A method for preparing allantoin nanoemulsion based on parameter optimization

Abstract

The present application relates to the technical field of allantoin nanoemulsion preparation, and specifically to a method for preparing allantoin nanoemulsion based on parameter optimization, the method comprising: collecting the real-time homogenization pressure, homogenization temperature and average particle size of the allantoin nanoemulsion during the pressurized homogenization process; determining the optimal homogenization parameter combination by analyzing the real-time growth rate of the homogenization pressure and the homogenization temperature and the characteristics of the change relationship between the homogenization pressure and the average particle size; controlling the high-pressure homogenizer in the preparation process of the allantoin nanoemulsion according to the optimal homogenization parameter combination to prepare the allantoin nanoemulsion. The present application aims to improve the preparation efficiency and ensure the quality and stability of the allantoin nanoemulsion.

Description

Technical Field

[0001] The present application relates to the technical field of allantoin nanoemulsion preparation, and in particular to a method for preparing allantoin nanoemulsion based on parameter optimization. Background Art

[0002] Allantoin nanoemulsion is a skin care product or pharmaceutical preparation that combines allantoin with nanotechnology. Allantoin is a natural compound with moisturizing, anti-inflammatory and cell regeneration properties, and is often used in skin care products and drugs for treating skin diseases. The preparation of allantoin nanoemulsion involves multiple steps, including emulsification, homogenization of nanoparticles, stabilization and other processes. Some parameters in the overpressure homogenization process affect the size of the emulsion particles, so it is necessary to determine the optimal parameters to ensure the quality and stability of allantoin nanoemulsion.

[0003] During the high-pressure homogenization process of preparing allantoin nanoemulsion, the particle size of the emulsion decreases with the increase of the homogenization pressure, but the particle size decreases to a certain extent and tends to converge. At this time, continuing to increase the homogenization pressure has no obvious effect, resulting in low preparation efficiency. At the same time, when determining this critical homogenization pressure during the preparation process, it is generally determined by monitoring the change trend of the particle size. Since the convergence process of the particle size is not obvious, there is a certain subjectivity, and the optimal homogenization pressure cannot be accurately and scientifically obtained, and the quality and stability of the prepared allantoin nanoemulsion cannot be guaranteed. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a method for preparing allantoin nanoemulsion based on parameter optimization to solve the existing problems.

[0005] The present invention discloses a method for preparing allantoin nanoemulsion based on parameter optimization, which adopts the following technical scheme:

[0006] An embodiment of the present application provides a method for preparing an allantoin nanoemulsion based on parameter optimization, the method comprising the following steps:

[0007] Step 1: collecting the real-time homogenization pressure, homogenization temperature and average particle size of the allantoin nanoemulsion during the pressurized homogenization process;

[0008] Step 2: Determine the optimal homogenization parameter combination by analyzing the real-time growth rate of homogenization pressure and homogenization temperature and the characteristics of their changing relationship with the average particle size; specifically:

[0009] A1, between the adjacent collection moments of any collection moment, respectively obtain the growth rates of the homogenization pressure and the homogenization temperature; combine the growth rates of the homogenization pressure and the homogenization temperature to determine the influence coefficient of the pressure and temperature on the particle size at any collection moment;

[0010] A2, based on the difference between the influence coefficients of pressure and temperature on particle size at adjacent collection moments, the difference between the average particle sizes of samples at adjacent collection moments, and the difference between the average particle size of the sample at any collection moment and the preset convergent particle size value, determine the difference variation coefficient at any collection moment;

[0011] A3, based on the difference mean between the difference variation coefficients of all adjacent collection moments before any collection moment, and the difference variation between the difference variation coefficients of any collection moment and its adjacent collection moments, determine the possibility that the homogenization pressure at any collection moment is the optimal homogenization pressure, and determine the optimal homogenization parameter combination;

[0012] Step 3: Control the high-pressure homogenizer in the preparation process of the allantoin nanoemulsion according to the optimal homogenization parameter combination to prepare the allantoin nanoemulsion.

