Component analysis method and system applied to preparation of skin moisturizer

Abstract

The invention relates to the field of quality control analysis, in particular to a component analysis method and system applied to preparation of a skin moisturizer, and the method comprises the following steps: screening an initial component set, obtaining a target component set, obtaining an analysis method set, and constructing a plurality of experimental groups based on a skin moisturizing sample set, the target component set and the analysis method set, performing the following operations on the target experimental group: confirming a target component and a target analysis method set based on the target experimental group, and performing the following operations on target analysis methods in the target analysis method set: acquiring actual concentrations based on the skin moisturizing sample set, summarizing the actual concentrations to obtain an actual concentration set corresponding to the target component set, and obtaining component analysis data based on the actual concentration set, and performing quality control analysis on the target moisturizing product based on the component analysis data to obtain a quality control result. The method can realize quality control analysis on the components in the skin moisturizer by using the standard curve.

Description

Technical Field

[0001] The present invention relates to the technical field of quality control analysis, and particularly to a method and system for component analysis applied to the preparation of skin moisturizers. Background Art

[0002] In the research and development and production process of skin moisturizers, component analysis and quality control are the core links to ensure the efficacy and safety of products. With the increasing complexity of cosmetic ingredients, how to achieve component analysis is crucial.

[0003] Traditional quality control methods mainly rely on single detection techniques, such as high-performance liquid chromatography, ultraviolet spectrophotometry, etc. First, quantitative analysis is performed on specific components, and then the qualification of components is determined by manual experience or static standard thresholds.

[0004] Although the above methods can achieve the analysis of cosmetics, they fail to effectively combine the experimental data of multiple inspection methods, resulting in the quality control results being easily affected by errors. Therefore, a method is needed that can integrate the experimental concentrations obtained by multiple analysis methods and construct a standard curve for quality control analysis. Summary of the Invention

[0005] The present invention provides a method for component analysis applied to the preparation of skin moisturizers and a computer-readable storage medium, and its main purpose is to perform quality control analysis on the components in skin moisturizers using a standard curve.

[0006] To achieve the above object, a method for component analysis applied to the preparation of skin moisturizers provided by the present invention includes:

[0007] Obtain a target moisturizing product and a set of skin moisturizing samples corresponding to the target moisturizing product, obtain an initial component set based on the target moisturizing product, screen the initial component set to obtain a target component set, obtain a set of analysis methods corresponding to the target component set using a pre-constructed database, and construct multiple experimental groups based on the set of skin moisturizing samples, the target component set, and the set of analysis methods;

[0008] Extract experimental groups from multiple experimental groups in sequence to obtain a target experimental group, and perform the following operations on the target experimental group:

[0009] Based on the target experimental group, confirm the target components and the set of target analysis methods, and perform the following operations on the target analysis methods in the set of target analysis methods:

[0010] Obtain a set of target experimental samples corresponding to the target experimental group based on the set of skin moisturizing samples, and measure the target components in the set of target experimental samples using the set of target experimental samples and the target analysis methods to obtain a set of response values;

[0011] Analyze the set of response values using a pre-constructed set of standard curves to obtain a set of target component concentration values, and calculate the unit actual concentration corresponding to the target component based on the set of target component concentration values;

[0012] Summarize the set of target component concentration values, the unit actual concentration, the target analysis method, and the target component to obtain component data;

[0013] Summarize the component data to obtain a component data set corresponding to the target experimental group, and calculate the actual concentration of the target component in the target experimental group based on the component data set;

[0014] Summarize the actual concentrations to obtain a set of actual concentrations corresponding to the target component set, obtain component analysis data based on the set of actual concentrations, and perform quality control analysis on the target moisturizing product based on the component analysis data to obtain a quality control result.

[0015] Optionally, the screening of the initial component set to obtain the target component set includes:

[0016] Sequentially extract the initial components from the initial component set and retrieve the initial components in the database. If the initial components exist in the database, obtain the component information table corresponding to the initial components based on the database, where the component information includes: component name, mechanism of action, and common grades, and the common grades include basic components and non-basic components;

[0017] If the common grade corresponding to the initial component is the basic component, skip the initial component; otherwise, confirm the initial component as a sub-preferred component to be tested;

[0018] Obtain the historical detection data of the sub-preferred components to be tested. If there is no pre-constructed toxicity report in the historical detection data, confirm the sub-preferred components to be tested as components to be tested; otherwise, send a pre-constructed warning message to the pre-constructed test result receiving end;

[0019] If the initial components do not exist in the database, confirm the initial components as components to be tested;

[0020] Summarize the components to be tested to obtain the target component set.

[0021] Optionally, the obtaining of the historical detection data of the sub-preferred components to be tested includes:

[0022] Construct a standard test experiment, where the standard test experiment includes: multiple safety experiments and multiple functional experiments, and the multiple safety experiments include: phototoxicity experiment, irritation experiment, corrosion experiment, and sensitization experiment, and the multiple functional experiments include multiple moisturizing experiments and multiple other efficacy experiments;

[0023] Obtain a set of safety inspection methods based on standard inspection experiments. Among them, the set of safety inspection methods includes multiple safety inspection methods, and the multiple safety inspection methods include: multiple phototoxicity methods, multiple irritation methods, multiple corrosion methods, and multiple sensitization methods;

[0024] Construct multiple safety category labels based on the multiple phototoxicity methods, multiple irritation methods, multiple corrosion methods, and multiple sensitization methods, and perform identification operations on the multiple safety inspection methods using the multiple safety category labels to obtain an identified experimental method set;

[0025] Obtain historical detection data based on the identified experimental method set.

[0026] Optionally, the obtaining of historical detection data based on the identified experimental method set includes:

[0027] Obtain the experimental concentration sequence of the sub-preferred test ingredient, sequentially extract the experimental concentrations from the experimental concentration sequence, and obtain the unit experimental group and the unit control group based on the extracted experimental concentrations, and use the experimental concentrations to identify the unit experimental group and the unit control group to obtain the unit group;

[0028] Summarize the unit groups to obtain a set of unit groups;

[0029] Construct a historical safety experimental group using the identified experimental method set and the set of unit groups. Among them, the historical safety experimental group includes multiple historical safety experiments, and one historical safety experiment includes: one identified experimental method and one set of unit groups, and the sets of unit groups corresponding to the multiple historical safety experiments are the same;

[0030] Perform the following operations on all the historical safety experiments in the historical safety experimental group:

[0031] Sequentially extract the unit groups from the set of unit groups corresponding to the historical safety experiment, and perform inspection operations based on the identified experimental method on the extracted unit groups to obtain inspection index parameters;

[0032] If the inspection index parameters meet the preset inspection index conditions, obtain the experimental concentration corresponding to the unit group to obtain the safe concentration value, and merge the safe concentration value and the inspection index parameters to obtain the unit safety experimental data. Otherwise, confirm the experimental concentration corresponding to the unit group as the preset abnormal concentration value, and merge the abnormal concentration value and the inspection index parameters to obtain the unit abnormal experimental data;

[0033] Summarize the unit safety experimental data and the unit abnormal experimental data to obtain the historical unit data corresponding to the historical safety experiment;

[0034] Summarize the historical unit data to obtain a historical unit data set, and obtain historical detection data based on the historical unit data set.

[0035] Optionally, obtaining historical detection data based on the historical unit dataset includes:

[0036] Sequentially extract historical unit data from the historical unit dataset to obtain target data, and perform the following operations on the target data:

[0037] If there is no unit safety experiment data in the target data, generate a toxicity report corresponding to the target data based on the secondary preferential test components, historical safety experiments, historical unit data, and safety category labels corresponding to the target data;

[0038] If there is unit safety experiment data in the target data, extract and summarize the safety concentration values corresponding to all unit safety experiment data in the target data to obtain a set of safety concentration values, and construct a unit safety concentration interval corresponding to the target data based on the set of safety concentration values;

[0039] Summarize the unit safety concentration intervals according to multiple safety category labels respectively to obtain multiple category safety interval sets corresponding to the historical unit dataset;

[0040] Calculate the skin care safety concentration interval and the skin care abnormal concentration interval based on multiple category safety interval sets;

[0041] If the intersection between the skin care safety concentration interval and the skin care abnormal concentration interval is a preset empty set, construct a safety report for the secondary preferential test components based on the skin care safety concentration interval, the skin care abnormal concentration interval, and multiple category safety interval sets;

[0042] Otherwise, calculate and update the safety concentration interval and the updated abnormal concentration interval based on the skin care safety concentration interval and the skin care abnormal concentration interval, and construct a safety report for the secondary preferential test components based on the updated safety concentration interval and the updated abnormal concentration interval, and summarize the safety report and the toxicity report to obtain historical detection data, where the calculation formulas for the updated safety concentration interval and the updated abnormal concentration interval are as follows:

[0043]

[0044] Among them, represents the updated safety concentration interval, C a represents the skin care safety concentration interval, \ represents the difference set operator, ∩ represents the intersection operator, C Y represents the skin care abnormal concentration interval, represents the updated abnormal concentration interval, ∪ represents the union operator.

