Method for simultaneously detecting protein content and sodium chloride content in heparin sodium mixture on line

Abstract

The invention relates to the technical field of substance detection, in particular to a method for simultaneous online detection of protein content and sodium chloride content in a heparin sodium mixture. According to the method for simultaneously detecting the protein content and the sodium chloride content in the heparin sodium mixture on line, a double-layer model of'spectrum-protein content prediction 'and'protein content prediction value + density-sodium chloride content prediction' is established by introducing a density index, so that the weakness of near infrared in the aspect of inorganic matter quantification is effectively solved, and the accuracy of detection is improved. The two indexes of the protein content and the sodium chloride content in the heparin sodium mixture are monitored on line at the same time, and a technical basis is provided for industrial automatic production.

Description

Technical Field

[0001] The invention relates to the technical field of material detection, and in particular to a method for simultaneously online detecting protein content and sodium chloride content in a heparin sodium mixture. Background Art

[0002] Heparin sodium is a sodium salt of aminoglucosan sulfate extracted from the pig small intestinal mucosa, which has the effect of delaying blood clotting time. Injection preparations made from heparin sodium as a raw material are classic anticoagulant drugs and are widely used to prevent thrombosis and embolism, as well as other anticoagulant scenarios in vivo and in vitro.

[0003] At present, the extraction process of sodium heparin mostly adopts the "enzymatic method" - collecting the pig small intestinal mucosa in the enzymatic tank, adding protease for hydrolysis, and then adding resin to absorb and enrich the sodium heparin from the enzymatic solution. In this process, there are two key parameters that directly affect the product yield and purity - the amount of mucosa added and the salt content of the enzymatic solution. Among them, the amount of mucosa added is the amount of raw material added, and the subsequent amount of protease and resin added will be calculated based on this. However, in actual production, the small intestinal mucosa is collected by water scraping. The raw material is a solid-liquid mixture, and the water content is affected by the processing process and fluctuates greatly. At present, sodium heparin manufacturers all use the progress of scraping to calculate the amount of mucosa added, but this method uses the number of small intestine roots as the unit of measurement, does not fully consider the difference in the average weight of different pig small intestine roots, and cannot reflect the actual total amount of enzymatic substrate. Secondly, when using resin adsorption, sodium chloride needs to be added and a certain ion concentration "threshold" needs to be set to prevent a large amount of impurity proteins from competing with sodium heparin for adsorption, thereby ensuring the adsorption effect and enrichment purity of sodium heparin. At present, heparin sodium manufacturers all use the Baume meter as a salinity detection method, but this method actually measures the density of the enzymatic solution, which is not only greatly affected by the sampling temperature of the feed solution, but also interfered by non-salt solutes in the enzymatic solution, and cannot truly reflect the salt content of the feed solution. Moreover, the records of the above two indicators are completed manually, lacking traceability.

[0004] As an online detection technology that has developed rapidly in recent years, near-infrared technology has been widely used in grain, oil, dairy, chemical and other fields due to its advantages such as rapidity and non-destructiveness. However, its detection objects are all solid or liquid samples with uniform texture, and there is no detection case of solid-liquid mixtures such as heparin sodium before enzymatic hydrolysis. In addition, near-infrared spectroscopy records the double frequency and combined frequency absorption of the vibration of hydrogen-containing groups XH (X can be C, N, O), and theoretically cannot detect the sodium chloride content.

[0005] At present, there is no report on the simultaneous online detection of organic and inorganic substances in heparin sodium hydrolysate and solid-liquid mixture before hydrolysis by near infrared. Summary of the invention

[0006] The present invention aims to solve one of the technical problems in the related art at least to a certain extent. To this end, one purpose of the present invention is to provide a method for simultaneously online detecting the protein content and sodium chloride content in a heparin sodium mixture (heparin sodium enzymolysis solution and heparin sodium to be enzymolysis solution in a solid-liquid mixed state), by introducing the density index through the method of the present invention, establishing a double-layer model of "spectrum → protein content prediction" and "protein content prediction value + density → sodium chloride content prediction", effectively solving the short board of near infrared in the quantitative aspect of inorganic matter, realizing the simultaneous online monitoring of the two indicators of protein content and sodium chloride content of the heparin sodium mixture, and providing a technical basis for the industry's automated production.

