Quantitative determination device and quantitative determination method

Abstract

A quantitative determination device 1 comprises a measurement unit 10, a preprocessing unit 20, and an analysis unit 30. The measurement unit 10 includes: a light source 11 that outputs light; and a spectroscope 12 that disperses the light that has been output from the light source 11 and has passed through a sample S, and measures a spectrum. The preprocessing unit 20 performs preprocessing on the as-measured spectrum measured by the spectrometer 12. The preprocessing unit 20 does not perform processing using a spectrum that is obtained by dispersing, by the spectroscope 12, the light output from the light source 11 and reaching the spectroscope 12 without passing through the sample S. The analysis unit 30 analyzes the spectrum after the preprocessing and determines the quantity of a component contained in the sample S. This configuration makes it possible to achieve a quantitative determination device and a quantitative determination method, with which it is possible to determine the quantity of a component contained in a sample at high speed.

Description

Quantitative measurement device and quantitative measurement method

[0001] The present disclosure relates to a quantitative measurement device and a quantitative measurement method.

[0002] Absorption spectroscopy (absorption spectroscopy) is a known technique for quantifying components contained in a sample. In this quantification technique, a sample is irradiated with light, and the intensity of light transmitted, reflected, or diffusely reflected by the sample is measured. Based on the light intensity, the degree of light absorption in the sample is determined, and the components contained in the sample are quantified (Patent Documents 1 to 3). The light irradiated onto the sample is light that is absorbed by the components contained in the sample, and in many cases, light in the near-infrared region is used.

[0003] Such quantification techniques are used in various fields, for example, to quantify the amount of components contained in pharmaceuticals. In particular, in recent years, the pharmaceutical and formulation industries have been promoting the establishment of continuous production, which connects multiple manufacturing processes, in order to reduce human error and improve production efficiency. This has led to a need for automation of the inspection process. In this inspection process, there is a demand for rapid quantification of the components contained in the product during production and for the entire amount of pharmaceutical products.

[0004] JP 2022-52371 A JP 2007-187624 A JP 2019-155423 A

[0005] However, it is difficult to rapidly quantify the contained components using conventional quantitative techniques.

[0006] An object of the present invention is to provide a quantitative determination device and a quantitative determination method that can rapidly determine the quantity of components contained in a sample.

[0007] An embodiment of the present invention is a quantitative measurement apparatus that includes: (1) a measurement unit including a light source that outputs light and a spectroscope that measures the spectrum of the light output from the light source after passing through a sample, (2) a preprocessing unit that preprocesses the spectrum of the light measured by the spectroscope after passing through the sample, and (3) an analysis unit that analyzes the spectrum preprocessed by the preprocessing unit to quantify components contained in the sample.

[0008] An embodiment of the present invention is a quantification method, which includes: (1) a measurement step of measuring a spectrum by using a spectroscope to disperse light output from a light source and passed through a sample, (2) a preprocessing step of preprocessing the spectrum measured as is for the light passed through the sample in the measurement step, and (3) an analysis step of analyzing the spectrum preprocessed in the preprocessing step to quantify components contained in the sample.

[0009] According to an embodiment of the present invention, the components contained in a sample can be quantified at high speed.

[0010] FIG. 1 is a diagram showing the configuration of the quantitative measurement device 1. FIG. 2 is a flowchart of the quantitative measurement method. FIG. 3 is a diagram showing the absorbance spectrum A(λ) of each of five types of samples assumed in the simulation. FIG. 4 is a diagram showing the reference spectrum (log 10 FIG. 5 shows the absorption spectra (-log 10 6 shows the absorption spectra (-log (I(λ))) of the five types of samples assumed in the simulation after random noise addition and SNV processing. 10 Figure 7 shows the calibration curve obtained by simulation. Figure 8 shows the spectrum of a tablet sample obtained in an experiment after SNV processing and second derivative. Figure 9 shows the calibration curve obtained in an experiment.

