes. Particle size and polydispersity were measured using a DLS (Malvin Nano ZS Zetasizer) with 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 10-second run duration, with the number of runs automatically determined. Each measurement was taken at a fixed position of 4.65 mm in the tube with automatic attenuation selection. Diameter was reported as the z-mean. The same system was also used to measure potential. Figures 7, 8, and 10 show that group J exhibited the most significant increases in average particle size and PDI after 12 weeks of biostability storage at 40℃, while its potential was the lowest, approaching zero, indicating poor stability during long-term storage. In contrast, groups A and I showed relatively smaller changes in average particle size, demonstrating better stability. This is consistent with the predictions made by Nano Temper.

[0066] Encapsulation efficiency: RNA encapsulation efficiency and concentration were determined using Quant-iT Ribo Green analysis (Life Technologies). RNA quantification in the mRNA-LNP liquid formulation was performed using standard curves generated from the corresponding RNA dilutions. Standards and samples were diluted with 1x Tris-EDTA(TE) buffer (pH 8.0). Sample concentrations were brought to 0.1 ng / μL in polystyrene cuvettes. Fluorescence was measured using a fluorescence spectrophotometer (Varian Cary Eclipse) set to excitation at 500 nm and emission at 525 nm. Standard curves were calculated using linear regression analysis of fluorescence intensity against standard concentrations. RNA encapsulation in LNPs samples was determined by comparing the signal of the fluorescent dye Ribo Green in the absence and presence of detergent (0.1% Triton X-100). The results in Figure 9 show that group J exhibited the most significant decrease in encapsulation efficiency after 12 weeks of storage, indicating poor stability during long-term storage, while groups A and I showed relatively stable encapsulation efficiency, demonstrating better storage stability. This further confirms the accuracy of the Nano Temper prediction results.

[0067] The embodiments described above provide a detailed explanation of the technical solutions of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, additions, or similar substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predicting or evaluating the stability of mRNA-LNP liquid formulations, characterized in that, include: After centrifugation and equilibration of the mRNA-LNP liquid formulation, it was placed in a multifunctional protein stability analyzer to test the changes in turbidity, hydrodynamic radius, and intermolecular interactions of the mRNA-LNP liquid formulation with temperature, and the stability assessment temperature T was calculated. stability Based on the data obtained from the test and T stability The overall stability score S is obtained. 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 mRNA-LNP liquid formulations according to claim 1, characterized in that, The mRNA-LNP liquid formulation contains lipid nanoparticles loaded with mRNA.

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

4. The method for predicting or evaluating the stability of mRNA-LNP liquid formulations according to claim 1, characterized in that, The centrifugation speed is 10,000-15,000 rpm, the centrifugation time is 15-30 minutes, and the centrifugation temperature is 3.5-4.5℃.

5. The method for predicting or evaluating the stability of mRNA-LNP liquid formulations according to claim 1, characterized in that, Equilibrate at 20-25℃ for 20-30 minutes.

6. The method for predicting or evaluating the stability of mRNA-LNP liquid formulations 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 dynamic light scattering technology, and intermolecular interactions are detected based on static light scattering technology.

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

8. The method for predicting or evaluating the stability of mRNA-LNP liquid formulations according to claim 7, characterized in that, Overall stability score S stability The calculation method is as follows: Where, Δ Turbidity Δ represents the change in turbidity with temperature. rH Δ represents the change in hydraulic radius with temperature. Scattering This indicates the change in intermolecular interactions with temperature.

9. The application of the method for predicting or evaluating the stability of mRNA-LNP liquid formulations according to any one of claims 1-8 in the quality control of mRNA-LNP vaccines or the development of mRNA-LNP vaccines.

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