[0013] Preferably, between adjacent collection moments to any collection moment, the adjacent collection moment is further determined as the previous adjacent collection moment of the any collection moment.

[0014] Preferably, the process of obtaining the growth rate is:

[0015] The homogenization pressure and homogenization temperature are recorded as homogenization parameters;

[0016] For any homogeneous parameter, calculate the difference between the value at any collection time and its adjacent collection time; obtain the preset sampling interval between adjacent collection times;

[0017] The ratio of the difference to the preset sampling interval is used as the growth rate of any homogeneous parameter at any sampling moment.

[0018] Preferably, the influence coefficient of pressure and temperature on the particle size is determined by the product of the growth rate of the mean pressure and the homogenization temperature at any collection time.

[0019] Preferably, the method for determining the difference variation coefficient is:

[0020] Calculate the difference between the influence coefficients and the average particle sizes;

[0021] The product of the difference result and the difference value is used as the difference variation coefficient at any collection time.

[0022] Preferably, the difference between the influence coefficients is further determined as a ratio of the influence coefficients of pressure and temperature on the particle size at a later collection moment and a previous collection moment in adjacent collection moments.

[0023] Preferably, the difference between the average particle sizes is further determined as a ratio between the average particle sizes of samples at a later collection moment and a previous collection moment in adjacent collection moments.

[0024] Preferably, the possibility that the homogenization pressure at any acquisition moment is the optimal homogenization pressure is determined by a normalized value of a ratio result of the difference mean and the difference change.

[0025] Preferably, in the difference change between the difference change coefficients of any acquisition moment and its adjacent acquisition moment, the adjacent acquisition moment is the next adjacent acquisition moment after any acquisition moment.

[0026] Preferably, the method for determining the optimal homogenization parameter combination is:

[0027] In the process of pressurized homogenization, the homogenization temperature and homogenization pressure at the collection moment corresponding to the preset possibility threshold value are used to form the optimal homogenization parameter combination.

[0028] This application has at least the following beneficial effects:

[0029] The present application calculates the influence coefficient of pressure and temperature on particle size by analyzing the growth rate of the real-time increasing homogenization pressure and the homogenization temperature, which is used to measure the degree of influence of the two on the particle size; then, the difference variation coefficient is determined based on the influence coefficient of pressure and temperature on particle size and the real-time average particle size of the sample, which is used to analyze the relationship between the change trend of the average particle size and the change characteristics of the influence coefficient in real time to judge the convergence of the particle size; finally, the optimal homogenization parameter combination is selected based on the change characteristics of the difference variation coefficient, which can improve the accuracy of selecting the optimal homogenization parameters; thereby, the high-pressure homogenizer can maintain a lower pressure load while achieving particle size convergence, improve production efficiency, and prepare a stable and efficient nanoemulsion product. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 A flow chart of a method for preparing allantoin nanoemulsion based on parameter optimization provided in this application;

[0032] Figure 2 A flow chart of the preparation process of the allantoin nanoemulsion provided in one embodiment of the present application;

[0033] Figure 3 A specific process flow chart for determining the optimal homogenization parameter combination provided for one embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the method for preparing an allantoin nanoemulsion based on parameter optimization proposed in the present application, its specific implementation, structure, characteristics and effects thereof, as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0035] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0036] The specific scheme of the method for preparing allantoin nanoemulsion based on parameter optimization provided by the present application is described in detail below in conjunction with the accompanying drawings.

[0037] An embodiment of the present application provides a method for preparing an allantoin nanoemulsion based on parameter optimization.

[0038] Specifically, the following method for preparing allantoin nanoemulsion based on parameter optimization is provided, please refer to Figure 1 , the method comprises the following steps:

[0039] Step 1: Collect the real-time homogenization pressure, homogenization temperature and average particle size of the allantoin nanoemulsion during the pressurized homogenization process.