[0011] Hereinafter, embodiments of the quantitative measurement device and quantitative measurement method will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same elements are given the same reference numerals, and duplicate explanations will be omitted. The present invention is not limited to these examples, but is defined by the claims, and is intended to include all modifications within the meaning and scope equivalent to the claims.

[0012] 1 is a diagram showing the configuration of a quantification apparatus 1. The quantification apparatus 1 includes a measurement unit 10, a preprocessing unit 20, and an analysis unit 30. The measurement unit 10 includes a light source 11 and a spectroscope 12. The preprocessing unit 20 and the analysis unit 30 can be configured by a computer including a calculation unit such as a CPU that performs calculation processing, a storage unit such as a hard disk drive or memory that stores various data and programs, a display unit such as a liquid crystal display that displays calculation results, and an input unit such as a keyboard or mouse that accepts instructions from an operator.

[0013] The light source 11 outputs light having a wavelength band. The wavelength band of the light output by the light source 11 includes the wavelengths of light absorbed by the component to be quantified contained in the sample S, and is, for example, the near-infrared band (wavelengths of 800 nm to 2500 nm). The light output from the light source 11 is input to the spectrometer 12 after passing through the sample S. The light input to the spectrometer 12 may be light that has passed through the sample S, or light that has been reflected, totally reflected, or diffusely reflected by the sample S. The spectrometer 12 inputs and separates the light that has passed through the sample S, and measures the light intensity for each wavelength λ of the light, i.e., the spectrum.

[0014] The preprocessing unit 20 performs preprocessing on the spectrum measured by the spectrometer 12 after the light has passed through the sample S. The preprocessing performed here includes, for example, smoothing to remove noise, data interpolation to make the spectral data evenly spaced, standard normal variate (SNV), first and second derivatives, etc.

[0015] The analysis unit 30 analyzes the spectrum after preprocessing by the preprocessing unit 20 to quantify the components contained in the sample S. The analysis performed here is preferably multivariate analysis, such as partial least squares (PLS), principal component analysis (PCA), principal component regression (PCR), and processing using a neural network (e.g., a convolutional neural network).

[0016] In this embodiment, during preprocessing and analysis, the spectrum measured by the spectrometer 12 for the light after it has passed through the sample S is used as the target for processing, and no processing is performed using other spectra (for example, the spectrum obtained by dispersing light output from the light source 11 and reaching the spectrometer 12 directly without passing through the sample S using the spectrometer 12).

[0017] 2 is a flowchart of the quantification method. The quantification method sequentially includes a measurement step S1, a pretreatment step S2, and an analysis step S3. In the measurement step S1, the measurement unit 10 measures the spectrum of light emitted from the light source 11 and passing through the sample S using the spectroscope 12.

[0018] In the preprocessing step S2, the preprocessing unit 20 performs preprocessing on the spectrum measured by the measurement unit 10. In the analysis step S3, the analysis unit 30 analyzes the spectrum after preprocessing by the preprocessing unit 20, and quantifies the components contained in the sample S.

[0019] In the following description, it is assumed that light output from the light source 11 and transmitted through the sample S is dispersed by the spectroscope 12. The light intensity at wavelength λ measured by the spectroscope 12 when the sample S is placed on the optical path between the light source 11 and the spectroscope 12 is I(λ). Furthermore, the light intensity at wavelength λ measured by the spectroscope 12 when the sample S is not placed on the optical path between the light source 11 and the spectroscope 12 is I(λ). The absorbance A(λ) of the sample S at wavelength λ is expressed by the following equation (1):

[0020] If the absorption coefficient of sample S at wavelength λ is α(λ) and the content of the component to be quantified in sample S is C, the absorbance A(λ) of sample S at wavelength λ is expressed by the following formula (2). Based on this proportional relationship, a calibration curve can be created in advance. That is, if α(λ) is known, the content C can be determined by measuring A(λ).

