CN103792205A - High-flux near-infrared sensitive fast non-destructive analysis for impurities and tensile strength of tablets - Google Patents
High-flux near-infrared sensitive fast non-destructive analysis for impurities and tensile strength of tablets Download PDFInfo
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- CN103792205A CN103792205A CN201410044543.3A CN201410044543A CN103792205A CN 103792205 A CN103792205 A CN 103792205A CN 201410044543 A CN201410044543 A CN 201410044543A CN 103792205 A CN103792205 A CN 103792205A
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Abstract
The invention relates to high-flux near-infrared sensitive fast non-destructive analysis for the impurities and tensile strength of tablets, belonging to the field of analyzing pharmaceutical preparation. The high-flux near-infrared sensitive fast non-destructive analysis comprises the following steps: preparing or collecting a tablet sample; collecting the near-infrared diffusion spectroscopy (NIR-DRS) of the known tablet sample through a fourier transform near infrared spectroscope; determining the reference value of impurity content of the tablets by using high performance liquid chromatography (HPLC); determining the reference value of the tensile strength through a vernier caliper and a tablet hardness tester; preprocessing the spectrum; selecting the optimal modeling wavenumber range and rejecting singular value; respectively establishing an NIR-DRS-based impurity and tensile strength correction model and evaluating the performance of the models; collecting the NIR-DRS of the unknown tablet samples; performing preprocessing identical with that of the NIR-DRS of the known sample on the NIR-DRS of the unknown tablet sample; and predicting the impurity content and tensile strength of the unknown tablet sample by using the established models. The method is high in sensitivity, free from preprocessing of the samples, fast and non-destructive in analyzing, and accurate in results.
Description
Technical field
The present invention relates to a kind of method of impurity and tensile strength in fast detecting medicinal tablet, specifically adopt using Fourier transform near infrared spectroscopy to detect the method for impurity and tensile strength in tablet in conjunction with the stoichiometry quick nondestructive that learns a skill, belong to System In Pharmaceutical Preparation Analysis field.
Background technology
Tablet, refers to after medicine and pharmaceutic adjuvant evenly mix and suppresses the Formulation forming.The advantages such as tablet has taking convenience, chemical stability is good, dosage is accurate, easy to carry.In the preparation recording at world's pharmacopoeia of each country at present, take tablet as maximum.
In the production and storage of tablet, usually can introduce some impurity, affect stability and the curative effect of tablet, be even detrimental to health.Therefore, need to carry out the determination of foreign matter of tablet, to guarantee its safety, effective, simultaneously also for the drug quality supervision and management of production and the process of circulation provides foundation.In pharmacopoeia of each country and document, tablet dirt content test method mostly is high performance liquid chromatography (HPLC), vapor-phase chromatography (GC), LC-MS technology (LC-MS), gas chromatography mass spectrometry technology (GC-MS) etc.Above-mentioned analytical approach relates to the weighing that sheet is heavy, the preparation of need testing solution, the analysis of long period, and efficiency is low, and destroys sample, can not realize automatic on-line quality control.
Tensile strength, a kind of important tablet physical parameter, can reflect disintegration time limited and the dissolution rate etc. of tablet, the computing formula of tablet tensile strength (radial tensile strenghh, RTS) is:
Wherein, the hardness that F is tablet, D is diameter, t is thickness.The mensuration of thickness and diameter is often used vernier caliper, and Determination of Hardness uses hardness tester.Measuring process relates to the measurement of tablet diameters and thickness, the mensuration of tablet hardness, also needs to carry out the calculating of tensile strength.Complex operation and destruction sample, be not suitable for the express-analysis of a large amount of samples and the On-line Control of technological process.
Frequency multiplication and sum of fundamental frequencies that near infrared spectrum characterizes hydric group in molecular vibration transition absorb.Near-infrared spectral analysis technology is a kind of Nondestructive Detection technology, there is high flux, quick, easy, automatable advantage, simultaneously number of chemical information and the physical message in analytic sample, has a wide range of applications at aspects such as the qualitative and quantitative analysis of pharmaceutical preparation.
At present, there is no the document of impurity and the sensitive near-infrared spectrum analysis of tensile strength high flux in tablet.