[0045] Optionally, calculating the skin care safety concentration interval and the skin care abnormal concentration interval based on multiple category safety interval sets includes:

[0046] Perform the following operations on each category safety interval set in multiple category safety interval sets:

[0047] Calculate the total experimental interval based on the experimental concentration sequence;

[0048] Calculate the intersection of the category safety interval set to obtain the category safety interval, calculate the complement of the category safety interval in the total experimental interval, and obtain the category abnormal interval;

[0049] Summarize the category safety intervals, and calculate the intersection of the summarized category safety intervals to obtain the skin care safety concentration interval of the suboptimal ingredient to be tested; summarize the category abnormal intervals, and calculate the union of the summarized category abnormal intervals to obtain the skin care abnormal concentration interval.

[0050] Optionally, the using a pre-constructed standard curve set to parse the response value set to obtain a target component concentration value set, and calculating the unit actual concentration corresponding to the target component based on the target component concentration value set, comprises:

[0051] Obtaining a standard curve set of a historical safety experiment group, identifying a historical safety experiment corresponding to a target analysis method in the historical safety experiment group to obtain a target historical experiment, and extracting a standard curve corresponding to the target historical experiment from the standard curve set to obtain a target curve;

[0052] Extract response values from the response value set in sequence, query the horizontal coordinates corresponding to the extracted response values in the target curve, and obtain the concentration value of the target component;

[0053] The target component concentration values are summarized to obtain a target component concentration value set, and the mean of the target component concentration value set is calculated to obtain the unit actual concentration.

[0054] Optionally, acquiring component analysis data based on the actual concentration set includes:

[0055] The actual concentrations are extracted from the actual concentration set in sequence, and the partial component ratio of the actual concentration is calculated, where the calculation formula of the partial component ratio is as follows:

[0056]

[0057] Among them, p represents the partial component ratio, r represents the actual concentration, and l represents the ideal concentration value of the target component in the target moisturizing product;

[0058] Merge the target component and the partial component ratio to obtain unit component data, summarize the unit component data to obtain an initial unit component data set, remove the target component set from the initial component set to obtain other component sets, and construct other component data sets based on the other component sets;

[0059] Construct component analysis data based on other component data sets and the initial unit component data set.

[0060] Optionally, perform quality control analysis on the target moisturizing product based on the component analysis data to obtain a quality control result, including:

[0061] Successively extract component data from the component analysis data, where the extracted component data includes: actual components, actual component concentrations, ideal concentration values of components, actual partial component ratios, safe concentration ranges corresponding to the actual components, and abnormal concentration ranges corresponding to the actual components;

[0062] If the actual component concentration is within the safe concentration range corresponding to the actual component, determine whether the actual partial component ratio is within the preset controllable partial component ratio range. If the actual partial component ratio is within the controllable partial component ratio range, confirm that the component data is the preset initial quality control qualified; otherwise, send a pre-constructed quality control warning message to the pre-constructed test result receiving end;

[0063] If all the component data in the component analysis data are confirmed to be the initial quality control qualified, confirm that the target moisturizing product is the preset safe quality control qualified;

[0064] If it is confirmed that the target moisturizing product is the preset function quality control qualified based on the multiple functional experiments, summarize the safe quality control qualified and the function quality control qualified to obtain the quality control result.

[0065] To achieve the above object, the present invention also provides a component analysis system applied to the preparation of skin moisturizers, including:

[0066] An experimental group module, configured to obtain a target moisturizing product and a set of skin moisturizing samples corresponding to the target moisturizing product, obtain an initial component set based on the target moisturizing product, screen the initial component set to obtain a target component set, use a pre-constructed database to obtain an analysis method set corresponding to the target component set, and construct multiple experimental groups based on the set of skin moisturizing samples, the target component set, and the analysis method set;

[0067] A response value set module, configured to successively extract experimental groups from multiple experimental groups to obtain a target experimental group, and perform the following operations on all target experimental groups: confirm the target components and the target analysis method set based on the target experimental group, and perform the following operations on the target analysis methods in the target analysis method set: obtain a target experimental sample set corresponding to the target experimental group based on the set of skin moisturizing samples, and measure the target components in the target experimental sample set using the target experimental sample set and the target analysis method to obtain a response value set;

[0068] A component data module, configured to analyze the response value set using a pre-constructed standard curve set to obtain a set of target component concentration values, calculate the unit actual concentration corresponding to the target components based on the set of target component concentration values, and summarize the set of target component concentration values, the unit actual concentration, the target analysis method, and the target components to obtain component data;

[0069] A quality control module, which is used to summarize the component data to obtain a component data set corresponding to a target experimental group, calculate the actual concentration of a target component in the target experimental group based on the component data set, summarize the actual concentrations to obtain an actual concentration set corresponding to a target component set, obtain component analysis data based on the actual concentration set, and perform quality control analysis on a target moisturizing product based on the component analysis data to obtain a quality control result.

[0070] To solve the above problems, the present invention also provides an electronic device, which includes:

[0071] A memory that stores at least one instruction; and a processor that executes the instruction stored in the memory to implement the above-mentioned component analysis method applied to the preparation of skin moisturizers.

[0072] To solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned component analysis method applied to the preparation of skin moisturizers.

[0073] To solve the problems described in the background art, the present invention screens the initial ingredient set to obtain a target ingredient set. If the initial ingredient exists in the database, it indicates that the initial ingredient has been detected before the present invention. Therefore, the ingredient information table and historical experimental data corresponding to the initial ingredient can be obtained through the database, providing a basis for experimenters to analyze the safety of the ingredient. The following operations are performed on all target experimental groups: Based on the target experimental group, the target ingredient and the target analysis method set are confirmed. For each target analysis method in the target analysis method set, the following operations are performed: Based on the skin moisturizing sample set, the actual concentration is obtained, and the actual concentrations are summarized to obtain the actual concentration set corresponding to the target ingredient set. The present invention establishes a quantitative relationship between the concentration and the test index parameters through standard samples with known concentrations (a unit group at a certain experimental concentration in historical safety experiments), and considers the problem of error during the test process. Therefore, multiple different target analysis methods are also used to test the target ingredient, which is beneficial to reducing experimental errors. Therefore, the present invention performs operations to obtain ingredient data based on different target analysis methods on all target experimental groups, which is achieved by calculating the mean value corresponding to all unit actual concentrations in the ingredient dataset, and the actual concentration is confirmed as the concentration of the target ingredient in the target moisturizing product. Based on the actual concentration set, ingredient analysis data is obtained, and quality control analysis is performed on the target moisturizing product based on the ingredient analysis data to obtain a quality control result. If the safety quality control is qualified, it means that all ingredients in the target moisturizing product will not have an adverse effect on the skin. Therefore, if the target moisturizing product is confirmed to be qualified for the preset functional quality control based on the multiple functional experiments, it means that the moisturizing effect of the target moisturizing product can also reach the expected effect set by humans, indicating that the target moisturizing ingredient meets the expectations and the quality control is qualified. Otherwise, a pre-constructed warning message needs to be sent to the pre-constructed test result receiving end. Therefore, the present invention can realize quality control analysis of the ingredients in skin moisturizers using standard curves. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 FIG. is a schematic flowchart of an ingredient analysis method applied to the preparation of skin moisturizers according to an embodiment of the present invention;

[0075] Figure 2 FIG. is a functional module diagram of an ingredient analysis system applied to the preparation of skin moisturizers according to an embodiment of the present invention;

[0076] Figure 3 FIG. is a schematic structural diagram of an electronic device for implementing the ingredient analysis method applied to the preparation of skin moisturizers according to an embodiment of the present invention.

[0077] DESCRIPTION OF THE REFERENCE NUMERALS:

[0078] 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0079] The implementation, functional features, and advantages of the present invention will be further described in conjunction with embodiments with reference to the accompanying drawings. Detailed implementation manners

[0080] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0081] The embodiment of the present application provides a method for component analysis in the preparation of skin moisturizers. The execution subject of the method for component analysis in the preparation of skin moisturizers includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for component analysis in the preparation of skin moisturizers can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc.

[0082] Refer to Figure 1 As shown, it is a schematic flowchart of a method for component analysis in the preparation of skin moisturizers provided by an embodiment of the present invention. In this embodiment, the method for component analysis in the preparation of skin moisturizers includes:

[0083] S1. Obtain a target moisturizing product and a skin moisturizing sample set corresponding to the target moisturizing product, obtain an initial component set based on the target moisturizing product, screen the initial component set to obtain a target component set, obtain an analysis method set corresponding to the target component set by using a pre-constructed database, and construct multiple experimental groups based on the skin moisturizing sample set, the target component set, and the analysis method set.

[0084] It should be noted that the target moisturizing product is the product to be tested in the embodiment of the present invention, and the target moisturizing product can be applied to skin moisturization. The skin moisturizing sample set is a set composed of samples prepared based on the target moisturizing product and is used for subsequent experiments. The initial component set is a set composed of all components in the target moisturizing product. The database can be a local database or an online database, and can query relevant information of the target component, such as: chemical formula, analysis method, component information table, etc. Among them, the analysis method is a method for analyzing the target product. For example, if the target component is hyaluronic acid, the analysis method can include the carbazole sulfuric acid colorimetric method, ultraviolet spectrophotometry, etc., and will not be listed one by one here.