[0021] The absorbance A(λ) measured at multiple wavelengths λ by the spectrometer 12 is called an absorbance spectrum. The shape of the absorbance spectrum A(λ) varies depending on the type and amount of components contained in the sample, so the absorbance spectrum A(λ) can be used to analyze the type and amount of components contained in the sample. Furthermore, the absorbance spectrum A(λ) has a large absorption coefficient at wavelengths with high absorbance, so it is used to select appropriate wavelengths for creating the above-mentioned calibration curve.

[0022] For example, when quantifying components contained in actual samples such as pharmaceuticals, it is often difficult to quantify them at a single wavelength using the relationship in equation (2). In such cases, it is preferable to quantify them using multivariate analysis, using absorbances over the entire spectrum or at multiple wavelengths within the spectrum.

[0023] Furthermore, when quantifying components contained in an actual sample, the baseline of the spectrum measured by the spectrometer may fluctuate, which may interfere with subsequent quantitative analysis. Therefore, to improve the accuracy of the quantification, it is preferable to perform preprocessing on the spectrum prior to the quantitative analysis. Examples of preprocessing include normalization of the center of gravity of the spectrum and baseline correction.

[0024] The above formula (1) can also be expressed as the following formula (3): From this formula (3) and the above formula (2), it can also be expressed as the following formula (4).

[0025] As expressed by this equation (4), the absorption spectrum (-log 10 (I(λ))) and a reference spectrum (-log 10 The difference between the absorption spectrum (-log 10 (I(λ))) as well as the reference spectrum (-log 10(I0(λ))) and then perform multivariate analysis on the difference spectrum between the two spectra (left side of equation (4)), thereby determining the amount of component C in sample S.

[0026] However, with such a conventional quantification method, it is necessary to measure not only the intensity spectrum I(λ) when the sample S is present, but also the intensity spectrum I(λ) when the sample S is absent, making it difficult to rapidly quantify the amount of component C in the sample S.

[0027] For example, in the pharmaceutical and formulation industries, automation of testing processes is becoming increasingly necessary with the establishment of continuous production, and rapid quantification of components during production or for the entire amount of pharmaceutical products is required, but the above-mentioned quantification methods are difficult to meet this requirement. Furthermore, when measuring the intensity spectrum during the transportation of a pharmaceutical product, a major problem arises as to when to measure the intensity spectrum when the pharmaceutical product is not present, using the same measurement system.

[0028] In the quantitative determination apparatus and quantitative determination method of the present embodiment described below, in order to solve this problem, it is not necessary to measure the intensity spectrum I(λ) when there is no sample S, and the reference spectrum (-log 10 (I0(λ))) 10 By performing quantitative analysis of the component amount C in the sample S based on (I(λ)), the quantification can be performed at high speed.

[0029] In the above equation (4), I(λ) is the intensity spectrum measured by the spectroscope 12 when the sample S is not present, so the reference spectrum (−log 10 The value of (I0(λ)) at each wavelength does not depend on the amount C of the component contained in the sample S.

[0030] On the other hand, I(λ) is the intensity spectrum measured by the spectroscope 12 when the sample S is present. Therefore, the greater the amount C of a component contained in the sample S, the greater the light absorption by that component, and the greater the absorption spectrum (-log 10 The value of (I(λ)) at each wavelength is large. The absorption spectrum (-log 10The value of (I(λ)) at each wavelength has a linear relationship with the component amount C with α(λ) as a coefficient.

[0031] In this embodiment, this fact is utilized. In this embodiment, in the preprocessing step S2, the preprocessing unit 20 does not perform processing using a spectrum obtained by dispersing light, which is output from the light source 11 and reaches the spectroscope 12 without passing through the sample S, by the spectroscope 12. That is, the preprocessing unit 20 does not perform processing using the intensity spectrum I(λ) when there is no sample S or the reference spectrum (-log 10 (I0(λ))) is not used.

