CN110887810A - Method for evaluating quality consistency of Xuesaitong dropping pills based on near infrared spectrum technology - Google Patents
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- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
Abstract
The invention discloses a method for evaluating the batch quality consistency of Xuesaitong dropping pills based on a near infrared spectrum technology, which comprises the following steps of firstly, selecting Xuesaitong dropping pills of different batches of the same manufacturer as samples, randomly extracting a sample from the samples to optimize a near infrared spectrum acquisition condition, and performing spectrum acquisition on the samples under the optimized acquisition condition; then, selecting a proper spectrum waveband for modeling, and preprocessing the spectrum; and finally, analyzing and integrating the spectral data by using a multivariate analysis tool, establishing a quality consistency inspection model of the Xuesaitong dripping pill samples, setting control limits for the quality of different batches of samples, evaluating the quality of the samples to be tested by using the established evaluation model and the control limits obtained by calculation, wherein the samples exceeding the control limits are abnormal samples, and otherwise, the sample quality consistency is better. The evaluation method is beneficial to improving the quality control level in the production process, ensures the stable and controllable product quality and has wide application value.
Description
Technical Field
The invention relates to a quality consistency evaluation method of a Xuesaitong dropping pill sample, in particular to a method which can simply, conveniently, rapidly, scientifically and accurately evaluate the quality consistency of different batches of dropping pill samples based on the combination of a near infrared spectrum technology and a related chemometrics technology, and belongs to the technical field of traditional Chinese medicine detection and quality control.
Background
The Xuesaitong dripping pill is prepared with notoginseng total saponin and proper amount of polyglycol, and has the features of fast dissolving out speed, high bioavailability, high curative effect, less toxic side effect, convenient storage and carrying, simple preparation, etc. The Chinese medicinal composition has the main effects of promoting blood circulation to remove blood stasis, dredging collaterals and activating collaterals, inhibiting platelet aggregation, increasing cerebral blood flow and the like, and is clinically used for treating symptoms such as cerebral collateral stasis, apoplexy, hemiplegia, thoracic obstruction, cardiodynia, coronary heart disease, angina pectoris and the like.
Currently, the quality consistency of medicines is about the safety of clinical curative effect, and how to evaluate the batch consistency of the quality of the medicines becomes a key common problem in the internationalization process of traditional Chinese medicines. In recent years, the quality consistency evaluation research of the Xuesaitong dropping pills is less, and the evaluation and detection means mainly based on the Xuesaitong dropping pills are thin-layer chromatography, liquid chromatography and the developed mature fingerprint spectrum similarity evaluation. The technologies are mainly based on an off-line detection means, the pretreatment process of the sample is complicated, and the consumed time is long; the consumption of chemical reagents is serious, so that environmental pollution is easily caused and the detection cost is increased; and is susceptible to subjective factors. Therefore, it is necessary to develop a simple, convenient, fast and accurate evaluation method.
The near infrared spectrum is electromagnetic radiation wave between visible light and middle infrared, has the wavelength range of 780-2526 nm, and has the characteristics of high analysis speed, no damage, environmental protection, low cost and the like. Although near infrared spectroscopy does not show significant differences between the characteristic peaks, like infrared spectroscopy, it represents a rich chemical structure information in the sample, mainly reflecting the information of the C-H, N-H and O-H bonds in the organic compound molecules. In recent years, with the development of chemometrics technology, the near infrared spectrum technology is widely applied in the field of traditional Chinese medicines, and has certain research on the aspects of traditional Chinese medicine raw material source identification, content determination, traditional Chinese medicine adulteration, pharmaceutical process monitoring and the like, but no published report for establishing a method for quickly evaluating the quality consistency of different batches of Xuesaitong dropping pills by utilizing the near infrared spectrum technology exists so far.
Disclosure of Invention
The invention aims to provide a method for evaluating the quality consistency of different batches of Xuesaitong dropping pills based on near infrared spectrum, compared with other methods, the method is simple, convenient, rapid, scientific and accurate, and can objectively, quantifiably and digitally evaluate the quality consistency.