[0007] To this end, the first aspect of the present invention provides a method for simultaneously online detecting the protein content and sodium chloride content of a heparin sodium mixture. According to an embodiment of the present invention, the method comprises:

[0008] (1) obtaining near infrared spectral data, density, protein content, and sodium chloride content of multiple groups of heparin sodium mixtures to be tested;

[0009] (2) establishing a prediction model 1 of the near infrared spectroscopy data and protein content;

[0010] (3) establishing a prediction model 2 for the protein content, density and sodium chloride content;

[0011] (4) using the prediction model 1 to obtain a predicted protein content based on the near infrared spectroscopy data of the heparin sodium mixture to be tested;

[0012] (5) Based on the predicted protein content obtained in (4) and the measured density value of the heparin sodium mixture to be tested, the prediction model 2 is used to obtain the predicted sodium chloride content of the heparin sodium mixture to be tested.

[0013] At present, the extraction process of sodium heparin mostly adopts the "enzymatic hydrolysis method" - collecting the pig small intestinal mucosa in the enzymatic hydrolysis tank, adding protease for hydrolysis, and then adding resin to absorb and enrich the sodium heparin from the enzymatic hydrolyzate. In this process, there are two key parameters that directly affect the product yield and purity - the amount of mucosa added and the salt content of the enzymatic hydrolyzate (the sodium chloride content of the enzymatic hydrolyzate). The most accurate detection method for these two parameters is to use laboratory physical and chemical analysis, but this method is an offline detection, which takes a long time and cannot guide workshop production in real time.

[0014] Although near infrared technology is widely used in the fields of grain, oil, dairy products, chemical industry, etc., its detection object is generally a solid or liquid sample with uniform texture, and there is no detection case of a solid-liquid mixture similar to heparin sodium to be enzymolyzed solution (mixture before enzymolysis). The inventor found through experimental research that the method of the present invention can be used for heparin sodium to be enzymolyzed solution in a solid-liquid mixed state before small intestinal mucosal enzymolysis and heparin sodium enzymolyzed solution with uniform texture. In addition, near infrared spectroscopy online analysis of material protein content is more commonly used, but near infrared spectroscopy records the frequency doubling and combined frequency absorption of hydrogen-containing groups XH (X can be C, N, O) vibration, and theoretically sodium chloride content cannot be directly detected; although the sodium chloride ion concentration will affect the change of the absorption peak of water, it is also possible to directly predict the salt content through near infrared spectroscopy; but due to the strong background absorption of water itself is the main interference factor of near infrared quantitative analysis, according to the research of the present invention, the prediction model directly using near infrared to quantify salt content has poor anti-interference ability, which is only effective in a relatively narrow range, and when the components of the enzymolyzed solution change, especially when the material concentration is low, the prediction error increases significantly.

[0015] To solve the above problems, the inventors used near-infrared technology for the first time to collect the near-infrared spectrum of the solid-liquid mixture of sodium heparin hydrolyzate. By introducing the density indicator, a double-layer model of "spectrum → protein content prediction" and "protein content prediction value + density → sodium chloride content prediction" was established, which effectively solved the shortcomings of near-infrared in the quantification of inorganic matter, and realized the simultaneous online monitoring of the two indicators of protein content and sodium chloride content in the sodium heparin mixture, providing a technical basis for the industry's automatic production.

[0016] According to an embodiment of the present invention, the plurality of groups of heparin sodium mixtures include at least 80 groups. Those skilled in the art will appreciate that when more heparin sodium mixtures are tested, the predicted value obtained will be more accurate.