[0085] It is understandable that the experimental group is a data set constructed for experiments when analyzing target components. Exemplarily, the target component set includes target component A and target component B, analysis method A corresponding to target component A, analysis methods B and C corresponding to target component B. Then, the analysis method set consists of analysis method A, analysis method B, and analysis method C. Each of the multiple experimental groups includes a target component, all the analysis methods corresponding to the target component, and a skin moisturizing sample set. Therefore, the experimental group corresponding to target component A is: [Target component A, Analysis method A, Skin moisturizing sample set]. Therefore, the experimental group corresponding to target component B is: [Target component B, Analysis methods B and C, Skin moisturizing sample set].

[0086] Further, screening the initial component set to obtain the target component set includes:

[0087] Sequentially extract initial components from the initial component set and retrieve the initial components in the database. If the initial components exist in the database, obtain the component information table corresponding to the initial components based on the database. Among them, the component information includes: component name, mechanism of action, and common level. Among them, the common level includes basic components and non-basic components;

[0088] If the common level corresponding to the initial component is the basic component, skip the initial component. Otherwise, confirm the initial component as a secondary preferred component to be tested;

[0089] Obtain the historical detection data of the secondary preferred components to be tested. If there is no pre-constructed toxicity report in the historical detection data, confirm the secondary preferred components to be tested as components to be tested. Otherwise, send a pre-constructed warning message to the pre-constructed test result receiving end;

[0090] If the initial component does not exist in the database, confirm the initial component as a component to be tested;

[0091] Summarize the components to be tested to obtain the target component set.

[0092] It is understandable that if the initial ingredient exists in the database, it indicates that the initial ingredient has been detected before the embodiment of the present invention. Therefore, the ingredient information table corresponding to the initial ingredient can be queried from the database. The ingredient name is the chemical name of the initial ingredient. For example, hyaluronic acid, and the mechanism of action is the way for the initial ingredient to achieve moisturizing. For example, hyaluronic acid has water absorption, can form a breathable hydration film on the skin surface, reduce transdermal water loss, and can also up-regulate the expression of AQP3 in the basal layer of the skin through the signal pathway, so as to enhance the ability of cells to actively transport water. Among them, the common grades include basic ingredients and non-basic ingredients. Basic ingredients are commonly used in the database and have been confirmed not to cause damage to the skin, such as water and glycerin. Non-basic ingredients are opposite to basic ingredients. If the initial ingredient is not a basic ingredient, the initial ingredient is classified as a non-basic ingredient.

[0093] Furthermore, by way of example, if the initial ingredient is water, then there is no further need to detect the safety of applying water to the skin. If the initial ingredient is alcohol, even though there are papers and studies proving that alcohol exists in skin moisturizers and alcohol also has the effect of disinfecting, but if the concentration of alcohol in the target moisturizing product exceeds a certain mass concentration, there is also a possibility of causing damage to the skin. Therefore, alcohol is classified as a non-basic ingredient, and the alcohol is confirmed as a secondary preferential component to be tested and analyzed in the subsequent steps.

[0094] It should be noted that the historical detection data is the data stored in the database, including the detection and related data of the secondary preferential component to be tested before the embodiment of the present invention. For specific details, please refer to the subsequent embodiments. The toxicity report is a literal narrative report, which is used to indicate that there is no unit safety experiment data of the secondary preferential component to be tested in a certain historical safety experiment. That is to say, in the certain historical safety experiment, the secondary preferential component has damage to the skin at any experimental concentration in any experimental concentration sequence. Therefore, it is necessary to send a pre-constructed warning message to the pre-constructed test result receiving end. The test result receiving end can be a computer, which is used to receive the component analysis result of the skin moisturizer. The warning message includes the literal information for warning, such as: "There is ingredient G", and also includes the toxicity report. Therefore, the content included in the warning message can be specified by humans.

[0095] It should be noted that the target ingredient set is a set obtained by summarizing the components to be tested. Therefore, the target ingredient set includes multiple target ingredients, and the target ingredients correspond to the components to be tested one by one.

[0096] Furthermore, the obtaining of the historical detection data of the secondary preferential component to be tested includes:

[0097] Construct a standard test experiment, where the standard test experiment includes: multiple safety experiments and multiple functional experiments, and the multiple safety experiments include: phototoxicity experiment, irritation experiment, corrosion experiment and sensitization experiment, and the multiple functional experiments include multiple moisturizing experiments and multiple other efficacy experiments;

[0098] Obtain a set of safety test methods based on the standard test experiment, where the set of safety test methods includes multiple safety test methods, and the multiple safety test methods include: multiple phototoxicity methods, multiple irritation methods, multiple corrosion methods and multiple sensitization methods;

[0099] Construct multiple safety category labels based on the multiple phototoxicity methods, multiple irritation methods, multiple corrosion methods and multiple sensitization methods, and perform an identification operation on all the multiple safety test methods using the multiple safety category labels to obtain a set of labeled experimental methods;

[0100] Obtain historical detection data based on the set of labeled experimental methods.

[0101] It should be noted that the moisturizing experiment is an experiment for detecting the moisturizing ability of skin care products, and the other efficacy experiments can include experiments for detecting the whitening, anti-aging and other effects of skin care products, which will not be elaborated here.

[0102] It can be understood that the phototoxicity experiment is an experiment for testing the phototoxicity of the test components, and the multiple phototoxicity methods are multiple methods for performing the phototoxicity experiment. For example, GB / T21769—2008 Chemicals in vitro 3T3-Neutral red uptake phototoxicity test method, SN / T5560—2023 Cosmetics phototoxicity experiment-Determination of photoreactivity Reactive oxygen species experiment, etc.

[0103] It can be understood that the irritation experiment is an experiment for testing the irritation of the test components, and the multiple irritation methods are multiple methods for performing the irritation experiment. For example, SN / T4577—2016 Cosmetics skin irritation detection-Reconstructed human epidermis model in vitro test method, etc.

[0104] It can be understood that the corrosion experiment is an experiment for testing the corrosion of the test components, and the multiple corrosion methods are multiple methods for performing the corrosion experiment. For example, GB / T27830—2011 Chemicals-In vitro skin corrosion Human skin model test method, etc.

[0105] It can be understood that the sensitization experiment is an experiment for testing the sensitization of the test components, and the multiple sensitization methods are multiple methods for performing the sensitization experiment. For example, GB / T21608—2008 Chemicals-Skin sensitization test method, etc.

[0106] Further, the multiple safety category labels are multiple text-based identifiers, namely: phototoxicity, irritation, corrosion, and sensitization. The operation of performing the identification is prior art. A unique identifier can be generated using the text and the corresponding safety test method and added as a descriptive label, etc. The embodiments of the present invention do not limit this. The identification test method is the safety test method after being labeled with the safety category labels.

[0107] Further, obtaining the historical detection data based on the set of identification test methods includes:

[0108] Obtain the experimental concentration sequence of the sub-preferred test ingredient, sequentially extract the experimental concentrations from the experimental concentration sequence, and based on the extracted experimental concentrations, obtain the unit experimental group and the unit control group, and use the experimental concentrations to label the unit experimental group and the unit control group to obtain the unit group;

[0109] Summarize the unit groups to obtain the unit group set;

[0110] Construct a historical safety experimental group using the set of identification test methods and the unit group set. Among them, the historical safety experimental group includes multiple historical safety experiments, and one historical safety experiment includes: one identification test method and one unit group set, and the unit group sets corresponding to the multiple historical safety experiments are the same;

[0111] Perform the following operations on all the historical safety experiments in the historical safety experimental group:

[0112] Sequentially extract the unit groups from the unit group set corresponding to the historical safety experiment, and perform the test operation based on the identification test method on the extracted unit groups to obtain the test index parameters;

[0113] If the test index parameters meet the preset test index conditions, obtain the experimental concentration corresponding to the unit group to obtain the safe concentration value, and combine the safe concentration value and the test index parameters to obtain the unit safety experimental data. Otherwise, confirm the experimental concentration corresponding to the unit group as the preset abnormal concentration value, and combine the abnormal concentration value and the test index parameters to obtain the unit abnormal experimental data;

[0114] Summarize the unit safety experimental data and the unit abnormal experimental data to obtain the historical unit data corresponding to the historical safety experiment;

[0115] Summarize the historical unit data to obtain the historical unit data set, and obtain the historical detection data based on the historical unit data set.

[0116] It should be noted that the experimental concentration sequence is a sequence composed of multiple experimental concentrations. For example: [0.5 μmol / L, 1 μmol / L, 2.5 μmol / L, 5 μmol / L, 10 μmol / L, 25 μmol / L, 50 μmol / L...]. The specific values can be set by the experimental personnel, and the embodiments of the present invention do not limit this. The unit experimental group is a data group for experiments composed of experimental concentrations, which can be samples of the component to be tested at the experimental concentration. The component of the unit control group can be set as glycerol, and the concentration of glycerol is the sample at the experimental concentration. For the same component to be tested preferentially, the experimental concentration sequence in different historical safety experiments should be the same. However, for different components to be tested preferentially, different components to be tested preferentially have their respective corresponding ranges of experimental concentration sequences. This is because, in a skin moisturizer, the addition amounts and usage amounts corresponding to different components are different. For example, the maximum experimental concentration of hyaluronic acid in the experimental concentration sequence is greater than the maximum experimental concentration of alcohol in the experimental concentration sequence.

