Sample analyzer, method for analyzing sample, medicine analyzer, and method for analyzing medicine

Abstract

To suppress reduction of the accuracy of estimating a reaction model due to errors of an acceleration factor.SOLUTION: A sample analyzer 1 includes: a quantitative information calculation unit 22 for calculating plural pieces of quantitative measurement information of a material in a sample on the basis of plural pieces of measurement data MD; and an estimation unit 23 for estimating a parameter PM of the reaction model RM by providing the plural pieces of quantitative measurement information calculated by the quantitative information calculation unit 22 to the reaction model RM. The reaction model RM includes an integration error item in which errors from the set values of the temperature and the moisture set by a plurality of analysis conditions are integrated.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a sample analyzer and method for analyzing substances contained in a sample, and a pharmaceutical analyzer and method for analyzing active ingredients, impurities, etc. contained in pharmaceutical preparations and the like. [Background technology]

[0002] For example, accelerated testing is performed on products such as formulations. In this test, the product is stored under conditions that are stricter than normal storage conditions, and after a certain period of time, the product's components are analyzed using an analytical device. This makes it possible to perform component analysis testing of products that would normally require a long storage time in a short period of time, or to evaluate the variation in component analysis results. When analyzing the components of a product after long-term storage from the measurement results obtained in the accelerated testing, a reaction model is estimated using the Arrhenius equation or the modified Arrhenius equation. The following Non-Patent Document 1 shows a method for estimating life from accelerated test data. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Technical note, Determination of reaction model equations from DSC data by AKTS / Thermokinetics, http: / / www.palmetrics.co.jp / _userdata / TKTS_07_2019R.pdf Summary of the Invention [Problem to be solved by the invention]

[0004] In an accelerated test, for example, acceleration factors such as temperature and humidity are set to stricter values ​​than those under normal storage conditions. However, depending on the test environment, there may be an error between the actual temperature and humidity and the set values. This error reduces the accuracy of the reaction model estimation.

[0005] An object of the present invention is to suppress a decrease in the accuracy of reaction model estimation due to errors in acceleration factors. [Means for solving the problem]

[0006] A sample analysis apparatus according to one aspect of the present invention includes an acquisition unit that acquires multiple measurement data obtained by analyzing a sample in the analysis apparatus under multiple analytical conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates multiple quantitative measurement information of a substance contained in the sample based on the multiple measurement data; an estimation unit that reads out a reaction model stored in a memory device, models quantitative estimated information of the substance using the reaction model, and estimates parameters of the reaction model by providing the multiple quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; and a calculation unit that calculates quantitative estimated information of the substance at any time based on the parameters estimated by the estimation unit, or calculates information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, and the reaction model includes an integrated error term that integrates errors from the set values ​​of temperature and humidity set under the multiple analytical conditions.

[0007] A sample analysis apparatus according to another aspect of the present invention includes an acquisition unit that acquires multiple measurement data obtained by analyzing a sample in the analysis apparatus under multiple analysis conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates multiple quantitative measurement information of a substance contained in the sample based on the multiple measurement data; an estimation unit that reads out a reaction model stored in a memory device, models quantitative estimated information of the substance using the reaction model, and estimates parameters of the reaction model by providing the multiple quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; and a calculation unit that calculates quantitative estimated information of the substance at any time based on the parameters estimated by the estimation unit, or calculates information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, and an additional reaction is set in the reaction model according to an initial value.

[0008] A sample analysis apparatus according to another aspect of the present invention includes an acquisition unit that acquires multiple measurement data obtained by analyzing a sample in the analysis apparatus under multiple analysis conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates multiple quantitative measurement information of a substance contained in the sample based on the multiple measurement data; an estimation unit that reads out a reaction model stored in a memory device, models quantitative estimated information of the substance using the reaction model, and estimates parameters of the reaction model by providing the multiple quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; and a calculation unit that calculates quantitative estimated information of the substance at an arbitrary time based on the parameters estimated by the estimation unit, or calculates information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, and a time lag for the start of analysis is set in the reaction model.