[0017] According to an embodiment of the present invention, the protein content in step (1) is detected by Kjeldahl method.

[0018] According to an embodiment of the present invention, the sodium chloride content in step (1) is detected by silver nitrate titration.

[0019] According to an embodiment of the present invention, the near-infrared spectral data in step (1) is collected by an online near-infrared analyzer.

[0020] According to an embodiment of the present invention, the density index in step (1) is collected by an online density meter.

[0021] According to an embodiment of the present invention, the method further comprises:

[0022] Before constructing the prediction model 1, the near infrared spectrum data is preprocessed.

[0023] According to an embodiment of the present invention, the preprocessing includes performing at least one of Savitzky-Golay convolution derivation, SNV, and detrending algorithm on the near-infrared spectral data.

[0024] According to an embodiment of the present invention, the Model 1 and Model 2 are established by partial least squares regression analysis.

[0025] According to an embodiment of the present invention, when establishing Model 1 and Model 2, abnormal data are eliminated based on the cross-validation results in the calibration set.

[0026] According to an embodiment of the present invention, the heparin sodium mixture includes heparin sodium hydrolysis solution before small intestinal mucosal hydrolysis and / or heparin sodium hydrolysis solution after small intestinal mucosal hydrolysis, wherein the heparin sodium hydrolysis solution is in a solid-liquid mixed state.

[0027] According to an embodiment of the present invention, the enzyme comprises a protease and / or a pancreatin.

[0028] According to an embodiment of the present invention, the small intestinal mucosa is from pig.

[0029] A second aspect of the present invention provides a method for quality control of the protein content and sodium chloride content of a heparin sodium mixture during the production process of heparin sodium. According to an embodiment of the present invention, the method comprises:

[0030] The method for simultaneously online detecting the protein content and sodium chloride content of the heparin sodium mixture described in the first aspect is used to predict the protein content and sodium chloride content of the heparin sodium mixture sample derived from the production process, and the predicted protein content and sodium chloride content values ​​are compared with the target protein content value and the target sodium chloride content value to determine whether the heparin sodium mixture sample meets expectations.

[0031] The setting method and setting value of the "target value" are not particularly limited. It can be a measured value obtained by a technician in this field through actual testing of one or more existing or marketed heparin sodium products, or it can be an arbitrary value pre-set according to actual needs.

[0032] According to an embodiment of the present invention, the heparin sodium mixture includes heparin sodium hydrolysis solution before small intestinal mucosal hydrolysis and / or heparin sodium hydrolysis solution after small intestinal mucosal hydrolysis, wherein the heparin sodium hydrolysis solution is in a solid-liquid mixed state.

[0033] Beneficial effects of the present invention:

[0034] The present invention introduces the density index and utilizes the constructed double-layer model of "spectrum → protein content prediction" and "protein content prediction value + density → sodium chloride content prediction" to solve the shortcoming of near-infrared, a mature online monitoring technology, in the quantification of inorganic matter. It can simultaneously realize the real-time quantification of two indicators, organic matter (protein content) and inorganic matter (sodium chloride content), which not only solves the monitoring needs of the links before and after heparin sodium enzymatic hydrolysis, but also can be applied to similar fields such as enzymatic hydrolysis and fermentation.

[0035] Especially, due to the lack of online detection technology of key parameters, the industry cannot realize automatic control of heparin sodium enzymolysis process at this stage. Using the method described in the present invention, the raw material addition amount (protein content) and sodium chloride content of the enzymolysis process can be obtained in real time and losslessly, and after the monitoring signal is connected to the workshop control, the automatic addition of the feed liquid and the automatic adjustment of the salinity can be realized, which not only reduces the labor intensity of the workers' sampling and adjusting the material ratio, but also realizes the online tracing and standardized operation of the production process indicators, which will greatly improve the production level of the heparin sodium enzymolysis process, and is conducive to the stability of product quality and the improvement of yield indicators.