[0117] Furthermore, the unit group includes the unit experimental group and the unit control group after the experimental concentration is marked. The construction of the historical safety experimental group by using the marked experimental method set and the unit group set includes:

[0118] Extract the marked experimental methods from the marked experimental method set in sequence, and construct historical safety experiments based on the extracted marked experimental methods and the unit group set, and summarize the historical safety experiments to obtain the historical safety experimental group set.

[0119] It should be noted that the historical safety experiment is an experiment based on a marked experimental method and a unit group set. Since the error of performing an experiment once is very large in the actual experimental process, the inspection operation based on the marked experimental method is performed based on the extracted unit group to obtain the inspection index parameters, including:

[0120] Obtain multiple unit group experimental samples corresponding to the unit group based on the preset number of repeated experiments, perform the inspection operation based on the marked experimental method on all the multiple unit group experimental samples to obtain the initial experimental data set, perform data preprocessing on the initial experimental data set to obtain the optimized experimental data set, and calculate the average value of the optimized experimental data set to obtain the inspection index parameters.

[0121] It is understandable that the preset number of repeated experiments refers to the number of times of performing the inspection operation based on the identification experiment method on an experimental sample of a unit group. Therefore, the number of experimental samples of multiple unit groups is equal to the number of repeated experiments. Further, the initial experimental data set is a set of data obtained by performing the inspection operation on experimental samples of multiple unit groups using the identification experiment method. For example, if the identification experiment method is to measure the molar extinction coefficient to determine the phototoxicity of the secondary preferential experiment component, the initial experimental data set is a set of molar extinction coefficients obtained by measuring each experimental sample of multiple unit groups. The execution of data preprocessing can be: conventional data processing operations such as removing outliers. The removal of outliers can be: removing the experimental samples of the unit group with a measured molar extinction coefficient of 0. Therefore, the standard for removing outliers can be set manually or by other existing algorithms, and the embodiments of the present invention do not limit this. The optimized experimental data set is a set composed of all the data obtained after performing data preprocessing.

[0122] Further, if the identification experiment method is to measure the molar extinction coefficient, the inspection index parameter is the molar extinction coefficient corresponding to the unit experimental group in the unit group. If the identification experiment method is the 3T3 neutral red uptake phototoxicity experiment, the inspection index parameter is the cell viability of the unit experimental group relative to the unit control group in the unit group after a preset time. Therefore, the embodiments of the present invention use the inspection index parameter to refer to the index used to judge the detection result in the actual detection process for different identification experiment methods. If the identification experiment method is to measure the molar extinction coefficient, the inspection index condition can be that the inspection index parameter is less than the preset molar extinction coefficient threshold. Optionally, in this embodiment, the molar extinction coefficient threshold is set to 1000 L·mol -1 ·cm -1 , if the inspection index parameter is less than the molar extinction coefficient threshold, it is considered that the experimental concentration corresponding to the unit group is the safe concentration value and there is no phototoxicity that damages the skin. Further, if the identification experiment method is the 3T3 - neutral red uptake phototoxicity experiment, the inspection index parameter is the cell viability of the unit experimental group relative to the unit control group in the unit group after a preset time. Optionally, in the embodiments of the invention, the inspection index condition is set to be that the cell viability is greater than 50%. Therefore, when the inspection index parameter is greater than 50%, it is considered that the experimental concentration corresponding to the unit group is the safe concentration value and there is no phototoxicity that damages the skin.

[0123] It is understandable that the combination of the safe concentration value and the inspection index parameter to obtain the unit safety experimental data is: storing the safe concentration value and the inspection index parameter in one data, and the obtained data is the unit safety experimental data. The abnormal concentration value refers to the experimental concentration corresponding to the unit group when the inspection index parameter does not meet the inspection index condition. The unit abnormal experimental data is the data obtained by storing the abnormal concentration value and the inspection index parameter in one data.

[0124] It is understandable that each unit group can correspond to a unit safety experiment data or a unit abnormal experiment data. Therefore, by summarizing the unit safety experiment data and the unit abnormal experiment data, the historical unit data corresponding to the unit group set can be obtained. Then, by summarizing the historical unit data, the historical unit data set corresponding to the historical safety experiment group can be obtained. Therefore, there is a one-to-one correspondence between the historical unit data and the historical safety experiment.

[0125] Furthermore, obtaining the historical detection data based on the historical unit data set includes:

[0126] Sequentially extract historical unit data from the historical unit data set to obtain target data, and perform the following operations on the target data:

[0127] If there is no unit safety experiment data in the target data, generate a toxicity report corresponding to the target data based on the secondary preferential test components, historical safety experiments, historical unit data, and safety category labels corresponding to the target data;

[0128] If there is unit safety experiment data in the target data, extract and summarize the safety concentration values corresponding to all unit safety experiment data in the target data to obtain a safety concentration value set, and construct a unit safety concentration interval corresponding to the target data based on the safety concentration value set;

[0129] Summarize the unit safety concentration intervals according to multiple safety category labels respectively to obtain multiple category safety interval sets corresponding to the historical unit data set;

[0130] Calculate the skin care safety concentration interval and the skin care abnormal concentration interval based on the multiple category safety interval sets;

[0131] If the intersection between the skin care safety concentration interval and the skin care abnormal concentration interval is a preset empty set, construct a safety report for the secondary preferential test components based on the skin care safety concentration interval, the skin care abnormal concentration interval, and the multiple category safety interval sets;

[0132] Otherwise, calculate and update the safety concentration interval and the updated abnormal concentration interval based on the skin care safety concentration interval and the skin care abnormal concentration interval, and construct a safety report for the secondary preferential test components based on the updated safety concentration interval and the updated abnormal concentration interval. Summarize the safety report and the toxicity report to obtain the historical detection data, where the calculation formulas for the updated safety concentration interval and the updated abnormal concentration interval are as follows:

[0133]

[0134] Wherein, represents the updated safety concentration interval, C a represents the skin care safety concentration interval, \ represents the difference set operator, ∩ represents the intersection operator, CY Indicates the abnormal concentration range of skin care, Indicates the abnormal concentration range of update, and ∪ represents the union operator.

[0135] It should be noted that as described in the previous text of this embodiment, if the test index parameter meets the preset test index condition, a unit safety experiment data can be obtained. Therefore, when there is no unit safety experiment data in the target data, it means that in the corresponding historical safety experiment, any concentration in the experimental concentration sequence will cause adverse effects on the skin (the adverse effects are determined by the identification experiment method of the historical safety experiment. If the identification experiment method is to test phototoxicity, the adverse effect is the existence of phototoxicity). Therefore, the toxicity report generated based on the secondary preferred test ingredient, historical safety experiment, historical unit data, and safety category label corresponding to the target data includes, but is not limited to: the basic information of the secondary preferred test ingredient (such as name, chemical formula, etc.), the experimental data during the identification experiment method, such as: all recorded logs, safety category labels, historical unit data, etc. in the historical safety experiment. And at this time, the historical unit data only includes unit abnormal experiment data, and can also include the above warning information of this embodiment, and other contents can also be added according to the needs of the experimenter to describe the experimental process and experimental results of the secondary preferred test ingredient under the historical safety experiment.

[0136] Further, the lower limit of the unit safety concentration range is the lower limit of the total experimental range, and the upper limit is the range composed of the largest safety concentration value in the safety concentration value set.

[0137] For example, the safety concentration values corresponding to all unit safety experiment data in the target data are obtained according to the experimental concentration. For example, the safety concentration value set is obtained according to multiple experimental concentrations of [0.5 μmol / L, 1 μmol / L, 2.5 μmol / L, 5 μmol / L, 10 μmol / L, 25 μmol / L], and the safety concentration value corresponds one-to-one with multiple experimental concentrations of [0.5 μmol / L, 1 μmol / L, 2.5 μmol / L, 5 μmol / L, 10 μmol / L, 25 μmol / L]. Also, since the lower limit of the total experimental range is less than or equal to the largest safety concentration value in the safety concentration value set, the construction method of the unit safety concentration range can summarize the concentration range in which the secondary preferred test ingredient does not cause adverse effects on the skin under the identification experiment method.

[0138] It can be understood that during the process of summarizing the unit safety concentration range according to multiple safety category labels respectively, the unit safety concentration ranges corresponding to the same safety category label are stored in the same category safety range set. Therefore, there are four category safety range sets, which respectively correspond to the four safety category labels of phototoxicity, irritation, corrosion, and sensitization.

[0139] It is understandable that the safety report is similar to the toxicity report and can achieve the same effect. The difference is that the safety report is used to present the experimental data of the sub-preferred test ingredient in each historical safety experiment in the historical safety experimental group, and also includes the skin care safety concentration range, the skin care abnormal concentration range, multiple category safety range sets, etc., which are beneficial for experimenters to judge the safety of the sub-preferred test ingredient, and is more comprehensive than the toxicity report.