Summary of the invention
The object of this invention is to provide a kind of sensitive, analysis speed is fast, the near-infrared spectral analytical method of easy and simple to handle, pollution-free, automatable tablet impurity and tensile strength.Mainly comprise the steps:
1. preparation or collection tablet samples;
2. gather the near-infrared diffuse reflection spectrum (NIR-DRS) of tablet samples;
3. measure the content reference value of impurity in tablet samples with HPLC;
4. measure diameter, thickness and the hardness of tablet samples with vernier caliper and tablet hardness tester, calculate tensile strength reference value;
5. couple original NIR-DRS carries out pre-service;
6. select optimum modeling wave-number range, reject singular value;
7. select respectively optimum factor number to set up impurity content and the tensile strength calibration model of the NIR-DRS based on tablet samples, and model performance is evaluated;
8. gather the NIR-DRS of unknown sample
9. the NIR-DRS of pair unknown sample carries out corresponding pre-service;
10. impurity content and the tensile strength of application institute established model prediction unknown sample.
Wherein, conventionally application Fourier Transform Near Infrared instrument gathers the NIR-DRS of tablet, sampling apparatus can use tablet diffuse transmission sampling annex, and signals collecting software includes but not limited to: Result3.0, data processing software includes but not limited to: TQAnalyst8.0.The drainage pattern of spectrum includes but not limited to: NIR-DRS.Resolution in NIR-DRS measurement parameter includes but not limited to: 8cm
-1, scanning times includes but not limited to: 64, and spectral range includes but not limited to: 10000～4000cm
-1.
Preprocess method to original spectrum and data includes but not limited to: untreated, polynary scatter correction or standard normal conversion, first order derivative or second derivative, Norris are level and smooth or Savitzky-Golay level and smooth, average centralization, calibration etc.One or more in said method are combined use, to reach best model prediction performance.
Can be by modeling software automatic screening for the spectrum wave-number range of modeling, and according to the near infrared characteristic absorption of analyte the scope artificial optimization to automatic screening, make calibration model there is low predicated error and high related coefficient.
Singular value can be by modeling software automatic screening and rejecting, and according to spectroscopic data, reference value or prediction effect artificial screening and rejecting.
The calibration model method of setting up impurity content in tablet samples or tensile strength based on NIR-DRS includes but not limited to: partial least square method (PLS).Determine the best main cause subnumber of PLS model by cross validation, and with calibration set root-mean-square error (RMSEC), cross validation root-mean-square error (RMSECV), forecast set root-mean-square error (RMSEP), calibration set related coefficient (R
c) and forecast set related coefficient (R
p) evaluate the performance of calibration model.
The parameter value that gathers unknown sample NIR-DRS is consistent with the acquisition method of known sample spectrum in calibration model.Based on the NIR-DRS of unknown sample, application institute established model, can high flux, sensitive, impurity content and the tensile strength of predicting rapidly unknown sample.
The express-analysis that the method is applicable to one or more impurity in tablet and tensile strength, without carrying out complicated sample pretreatment, does not destroy sample, pollution-free.
Accompanying drawing explanation
The structural formula of Fig. 1 reduced glutathione (reduced glutathione, GSH) and oxidized form of glutathione (oxidized glutathione, GSSG)
The original Fourier transform NIR-DRS of 30 reduced glutathione sheet samples of Figure 23.
Fig. 3 A, B are respectively graph of a relation and forecast set reference value and the predicted value linear dependence figure of oxidized form of glutathione PLS model main cause subnumber and RMSECV.
Fig. 4 A, B are respectively graph of a relation and forecast set reference value and the predicted value linear dependence figure of tensile strength PLS model main cause subnumber and RMSECV.
Embodiment
The fast detecting that method of the present invention is applied to oxidized form of glutathione and tensile strength in reduced glutathione sheet, describes embodiment below in conjunction with accompanying drawing.
Embodiment
1. tablet samples preparation and NIR-DRS thereof gather.
Reduced glutathione sheet sample (100mg/ sheet) is by entrusting producer to make by registration prescription process reform main ingredient inventory.
Instrument: Fourier Transform Near Infrared instrument, sampling apparatus is tablet diffuse transmission sampling annex, and signals collecting software is Result3.0, and data processing is soft is part TQ Analyst8.0.
The condition of scanning: use integrating sphere tablet diffuse transmission sampling annex all to scan tablet pros and cons.Before scanning samples, first scanning background.
Measuring condition: the resolution in NIR-DRS measurement parameter is 8cm
-1, scanning times is 64, spectral range is 10000～4000cm
-1.
2. measure the content of oxidized form of glutathione impurity in tablet samples with HPLC, as reference value.
Chromatographic condition, with reference to the standard YBH1824-2004 of State Food and Drug Administration, is measured impurity peak area the content by oxidized form of glutathione in 186 samples of external standard method calculating in tablet samples.