[0040] At present, the preparation of allantoin nanoemulsion is generally divided into: 1. Preparation of oil phase and water phase (including allantoin); 2. Mixing and stirring; 3. High-pressure homogenization; 4. Cooling and stabilization; 5. Filtration. The preparation process flow chart of allantoin nanoemulsion is as follows Figure 2 shown.

[0041] The particle size of allantoin nanoemulsion during preparation determines the quality and bioavailability of the product. The smaller and more uniform the particle size, the better the medicinal effect of the emulsion. During the high-pressure homogenization process during preparation, the homogenization pressure and homogenization temperature are two important parameters that have a significant impact on the final particle size and quality.

[0042] Generally, a high-pressure homogenizer directly pressurizes the sample to a preset high-pressure value through a high-pressure pump by gradually increasing the pressure, and maintains this high-pressure level to ensure that the sample is subjected to continuous high pressure when passing through the homogenization valve. These physical effects effectively break up and refine the particles or droplets in the sample. Since the particle size tends to converge with the increase of the pressure value, determining the optimal pressure value is of great significance for optimizing the particle size and the load of the high-pressure homogenizer.

[0043] Therefore, the present application uses relevant sensors to monitor the real-time homogenization pressure and homogenization temperature in the high-pressure homogenizer as well as the size data of the particle size to determine the optimal homogenization pressure value. The sampling interval in this embodiment is set to 0.2 seconds, which can be set by the implementer.

[0044] Step 2: Determine the optimal homogenization parameter combination by analyzing the real-time growth rate of homogenization pressure and homogenization temperature and the changing relationship between them and the average particle size;

[0045] Since the increase in homogenization pressure will increase the homogenization temperature, and the size of both will affect the size of the emulsion particles, in order to obtain the optimal homogenization pressure corresponding to the particle size convergence, the present application calculates the corresponding growth rate by analyzing the growth characteristics of the real-time homogenization pressure and the homogenization temperature, and then determines the corresponding particle size influence coefficient by comprehensively considering the growth rates of the homogenization pressure and the homogenization temperature. Then, the difference between the real-time particle size influence coefficient and the particle size change trend is analyzed to calculate the difference variation coefficient, thereby determining the optimal homogenization parameter combination based on the change relationship of the real-time difference variation coefficient.

[0046] Based on this, the specific process flow chart for determining the optimal homogenization parameter combination in this embodiment is shown in the attached figure. Figure 3 As shown, specifically:

[0047] A1, between the adjacent collection moments of any collection moment, respectively obtain the growth rates of the homogenization pressure and the homogenization temperature; combine the growth rates of the homogenization pressure and the homogenization temperature to determine the influence coefficient of the pressure and temperature on the particle size at any collection moment;

[0048] During the gradual pressurization process of the high-pressure homogenizer, the sample will experience severe shearing, collision and cavitation, which will generate a lot of heat, causing the sample temperature to rise, thereby increasing the homogenization temperature. The appropriate high temperature can reduce the viscosity of the material, making the high-pressure shearing and crushing more effective, thereby obtaining a finer and more uniform particle size.

[0049] Therefore, in order to obtain the influence of homogenization pressure and homogenization temperature on the particle size, this step first calculates the corresponding growth rate based on the homogenization pressure and homogenization temperature at adjacent moments.

[0050] When the high-pressure homogenizer pressurizes the sample, the homogenization temperature will also fluctuate with the increase of the homogenization pressure. Since both have an impact on the particle size, in order to measure the degree of this impact, the growth rate of the homogenization pressure and the homogenization temperature are obtained at any sampling time and its adjacent sampling time during the pressurized homogenization process.

[0051] Specifically, between adjacent collection moments to any collection moment, the growth rates of the homogenization pressure and the homogenization temperature are respectively obtained.

[0052] Preferably, in this embodiment, the adjacent collection time is further determined as the previous adjacent collection time of any collection time. In other embodiments, the next adjacent collection time of any collection time can also be selected as the adjacent collection time of any collection time.