[0032] The conditions and results of a simulation performed on the quantification method of this embodiment will be described with reference to FIGS. 3 to 7. In this simulation, five types of samples were assumed in which the content C of the component to be quantified was 0.25, 0.50, 1.00, 1.25, and 1.50. FIG. 3 shows the absorbance spectrum A(λ) of each of the five types of samples assumed in the simulation. FIG. 4 shows the reference spectrum (log 10 FIG. 10 is a diagram showing the relationship between I(λ) and I(λ).

[0033] Using the absorbance spectrum in FIG. 3 and the reference spectrum in FIG. 4, the absorption spectrum (-log 10 Figure 5 shows the absorption spectra (-log 10 FIG. 1 is a diagram showing I(λ) (I(λ)).

[0034] A 2% random noise was added to the absorption spectrum in Figure 5 to generate an absorption spectrum close to that obtained by actual measurement. Furthermore, the absorption spectrum after adding the random noise was subjected to standard normalization (SNV) as a preprocessing step.

[0035] SNV is a process in which the mean value and standard deviation of the spectral data are calculated, the mean value is subtracted from each piece of spectral data, and the result is divided by the standard deviation. After SNV processing, the mean value of the spectral data is 0 and the standard deviation is 1. Figure 6 shows the absorption spectra (-log 10 FIG. 1 is a diagram showing I(λ) (I(λ)).

[0036] For each of the five types of samples, the absorption spectrum (-log 10 Six patterns of (I(λ)) were created. Three of these patterns were used as calibration data, and the other three patterns were used as validation data. Quantitative analysis was performed using the partial least squares (PLS) method as multivariate analysis, and calibration was performed.

[0037] FIG. 7 is a diagram showing the calibration curve obtained by simulation. The horizontal axis represents the assumed content of the component to be quantified in the sample, and the vertical axis represents the content predicted by PLS. In the figure, black squares represent calibration data, and open triangles represent validation data. The squared value of the correlation coefficient for the validation data is 0.972, which indicates that a good calibration curve was obtained. As described above, the reference spectrum (-log 10 It was shown that quantification is possible without pretreatment using (I0(λ)).

[0038] Next, the conditions and results of an experiment conducted using the quantification method of this embodiment will be described with reference to Figures 8 and 9. In this experiment, tablet samples consisting of an active ingredient and an additive were used. The weight of each tablet sample was 130 mg, and the content C of the active ingredient to be quantified was 2 mg, 4 mg, 8 mg, and 12 mg. The tablet sample was irradiated with light in the near-infrared band, and the intensity spectrum I(λ) of the light transmitted through the tablet sample was measured.

[0039] The absorption spectrum (-log 10As pretreatment, SNV processing and second derivative were performed on (I(λ)). Figure 8 shows the spectra of the tablet samples obtained in the experiment after SNV processing and second derivative. This figure shows the spectra of tablet samples with active ingredient contents C of 2 mg and 12 mg, respectively.

[0040] For each of the four types of active ingredient content C, 20 tablet samples were used to perform the above-described measurements and preprocessing (SNV processing and second derivative) to create 20 patterns of spectra as shown in Figure 8. Of these, 10 patterns were used as calibration data, and the other 10 patterns were used as validation data. Quantitative analysis was performed using the PLS method as multivariate analysis, and calibration was performed.

[0041] FIG. 9 shows the calibration curve obtained in the experiment. The horizontal axis represents the content of the component to be quantified in the tablet sample, and the vertical axis represents the content predicted by PLS. In the figure, black squares represent calibration data, and open triangles represent validation data. The squared value of the correlation coefficient for the validation data is 0.991, which indicates that a good calibration curve was obtained. As described above, the reference spectrum (-log 10 Not only the simulation results but also the experimental results showed that quantification is possible without pretreatment using (I0(λ)).