The purpose of the invention is realized by the following technical scheme:
a method for evaluating quality consistency of Xuesaitong dripping pills based on near infrared spectrum technology comprises the following steps:
(1) collecting a sample: selecting different batches of Xuesaitong dropping pill products of the same manufacturer as samples, determining the samples as normal batches according to conventional product property indexes, and ensuring the quality consistency to be better;
(2) optimizing the acquisition condition of the near infrared spectrum: randomly extracting a batch of samples, keeping other conditions stable, selecting a plurality of levels under the three processing conditions of scanning times, resolution and optimized gain, scanning for 6 times under each condition combination according to a random combination mode, drawing a trend change chart according to the relative standard deviation corresponding to each wave number, and taking the most stable trend change as the optimal condition to complete the optimization of the three scanning conditions of scanning times, resolution and optimized gain;
(3) collecting near infrared spectrum data: performing spectrum collection on the collected Xuesaitong dripping pill samples in a diffuse reflection mode to obtain original spectrum data containing quality information of the Xuesaitong dripping pill samples;
in the process, the used near infrared spectrum measuring instrument is an Antaris II Fourier near infrared instrument of Thermo Fisher company in America, a diffuse reflection module and a solid sample rotating cup are arranged, acquisition software is Result 3.0 spectral analysis software, and analysis software is TQ analysis software; the method for collecting the near infrared spectrum data comprises the steps of taking about 100 samples of each batch, placing the samples in a rotating cup, uniformly flattening the samples, ensuring the compactness and the seamless performance, taking air as reference, and collecting the near infrared spectrum after background interference is deducted;
in the process, the temperature and the humidity are kept unchanged at 25 +/-0.5 ℃ and 55 +/-2%, the scanning times are 1-128 times, and the resolution is 4-16 cm-1The optimized gain is 1-8 x and is 10000-4000 cm-1Collecting near infrared spectrum in the wave number range, repeating the measurement for 6 times for each sample, and taking the average spectrum as the sample spectrum;
(4) selecting and preprocessing a spectrum wave band: selecting a proper spectrum band for modeling according to the characteristics of the original spectrum of the sample, and preprocessing the original spectrum of the sample by using a chemometrics method to remove irrelevant interference;
the spectrum band range can directly influence the performance and the operation efficiency of the model, and redundant information can be prevented from being introduced through band screening. Preferably, the band selected by the method through TQ analysis is 4500-6300 cm-1And 7000 to 9000cm-1The data between the two spectral ranges were modeled.
When the near infrared spectrum is collected, noise, baseline shift or drift, scattering errors caused by uneven sample distribution and the like can interfere with effective information in the near infrared spectrum. Preferably, one or more combinations of smoothing, derivative, standard regularization, multivariate scatter correction, and wavelet de-noising and compression are used to eliminate possible sample property-independent interferences in the spectrum, thereby attenuating or eliminating these extraneous interferences to highlight useful information.
(5) Establishing a consistency check model: adopting SIMCA software to carry out principal component analysis on the near infrared spectrum data after the selection and the pretreatment of the wave band to obtain Hotelling's T2And DModX control charts, and to Hotelling's T, respectively2The control chart is set to 95% of warning limit and 99%And the control limit, namely setting a mean value +3SD (standard deviation) as the upper control limit for the DModX control chart, so as to realize the evaluation of the consistency of the quality of samples of different batches.
Hotelling’s T2And DModX control charts were developed for monitoring different batches of product, and are two complementary multivariate analytical tools. Hotelling's T2The statistic is the standard square sum of all principal component score vectors, represents the degree of deviation of each sampling information from the principal component model in the variation trend and the amplitude, and can reflect the variation condition of the principal component vectors in the model, and the calculation formula is as follows:
wherein A is the number of major components, tiIs a principal component score vector matrix TARow i of (1), λiIs the X covariance matrix eigenvalue.
Hotelling’s T2The control limit UCL for the statistics may be calculated using the F distribution as follows:
where N is the number of sample observations in the working set, α is the level of significant examination, and Fα(A,N-A)Is the critical value of the F distribution for degrees of freedom A and N-A corresponding to significance level α, here obtained by calculation at α -0.05 (95%) and α -0.01 (99%) 'Hotelling's T2An alert limit and a control limit for the statistical quantity.
The DModX statistic is the sum of the squares of model residuals, which is a measure of the variation of data outside the model, and is the distance of the sample to the model in the principal component space, which can be understood as the variation of the sampled information that is not interpreted by the model. The calculation formula is as follows:
DModX＝e·eT/(N-A)
wherein e is the prediction residual of the sampling point, and in practical application, the prediction residual is usually normalized by dividing by the total standard deviation to obtain DModXnorm. Where I amThe DModX control charts establish the mean +3SD (standard deviation) as the upper control limit.