[0053] Preferably, in this embodiment, the homogenization pressure and the homogenization temperature are both recorded as homogenization parameters; for any homogenization parameter, the difference between the values ​​at any collection moment and its adjacent collection moment is calculated; the preset sampling interval between adjacent collection moments is obtained; and the ratio of the difference to the preset sampling interval is used as the growth rate of any homogenization parameter at any collection moment.

[0054] As an implementation method, taking the acquisition time i as an example, the growth rate V of any homogenization parameter at the acquisition time i during the pressurized homogenization process is i It can be expressed as: Where V i is the growth rate of any homogeneous parameter at the acquisition time i, m i is the value of any homogeneous parameter at the acquisition time i, m i-1 is the value of any homogeneous parameter at the sampling time i-1, t0 is the preset sampling interval, and ε represents an infinitesimal value, which is used to prevent V i The result is 0.

[0055] It should be understood that It represents the rate of change of the homogeneity parameter from the previous acquisition time i-1 to the acquisition time i. If its value is larger, it means that the degree of change of the homogeneity parameter at time i is greater, and the influence on the particle size is greater.

[0056] The above method is used to calculate the growth rate of the corresponding real-time data for the real-time homogenization pressure and the homogenization temperature.

[0057] As the pressure and temperature of the sample gradually increase in the high-pressure homogenizer, the increase in pressure and temperature will cumulatively affect the inside of the sample, and as the two increase, the corresponding sample particle size will gradually decrease. The real-time growth rate of the two factors can indicate the degree of this influence.

[0058] Specifically, the influence coefficients of pressure and temperature on the particle size at any sampling moment are determined by combining the growth rates of the homogenization pressure and the homogenization temperature.

[0059] Preferably, in this embodiment, the influence coefficient of pressure and temperature on the particle size is determined by the result of forward fusion of the growth rate of the mean pressure and the homogenization temperature at any acquisition moment.

[0060] It can be understood that forward fusion is a fusion method such as addition and multiplication between data. The specific forward fusion method is determined by the implementer according to the actual situation, and this application does not impose any special restrictions.

[0061] As an implementation method, the product of the growth rate of the mean pressure and the homogenization temperature at any collection time is used as the influence coefficient of the pressure and temperature on the particle size at the collection time.

[0062] As another implementation, taking the collection time i as an example, the influence coefficient G of pressure and temperature on particle size is i It can be expressed as: In the formula, G i is the influence coefficient of pressure and temperature on particle size at the acquisition time i, is the homogenized pressure at the sampling time k, is the homogeneous temperature at the sampling time k, and norm represents the normalization function.

[0063] It should be understood that It is the cumulative influence of the homogenization pressure and the homogenization temperature from the start of sampling to the sampling time i, which is obtained by accumulating the real-time growth rate. The larger the value, the greater the cumulative influence of temperature and pressure on the particle size at this moment, and the sample particle size will become smaller and smaller. Finally, the result is normalized to the range of [0,1].

[0064] A2, based on the difference between the influence coefficients of pressure and temperature on particle size at adjacent collection moments, the difference between the average particle sizes of samples at adjacent collection moments, and the difference between the average particle size of the sample at any collection moment and the preset convergent particle size value, determine the difference variation coefficient at any collection moment;

[0065] Since the sample will be subjected to high pressure and high temperature at the same time during the pressurized homogenization process, which have a cumulative effect on the particle size, this step is based on the influence coefficient of the two factors on the particle size. The difference variation coefficient is calculated based on the relationship between the difference between adjacent collection moments and the difference in average particle size at adjacent collection moments, so as to determine the best parameter combination according to the size of the difference variation coefficient.

[0066] Through step A1, the real-time influence coefficients of homogenization pressure and homogenization temperature on particle size at different collection times during the pressurized homogenization process are obtained. In order to determine whether a certain collection time is the optimal homogenization pressure, it is necessary to make a judgment based on the relationship between the real-time particle size change trend and the change characteristics of the influence coefficient.