[0042] As described above, in this embodiment, the reference spectrum (-log 10 (I0(λ))) 10 Since quantitative analysis of the amount C of a component in the sample S is performed based on the intensity spectrum I(λ), it is not necessary to measure the intensity spectrum I(λ) when the sample S is not present, and therefore the amount of a component contained in the sample can be quantified quickly.

[0043] The quantitative measurement device and quantitative measurement method are not limited to the above-described embodiment and configuration examples, and various modifications are possible.

[0044] The first aspect of the quantitative device according to the above embodiment comprises: (1) a measurement unit including a light source that outputs light; and a spectrometer that disperses the light output from the light source after passing through a sample to measure the spectrum; (2) a pre-processing unit that pre-processes the spectrum measured by the spectrometer after the light has passed through the sample; and (3) an analysis unit that analyzes the spectrum after pre-processing by the pre-processing unit to quantify the components contained in the sample.

[0045] In the quantitative device of the second aspect, in the configuration of the first aspect, the pre-processing unit may be configured to perform any of smoothing processing, data interpolation, standard normalization, first differentiation, and second differentiation as pre-processing of the spectrum.

[0046] In the quantitative device of the third aspect, in the configuration of the first or second aspect, the analysis unit may be configured to perform any of partial least squares, principal component analysis, principal component regression, and neural network processing to analyze the spectrum.

[0047] The quantification method of the first aspect according to the above embodiment includes: (1) a measurement step in which light output from a light source and passing through a sample is dispersed using a spectroscope to measure the spectrum; (2) a preprocessing step in which preprocessing is performed on the spectrum measured as is for the light after passing through the sample in the measurement step; and (3) an analysis step in which the spectrum preprocessed in the preprocessing step is analyzed to quantify the components contained in the sample.

[0048] In the quantitative method of the second aspect, in the configuration of the first aspect, the preprocessing step may be configured to perform any one of smoothing processing, data interpolation, standard normalization, first differentiation, and second differentiation as preprocessing of the spectrum.

[0049] In the quantitative method of the third aspect, in the configuration of the first or second aspect, the analysis step may be configured to perform any one of partial least squares analysis, principal component analysis, principal component regression, and neural network processing as the analysis of the spectrum.

[0050] The present invention can be used as a quantitative determination device and a quantitative determination method that can rapidly determine the quantity of components contained in a sample.

[0051] 1...quantification device, 10...measurement unit, 11...light source, 12...spectroscope, 20...pretreatment unit, 30...analysis unit, S...sample.

Claims

1. A quantitative measurement device comprising: a measurement unit including a light source that outputs light; and a spectroscope that disperses the light output from the light source after it has passed through a sample and measures its spectrum; a pre-processing unit that pre-processes the spectrum measured by the spectroscope after it has passed through the sample; and an analysis unit that analyzes the spectrum pre-processed by the pre-processing unit and quantifies the components contained in the sample.

2. The quantitative device according to claim 1, wherein the preprocessing unit performs one of smoothing, data interpolation, standard normalization, first differentiation, and second differentiation as preprocessing of the spectrum.

3. The quantitative measurement device according to claim 1 or 2, wherein the analysis unit performs one of partial least squares analysis, principal component analysis, principal component regression, and neural network processing to analyze the spectrum.

4. A quantitative method comprising: a measurement step in which light output from a light source and passed through a sample is dispersed by a spectroscope to measure a spectrum; a preprocessing step in which preprocessing is performed on the spectrum measured as is for the light that has passed through the sample in the measurement step; and an analysis step in which the spectrum preprocessed in the preprocessing step is analyzed to quantify components contained in the sample.

5. The quantitative method according to claim 4, wherein in the preprocessing step, the spectrum is preprocessed by any one of smoothing, data interpolation, standard normalization, first differentiation, and second differentiation.

6. The quantitative method according to claim 4 or 5, wherein in the analysis step, the spectrum is analyzed by any one of partial least squares, principal component analysis, principal component regression, and neural network processing.

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