In practical application, the two statistics complement each other, and the quality of the sample under the control limit has better consistency, otherwise, when any statistic exceeds the control limit, the quality of the sample is different from that of the normal sample, and the sample is an abnormal sample.
(6) Application of the consistency check model: collecting several new batches of samples, collecting the near infrared spectra of the samples, selecting and preprocessing the bands of the spectra by using the method in the step (4), and substituting the bands into the model established in the step (5) to evaluate the quality of the spectra.
The method evaluates the quality consistency of the Xuesaitong dropping pill sample by utilizing the near infrared analysis method for the first time, has the advantages of rapidness, accuracy, simple and convenient operation, environmental protection, low cost and the like compared with the traditional method, and has better application prospect in the quality evaluation of Xuesaitong dropping pill products.
Drawings
FIG. 1 is a near infrared raw average spectrum of different batches of Xuesaitong dripping pill samples;
FIG. 2 shows Hotelling's T of the quality consistency test model of the built Xuesaitong dropping pill samples A1-A142A control chart;
FIG. 3 is a DModX control chart of the quality consistency test model of the built Xuesaitong dripping pills, samples A1-A14;
FIG. 4 shows Hotelling's T of the model for testing the consistency of the quality of B1-B8 batches2A control chart;
FIG. 5 is a DModX control chart of the quality consistency test model for lots B1-B8.
Detailed Description
The present invention will be further described with reference to the following specific examples. The examples are illustrative only and do not limit the scope of the present invention in any way.
The instrument used in the invention is an Antaris II Fourier near infrared instrument of Thermo Fisher company in America, and is provided with a diffuse reflection module and a solid sample rotating cup; result 3.0 spectrum acquisition software; TQ Analyst analysis software. The pre-processing and modeling software used was SIMCA.
Example 1
1. Collection of samples
Selecting 14 normal batches of Xuesaitong dropping pill samples, wherein the number of dropping pills in each batch of samples is at least 100. In addition, the normal batch samples need to satisfy the following conditions, namely: the content of panax notoginseng saponins in each dripping pill is about 10 mg; dissolving completely within 30 min; the appearance is round and neat, and the color is uniform; the weight variation limit was. + -. 15%.
2. Optimization of near infrared spectrum acquisition conditions
Randomly selecting a sample with wave number ranging from 10000 cm to 4000cm-1The three parameter conditions of scanning times, resolution and optimization gain are optimized, and 27 combination modes are combined according to 3 multiplied by 3 random combination, and the specific information is shown in table 1. Scanning each condition for 6 times, making trend change chart according to relative standard deviation of absorbance under each wave number, and determining the optimal condition with minimum change level as standard, wherein the scanning time is 128 times, and the resolution is 8cm-1The optimum gain is Empty × 4.
TABLE 1. information of different levels of three parameters of near infrared spectrum
3. Near infrared spectral data acquisition
About 100 samples of each batch are taken and placed in a solid rotating cup, so that the samples are uniformly flattened to ensure the compactness and the seamless performance, and near infrared spectrums are collected after background interference is deducted by taking air as reference. The measurement was repeated 3 times for each sample, and the average spectrum was taken as the sample spectrum. The indoor temperature and humidity are ensured to be about 25 ℃ and 55% respectively in the collection process.
4. Band selection and pretreatment of spectra
Screening the wave band range by using the TQ analysis software of the instrument, and finally selecting the wave band of 4500-6300 cm-1And 7000 to 9000cm-1Carrying out modeling analysis on the spectrum in the range; correlation between noise and baseline drift due to the presence of spectral noiseTherefore, multivariate scatter correction, S-G smoothing and 2-order derivative are respectively selected to preprocess the spectrum.
5. Establishment of consistency check model
The spectral data in the TQ analysis software is exported, then, the spectrum data after pretreatment is subjected to principal component analysis by adopting SIMCA software, 4 principal components are generated after the model is automatically fitted, the variance cumulative contribution rate is 99.6%, the variation of 99.6% of the sample is explained, the representativeness is better, and the method can be used for representing the quality integral information of the 14 batches of the Xuesaitong dropping pills.