[0140] Furthermore, the calculation principles of the updated safety concentration range and the updated abnormal concentration range are as follows: If the intersection between the skin care safety concentration range and the skin care abnormal concentration range is not an empty set, it means that there are overlapping values between the skin care safety concentration range and the skin care abnormal concentration range. Also, since when the experimental concentration is in the skin care abnormal concentration range, the sub-preferred test ingredient will have an adverse effect on the skin in one of the aspects of phototoxicity, irritation, corrosion, and sensitization mentioned above, it is necessary to mark the intersection between the skin care safety concentration range and the skin care abnormal concentration range as the skin care abnormal concentration range, and remove the intersection between the skin care safety concentration range and the skin care abnormal concentration range from the skin care safety concentration range, so as to obtain the updated safety concentration range and the updated abnormal concentration range.

[0141] Furthermore, the construction of the safety report of the sub-preferred test ingredient based on the updated safety concentration range and the updated abnormal concentration range is similar to the construction of the safety report of the sub-preferred test ingredient based on the skin care safety concentration range, the skin care abnormal concentration range, and multiple category safety range sets, and can achieve the same effect, which will not be elaborated here.

[0142] Furthermore, the calculation of the skin care safety concentration range and the skin care abnormal concentration range based on multiple category safety range sets includes:

[0143] Perform the following operations on each category safety range set in the multiple category safety range sets:

[0144] Calculate the total experimental range based on the experimental concentration sequence;

[0145] Calculate the intersection of the category safety range sets to obtain the category safety range, and calculate the complement of the category safety range in the total experimental range to obtain the category abnormal range;

[0146] Summarize the category safety ranges, and calculate the intersection of the summarized category safety ranges to obtain the skin care safety concentration range of the sub-preferred test ingredient. Summarize the category abnormal ranges, and calculate the union of the summarized category abnormal ranges to obtain the skin care abnormal concentration range.

[0147] Furthermore, the lower limit of the total experimental range is the minimum experimental concentration in the experimental concentration sequence, and the upper limit of the total experimental range is the maximum experimental concentration in the experimental concentration sequence.

[0148] It should be noted that the concentration of the secondary preferential test component in the category safety interval can ensure that the test index parameters corresponding to any one of the identification test methods in the category safety interval set can meet the test index conditions. That is, when the concentration of the secondary preferential test component is within the category safety interval and the safety category label is phototoxic, it will not have an adverse effect on the skin due to phototoxicity. Therefore, after calculating the complement of the category safety interval in the total experimental interval, the obtained category abnormal concentration interval can be expressed as: when the concentration of the secondary preferential test component in the category abnormal concentration interval is applied to skin care products, it may have an adverse effect on the skin due to phototoxicity. Therefore, the category safety interval and the category abnormal interval are discussed under the same safety category label.

[0149] Furthermore, after calculating the intersection of the category safety intervals after summarization, the obtained skin care safety concentration interval of the secondary preferential test component is discussed under all safety category labels. Therefore, when the concentration of the secondary preferential test component is within the skin care safety concentration interval, the test index parameters corresponding to any one of the historical safety experiments in the historical safety experimental group can meet the test index conditions, that is, it will not have an adverse effect on the skin in any of the aspects of phototoxicity, irritation, corrosion, and sensitization mentioned above. When the concentration of the secondary preferential test component is within the skin care abnormal concentration interval, there are one or more test index parameters corresponding to one or more historical safety experiments that cannot meet the test index conditions. Therefore, there may be one or more aspects among phototoxicity, irritation, corrosion, and sensitization mentioned above that have an adverse effect on the skin.

[0150] S2. Sequentially extract experimental groups from multiple experimental groups to obtain the target experimental group.

[0151] Furthermore, the target experimental group is the experimental group extracted from multiple experimental groups.

[0152] S3. Perform the following operations on all target experimental groups: Based on the target experimental group, confirm the target component and the target analysis method set, and perform the following operations on each target analysis method in the target analysis method set: Obtain the target experimental sample set corresponding to the target experimental group based on the skin moisturizing sample set.

[0153] Furthermore, the target analysis method set is a set composed of methods that can perform experiments corresponding to each safety category label in multiple safety category labels for the target component.

[0154] It should be noted that, for example, in a general irritation experiment, such as the in vitro test method for reconstructing human epidermis model in SN / T 4577—2016 Detection of Skin Irritation of Cosmetics, skin care product samples are often directly used for the irritation experiment. However, in this invention, when conducting the experiment, the performance of components under a certain experimental concentration in the irritation experiment is mainly considered. Therefore, before the irritation experiment, some pretreatment is carried out on the skin care product samples, so that after constructing the historical safety experiment corresponding to the irritation experiment in this invention, the test index parameters obtained can reflect the concentration of the target component in the historical safety experiment through the response curve. For the construction of the response curve, please refer to the following embodiments. Therefore, for the target component, in one irritation experiment, as long as the same irritation experiment as that of the target component in the database is adopted, the test index parameters of the target component under the irritation experiment can be obtained, and the concentration corresponding to the test index parameters can be queried by calling the response curve existing in the database, so as to estimate the concentration of the target component.

[0155] It should be noted that when the target component does not exist in the database, the acquisition of the target analysis method set can be processed by referring to the experiments of other target components existing in the database. For example, a certain existing technology is used to extract the target component, and according to the standard test experiment existing in the database, a response curve reflecting the concentration of the target component is constructed. Therefore, the target experimental sample set is the set composed of the experimental samples obtained after the above-mentioned pretreatment.

[0156] S4. Measure the target component in the target experimental sample set by using the target experimental sample set and the target analysis method to obtain a response value set.

[0157] It can be understood that the process of measuring the target component in the target experimental sample set is to perform the same experiment on each target experimental sample in the target experimental sample set by using the target analysis method, and the same experiment is the target analysis method. The set composed of the obtained test index parameters is the response value set, and the response value corresponds to the target experimental sample one by one. The specific implementation manner of obtaining a response value is similar to the above-mentioned performing the test operation based on the identification experiment method on the extracted unit group to obtain the test index parameters, and can achieve the same effect, which will not be elaborated here.

[0158] S5. Analyze the response value set by using the pre-constructed standard curve set to obtain a target component concentration value set, and calculate the unit actual concentration corresponding to the target component based on the target component concentration value set.

[0159] Furthermore, the process of analyzing the response value set by using the pre-constructed standard curve set to obtain a target component concentration value set and calculating the unit actual concentration corresponding to the target component based on the target component concentration value set includes:

[0160] Obtain the standard curve set of the historical safety experimental group, identify the historical safety experiment corresponding to the target analysis method in the historical safety experimental group to obtain the target historical experiment, and extract the standard curve corresponding to the target historical experiment from the standard curve set to obtain the target curve;

[0161] Extract the response values from the response value set in sequence, and query the abscissa corresponding to the extracted response value in the target curve to obtain the target component concentration value;

[0162] Summarize the target component concentration values to obtain the target component concentration value set, and calculate the mean of the target component concentration value set to obtain the unit actual concentration.

[0163] It should be noted that constructing a standard curve is a technique in analytical chemistry, instrument detection, etc., which is used to establish a quantitative relationship between concentration and test index parameters through standard samples with known concentrations (a unit group at a certain experimental concentration in the historical safety experiment). The unit actual concentration is the concentration value obtained for the target component in the detection of the target analysis method.

[0164] Further, the method for identifying the historical safety experiment corresponding to the target analysis method in the historical safety experimental group is: find the historical safety experiment corresponding to the same identification experiment method as the target analysis method in the historical safety experimental group.

[0165] S6. Summarize the target component concentration value set, the unit actual concentration, the target analysis method, and the target component to obtain the component data.

[0166] Further, the constructing of the standard curve includes

[0167] Perform the following operations on all the historical safety experiments in the historical safety experimental group:

[0168] Extract the unit groups from the unit group set corresponding to the historical safety experiment in sequence, and extract the experimental concentration and test index parameters corresponding to the unit group to obtain the curve independent variable and the curve dependent variable, where the curve independent variable is the experimental concentration corresponding to the unit group, and the curve dependent variable is the test index parameter corresponding to the unit group;

[0169] Based on the curve independent variable and the curve dependent variable, construct the experimental coordinates corresponding to the historical safety experiment, summarize the experimental coordinates to obtain the experimental coordinate set, use the pre-constructed fitting method to fit the experimental coordinate set into a curve to obtain the initial standard curve, and generate a curve identifier using the historical safety experiment and the safety category label, mark the initial standard curve with the curve identifier, and summarize the marked initial standard curves to obtain the standard curve set.

[0170] It is understandable that the experimental coordinates are two-dimensional coordinates constructed by the curve independent variable and the curve dependent variable, with the abscissa being the curve independent variable and the ordinate being the curve dependent variable. The fitting method can be performed using existing technologies such as MATLAB. The curve identifier is a text identifier used to identify the initial standard curve, and there are multiple existing technologies for the specific identification method, which will not be exemplified here.

[0171] Furthermore, the component data is data composed of logs for recording the experiments of the target analysis method to obtain the actual concentration per unit.

[0172] S7. Summarize the component data to obtain the component data set corresponding to the target experimental group, and calculate the actual concentration of the target component in the target experimental group based on the component data set.