[0036] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0038] Figure 1 A logic diagram showing model building and prediction according to one embodiment of the present invention;

[0039] Figure 2 The raw NIR spectra of 81 enzymatic hydrolysate samples are shown;

[0040] Figure 3 The spectra of 81 samples after SNV-SG first-order derivative preprocessing are shown;

[0041] Figure 4 The cross-validation effect of model 1 (predicting protein content with spectral data) is shown;

[0042] Figure 5 The interactive validation effect of Model 2 (predicting sodium chloride content by density and protein content) is shown;

[0043] Figure 6 The effect of predicting the protein content of out-group samples by model 1 is shown;

[0044] Figure 7The effect of model 2 in predicting the sodium chloride content of the out-group samples is shown. DETAILED DESCRIPTION

[0045] The embodiments of the present invention are described in detail below. The embodiments described below are exemplary and are only used to explain the present invention, and should not be understood as limiting the present invention.

[0046] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. Further, in the description of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0047] The endpoints and any values ​​of the ranges disclosed in this article are not limited to the precise ranges or values, and these ranges or values ​​should be understood to include values ​​close to these ranges or values. For numerical ranges, the endpoint values ​​of each range, the endpoint values ​​of each range and the individual point values, and the individual point values ​​can be combined with each other to obtain one or more new numerical ranges, which should be considered as specifically disclosed in this article.

[0048] In order to make the present invention more easily understood, certain technical and scientific terms are specifically defined below. Unless otherwise clearly defined elsewhere in this document, all other technical and scientific terms used herein have the meanings commonly understood by those skilled in the art to which the present invention belongs.

[0049] In this document, the terms “include” or “comprising” are open expressions, that is, including the contents specified in the present invention but not excluding other contents.

[0050] As used herein, the terms "optionally", "optional" or "optionally" generally mean that the subsequently described event or circumstance may but need not occur, and that the description includes instances where the event or circumstance occurs and instances where it does not.

[0051] According to a specific embodiment of the present invention, the present invention provides a method for simultaneously online detecting the protein content and sodium chloride content of a heparin sodium mixture, the method comprising:

[0052] (1) obtaining near infrared spectral data, density, protein content, and sodium chloride content of multiple groups of heparin sodium mixtures to be tested;

[0053] (2) establishing a prediction model 1 of the near infrared spectroscopy data and protein content;

[0054] (3) establishing a prediction model 2 for the protein content, density and sodium chloride content;

[0055] (4) using the prediction model 1 to obtain a predicted protein content based on the near infrared spectroscopy data of the heparin sodium mixture to be tested;

[0056] (5) Based on the predicted protein content obtained in (4) and the measured density value of the heparin sodium mixture to be tested, the prediction model 2 is used to obtain the predicted sodium chloride content of the heparin sodium mixture to be tested.

[0057] The logic diagram of model building and prediction of one embodiment of the present invention is as follows: Figure 1 shown.

[0058] The present invention establishes a double-layer model of "spectrum → protein content prediction" and "protein content prediction value + density → sodium chloride content prediction", and acquires two types of online data, near-infrared spectrum and density. The model can be used to perform real-time online analysis on the hydrolyzate to be processed or the hydrolyzate, and two production parameters, protein content and sodium chloride content, can be obtained at the same time.

[0059] In particular, the present invention provides a new method for detecting inorganic content. Because the protein content, sodium chloride content and enzymatic hydrolysate density are in an ideal binary linear relationship, after predicting the protein content by near infrared, the sodium chloride content can be predicted from the density and protein content. Compared with directly using near infrared to predict salt content, this method has strong anti-interference ability, is less affected by the material concentration range, and has strong applicability.

[0060] The present invention provides a method for obtaining the protein content and sodium chloride content of a heparin sodium mixture in real time by using near infrared and density online detection. The method utilizes the binary linear regression relationship between solution density and protein content and sodium chloride content, and by adding the detection of density index, the content of organic matter and inorganic matter in a solution to be hydrolyzed or in a hydrolyzed solution can be obtained simultaneously, thereby solving the problem that it is difficult to quantify inorganic salts such as sodium chloride by near infrared.