[0009] The present invention is also directed to a sample analysis method, a pharmaceutical analysis apparatus and a pharmaceutical analysis method. Effect of the Invention

[0010] According to the present invention, it is possible to suppress a decrease in the accuracy of the estimation of a reaction model due to an error in an acceleration factor. [Brief description of the drawings]

[0011] [Figure 1] 1 is a configuration diagram of a sample analyzer according to an embodiment of the present invention. [Diagram 2] 1 is a functional block diagram of a sample analyzer according to an embodiment of the present invention. [Diagram 3] FIG. 13 is a diagram showing contours of log-likelihood. [Figure 4] FIG. 4 is a diagram showing a cross section taken along the contour line AB in FIG. [Diagram 5] FIG. 13 is a graph showing the change in peak area ratio when no additional reaction occurs. [Figure 6] FIG. 13 is a diagram showing the change in peak area ratio when an additional reaction occurs. [Figure 7] FIG. 13 is a diagram showing deviations in estimated shelf-life. [Figure 8] FIG. 13 is a diagram showing a functional model of an additional reaction. [Figure 9] This is a diagram modeled with an offset from t=0 as Δt. [Figure 10] 3 is a flowchart showing a sample analysis method according to an embodiment. [Figure 11] 3 is a flowchart showing a sample analysis method according to an embodiment. [Figure 12] 3 is a flowchart showing a sample analysis method according to an embodiment. [Figure 13] FIG. 13 is a diagram showing simulation data of peak area ratios. [Figure 14] FIG. 13 is a diagram showing an estimation result obtained by the model formula of Equation (6). [Figure 15] FIG. 13 is a diagram showing the estimation results obtained by a model formula into which hierarchical error is introduced. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Next, a sample analyzing apparatus and method and a pharmaceutical analyzing apparatus and method according to embodiments of the present invention will be described with reference to the accompanying drawings.

[0013] (1) Configuration of the sample analyzer 1 is a configuration diagram of a sample analyzer 1 according to an embodiment. Sample analyzer 1 of this embodiment acquires measurement data MD of a sample obtained by an analyzer such as a liquid chromatograph, a gas chromatograph, or a mass spectrometer. In this embodiment, sample analyzer 1 will be described as being used as a pharmaceutical analyzer that analyzes pharmaceuticals (formulations or drug substances) as samples.

[0014] The sample analyzer 1 of this embodiment is configured with a personal computer. As shown in Figure 1, the sample analyzer 1 includes a CPU (Central Processing Unit) 11, a RAM (Random Access Memory) 12, a ROM (Read Only Memory) 13, an operation unit 14, a display 15, a storage device 16, a communication interface (I / F) 17, and a device interface (I / F) 18.

[0015] The CPU 11 performs overall control of the sample analyzer 1. The RAM 12 is used as a work area when the CPU 11 executes a program. The ROM 13 stores various data, programs, etc. The operation unit 14 accepts input operations by the user. The operation unit 14 includes a keyboard and a mouse, etc. The display 15 displays information such as analysis results. The storage device 16 is a storage medium such as a hard disk. The storage device 16 stores a program P1, measurement data MD, peak area ratio data PS, a reaction model RM (data that defines a reaction model function), and parameters PM.

[0016] The program P1 models quantitative estimated information of substances contained in the sample using a reaction model RM read from the storage device 16. The program P1 also estimates parameters PM of the reaction model RM by providing quantitative measurement information of a plurality of substances to the reaction model RM. The program P1 also calculates quantitative estimated information of the substances at any time based on the estimated parameters PM. The program P1 also calculates information regarding the time until the quantitative estimated information of the substances reaches a predetermined threshold value based on the estimated parameters PM.

[0017] The communication interface 17 is an interface for performing wired or wireless communication with other computers. The device interface 18 is an interface for accessing a storage medium 19 such as a CD, a DVD, or a semiconductor memory.

[0018] (2) Functional configuration of the sample analyzer Fig. 2 is a block diagram showing the functional configuration of the sample analyzer 1. In Fig. 2, the control unit 20 is a functional unit that is realized by the CPU 11 executing the program P1 while using the RAM 12 as a work area. The control unit 20 includes an acquisition unit 21, a quantitative information calculation unit 22, an estimation unit 23, a calculation unit 24, and an output unit 25. In other words, the acquisition unit 21, the quantitative information calculation unit 22, the estimation unit 23, the calculation unit 24, and the output unit 25 are functional units that are realized by the execution of the program P1. In other words, each of the functional units 21 to 25 can be said to be a functional unit provided in the CPU 11.

[0019] The acquisition unit 21 inputs the measurement data MD. For example, the acquisition unit 21 inputs the measurement data MD from an analysis device such as a liquid chromatograph, a gas chromatograph, or a mass spectrometer, or from another computer via the communication interface 17. Alternatively, the acquisition unit 21 inputs the measurement data MD stored in the storage medium 19 via the device interface 18. The measurement data MD acquired by the acquisition unit 21 is, for example, multidimensional data acquired by a multidimensional detector provided in the chromatograph. For example, the measurement data MD is three-dimensional data having elements of a retention time direction, a spectrum direction (frequency direction), and intensity. In this case, the measurement data MD is expressed as matrix data having, for example, the retention time direction as rows, the spectrum direction as columns, and intensity as an element. For example, the measurement data MD is data acquired in a liquid chromatograph equipped with a PDA detector (photodiode array detector). The acquisition unit 21 stores the acquired measurement data MD in the storage device 16.