[0173] Furthermore, in one component data, the target component corresponds to only one target analysis method. However, in the actual detection process, using multiple different target analysis methods to test the target component is beneficial to reducing experimental errors. Therefore, in the present invention, operations of obtaining component data based on different target analysis methods are performed on all target experimental groups. Optionally, calculate the mean value of all actual concentrations per unit in the component data set as the actual concentration of the target component, and confirm the actual concentration as the concentration of the target component in the target moisturizing product.

[0174] S8. Summarize the actual concentrations to obtain the actual concentration set corresponding to the target component set, obtain component analysis data based on the actual concentration set, and perform quality control analysis on the target moisturizing product based on the component analysis data to obtain the quality control result.

[0175] Furthermore, the obtaining of component analysis data based on the actual concentration set includes:

[0176] Extract the actual concentrations from the actual concentration set in sequence, and calculate the partial component ratio of the actual concentration. The calculation formula of the partial component ratio is as follows:

[0177]

[0178] where p represents the partial component ratio, r represents the actual concentration, and l represents the ideal concentration value of the target component in the target moisturizing product;

[0179] Combine the target component and the partial component ratio to obtain the unit component data, summarize the unit component data to obtain the initial unit component data set, remove the target component set from the initial component set to obtain the other component set, and construct the other component data set based on the other component set;

[0180] Construct component analysis data based on the other component data set and the initial unit component data set.

[0181] It is understandable that the ideal concentration value is the standard concentration value artificially specified when the target moisturizing product is initially configured, and is used to guide the concentration of the target component in the actual production process of the target moisturizing product. Therefore, the partial component ratio is used to describe the difference between the target component and the ideal concentration value.

[0182] Furthermore, the operation of combining the target component and the partial component ratio is to store the target component and the partial component ratio in the same data, and the obtained data is the unit component data. The method of constructing other component data sets based on other component sets is similar to the method of obtaining the initial unit component data set according to the target component set. Its main purpose is to obtain data such as the partial component ratio and the actual concentration of each other component data in the other component data. Therefore, an other component data should include: other components and the partial component ratio of the other components.

[0183] Furthermore, performing quality control analysis on the target moisturizing product based on the component analysis data to obtain a quality control result, including:

[0184] Sequentially extract component data from the component analysis data, where the extracted component data includes: actual component, actual component concentration, ideal concentration value of the component, actual partial component ratio, safe concentration range corresponding to the actual component, and abnormal concentration range corresponding to the actual component;

[0185] If the actual component concentration is within the safe concentration range corresponding to the actual component, then determine whether the actual partial component ratio is within the preset controllable partial component ratio range. If the actual partial component ratio is within the controllable partial component ratio range, then confirm the component data as the preset initial quality control qualified, otherwise, send a pre-constructed quality control warning message to the pre-constructed test result receiving end;

[0186] If all the component data in the component analysis data are confirmed as the initial quality control qualified, then confirm the target moisturizing product as the preset safe quality control qualified;

[0187] If it is confirmed based on the multiple functional experiments that the target moisturizing product is preset function quality control qualified, then summarize the safe quality control qualified and the function quality control qualified to obtain the quality control result.

[0188] It should be noted that the component analysis data is a set of component data corresponding to all components in the target moisturizing product.

[0189] Furthermore, the component data includes but is not limited to the actual component, the actual component concentration, the ideal concentration value of the component, the actual partial component ratio, the safe concentration range corresponding to the actual component, and the abnormal concentration range corresponding to the actual component. Its purpose is to record the experimental data and experimental results of all components in the target moisturizing product, so as to guide the experimenter to perform quality control analysis on the target moisturizing product.

[0190] It is understandable that the actual ingredient is an ingredient in the target moisturizing product. The actual concentration of the ingredient, the ideal concentration value of the ingredient, the actual deviation ingredient ratio and the deviation ingredient ratio have the same meanings. The safety concentration range corresponding to the actual ingredient and the abnormal concentration range corresponding to the actual ingredient have the same meanings as the skin care safety concentration range and the skin care abnormal concentration range, and will not be elaborated here.

[0191] Furthermore, the controllable deviation ingredient ratio range is an artificially set range of the deviation ingredient ratio. When the deviation ingredient ratio range is not within the controllable deviation ingredient ratio range, it indicates that the addition amount of the actual ingredient in the target moisturizing product is too high (greater than the upper limit of the controllable deviation ingredient ratio range) or too low (less than the lower limit of the controllable deviation ingredient ratio range). The quality control warning information is text used to describe unqualified quality control analysis. For example: "The addition amount of ingredient A is too high".

[0192] It should be noted that the qualified safety quality control means that all ingredients in the target moisturizing product will not have an adverse effect on the skin. Therefore, if it is confirmed based on the multiple functional experiments that the target moisturizing product is qualified for the preset functional quality control, it means that the moisturizing effect of the target moisturizing product can also reach the expected effect set artificially. For the inspection of the moisturizing effect of the target skin care product, there are many existing technologies to achieve it. For example, taking the moisture value change rate of 4% glycerol as the standard, the moisturizing ability of the moisturizer can be judged by the value obtained by dividing the moisture content change rate after applying the moisturizer by the moisture content change rate after using glycerol. Since this technology is an existing technology, it will not be elaborated here.

[0193] To solve the problems described in the background art, the present invention screens the initial ingredient set to obtain a target ingredient set. If the initial ingredient exists in the database, it indicates that the initial ingredient has been detected before the embodiment of the present invention. Therefore, the ingredient information table and historical experimental data corresponding to the initial ingredient can be obtained from the database, which is beneficial to providing a basis for the safety analysis of ingredients by experimental personnel. The following operations are performed on all target experimental groups: Based on the target experimental group, the target ingredients and the target analysis method set are confirmed. For each target analysis method in the target analysis method set, the following operations are performed: Based on the skin moisturizing sample set, the actual concentration is obtained, and the actual concentrations are aggregated to obtain the actual concentration set corresponding to the target ingredient set. The present invention establishes a quantitative relationship between the concentration and the test index parameters through standard samples with known concentrations (a unit group at a certain experimental concentration in historical safety experiments), and the problem of error is considered during the test process. Therefore, multiple different target analysis methods are also used to test the target ingredients, which is beneficial to reducing experimental errors. Therefore, in the present invention, the operations of obtaining ingredient data based on different target analysis methods are performed on all target experimental groups, which is achieved by calculating the mean value corresponding to all unit actual concentrations in the ingredient dataset, and the actual concentration is confirmed as the final concentration of the target ingredient in the target moisturizing product. Ingredient analysis data is obtained based on the actual concentration set, and quality control analysis is performed on the target moisturizing product based on the ingredient analysis data to obtain a quality control result. If the safety quality control is qualified, it means that all ingredients in the target moisturizing product will not have an adverse effect on the skin. Therefore, if it is confirmed that the target moisturizing product is qualified for the preset functional quality control based on the multiple functional experiments, it means that the moisturizing effect of the target moisturizing product can also reach the expected effect set by humans, indicating that the target moisturizing ingredient meets the expectations and the quality control is qualified. Otherwise, a pre-constructed warning message needs to be sent to the pre-constructed test result receiving end. Therefore, the present invention can realize quality control analysis of the ingredients in skin moisturizers using a standard curve.

[0194] As Figure 2 shown, it is a functional module diagram of an ingredient analysis system applied to the preparation of skin moisturizers provided by an embodiment of the present invention.

[0195] The ingredient analysis system 100 applied to the preparation of skin moisturizers according to the present invention can be installed in an electronic device. According to the functions achieved, the ingredient analysis system 100 applied to the preparation of skin moisturizers can include an experimental group module 101, a response value set module 102, an ingredient data module 103, and a quality control module 104. The modules of the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by the processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0196] The experimental group module 101 is used to obtain a target moisturizing product and a skin moisturizing sample set corresponding to the target moisturizing product, obtain an initial ingredient set based on the target moisturizing product, screen the initial ingredient set to obtain a target ingredient set, use a pre-constructed database to obtain an analysis method set corresponding to the target ingredient set, and construct multiple experimental groups based on the skin moisturizing sample set, the target ingredient set, and the analysis method set;

[0197] The response value set module 102 is used to sequentially extract experimental groups from multiple experimental groups to obtain a target experimental group, and perform the following operations on the target experimental group: confirm the target ingredients and the target analysis method set based on the target experimental group, and perform the following operations on the target analysis methods in the target analysis method set: obtain a target experimental sample set corresponding to the target experimental group based on the skin moisturizing sample set, and measure the target ingredients in the target experimental sample set using the target experimental sample set and the target analysis methods to obtain a response value set;

[0198] The ingredient data module 103 is used to analyze the response value set using a pre-constructed standard curve set to obtain a target ingredient concentration value set, calculate the unit actual concentration corresponding to the target ingredient based on the target ingredient concentration value set, and summarize the target ingredient concentration value set, the unit actual concentration, the target analysis method, and the target ingredient to obtain ingredient data;

[0199] The quality control module 104 is used to summarize the ingredient data to obtain an ingredient data set corresponding to the target experimental group, calculate the actual concentration of the target ingredient in the target experimental group based on the ingredient data set, summarize the actual concentrations to obtain an actual concentration set corresponding to the target ingredient set, obtain ingredient analysis data based on the actual concentration set, and perform quality control analysis on the target moisturizing product based on the ingredient analysis data to obtain a quality control result.