[0067] During the process of pressurized homogenization, as the pressure and temperature increase, the influence coefficient on the particle size increases, and the particle size gradually decreases. When the influence coefficient gradually increases at the initial moment, the particle size gradually decreases, and the difference in growth rate between the two increases; as the pressure increases, the particle size tends to converge and no longer decreases, while the influence coefficient still increases, and the difference in growth rate between the two slows down. When the particle size decreases to a certain extent, it tends to converge, and then the reduction in particle size is not significant if the pressure is continued.

[0068] Based on this feature, the difference variation coefficient at any collection time is calculated to analyze whether there is a convergence phenomenon in the average particle size of the sample at this collection time.

[0069] Specifically, based on the difference between the influence coefficients of pressure and temperature on particle size at adjacent collection moments, the difference between the average particle sizes of samples at adjacent collection moments, and the difference between the average particle size of the sample at any collection moment and the preset convergent particle size value, the difference variation coefficient at any collection moment is determined.

[0070] Preferably, in this embodiment, the difference result between the difference between the influence coefficients and the difference between the average particle sizes is calculated; the difference result is forwardly fused with the difference value to obtain the difference variation coefficient at any acquisition moment.

[0071] The difference between the influence coefficients is further determined as the ratio of the influence coefficients of pressure and temperature on the particle size at the next acquisition moment and the previous acquisition moment in the adjacent acquisition moments. The difference between the average particle sizes is further determined as the ratio of the average particle sizes of the samples at the next acquisition moment and the previous acquisition moment in the adjacent acquisition moments.

[0072] As an implementation mode, the product of the difference result and the difference value is used as the difference variation coefficient at any collection moment.

[0073] As another implementation, taking the acquisition time i as an example, the difference variation coefficient at the acquisition time i is calculated as follows: Where Y i is the coefficient of variation of the difference at the acquisition time i, G i With G i-1 are the influence coefficients of pressure and temperature on particle size at acquisition time i and acquisition time i-1, respectively, R i With R i-1are the average particle sizes of the samples at the collection time i and the collection time i-1 respectively, R0 is the preset convergent particle size value, which is 100 nanometers in this embodiment and can be set by the implementer, and exp represents an exponential function with the natural constant e as the base.

[0074] It should be understood that Represents the real-time change characteristics of the coefficients of influence of pressure and temperature on particle size, Represents the real-time variation characteristics of the average particle size of the sample, It represents the difference between the two real-time change characteristics at the collection time i. When the pressurized homogenization starts, the difference rate between the two will gradually increase as the homogenization pressure increases and the particle size gradually decreases. Therefore, the difference change coefficient will gradually increase. As the particle size converges, the difference rate between the two will gradually decrease, and this difference change coefficient will also gradually decrease.

[0075] At the same time, the difference between the particle size at the corresponding collection time and the preset convergence particle size value | R i -R0|, the smaller the difference value is, the closer it is to the convergence moment of the particle size, and the smaller the corresponding difference variation coefficient is. Finally, the corresponding difference variation coefficient is calculated at any time of pressurized homogenization and differential mapping is performed through an exponential function.

[0076] In order to determine the optimal homogenization pressure and homogenization temperature corresponding to the particle size convergence, it is necessary to perform accurate calculations based on the change characteristics of the above-mentioned real-time difference change coefficient.

[0077] A3, based on the difference mean between the difference variation coefficients of all adjacent collection moments before any collection moment, and the difference variation between the difference variation coefficients of any collection moment and its adjacent collection moments, determine the possibility that the homogenization pressure at any collection moment is the optimal homogenization pressure, and determine the optimal homogenization parameter combination;

[0078] Since the size of the difference variation coefficient represents the difference between the influence coefficient of pressure and temperature on particle size and the change characteristics of particle size, and as the difference variation coefficient gradually decreases, the particle size gradually tends to converge. However, since the real-time particle size value difference is relatively subtle when tending to converge, the method of directly determining whether the mean parameter is the optimal result by the change difference of the particle size value is controversial. The difference variation coefficient provides a more differentiated measurement method by comparing the influence coefficient and the trend difference of the particle size. By analyzing the difference changes in the difference variation coefficient at adjacent acquisition moments, it is used to determine the optimal homogenization parameter combination, thereby achieving the purpose of improving the accuracy of selecting the optimal homogenization parameters.