[0061] According to a specific embodiment of the present invention, the plurality of groups of heparin sodium mixtures to be tested include at least 80 groups. For example, the plurality of groups of heparin sodium mixtures to be tested may be 100 groups, 150 groups, 200 groups, 250 groups, 500 groups or more.

[0062] According to a specific embodiment of the present invention, the protein content in step (1) includes but is not limited to being detected by the Kjeldahl method.

[0063] According to a specific embodiment of the present invention, the sodium chloride content in step (1) is detected by silver nitrate titration.

[0064] According to a specific embodiment of the present invention, the near infrared spectrum data in step (1) can be collected by an online near infrared analyzer. The optional equipment can be, for example, a diffuse reflectance near infrared analyzer.

[0065] According to a specific embodiment of the present invention, the density index in step (1) includes but is not limited to being collected by an online density meter. The optional device may be, for example, a differential pressure density meter.

[0066] According to a specific embodiment of the present invention, the method further comprises:

[0067] Before constructing the prediction model 1, the near infrared spectrum data is preprocessed.

[0068] According to a specific embodiment of the present invention, the preprocessing includes but is not limited to performing at least one of Savitzky-Golay convolution derivation, SNV, and detrending algorithms on the near-infrared spectral data.

[0069] For example, the preprocessing may be to perform Savitzky-Golay convolution derivation on the near-infrared spectral data only, or to perform SNV processing on the near-infrared spectral data only, or to perform detrending algorithm processing on the near-infrared spectral data only; or, the preprocessing may be to perform Savitzky-Golay convolution derivation and SNV processing on the near-infrared spectral data, or the preprocessing may be to perform Savitzky-Golay convolution derivation and detrending algorithm processing on the near-infrared spectral data, or the preprocessing may be to perform SNV and detrending algorithm processing on the near-infrared spectral data; or the preprocessing may be to perform Savitzky-Golay convolution derivation, SNV and detrending algorithm processing on the near-infrared spectral data. In addition, the processing order of the various processing methods used in the preprocessing is not particularly limited, and any combination of the various methods and any order change can be used in the present application.

[0070] According to a specific embodiment of the present invention, the model 1 and the model 2 are established by partial least squares regression analysis.

[0071] According to a specific embodiment of the present invention, when establishing Model 1 and Model 2, abnormal data are eliminated based on the cross-validation results in the calibration set.

[0072] According to a specific embodiment of the present invention, the heparin sodium mixture includes heparin sodium hydrolysis solution before small intestinal mucosal hydrolysis and / or heparin sodium hydrolysis solution after small intestinal mucosal hydrolysis, wherein the heparin sodium hydrolysis solution is in a solid-liquid mixed state.

[0073] According to a specific embodiment of the present invention, the enzyme comprises protease and / or pancreatin.

[0074] According to a specific embodiment of the present invention, the small intestinal mucosa is from pig.

[0075] The present invention also provides a method for quality control of protein content and sodium chloride content of a heparin sodium mixture during the production process of heparin sodium, the method comprising:

[0076] The protein content and sodium chloride content are predicted using the method for simultaneously online detecting the protein content and sodium chloride content in the heparin sodium mixture as described above, and the predicted protein content and sodium chloride content values ​​are compared with the standard values ​​of protein content and sodium chloride content obtained by the test to determine whether the sample meets the standard.

[0077] According to a specific embodiment of the present invention, the heparin sodium mixture includes heparin sodium hydrolysis solution before small intestinal mucosal hydrolysis and / or heparin sodium hydrolysis solution after small intestinal mucosal hydrolysis, wherein the heparin sodium hydrolysis solution is in a solid-liquid mixed state.