On the basis of the above calculation, Hotelling's T of the 14 samples was calculated2And DModX statistics, and plotting control charts of these statistics as a function of batch and establishing corresponding control limits. Hotelling's T2And setting a 95% warning limit and a 99% control limit for the control chart; the average value +3SD is set as the upper control limit for the DModX control chart, so that the consistency evaluation of the quality of different batches of the Xuesaitong dropping pills is realized. The normal lot control chart is shown in fig. 2 and 3.
6. Application of consistency check model
And selecting 3 normal batches and 5 abnormal batches of Xuesaitong dropping pill samples to verify the established model. Collecting near infrared spectrum in the same way as the modeling batch, selecting the same wave band and pretreatment method, substituting the data into the model, and observing the sample in Hotelling's T2And whether the statistical value of DModX exceeds the control limit to evaluate the quality of the sample. The specific information of the above batches is shown in table 2.
TABLE 2
(1) Quality evaluation of samples of normal batches
The control charts of the quality consistency check model of the samples of B1-B3 are shown in FIG. 4 and FIG. 5, 3 batches all fall within the control limits of the two control charts, the batch quality consistency is good, and the model verification result is accurate.
(2) Evaluation of sample quality with low drug loading
In this embodiment, the weight of each pill in the normal batch of Xuesaitong dripping pills is about 28mg, wherein the content of panax notoginseng saponins is required to reach 10 mg. The detection shows that the content of the panax notoginseng saponins in the samples of B4-B5 batches does not reach the standard, and the samples of the abnormal batches are obtained. Control charts of the quality consistency check model of the samples from the B4 batches to the B5 batches are shown in FIGS. 4 and 5, and the control limits of the two types of control charts are exceeded by the samples from the 2 batches, which indicates that the quality of the samples from the two types of batches is inconsistent with the quality of the samples from the normal batches.
(3) Quality evaluation of samples with unqualified appearance and shape of dripping pills
In this example, normal batches of Xuesaitong pills require that the pills be spherical in shape without breakage, uniform in color and within ± 15% of weight. In two batches of samples B6-B7, one of the samples is in an ellipsoid shape, the weight difference of each pill is obvious, and dripping pills with cavities exist; the color difference of other samples is obvious and the dropping pills are broken more frequently. Control charts of the quality consistency check model of the samples from the B6 batches to the B7 batches are shown in FIGS. 4 and 5, and the control limits of the two types of control charts are exceeded by the samples from the 2 batches, which indicates that the quality of the samples from the two types of batches is inconsistent with the quality of the samples from the normal batches.
(4) Quality evaluation of dripping pill conglomerated sample
A large number of the dripping pills of the B8 batch sample are adhered together to form an irregular mass which has small hardness and is fragile, and in addition, the dripping pills are washed by ethanol to cause the loss of active ingredients. The control chart of the quality consistency test model is shown in fig. 4 and 5, and the batch samples exceed the control limits of the two control charts, which shows that the quality of the batch samples is different from that of the normal batch samples, and the batch samples are abnormal samples.
Claims (11)
1. A method for evaluating the quality consistency of Xuesaitong dropping pills based on near infrared spectrum technology is characterized by comprising the following steps: the method comprises the following steps:
(1) collecting a sample: selecting different batches of Xuesaitong dropping pill products of the same manufacturer as samples;
(2) optimizing the acquisition condition of the near infrared spectrum: randomly extracting a sample, and optimizing three scanning conditions of scanning times, resolution and optimization gain;
(3) collecting near infrared spectrum data: performing spectrum collection on the collected Xuesaitong dripping pill samples in a diffuse reflection mode to obtain original spectrum data containing quality information of the Xuesaitong dripping pill samples;
(4) selecting and preprocessing a spectrum wave band: selecting a proper spectrum band for modeling according to the characteristics of the original spectrum of the sample, and preprocessing the original spectrum of the sample by using a chemometrics method to remove irrelevant interference;
(5) establishing a consistency check model: performing principal component analysis on the near infrared spectrum data subjected to the wave band selection and pretreatment, generating a qualitative model through model automatic fitting, and obtaining Hotelling's T by combining calculation2And a DModX control chart and a control limit, which are jointly used as a sample quality consistency test model to evaluate the quality of the sample.