[0079] Therefore, the difference variation coefficients of all acquisition moments form a sequence A, A = {Y1, Y2, Y3…Y x ,Y x+1}, where Y1, Y2, Y3, …, Y x and Y x+1 They represent the difference variation coefficients at the 1st, 2nd, 3rd, ..., x and x+1st acquisition times respectively.

[0080] Specifically, based on the difference mean between the difference variation coefficients of all adjacent acquisition moments before any acquisition moment and the difference variation between the difference variation coefficients of any acquisition moment and its adjacent acquisition moments, the possibility that the homogenization pressure at any acquisition moment is the optimal homogenization pressure is determined, and the optimal homogenization parameter combination is determined.

[0081] Preferably, in this embodiment, the possibility that the homogenization pressure at any acquisition moment is the optimal homogenization pressure is determined by the result of reverse fusion of the difference mean and the difference change.

[0082] It can be understood that reverse fusion is a fusion method such as subtraction and division between data. The specific reverse fusion method is determined by the implementer according to the actual situation, and this application does not impose any special restrictions.

[0083] As an implementation mode, the normalized value of the ratio of the difference mean to the difference change is used as the possibility that the homogenization pressure at any acquisition time is the optimal homogenization pressure.

[0084] Taking the collection time x as an example, if the particle size converges at the collection time x, the difference change coefficient corresponding to the collection time x+1 will drop suddenly, among which, the probability Q of the homogenization pressure at the collection time x being the optimal homogenization pressure x It can be expressed as: In the formula, Q x is the probability that the homogenization pressure at the acquisition time x is the optimal homogenization pressure, Y k+1 With Y k are the coefficients of variation between the acquisition time k+1 and the acquisition time k, Y x With Y x+1 are the coefficients of variation of the difference between the acquisition time x and the acquisition time x+1, G x+1 With G x are the particle size influence coefficients at the collection time x+1 and the collection time x, respectively, and sigmoid is the normalized function.

[0085] It should be understood that Represents the difference in the difference coefficient between the collection time x+1 and the historical collection time. Since the difference coefficient increases gradually when the particle size does not converge, the average value of the difference coefficient of any two adjacent historical collection times before the collection time x is represents this growth trend, and if the particle size converges at the collection time x, then Y x+1 -Y xThe value of will decrease, thus deviating from the growth trend, so The larger the value of is, the more likely the particle size convergence is at the acquisition time x, and the greater the possibility that the homogenization pressure at the corresponding acquisition time is the optimal homogenization pressure.

[0086] In summary, the values ​​of the probability that the homogenization pressure at all acquisition moments is the optimal homogenization pressure have been normalized to the range of [0,1]. In this embodiment, the homogenization pressure and homogenization temperature at the acquisition moment corresponding to the probability of the optimal homogenization pressure Q≥T that appears for the first time during the pressurized homogenization process are selected to form the optimal homogenization parameter combination. Among them, T is the possibility threshold preset in this embodiment, and the value in this embodiment is 0.9, which can be set by the implementer.

[0087] Step 3: Control the high-pressure homogenizer in the preparation process of the allantoin nanoemulsion according to the optimal homogenization parameter combination to prepare the allantoin nanoemulsion.

[0088] Based on the homogenization pressure and homogenization temperature in the optimal homogenization parameter combination, the sample was pressurized and stabilized by a high-pressure homogenizer to prepare an allantoin nanoemulsion. This method can better refine the emulsion particle size, ensure the quality and stability of the allantoin nanoemulsion, and at the same time improve the preparation efficiency and reduce the load of the high-pressure homogenizer.

[0089] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0090] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the sentence "including one..." does not exclude the existence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items.

[0091] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not invented by the present application.