3. measure the tensile strength of tablet.
With thickness and the diameter of vernier caliper working sample, by tablet hardness tester working sample hardness, and according to the tensile strength of 315 reduced glutathione sheet samples of formula calculating.
4. partial least square method (PLS) is measured the content of major impurity oxidized form of glutathione in reduced glutathione sheet.
For reaching the object of Accurate Prediction, calibration set and forecast set are carefully screened, in the analysis of oxidized form of glutathione, the spectrum of calibration set and forecast set is sieved in the ratio of 2:1, and the oxidized form of glutathione content reference value of forecast set is uniformly distributed in the scope of calibration set reference value.Then remove exceptional spectrum with TQ Analyst8.0 self-verifying.Finally obtain: the oxidized form of glutathione content reference value (15.85-22.18mg/g) of 62 forecast set samples is evenly distributed in reference value (15.81-22.20mg/g) scope of 124 calibration set samples; The preprocessing procedures of oxidized form of glutathione normalization model is average centralization.
Modeling wave-number range is by TQ Analyst8.0 automatic screening, then according to forecast set root-mean-square error (RMSEP) value, modeling wave-number range is carried out to artificial optimization to obtain optimum modeling effect.Spectral range (8633.39～the 4133.15cm of oxidized form of glutathione calibration model
-1) comprising the carboxyl of oxidized form of glutathione, the frequency multiplication of the main functional group such as primary amino radical and amide group absorbs: the secondary frequency multiplication peak (5260cm of C=O in carboxyl
-1), the one-level frequency multiplication (6920cm of O-H in carboxyl
-1), the one-level frequency multiplication (6600cm of N-H in primary amino radical
-1), one-level frequency multiplication (6803～6711cm of N-H in amide group
-1), and one-level frequency multiplication (5882～5555cm of C-H
-1).
Adopt cross-validation method to determine that the best main cause subnumber of PLS model, main cause subnumber 12 used be the main cause subnumber of hour correspondence of RMSECV.
Institute's established model performance is evaluated by following parameter: calibration set root-mean-square error (RMSEC), cross validation root-mean-square error (RMSECV) and forecast set root-mean-square error (RMSEP), calibration set related coefficient (R
c), forecast set related coefficient (R
p).
The calibration model property indices of setting up is as shown in table 1.
The property indices of table 1. oxidized form of glutathione normalization model and tensile strength calibration model
As shown in table 1, the RMSEC of model, RMSECV and RMSEP are respectively 0.575,0.729 and 0.607mg/g, R
cand R
pbe respectively 0.9173 and 0.9182.Forecast set reference value and the predicted value of oxidized form of glutathione are good linear relationship, forecast set regression equation y=0.8614x+2.6982.Institute's established model error is little, and related coefficient is high, although show the reduced glutathione main ingredient of the structural similarity that has high-load in sample, the oxidized form of glutathione of low content still can be by near infrared spectroscopy Measurement accuracy.
5. partial least square method (PLS) is measured the tensile strength of reduced glutathione sheet.
In the analysis of tensile strength, the spectrum of calibration set and forecast set is sieved in the ratio of 2:1, and the tensile strength reference value of forecast set is uniformly distributed in the scope of calibration set reference value.Then remove exceptional spectrum with TQ Analyst8.0 self-verifying.Finally obtain: the tensile strength reference value (298.65-1119.61kPa) of 105 forecast set samples is evenly distributed in tensile strength reference value (270.76-1145.14kPa) scope of 210 calibration set samples.
The preprocessing procedures of tensile strength calibration model is that 7: 3 Savitzky-Golay are level and smooth, average Centering and scaling.
Modeling wave-number range is by TQ Analyst8.0 automatic screening, then according to forecast set root-mean-square error (RMSEP) value, modeling wave-number range is carried out to artificial optimization to obtain optimum modeling effect.The spectral range of tensile strength calibration model is (8974.47～4039.12cm
-1).
Adopt cross-validation method to determine that the best main cause subnumber of PLS model, main cause subnumber 9 used be the main cause subnumber of hour correspondence of RMSECV.
The calibration model property indices of setting up is as shown in table 1.
As shown in table 1, RMSEC, the RMSECV of model and RMSEP are respectively 58.2,61.3 and 69.0kPa, R
cand R
pbe respectively 0.9393 and 0.9151.Tensile strength forecast set reference value and predicted value are good linear relationship, forecast set regression equation y=0.8211x+113.3224.Institute's established model error is little, and related coefficient is high, shows that the physical parameter tensile strength of tablet can be by near infrared spectroscopy Measurement accuracy.