[0020] The quantitative information calculation unit 22 calculates the peak area ratio data PS based on the measurement data MD read from the storage device 16. The peak area ratio data PS is an example of the "quantitative measurement information of substances contained in a sample" in the present invention. In this embodiment, the ratio of the peak area of ​​an impurity to the peak area of ​​an active ingredient contained in a medicine will be described as an example of the quantitative measurement information of substances contained in a sample. The quantitative information calculation unit 22 stores the calculated peak area ratio data PS in the storage device 16.

[0021] Here, the measurement data MD acquired by the acquisition unit 21 includes a plurality of data obtained by analyzing a sample under a plurality of analysis conditions in an analysis device such as a liquid chromatograph. Therefore, the quantitative information calculation unit 22 calculates a plurality of peak area ratio data PS corresponding to the plurality of measurement data MD. Particularly, in this embodiment, the measurement data MD acquired by the acquisition unit 21 is data obtained under a plurality of analysis conditions with temperature and humidity as acceleration factors. Therefore, the plurality of peak area ratio data PS calculated by the quantitative information calculation unit 22 is data obtained under a plurality of analysis conditions with temperature and humidity as acceleration factors.

[0022] The estimation unit 23 uses the reaction model RM read out from the storage device 16 to model quantitative estimated information of a substance contained in a sample with the reaction model RM. In this example, the estimation unit 23 models a peak area ratio (ratio of the peak area of ​​an impurity to the peak area of ​​an active ingredient contained in a pharmaceutical) as "quantitative estimated information of a substance" with the reaction model RM. The estimation unit 23 estimates parameters PM of the reaction model RM by providing the peak area ratio data PS (quantitative measurement information of a substance) calculated by the quantitative information calculation unit 22 to the reaction model RM. The estimation unit 23 stores the estimated parameters PM in the storage device 16.

[0023] The calculation unit 24 calculates estimated information of the peak area ratio at any time (quantitative estimated information of a substance) based on the parameters PM estimated by the estimation unit 23. The quantitative estimated information includes a quantitative value, a confidence interval, or a quantile of the substance at any time. The calculation unit 24 also calculates information about the time until the estimated information of the peak area ratio (quantitative estimated information of a substance) reaches a predetermined threshold value based on the parameters PM estimated by the estimation unit 23. The information about time includes the time until the quantitative estimated information of the substance reaches a predetermined threshold value, a confidence interval, or a quantile.

[0024] The output unit 25 causes the display 15 to display the quantitative estimated information of the substance. The output unit 25 also causes the display 15 to display information relating to the time it takes for the quantitative estimated information of the substance to reach a predetermined threshold value.

[0025] A case will be described in which the program P1 is stored in the storage device 16 as an example. In another embodiment, the program P1 may be provided by being stored in the storage medium 19. The CPU 11 may access the storage medium 19 via the device interface 18, and store the program P1 stored in the storage medium 19 in the storage device 16 or the ROM 13. Alternatively, the CPU 11 may access the storage medium 19 via the device interface 18, and execute the program P1 stored in the storage medium 19. Alternatively, the CPU 11 may download the program P1 stored in a server on a network via the communication interface 17.

[0026] (3) Estimation process (3-1) Basic concept of estimation processing Before describing the details of the estimation process executed by the estimation unit 23, the basic concept of the estimation process will be described. The peak area ratio β(t, T, H) when a sample is stored at absolute temperature T [K] and relative humidity H [%] for a period t [days] can be modeled by combining the modified Arrhenius equation and a solid-state reaction model equation. Here, an example will be described in which the peak area ratio β is the ratio of the peak area of ​​an impurity to the peak area of ​​an active ingredient contained in a pharmaceutical. First, the modified Arrhenius equation is expressed as in Equation (1).

[0027]

number

[0028] In equation (1), R is the gas constant (≒8.314 J / (K mol)), A is the frequency factor, E is the activation energy, and B is a parameter related to humidity. There are various solid-state reaction models, but as an example, consider a model like equation (2) using the reaction rate α(t) and parameters m and n.

[0029]

number

[0030] Peak area ratio β at t=∞ ∞ Using the above, the relationship between the peak area ratio β(t) and the reaction progress rate α(t) can be expressed as shown in Equation (3).

[0031]

number

[0032] By substituting equation (3) into equation (2), we obtain the following equation (4).

[0033]

number

[0034] The initial value of the peak area ratio β(t,T,H) is β 0 Combining formula (4) and formula (1), the peak area ratio β(t, T, H) at any t, T, and H is expressed as formula (5).