[0092] It should be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A method for preparing allantoin nanoemulsion based on parameter optimization, characterized in that: The method comprises the following steps: Step 1: collecting the real-time homogenization pressure, homogenization temperature and average particle size of the allantoin nanoemulsion during the pressurized homogenization process; Step 2: Determine the optimal homogenization parameter combination by analyzing the real-time growth rate of homogenization pressure and homogenization temperature and the characteristics of their changing relationship with the average particle size; specifically: A1, between the adjacent collection moments of any collection moment, respectively obtain the growth rates of the homogenization pressure and the homogenization temperature; combine the growth rates of the homogenization pressure and the homogenization temperature to determine the influence coefficient of the pressure and temperature on the particle size at any collection moment; A2, based on the difference between the influence coefficients of pressure and temperature on particle size at adjacent collection moments, the difference between the average particle sizes of samples at adjacent collection moments, and the difference between the average particle size of the sample at any collection moment and the preset convergent particle size value, determine the difference variation coefficient at any collection moment; A3, based on the difference mean between the difference variation coefficients of all adjacent collection moments before any collection moment, and the difference variation between the difference variation coefficients of any collection moment and its adjacent collection moments, determine the possibility that the homogenization pressure at any collection moment is the optimal homogenization pressure, and determine the optimal homogenization parameter combination; Step 3: Controlling the high-pressure homogenizer in the preparation process of the allantoin nanoemulsion according to the optimal homogenization parameter combination to prepare the allantoin nanoemulsion.

2. A method for preparing allantoin nanoemulsion based on parameter optimization as claimed in claim 1, characterized in that, Between adjacent collection moments to any collection moment, the adjacent collection moment is further determined as the previous adjacent collection moment of the any collection moment.

3. A method for preparing allantoin nanoemulsion based on parameter optimization as claimed in claim 2, characterized in that, The process of obtaining the growth rate is: The homogenization pressure and homogenization temperature are recorded as homogenization parameters; For any homogeneous parameter, calculate the difference between the value at any acquisition time and its adjacent acquisition time; obtain the preset sampling interval between adjacent acquisition times; The ratio of the difference to the preset sampling interval is used as the growth rate of any homogeneous parameter at any sampling moment.

4. A method for preparing allantoin nanoemulsion based on parameter optimization as claimed in claim 3, characterized in that, The influence coefficient of pressure and temperature on the particle size is determined by the product of the growth rate of the mean pressure and the homogenization temperature at any collection time.

5. A method for preparing allantoin nanoemulsion based on parameter optimization as claimed in claim 1, characterized in that, The method for determining the difference variation coefficient is: Calculate the difference between the influence coefficients and the average particle sizes; The product of the difference result and the difference value is used as the difference variation coefficient at any collection time.

6. A method for preparing allantoin nanoemulsion based on parameter optimization as claimed in claim 5, characterized in that: The difference between the influence coefficients is further determined as the ratio of the influence coefficients of pressure and temperature on the particle size at a later collection moment and a previous collection moment in adjacent collection moments.

7. A method for preparing allantoin nanoemulsion based on parameter optimization as claimed in claim 5, characterized in that: The difference between the average particle sizes is further determined as a ratio between the average particle sizes of samples at a later collection time and a previous collection time in adjacent collection times.

8. The method for preparing allantoin nanoemulsion based on parameter optimization according to claim 1, characterized in that: The possibility that the homogenization pressure at any acquisition moment is the optimal homogenization pressure is determined by the normalized value of the ratio result of the difference mean and the difference change.

9. The method for preparing allantoin nanoemulsion based on parameter optimization according to claim 1, characterized in that: In the difference change between the difference change coefficients of any acquisition moment and its adjacent acquisition moment, the adjacent acquisition moment is the next adjacent acquisition moment after the any acquisition moment.

10. The method for preparing allantoin nanoemulsion based on parameter optimization according to claim 1, characterized in that: The method for determining the optimal homogenization parameter combination is: In the process of pressurized homogenization, the homogenization temperature and homogenization pressure at the collection moment corresponding to the preset possibility threshold value are used to form the optimal homogenization parameter combination.

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