The present invention proposes a kind of method that NIR spectroscopic methodology quick nondestructive detects tablet impurity and tensile strength, result of study shows, by setting up PLS model, NIR spectroscopic analysis methods can accurately detect content and the tensile strength of major impurity oxidized form of glutathione in reduced glutathione sheet.Compared with classic method, this method selectivity is high, without carrying out sample pretreatment, analyzes fast, and result is accurate.For new direction has been opened up in the high flux of impurity in tablet and tensile strength, sensitive, quick nondestructive analysis.
Claims (10)
1. a near infrared quick nondestructive analytical approach for impurity and tensile strength in tablet, is characterized in that adopting following steps:
(1) preparation or collection tablet samples;
(2) near-infrared diffuse reflection spectrum (NIR-DRS) of collection tablet samples;
(3) use high performance liquid chromatography (HPLC) to measure the reference value of impurity content in tablet samples;
(4) measure and calculate the reference value of tablet samples tensile strength with vernier caliper and tablet hardness tester;
(5) original NIR-DRS is carried out to pre-service;
(6) select optimum modeling wave-number range, reject singular value;
(7) select respectively optimum factor number to set up impurity content and the tensile strength calibration model based on tablet samples NIR-DRS, and model performance is evaluated;
(8) NIR-DRS of collection unknown sample;
(9) NIR-DRS of unknown sample is carried out to corresponding pre-service;
(10) impurity content and the tensile strength of application institute established model prediction unknown sample.
2. the method for claim 1, is characterized in that: in described step (2), application Fourier Transform Near Infrared instrument gathers the double-edged NIR-DRS of tablet samples, and sampling apparatus is that tablet diffuse transmission gathers annex; Acquisition parameter is scanning times 32～128, resolution 4～16cm
-1, sweep limit 10000～4000cm
-1.
3. the method for claim 1, is characterized in that: in described step (3), measure the content of impurity in tablet samples with HPLC, by external standard method with calculated by peak area.
4. the method for claim 1, it is characterized in that: diameter and the thickness of in described step (4), first measuring tablet samples with vernier caliper, measure its hardness with tablet hardness tester again, then calculate the tensile strength of tablet according to formula (1).
5. the method for claim 1, is characterized in that: the preprocess method of spectrum and data is untreated, polynary scatter correction or standard normal conversion, first order derivative or second derivative in described step (5), Norris is level and smooth or Savitzky-Golay level and smooth, one or more in average Centering and scaling.
6. the method for claim 1, it is characterized in that: wave-number range optimum in described step (6) can be by modeling software automatic screening, and according to the near infrared characteristic absorption of analyte, the scope of automatic screening is carried out to artificial optimization, make calibration model there is low predicated error and high related coefficient.
7. the method for claim 1, is characterized in that: the rejecting of described step (6) singular value can be by modeling software automatic screening and rejecting, and according to spectroscopic data, reference value or prediction effect artificial screening and rejecting.
8. the method for claim 1, is characterized in that: the method for setting up calibration model in described step (7) is partial least square method, determines the best main cause subnumber of modeling by cross validation; Adopt calibration set root-mean-square error (RMSEC), cross validation root-mean-square error (RMSECV), forecast set root-mean-square error (RMSEP), calibration set related coefficient (R
c) and forecast set related coefficient (R
p) model performance is evaluated.
9. the method for claim 1, is characterized in that: the parameter value of the middle collection of described step (8) unknown sample NIR-DRS is consistent with known sample in calibration model.
10. the method for claim 1, is characterized in that: the preprocessing procedures of the middle unknown sample of described step (9) is consistent with known sample in calibration model.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104155263B (en) * | 2014-07-18 | 2016-08-31 | 重庆医科大学 | A kind of analysis method of medicinal tablet uniform quality sex-related factors |
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| CN106353281A (en) * | 2016-09-30 | 2017-01-25 | 中南林业科技大学 | Automatic online near infrared spectrum detecting device and control method |
| CN106353281B (en) * | 2016-09-30 | 2023-04-07 | 中南林业科技大学 | Near infrared spectrum automatic on-line detection device and control method |
| CN109212095A (en) * | 2018-10-31 | 2019-01-15 | 晨光生物科技集团股份有限公司 | A kind of method of Fast Evaluation STEVIA REBAUDIANA comprehensive quality |
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