[0035]

number

[0036] A, E, B, m, n, β 0 ,β ∞ are parameters in the model equation for the peak area ratio β(t). When values ​​are given for each parameter, β(t,T,H) can be calculated by integral calculation. This integral calculation may be performed approximately.

[0037] Absolute temperature T i , relative humidity H i So, t i The peak area ratio data {β(t 1 ,T 1 ,H 1 ),β(t 2 ,T 2 ,H 2 ),···,β (t L ,T L ,H L )} and use regression methods such as the least squares method, MAP estimation, and Bayesian estimation to calculate the parameters A, E, B, m, n, and β in equation (5). 0 ,β ∞ This allows the peak area ratio β to be estimated for any t, T, and H. In practice, the change over time of the peak area ratio β under long-term storage conditions of 25°C and 60% RH is often calculated, and the number of days until it exceeds a certain threshold is determined.

[0038] However, in Bayesian estimation, the error must also be explicitly modeled and a prior distribution must be given to the parameters.As an example, if we assume that an error following a normal distribution with a mean of 0 and a standard deviation of σ is added to the model expressed by formula (5) at the time of measurement, the model can be expressed as follows.

[0039]

number

[0040] Here, N(μ,σ) represents a normal distribution with mean μ and standard deviation σ. Parameters A, E, B, m, n, β 0 ,β ∞ By giving a prior distribution to ,σ and performing Bayesian estimation using MCMC (Markov Chain Monte Carlo), it is possible to derive the posterior distribution of each parameter and the posterior distribution of the peak area ratio β for any t, T, and H.

[0041] (3-2) First issue The inventors of the present application have found that the basic concept of the estimation process described in (3-1) above has two problems that make it difficult to make a valid estimation. The first problem is that it becomes difficult to make a valid estimation when errors from multiple acceleration factors are taken into account. Pharmaceuticals are made through complex processes, and there are various error factors other than measurement noise. Examples of errors related to acceleration factors include "temperature variation" and "humidity variation." In stability tests, pharmaceuticals are stored in spaces maintained at constant temperature and humidity, such as stability testers and stability test rooms, but temperature and / or humidity fluctuations may occur in these testers. For this reason, reactions may proceed faster or slower than under ideal storage conditions. If these errors are not incorporated into the model formula, it is assumed that pharmaceuticals stored in all testers are in the same condition, but in reality, data affected by temperature and humidity depending on the storage environment is measured. As a result, the measurement error may be estimated excessively large (overdispersion).

[0042] To address this issue, a method can be considered in which a hierarchical error term is given to the model equation for temperature and humidity for each sample stored in the same tester. For example, if the error distribution of temperature and humidity for each tester has an average of 0 and a standard deviation of σ T ,σ H Assuming that the peak area ratio β follows a normal distribution, the peak area ratio β can be modeled as shown in Equation (7).

[0043]

number

[0044] where C is the set of tester labels. i indicates the label of the tester in which the i-th measured pharmaceutical sample was stored. According to equation (7), the temperature error and humidity error depending on the tester in which it was stored are taken into account for each pharmaceutical sample.

[0045] However, when attempting to perform Bayesian estimation using MCMC for the model shown in formula (7), the calculation time increases significantly compared to the model shown in formula (6), or a valid posterior distribution may not be obtained. One of the reasons for this is thought to be a problem dependent on the MCMC method and the shape of the likelihood function.

[0046] There are many MCMC methods, but MCMC methods using the gradient of the likelihood, such as HMC (Hamiltonian Monte Carlo) and NUTS (No-U-Turn Sampler), have been widely used in recent years due to their computational efficiency. In these MCMC methods using the gradient of the likelihood, the next point is searched or sampled using the calculated gradient multiplied by a step size. Setting this step size appropriately according to the scale of the gradient has the effect of preventing the search point from being too far or too close, which would result in a decrease in efficiency. This step size can be determined manually or automatically.

[0047] Here, let us consider the likelihood function in this embodiment. In this embodiment, what is measured is the peak area ratio. The temperature and humidity in each tester are set to a predetermined value, but the actual temperature and humidity are not measured. Therefore, if the reaction in a certain tester is faster than the ideal condition, it is difficult to know whether this is due to a difference in temperature or humidity. Based on this, σ T Axis and σ H The likelihood function for the axis (with other parameters fixed) is σ T and σ H There can be a trade-off between σ T Axis and σ H The contours of a 3D graph plotting the negative log-likelihood against the axis are shown. Figure 4 shows a cross section of the 3D graph taken along the line AB in Figure 3. As shown in Figure 4, the negative log-likelihood has a bathtub shape, with some areas having a steep slope and others having a shallow slope.