[0200] Specifically, each module in the ingredient analysis system 100 applied to the preparation of skin moisturizers in the embodiments of the present invention uses the same technical means as the ingredient analysis method applied to the preparation of skin moisturizers described above Figure 1 and can produce the same technical effects, which will not be elaborated here.

[0201] As Figure 3 shown, it is a schematic structural diagram of an electronic device for implementing an ingredient analysis method applied to the preparation of skin moisturizers provided by an embodiment of the present invention.

[0202] The electronic device 1 may include a processor 10, a memory 11, and a bus 12, and may further include a computer program stored in the memory 11 and executable on the processor 10, such as an ingredient analysis method program applied to the preparation of skin moisturizers.

[0203] Among them, the memory 11 at least includes one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), magnetic memory, magnetic disk, optical disc, etc. The memory 11 can be an internal storage unit of the electronic device 1 in some embodiments, such as the mobile hard disk of the electronic device 1. The memory 11 can also be an external storage device of the electronic device 1 in some other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the electronic device 1. Further, the memory 11 also includes the internal storage unit of the electronic device 1 and also includes an external storage device. The memory 11 can not only be used to store application software installed on the electronic device 1 and various types of data, such as the code of the component analysis method program applied to the preparation of skin moisturizer, etc., but also be used to temporarily store data that has been output or will be output.

[0204] The processor 10 can be composed of integrated circuits in some embodiments. For example, it can be composed of a single packaged integrated circuit, or can also be composed of multiple integrated circuits with the same or different functions packaged, including a combination of one or more Central Processing Units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, connecting various components of the entire electronic device through various interfaces and lines, and by running or executing programs or modules stored in the memory 11 (such as the component analysis method program applied to the preparation of skin moisturizer, etc.), and calling the data stored in the memory 11, to execute various functions of the electronic device 1 and process data.

[0205] The bus 12 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is set to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0206] Figure 3 Only the electronic device with components is shown. Those skilled in the art can understand that, Figure 3The structure shown does not constitute a limitation on the electronic device 1, and it may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0207] For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for powering each component. Preferably, the power source can be logically connected to the at least one processor 10 through a power management system, so as to implement functions such as charge management, discharge management, and power consumption management through the power management system. The power source may also include any components such as one or more DC or AC power sources, a recharge system, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device 1 may also include various sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be elaborated here.

[0208] Further, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0209] Optionally, the electronic device 1 may also include a user interface. The user interface may be a display, an input unit (such as a keyboard), and optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display the information processed in the electronic device 1 and to display a visual user interface.

[0210] The program of the component analysis method applied to the preparation of skin moisturizers stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can implement:

[0211] Obtain a target moisturizing product and a set of skin moisturizing samples corresponding to the target moisturizing product, obtain an initial ingredient set based on the target moisturizing product, screen the initial ingredient set to obtain a target ingredient set, use a pre-constructed database to obtain an analysis method set corresponding to the target ingredient set, and construct multiple experimental groups based on the set of skin moisturizing samples, the target ingredient set, and the analysis method set;

[0212] Extract experimental groups from multiple experimental groups in sequence to obtain a target experimental group, and perform the following operations on each target experimental group:

[0213] Based on the target experimental group, confirm the target components and the set of target analysis methods, and perform the following operations on each target analysis method in the set of target analysis methods:

[0214] Obtain the set of target experimental samples corresponding to the target experimental group based on the skin moisturizing sample set, and measure the target components in the set of target experimental samples using the set of target experimental samples and the target analysis methods to obtain a set of response values;

[0215] Analyze the set of response values using the pre-constructed set of standard curves to obtain a set of target component concentration values, and calculate the unit actual concentration corresponding to the target component based on the set of target component concentration values;

[0216] Summarize the set of target component concentration values, the unit actual concentration, the target analysis methods, and the target components to obtain component data;

[0217] Summarize the component data to obtain the component data set corresponding to the target experimental group, and calculate the actual concentration of the target component in the target experimental group based on the component data set;

[0218] Summarize the actual concentrations to obtain the set of actual concentrations corresponding to the set of target components, obtain component analysis data based on the set of actual concentrations, and perform quality control analysis on the target moisturizing product based on the component analysis data to obtain a quality control result.

[0219] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 the description of the relevant steps in the corresponding embodiments, which will not be elaborated here.

[0220] Furthermore, if the modules / units integrated in the electronic device 1 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or system that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory).

[0221] The present invention also provides a computer-readable storage medium, and the readable storage medium stores a computer program, and when the computer program is executed by the processor of the electronic device, it can implement:

[0222] Obtain the target moisturizing product and the set of skin moisturizing samples corresponding to the target moisturizing product, obtain the initial component set based on the target moisturizing product, screen the initial component set to obtain the set of target components, obtain the set of analysis methods corresponding to the set of target components using the pre-constructed database, and construct multiple experimental groups based on the set of skin moisturizing samples, the set of target components, and the set of analysis methods;

[0223] Sequentially extract experimental groups from multiple experimental groups to obtain a target experimental group, and perform the following operations on all target experimental groups:

[0224] Based on the target experimental group, confirm the target components and the set of target analysis methods, and perform the following operations on all target analysis methods in the set of target analysis methods:

[0225] Obtain a set of target experimental samples corresponding to the target experimental group based on the skin moisturizing sample set, and measure the target components in the set of target experimental samples using the set of target experimental samples and the target analysis methods to obtain a set of response values;

[0226] Analyze the set of response values using a pre-constructed set of standard curves to obtain a set of target component concentration values, and calculate the unit actual concentration corresponding to the target component based on the set of target component concentration values;

[0227] Summarize the set of target component concentration values, the unit actual concentration, the target analysis methods, and the target components to obtain component data;

[0228] Summarize the component data to obtain a component data set corresponding to the target experimental group, and calculate the actual concentration of the target component in the target experimental group based on the component data set;

[0229] Summarize the actual concentrations to obtain a set of actual concentrations corresponding to the set of target components, obtain component analysis data based on the set of actual concentrations, and perform quality control analysis on the target moisturizing product based on the component analysis data to obtain a quality control result.

[0230] In several embodiments provided by the present invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and there may be other division methods in actual implementation.

[0231] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0232] In addition, in each embodiment of the present invention, the functional modules can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware, or in the form of a combination of hardware and software functional modules.

[0233] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0234] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for component analysis in the preparation of skin moisturizers, characterized in that, The method includes: Obtain a target moisturizing product and a skin moisturizing sample set corresponding to the target moisturizing product, obtain an initial ingredient set based on the target moisturizing product, screen the initial ingredient set to obtain a target ingredient set, use a pre-constructed database to obtain an analysis method set corresponding to the target ingredient set, and construct multiple experimental groups based on the skin moisturizing sample set, the target ingredient set, and the analysis method set; Extract experimental groups from multiple experimental groups in sequence to obtain a target experimental group, and perform the following operations on all target experimental groups: Based on the target experimental group, confirm the target ingredients and the target analysis method set, and perform the following operations on the target analysis methods in the target analysis method set: Obtain a target experimental sample set corresponding to the target experimental group based on the skin moisturizing sample set, and measure the target ingredients in the target experimental sample set using the target experimental sample set and the target analysis method to obtain a response value set; Analyze the response value set using a pre-constructed standard curve set to obtain a target ingredient concentration value set, and calculate the unit actual concentration corresponding to the target ingredient based on the target ingredient concentration value set; Summarize the target ingredient concentration value set, the unit actual concentration, the target analysis method, and the target ingredients to obtain ingredient data; Summarize the ingredient data to obtain an ingredient data set corresponding to the target experimental group, and calculate the actual concentration of the target ingredient in the target experimental group based on the ingredient data set; Summarize the actual concentrations to obtain an actual concentration set corresponding to the target ingredient set, obtain ingredient analysis data based on the actual concentration set, and perform quality control analysis on the target moisturizing product based on the ingredient analysis data to obtain a quality control result.

2. The component analysis method applied to the preparation of skin moisturizers according to claim 1, wherein The screening of the initial ingredient set to obtain a target ingredient set includes: Extract initial ingredients from the initial ingredient set in sequence and retrieve the initial ingredients in the database. If the initial ingredient exists in the database, obtain an ingredient information table corresponding to the initial ingredient based on the database. The ingredient information includes: ingredient name, mechanism of action, and common grades, where the common grades include basic ingredients and non-basic ingredients; If the common grade corresponding to the initial ingredient is the basic ingredient, skip the initial ingredient; otherwise, confirm the initial ingredient as a second-priority ingredient to be tested; Obtain the historical detection data of the second-priority ingredient to be tested. If there is no pre-constructed toxicity report in the historical detection data, confirm the second-priority ingredient to be tested as an ingredient to be tested; otherwise, send a pre-constructed warning message to a pre-constructed test result receiving end; If the initial ingredient does not exist in the database, confirm the initial ingredient as an ingredient to be tested; Summarize the ingredients to be tested to obtain a target ingredient set.