[0078] According to a specific embodiment of the present invention, the present invention uses an online near-infrared spectrometer and a densitometer to analyze the heparin sodium to be enzymolyzed liquid in a solid-liquid mixed state or the heparin sodium mixture in a liquid state with uniform texture online, obtain spectral data and density values, and synchronously sample, and perform physical and chemical tests on the protein content (indicating the amount of mucosal addition) and sodium chloride content of the feed liquid; Then, the spectral data is preprocessed using SG convolution derivation, SNV (standard normal variable transformation), detrending algorithm, etc., and a regression model (model 1) between spectral data and protein content is established using partial least squares regression analysis, and a regression model (model 2) between protein content, density and sodium chloride content is established at the same time. During prediction, model 1 can be used to obtain the predicted value of the protein content of the material through the spectrum, and then model 2 is used to obtain the predicted value of the sodium chloride content through the density and the protein content prediction value just obtained.

[0079] This method can ultimately use two mature online monitoring technologies, near-infrared spectroscopy and density meter, and a double-layer model to obtain real-time predicted values ​​of the protein content and sodium chloride content of the hydrolyzate and / or the hydrolyzate, improve production guidance and standardization, and realize data traceability of the production process, providing the necessary technical foundation for the implementation of automated production in this industry.

[0080] The scheme of the present disclosure will be explained below in conjunction with the examples. It will be appreciated by those skilled in the art that the following examples are only used to illustrate the present disclosure and should not be considered as limiting the scope of the present disclosure. Where specific techniques or conditions are not indicated in the examples, the techniques or conditions described in the literature in this area or the product instructions are used. The reagents or instruments used that do not indicate the manufacturer are all conventional products that can be obtained commercially.

[0081] Example 1 Method for simultaneously online detection of protein content and sodium chloride content in heparin sodium enzymatic hydrolyzate

[0082] Specific process: 81 random enzymatic hydrolyzate samples with a protein content of 0-6% and a sodium chloride content of 0-6% were taken, wherein the enzymatic hydrolyzate samples were obtained by enzymatic hydrolysis of pig small intestinal mucosa. During the experimental detection process, the absorption spectrum of each sample was collected at 950-1650nm, with a wavelength interval of 5nm (the equipment is Platinum Elmer's DA7440, electrically cooled diode array indium gallium arsenic detector, acquisition speed> 30 full spectra / second, spot diameter 10cm). At the same time, a differential pressure online densitometer was used to detect the material density, and the enzymatic hydrolyzate was sampled. The protein content was measured by the Kjeldahl nitrogen method (nitrogen content*6.25=protein content), and the sodium chloride content was measured by silver nitrate titration. Among them, the original near-infrared spectra of 81 enzymatic hydrolyzate samples are shown below. Figure 2 shown.

[0083] The spectral data, density, protein content, and sodium chloride content of the above 81 samples were used as calibration data. CAMO's "The Unscrambler" software was used to preprocess the spectral data using SNV (standard normal variable transformation) and Savitzky-Golay convolution derivative (first-order derivative) to eliminate the background interference and baseline drift of the spectrum. The spectra of the 81 samples after SNV-SG first-order derivative preprocessing are shown in the figure below. Figure 3 shown.

[0084] Then, partial least squares regression analysis (PLS) was used to establish the prediction models of "spectral data→protein content" and "(density+protein content)→sodium chloride content", respectively. The abnormal data were eliminated according to the cross-validation results in the calibration set, and the optimized model 1 (predicting protein content with spectral data) and model 2 (predicting sodium chloride content with (density+protein content)) were obtained. Figure 4 and Figure 5 The interactive validation (within-group validation) effects of Model 1 and Model 2 are shown respectively.

[0085] When using the model for real-time production prediction, it is only necessary to obtain the near-infrared spectrum and density data of the material online, and then the predicted values ​​of the protein content and sodium chloride content of the sample to be tested can be obtained through the established Model 1 and Model 2, respectively. The former is obtained by inputting spectral data into Model 1 for prediction, and the latter is obtained by inputting the predicted value of protein content (predicted by Model 1) and the actual measured value of density into Model 2 for prediction. Figure 6 The results show the effect of using model 1 to predict the protein content of 9 out-of-group samples. Figure 7 The effect of model 2 in predicting the sodium chloride content of 9 out-of-group samples is demonstrated.