[0048] In this case, if the step size is set to match the part with a large gradient, the search efficiency will deteriorate in the part with a small gradient. Conversely, if the step size is set to match the part with a small gradient, the search efficiency will deteriorate in the part with a large gradient. In this way, the inability to set a step size that can cover both areas leads to a deterioration in search efficiency or sampling efficiency. As a result, the number of iterations required for sufficient search increases significantly, resulting in problems such as long estimation time or inability to perform valid estimation. In regression methods other than Bayesian estimation, similar problems can occur in determining the step size when using the gradient of the likelihood.

[0049] (3-3) Second issue The second problem with the basic concept of the estimation process described in (3-1) above is that the model shown in formula (6) does not provide a good estimate when additional decomposition occurs immediately after the start of storage. When no additional decomposition occurs immediately after the start of storage, the time change of the peak area ratio β(t) is calculated by subtracting the initial value at t=0 from the 0 The result is as shown in Figure 5.

[0050] In contrast, Figure 6 shows the time change of the peak area ratio β(t) when additional decomposition occurs immediately after the start of storage. For example, at the start of storage, a reaction may proceed rapidly near the surface of the drug in contact with air. Acceleration conditions such as temperature and humidity affect this additional reaction.

[0051] When the model shown in Equation (6), which does not take into account the additional reaction, is used for measurement data obtained under such a condition in which the additional reaction is occurring, the peak area ratio under long-term storage conditions for the drug is estimated as shown in Figure 7. In other words, the initial value of the peak area ratio is estimated to be excessively high due to the additional reaction. If the period during which the peak area ratio does not exceed the threshold (shelf-life) is calculated from this estimation result, the shelf-life is estimated to be excessively short.

[0052] (3-4) Solution to the first problem As a solution to the first problem of (3-2) above, the estimation unit 23 of this embodiment performs the following estimation process. The estimation unit 23 does not set an error distribution for each acceleration factor, but sets an error distribution for the reaction rate constant k obtained by integrating these acceleration factors. That is, as shown in formula (7), instead of setting individual error distributions for temperature and humidity in the model formula, a single error distribution integrating temperature and humidity is set in the model formula. That is, the estimation unit 23 uses the reaction model RM shown in formula (8) instead of formula (7).

[0053]

number

[0054] As a result, the above-mentioned σ T and σ H The trade-off relationship between the above is resolved, and problems caused by the bathtub shape of the likelihood function are suppressed. Data defining the reaction model shown in formula (8) is stored in the storage device 16 as a reaction model RM. Note that the model formula shown in formula (8) is generated based on the solid reaction model shown in formula (2) and is an example. An error distribution integrating acceleration factors may be set based on another solid reaction model, as in formula (8). A plurality of reaction models RM may be stored in the storage device 16 and used by selecting them. In this way, by using a model formula in which an error distribution integrating acceleration factors is set, the step size problem caused by the bathtub shape described above is alleviated, and a more appropriate and useful estimation result that takes into account errors related to acceleration factors can be obtained in a realistic time.

[0055] (3-5) Solution to the second problem As a solution to the second problem of (3-3) above, the estimation unit 23 of this embodiment performs the following estimation process. The estimation unit 23 uses a model formula that assumes an additional reaction according to the acceleration conditions. There are two possible methods for modeling the additional reaction. One is to model the additional reaction as it is, and the other is to consider the additional reaction as a deviation from the true time and model it as a time offset.

[0056] (3-5-1) Modeling additional reactions Of the two methods, the method for modeling the additional reaction is as follows: The estimation unit 23 uses a reaction model RM expressed by Equation (9) in which the additional reaction is added to the model formula expressed by Equation (6).

[0057]

number

[0058] In equation (9), f is a function that represents the additional reaction. A conceptual diagram of the additional reaction function f is shown in Figure 8. For example, when the additional reaction occurs linearly with respect to the reaction rate constant k, that is, when x is a parameter that represents the magnitude of the additional reaction, and f(T,H)=x·k(T,H), the model formula is expressed as equation (10).

[0059]

number

[0060] Data defining the reaction model shown in formula (9) and formula (10) is stored in the storage device 16 as a reaction model RM. Note that the model formulas shown in formula (9) and formula (10) are generated based on the solid reaction model shown in formula (2) and are merely examples. Additional reactions can be added using other solid reaction models as a basis, as with formula (9) and formula (10). It is also possible to store multiple reaction models RM in the storage device 16 and select and use them. In this way, by modeling the additional reaction, even if there is an additional reaction, an estimation result that appropriately takes that into account can be obtained, and it is possible to prevent the shelf life from being estimated as being too short.

[0061] (3-5-2) Modeling time offsets Of the two methods, the method for modeling the time offset is as follows: The estimation unit 23 introduces a time offset term Δt into the model formula shown in formula (6), and uses a reaction model RM shown in formula (11). A conceptual diagram of the offset term Δt is shown in FIG. 9.