3. The component analysis method applied to the preparation of skin moisturizers as described in claim 2, wherein, The obtaining of the historical detection data of the second-priority ingredient to be tested includes: Construct a standard test experiment, where the standard test experiment includes: multiple safety experiments and multiple functional experiments, and the multiple safety experiments include: phototoxicity experiment, irritation experiment, corrosion experiment, and sensitization experiment, and the multiple functional experiments include multiple moisturizing experiments and multiple other efficacy experiments; Obtain a set of safety test methods based on standard test experiments. Among them, the set of safety test methods includes multiple safety test methods, and the multiple safety test methods include: multiple phototoxicity methods, multiple irritation methods, multiple corrosion methods, and multiple sensitization methods; Construct multiple safety category labels based on the multiple phototoxicity methods, multiple irritation methods, multiple corrosion methods, and multiple sensitization methods, and perform labeling operations on the multiple safety test methods using the multiple safety category labels to obtain a set of labeled test methods; Obtain historical detection data based on the set of labeled test methods.

4. The component analysis method applied to the preparation of skin moisturizers according to claim 3, characterized in that, The obtaining of historical detection data based on the set of labeled test methods includes: Obtain the experimental concentration sequence of the sub-preferred test ingredient, sequentially extract the experimental concentrations from the experimental concentration sequence, and obtain the unit experimental group and the unit control group based on the extracted experimental concentrations, and label the unit experimental group and the unit control group using the experimental concentrations to obtain the unit group; Summarize the unit groups to obtain a set of unit groups; Construct a historical safety experimental group using the set of labeled test methods and the set of unit groups. Among them, the historical safety experimental group includes multiple historical safety experiments, and one historical safety experiment includes: one labeled test method and one set of unit groups, and the sets of unit groups corresponding to the multiple historical safety experiments are the same; Perform the following operations on all the historical safety experiments in the historical safety experimental group: Sequentially extract the unit groups from the set of unit groups corresponding to the historical safety experiment, and perform the test operation based on the labeled test method on the extracted unit groups to obtain the test index parameters; If the test index parameters meet the preset test index conditions, obtain the experimental concentration corresponding to the unit group to get the safety concentration value, and merge the safety concentration value and the test index parameters to obtain the unit safety experimental data. Otherwise, confirm the experimental concentration corresponding to the unit group as the preset abnormal concentration value, and merge the abnormal concentration value and the test index parameters to obtain the unit abnormal experimental data; Summarize the unit safety experimental data and the unit abnormal experimental data to obtain the historical unit data corresponding to the historical safety experiment; Summarize the historical unit data to obtain a historical unit data set, and obtain historical detection data based on the historical unit data set.

5. The component analysis method applied to the preparation of skin moisturizers according to claim 4, characterized in that, The obtaining of historical detection data based on the historical unit data set includes: Sequentially extract the historical unit data from the historical unit data set to obtain the target data, and perform the following operations on the target data: If there is no unit safety experimental data in the target data, generate a toxicity report corresponding to the target data based on the sub-preferred test ingredient, historical safety experiment, historical unit data, and safety category label corresponding to the target data; If there is unit safety experimental data in the target data, extract and summarize the safety concentration values corresponding to all the unit safety experimental data in the target data to obtain a set of safety concentration values, and construct a unit safety concentration interval corresponding to the target data based on the set of safety concentration values; Summarize the unit safety concentration intervals according to multiple safety category labels respectively to obtain multiple category safety interval sets corresponding to the historical unit data set; Calculate the skin care safety concentration interval and the skin care abnormal concentration interval based on the multiple category safety interval sets; If the intersection between the skin care safety concentration range and the skin care abnormal concentration range is a preset empty set, a safety report of the secondary preferred test ingredient is constructed based on the skin care safety concentration range, the skin care abnormal concentration range, and multiple category safety range sets; Otherwise, the updated safety concentration range and the updated abnormal concentration range are calculated based on the skin care safety concentration range and the skin care abnormal concentration range, and a safety report of the secondary preferred test ingredient is constructed based on the updated safety concentration range and the updated abnormal concentration range. The safety report and the toxicity report are summarized to obtain historical detection data. The calculation formulas for the updated safety concentration range and the updated abnormal concentration range are as follows: Among them, represents the updated safe concentration range, C a represents the skin care safe concentration range, \ represents the difference set operator, ∩ represents the intersection operator, C Y represents the skin care abnormal concentration range, represents the updated abnormal concentration range, ∪ represents the union operator.

6. The component analysis method applied to the preparation of skin moisturizers according to claim 5, characterized in that, Calculating the skin care safety concentration range and the skin care abnormal concentration range based on multiple category safety range sets includes: Performing the following operations on each category safety range set in the multiple category safety range sets: Calculating the total experimental range based on the experimental concentration sequence; Calculating the intersection of the category safety range sets to obtain the category safety range, and calculating the complement of the category safety range in the total experimental range to obtain the category abnormal range; Summarizing the category safety ranges, and calculating the intersection of the summarized category safety ranges to obtain the skin care safety concentration range of the secondary preferred test ingredient. Summarizing the category abnormal ranges, and calculating the union of the summarized category abnormal ranges to obtain the skin care abnormal concentration range.

7. The component analysis method applied to the preparation of skin moisturizers according to claim 6, characterized in that, Analyzing the response value set using the pre-constructed standard curve set to obtain the target ingredient concentration value set, and calculating the unit actual concentration corresponding to the target ingredient based on the target ingredient concentration value set includes: Obtaining the standard curve set of the historical safety experimental group, identifying the historical safety experiment corresponding to the target analysis method in the historical safety experimental group to obtain the target historical experiment, and extracting the standard curve corresponding to the target historical experiment from the standard curve set to obtain the target curve; Sequentially extracting response values from the response value set, and querying the abscissa corresponding to the extracted response value in the target curve to obtain the target ingredient concentration value; Summarizing the target ingredient concentration values to obtain the target ingredient concentration value set, and calculating the mean value of the target ingredient concentration value set to obtain the unit actual concentration.

8. The component analysis method applied to the preparation of skin moisturizers according to claim 7, characterized in that, Obtaining the ingredient analysis data based on the actual concentration set includes: Sequentially extracting the actual concentrations from the actual concentration set, and calculating the partial component ratio of the actual concentration. The calculation formula for the partial component ratio is as follows: Where p represents the partial component ratio, r represents the actual concentration, and l represents the ideal concentration value of the target ingredient in the target moisturizing product; Combining the target ingredient and the partial component ratio to obtain the unit ingredient data. Summarizing the unit ingredient data to obtain the initial unit ingredient data set. Removing the target ingredient set from the initial ingredient set to obtain the other ingredient set, and constructing the other ingredient data set based on the other ingredient set; Constructing the ingredient analysis data based on the other ingredient data set and the initial unit ingredient data set.

9. The component analysis method applied to the preparation of skin moisturizers according to claim 8, characterized in that, Performing quality control analysis on the target moisturizing product based on the ingredient analysis data to obtain the quality control result includes: Sequentially extracting ingredient data from the ingredient analysis data. The extracted ingredient data includes: actual ingredient, actual ingredient concentration, ideal concentration value of the ingredient, actual partial component ratio, safety concentration range corresponding to the actual ingredient, and abnormal concentration range corresponding to the actual ingredient; If the actual concentration of the component is within the safety concentration range corresponding to the actual component, determine whether the actual deviation component ratio is within the preset controllable deviation component ratio range. If the actual deviation component ratio is within the controllable deviation component ratio range, confirm the component data as the preset initial quality control qualified; otherwise, send the pre-constructed quality control warning information to the pre-constructed test result receiver. If all the component data in the component analysis data are confirmed as the initial quality control qualified, confirm the target moisturizing product as the preset safety quality control qualified. If it is confirmed that the target moisturizing product is preset function quality control qualified based on the multiple functional experiments, summarize the safety quality control qualified and the function quality control qualified to obtain the quality control result.

10. An ingredient analysis system applied to the preparation of skin moisturizers, characterized in that, The system includes: An experimental group module, configured to obtain a target moisturizing product and a skin moisturizing sample set corresponding to the target moisturizing product, obtain an initial component set based on the target moisturizing product, screen the initial component set to obtain a target component set, use a pre-constructed database to obtain an analysis method set corresponding to the target component set, and construct multiple experimental groups based on the skin moisturizing sample set, the target component set, and the analysis method set. A response value set module, configured to sequentially extract experimental groups from the multiple experimental groups to obtain a target experimental group, and perform the following operations on all the target experimental groups: confirm the target component and the target analysis method set based on the target experimental group, and perform the following operations on the target analysis methods in the target analysis method set: obtain a target experimental sample set corresponding to the target experimental group based on the skin moisturizing sample set, and measure the target component in the target experimental sample set using the target experimental sample set and the target analysis method to obtain a response value set. A component data module, configured to parse the response value set using a pre-constructed standard curve set to obtain a target component concentration value set, calculate the unit actual concentration corresponding to the target component based on the target component concentration value set, summarize the target component concentration value set, the unit actual concentration, the target analysis method, and the target component to obtain component data. A quality control module, configured to summarize the component data to obtain a component data set corresponding to the target experimental group, calculate the actual concentration of the target component in the target experimental group based on the component data set, summarize the actual concentrations to obtain an actual concentration set corresponding to the target component set, obtain component analysis data based on the actual concentration set, and perform quality control analysis on the target moisturizing product based on the component analysis data to obtain a quality control result.

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