(6) Application of the consistency check model: and (5) collecting a plurality of new batches of samples, collecting the near infrared spectrums of the samples, selecting and preprocessing the wave bands of the spectrums by using the method in the step (4), and substituting the spectrums into the model established in the step (5) to evaluate the quality of the spectrums.
2. The method of claim 1, wherein: the acquired Xuesaitong dropping pill sample is determined to be a normal batch sample through the determination of the indexes of the panax notoginseng saponins content, the dissolution time limit, the appearance shape and the weight difference, and the quality consistency is good.
3. The method of claim 1, wherein: the near infrared spectrum measuring instrument used in the steps (2) and (3) is an Antaris II Fourier near infrared instrument of Thermo Fisher company in America, and is provided with a diffuse reflection module and a solid sample rotating cup; the acquisition software is Result 3.0 spectrum analysis software; the analysis software is TQ analysis software.
4. The method of claim 1, wherein: the method for acquiring the near infrared spectrum data in the steps (2) and (3) is to take about 100 samples of each batch, place the samples in a rotating cup, evenly spread the samples, ensure the compactness and the seamless performance, take air as reference, and acquire the near infrared spectrum after deducting background interference.
5. The method of claim 1, wherein: and (2) selecting a plurality of levels under the three processing conditions of scanning times, resolution and optimized gain, scanning for 6 times under each condition combination according to a random combination mode, drawing a trend change chart according to the relative standard deviation corresponding to each wave number, and taking the most stable trend change as the optimal condition.
6. The method of claim 1, wherein: in the step (3), the temperature is kept to be 25 +/-0.5 ℃ and the humidity is kept to be 55 +/-2%, the scanning times are 1-128 times, and the resolution is 4-16 cm-1The optimized gain is 1-8 x and is 10000-4000 cm-1The near infrared spectrum is collected in the wave number range of (2), each sample is repeatedly measured for 6 times, and the average spectrum is taken as the sample spectrum.
7. The method of claim 1, wherein: selecting 4500-6300 cm in the step (4)-1And 7000 to 9000cm-1And carrying out modeling analysis on the spectral data in the two spectral wavenumber ranges.
8. The method of claim 1, wherein: and (4) the chemometric method in the near infrared spectrum preprocessing comprises one or more combinations of smoothing, derivative, standard canonical transform, multivariate scattering correction and wavelet de-noising and compression so as to eliminate baseline drift and noise.
9. The method of claim 1, wherein: performing principal component analysis on the spectral data by using SIMCA software based on the optimal preprocessing method as described in the step (5)And generating a qualitative model by using the Hotelling's T obtained by calculation2And DModX control charts to evaluate the consistency of sample quality from batch to batch.
10. The method of claim 1, wherein: hotelling's T described in step (5)2And setting a 95% warning limit and a 99% control limit for the control chart, and setting a mean value +3SD (standard deviation) as an upper control limit for the DModX control chart, so that the consistency of the quality of the samples in different batches is evaluated, wherein the quality of the samples under the control limit has better consistency, and on the contrary, any control chart of the sample exceeds the control line and is an abnormal sample.
11. The method of claim 1, wherein: the new samples selected in the step (6) comprise normal batch samples and abnormal batch samples, the same spectrum collection method and pretreatment method are used for obtaining the effective spectrum information of the samples, and the effective spectrum information is substituted into the established model to calculate Hotelling's T2And values of the DModX statistic were evaluated for their quality to test the model's ability.
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| 严衍禄 等编著: "近红外光谱分析的原理、技术与应用", 《近红外光谱分析的原理、技术与应用》 * |
| 熊皓舒: "中药质量及制药过程一致性评价方法研究", 《中国优秀博硕士学位论文全文数据库（博士）医药卫生科技辑》 * |
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| CN111595816A (en) * | 2020-07-24 | 2020-08-28 | 江西中医药大学 | Method for distinguishing tablet coating end point based on near-infrared PCA analysis and application thereof |
| CN111595816B (en) * | 2020-07-24 | 2020-11-20 | 江西中医药大学 | Method for distinguishing tablet coating end point based on near-infrared PCA analysis and application thereof |
| CN113030007A (en) * | 2021-02-10 | 2021-06-25 | 河南中烟工业有限责任公司 | Method for rapidly testing quality stability of tobacco essence based on similarity learning algorithm |
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