[0062]

number

[0063] Data defining the reaction model shown in formula (11) is stored in the storage device 16 as a reaction model RM. Note that the model formula shown in formula (11) is one example, generated based on the solid reaction model shown in formula (2). The offset term Δt may be set similarly to formula (11) based on another solid reaction model. It is also possible to store a plurality of reaction models RM in the storage device 16 and select and use them. In this way, by setting a time lag for the start of analysis, even if there is an additional reaction, an estimation result that appropriately takes this into account is obtained, and it is possible to prevent the shelf life from being estimated as being too short.

[0064] (4) Sample analysis method Next, a sample analysis method according to an embodiment will be described with reference to the flowcharts of Figures 10 to 12. The flowcharts of Figures 10 to 12 show processes executed by the CPU 11 shown in Figure 1. In other words, these processes are executed by the functional units 21 to 24 shown in Figure 2 as the CPU 11 operates the program P1 using hardware resources such as the RAM 12.

[0065] First, a sample analysis method based on a solution to the first problem (3-4) above will be described with reference to Fig. 10. In step S11, the acquisition unit 21 acquires a plurality of measurement data MD obtained by analyzing a sample in an analysis device under a plurality of analysis conditions including temperature and humidity as acceleration factors. In other words, the measurement data MD is data obtained from a sample (medicine) stored under harsher conditions for temperature and humidity than the normal storage environment.

[0066] Next, in step S12, the quantitative information calculation unit 22 calculates a plurality of quantitative measurement information of the substances contained in the sample based on the plurality of measurement data MD. In this embodiment, the quantitative information calculation unit 22 calculates peak area ratio data PS (the ratio of the peak area of ​​the impurity to the peak area of ​​the active ingredient contained in the medicine).

[0067] Next, in step S13, the estimation unit 23 reads out the reaction model RM stored in the storage device 16, and models the quantitative estimation information of the substance using the reaction model RM. Here, the reaction model RM includes an integrated error term that integrates errors from the set values ​​of temperature and humidity, as shown in formula (8).

[0068] Next, in step S14, the estimation unit 23 estimates the parameters PM of the reaction model RM by providing the reaction model RM with a plurality of pieces of quantitative measurement information calculated by the quantitative information calculation unit 22. The estimation unit 23 estimates the parameters PM of the reaction model RM by performing a regression analysis such as Bayesian estimation, the least squares method, or MAP estimation.

[0069] Next, in step S15, the calculation unit 24 calculates quantitative estimated information of the substance at any time based on the parameters estimated by the estimation unit 23. In this embodiment, the calculation unit 24 calculates an estimated value of the peak area ratio (ratio of the peak area of ​​the impurity to the peak area of ​​the active ingredient contained in the medicine) at any time (number of days). Alternatively, the calculation unit 24 calculates information on the time until the quantitative estimated information of the substance reaches a predetermined threshold. In this embodiment, the calculation unit 24 calculates the time (number of days) until the estimated value of the peak area ratio (ratio of the peak area of ​​the impurity to the peak area of ​​the active ingredient contained in the medicine) reaches a predetermined value. The output unit 25 outputs the estimation result calculated by the calculation unit 24 to the display 15.

[0070] Furthermore, when the estimation unit 23 uses a regression analysis method for estimating a posterior distribution, such as Bayesian estimation, the calculation unit 24 calculates a confidence interval and a quantile of the quantitative value of the substance at any time, or calculates a confidence interval and a quantile of the time until the quantitative estimated information of the substance reaches a predetermined threshold.

[0071] Next, a sample analysis method based on the solution to the second problem in (3-5-1) above (modeling the additional reaction) will be described with reference to Figure 11. The processes in steps S21 and S22 are similar to steps S11 and S12 in Figure 10, so their description will be omitted.

[0072] In step S23, the estimation unit 23 reads out the reaction model RM stored in the storage device 16, and models quantitative estimation information of the substance using the reaction model RM. Here, in the reaction model RM, additional reactions are set according to the initial values, as shown in formulas (9) and (10). The following steps S24 and S25 are similar to steps S14 and S15 in Fig. 10, and therefore will not be described.

[0073] Next, a sample analysis method based on the solution to the second problem in (3-5-2) above (modeling the time offset) will be described with reference to Figure 12. The processes in steps S31 and S32 are similar to steps S11 and S12 in Figure 10, so their description will be omitted.

[0074] In step S33, the estimation unit 23 reads out the reaction model RM stored in the storage device 16, and models quantitative estimation information of the substance using the reaction model RM. Here, an offset term Δt indicating the time lag of the analysis start is set in the reaction model RM, as shown in formula (11). The following steps S34 and S35 are similar to steps S14 and S15 in Fig. 10, and therefore will not be described.