[0086] In the implementation case of the present invention, according to Figure 6 and Figure 7 According to the results analysis, the RMSEP (root mean square error of prediction) of the protein content in the enzymatic hydrolysate by model 1 is 0.0013357, that is, the average error between the predicted value of the protein content (model prediction) and the measured value (chemical detection) is ±0.13% (the protein content range of the samples is 0-6%); the RMSEP (root mean square error of prediction) of the sodium chloride content in the enzymatic hydrolysate by model 2 is 0.0010266, that is, the average error between the predicted value of the sodium chloride content (model prediction) and the measured value (chemical detection) is ±0.10% (the sodium chloride content of the samples is 0-6%); the accuracy of the two data is much higher than that of the current detection technology in production, and can better meet the needs of guiding production.

[0087] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", "some implementation schemes" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0088] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for simultaneously online detecting the protein content and sodium chloride content in a heparin sodium mixture, characterized in that: include: (1) obtaining near infrared spectral data, density, protein content, and sodium chloride content of multiple groups of heparin sodium mixtures to be tested; (2) establishing a prediction model 1 of the near infrared spectroscopy data and protein content; (3) establishing a prediction model 2 for the protein content, density and sodium chloride content; (4) using the prediction model 1 to obtain a predicted protein content based on the near infrared spectroscopy data of the heparin sodium mixture to be tested; (5) Based on the predicted protein content obtained in (4) and the measured density value of the heparin sodium mixture to be tested, the prediction model 2 is used to obtain the predicted sodium chloride content of the heparin sodium mixture to be tested.

2. The method according to claim 1, characterized in that The plurality of groups of heparin sodium mixtures to be tested include at least 80 groups.

3. The method according to claim 1, characterized in that: The protein content in step (1) is determined by the Kjeldahl method.

4. The method according to claim 1, characterized in that The method further comprises: Before constructing the prediction model 1, the near infrared spectrum data is preprocessed.

5. The method according to claim 1, characterized in that The model 1 and model 2 were established through partial least squares regression analysis.

6. The method according to claim 1, characterized in that When establishing Model 1 and Model 2, abnormal data were eliminated based on the cross-validation results in the calibration set.

7. The method according to claim 1, characterized in that The heparin sodium mixture includes heparin sodium solution to be hydrolyzed before small intestinal mucosal hydrolysis and / or heparin sodium hydrolyzed solution after small intestinal mucosal hydrolysis, wherein the heparin sodium solution to be hydrolyzed is in a solid-liquid mixed state.

8. The method according to claim 4, characterized in that The preprocessing includes performing at least one of Savitzky-Golay convolution derivation, SNV, and detrending algorithm on the near-infrared spectral data.

9. The method according to claim 7, characterized in that: The enzymes include proteases and / or pancreatin.

10. A method for quality control of protein content and sodium chloride content in a heparin sodium mixture during the production process of heparin sodium, characterized in that: The method comprises: The method for simultaneously online detecting the protein content and the sodium chloride content in the sodium heparin mixture according to any one of claims 1 to 9 is used to predict the protein content and the sodium chloride content of the sodium heparin mixture sample derived from the production process, and the predicted protein content and sodium chloride content values ​​are compared with the target protein content value and the target sodium chloride content value to determine whether the sodium heparin mixture sample meets expectations.

11. The method according to claim 10, characterized in that The heparin sodium mixture includes heparin sodium solution to be hydrolyzed before small intestinal mucosal hydrolysis and / or heparin sodium hydrolyzed solution after small intestinal mucosal hydrolysis, wherein the heparin sodium solution to be hydrolyzed is in a solid-liquid mixed state.

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