[0075] (5) Simulation results The simulation result of the estimation process in this embodiment will be described. As an example, it is assumed that simulation data as shown in FIG. 13 is obtained for the peak area ratio of a sample stored with variations in temperature and humidity. In FIG. 13, the horizontal axis is the number of days of storage, and the vertical axis is the peak area ratio to the main component. The figure shows data obtained by storage under accelerated conditions for about 30 days. Here, the legend of different symbols indicates that the data is for samples stored in different testers. For example, there are three types of symbols for 70°C 60% RH, each of which has a slightly different reaction rate. This indicates that even with the same set value of 70°C 60% RH, there is variation in temperature and humidity depending on the tester, resulting in a difference in the peak area ratio. Similarly, three types of varied data are simulated for set values ​​of 50°C 50% RH and 60°C 30% RH.

[0076] Using this simulation data, the prediction interval at 25°C 60% RH obtained by the model formula shown in Equation (6) is shown in Figure 14. In Figure 14, the horizontal axis indicates the number of days of storage, and the vertical axis indicates the peak area ratio to the main component. In Figure 14, the solid thick line indicates the median value of the estimate, the shaded area indicates the 90% prediction interval of the estimate, and the symbols indicate the data used for the estimate (the data shown in Figure 13). The peak area ratio after about 1000 days of storage is estimated from simulation data for about 30 days.

[0077] In contrast, the prediction interval at 25°C 60% RH obtained by using this simulation data and the model formula introducing the hierarchical error shown in formula (8) is shown in FIG. 15. In FIG. 15, the horizontal axis indicates the number of days of storage, and the vertical axis indicates the peak area ratio to the main component. Similarly, the peak area ratio after about 1000 days of storage is estimated from simulation data of about 30 days. In FIG. 15, the solid thick line is the median of the estimate, the shaded area is the 90% prediction interval of the estimate, and the symbols indicate the data used for the estimate (the data shown in FIG. 13). Comparing FIG. 14 and FIG. 15, it can be seen that the model formula introducing the hierarchical error has a narrower prediction interval.

[0078] (6) Other embodiments In each of the above-described embodiments, the sample analyzer 1 has been described as analyzing medicines as samples. The sample analyzer 1 of the present embodiments can be used to obtain quantitative estimated information of substances in various samples other than medicines. In the above-described embodiments, the peak area ratio has been described as an example of quantitative estimated information of a substance. The sample analyzer 1 of the present invention can also estimate peak areas, retention times, and the like as quantitative estimated information of a substance.

[0079] In the above embodiment, the case where temperature and humidity are used as the acceleration factors has been described as an example. Alternatively, light may be used as the acceleration factor. For example, temperature and light, or humidity and light, etc. may be used as the acceleration factors.

[0080] (7) Description It will be appreciated by those skilled in the art that the exemplary embodiments described above are examples of the following aspects.

[0081] (Section 1) A sample analyzer according to one embodiment comprises: an acquisition unit that acquires a plurality of measurement data obtained by analyzing a sample in an analysis device under a plurality of analysis conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates a plurality of quantitative measurement information of the substances contained in the sample based on the plurality of measurement data; an estimation unit that reads out a reaction model stored in a storage device, models quantitative estimation information of the substance using the reaction model, and estimates parameters of the reaction model by providing the plurality of pieces of quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; a calculation unit that calculates quantitative estimated information of the substance at an arbitrary time based on the parameters estimated by the estimation unit, or calculates information regarding a time until the quantitative estimated information of the substance reaches a predetermined threshold; Equipped with The reaction model includes an integrated error term that integrates errors from the set values ​​of the temperature and humidity that are set under the multiple analysis conditions.

[0082] It is possible to suppress a decrease in the accuracy of the reaction model estimation caused by errors in the acceleration factors.

[0083] (Section 2) A sample analyzer according to another aspect of the present invention comprises: an acquisition unit that acquires a plurality of measurement data obtained by analyzing a sample in an analysis device under a plurality of analysis conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates a plurality of quantitative measurement information of the substances contained in the sample based on the plurality of measurement data; an estimation unit that reads out a reaction model stored in a storage device, models quantitative estimation information of the substance using the reaction model, and estimates parameters of the reaction model by providing the plurality of pieces of quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; a calculation unit that calculates quantitative estimated information of the substance at an arbitrary time based on the parameters estimated by the estimation unit, or calculates information regarding a time until the quantitative estimated information of the substance reaches a predetermined threshold; Equipped with In the reaction model, an additional reaction is set according to the initial value.

[0084] Even if there are additional reactions, the estimation result appropriately takes them into account.

[0085] (Section 3) A sample analyzer according to another aspect of the present invention comprises: an acquisition unit that acquires a plurality of measurement data obtained by analyzing a sample in an analysis device under a plurality of analysis conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates a plurality of quantitative measurement information of the substances contained in the sample based on the plurality of measurement data; an estimation unit that reads out a reaction model stored in a storage device, models quantitative estimation information of the substance using the reaction model, and estimates parameters of the reaction model by providing the plurality of pieces of quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; a calculation unit that calculates quantitative estimated information of the substance at an arbitrary time based on the parameters estimated by the estimation unit, or calculates information regarding a time until the quantitative estimated information of the substance reaches a predetermined threshold; Equipped with A time lag for the start of analysis is set in the reaction model.

[0086] Even if there are additional reactions, the estimation result appropriately takes them into account.

[0087] (Section 4) In the sample analyzer according to any one of claims 1 to 3, The reaction model may be adapted to the Arrhenius equation or a modified Arrhenius equation.

[0088] Quantitative estimates can be obtained at any temperature, humidity, and time.

[0089] (Section 5) In the sample analyzer according to any one of claims 1 to 3, The acceleration factor may include light.

[0090] The accuracy of modeling is also improved for reactions accelerated by light.

[0091] (Section 6) In the sample analyzer according to any one of claims 1 to 3, A plurality of reaction models may be stored in the storage device.

[0092] Appropriate solid state reaction models are available.

[0093] (Section 7) In the sample analyzer according to any one of claims 1 to 3, The quantitative estimate of the substance may include a quantitative value, a confidence interval or a quantile of the substance at any time.

[0094] Quantitative estimated information enables a variety of analyses.

[0095] (Section 8) In the sample analyzer according to any one of claims 1 to 3, The time information may include a value, a confidence interval or a quantile of the time until the quantitative estimate of the substance reaches a predefined threshold.

[0096] Quantitative estimated information enables a variety of analyses.

[0097] (Section 9) In the sample analyzer according to any one of items 1 to 3, the sample may contain a formulation or an active ingredient, and the substance may contain an active ingredient or an impurity present in the formulation or the active ingredient.

[0098] It is possible to perform highly accurate analysis of pharmaceutical ingredients.

[0099] (Section 10) A sample analysis method according to another embodiment includes the steps of: acquiring a plurality of measurement data obtained by analyzing the sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; calculating a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; a step of reading out a reaction model stored in a storage device, modeling quantitative estimated information of the substance using the reaction model, and estimating parameters of the reaction model by providing the plurality of pieces of quantitative measurement information to the reaction model; calculating quantitative estimated information of the substance at any time based on the estimated parameters, or calculating information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold; Including, The reaction model includes an integrated error term that integrates errors from the set values ​​of the temperature and humidity that are set under the multiple analysis conditions.

[0100] It is possible to suppress a decrease in the accuracy of the reaction model estimation caused by errors in the acceleration factors.

[0101] (Section 11) A sample analysis method according to another embodiment includes the steps of: acquiring a plurality of measurement data obtained by analyzing the sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; calculating a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; a step of reading out a reaction model stored in a storage device, modeling quantitative estimated information of the substance using the reaction model, and estimating parameters of the reaction model by providing the plurality of pieces of quantitative measurement information to the reaction model; calculating quantitative estimated information of the substance at any time based on the estimated parameters, or calculating information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold; Including, In the reaction model, an additional reaction is set according to the initial value.

[0102] Even if there are additional reactions, the estimation result appropriately takes them into account.

[0103] (Section 12) A sample analysis method according to another embodiment includes the steps of: acquiring a plurality of measurement data obtained by analyzing the sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; calculating a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; a step of reading out a reaction model stored in a storage device, modeling quantitative estimated information of the substance using the reaction model, and estimating parameters of the reaction model by providing the plurality of pieces of quantitative measurement information to the reaction model; calculating quantitative estimated information of the substance at any time based on the estimated parameters, or calculating information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold; Including, A time lag for the start of analysis is set in the reaction model.

[0104] Even if there are additional reactions, the estimation result appropriately takes them into account.

[0105] (Section 13) In the sample analyzer according to any one of items 10 to 12, the sample may contain a formulation or an active ingredient, and the substance may contain an active ingredient or an impurity present in the formulation or the active ingredient.

[0106] It is possible to perform highly accurate analysis of pharmaceutical ingredients. [Explanation of symbols]

[0107] 1... sample analyzer, 11... CPU, 12... RAM, 13... ROM, 14... operation unit, 15... display, 16... storage device, 21... acquisition unit, 22... quantitative information calculation unit, 23... estimation unit, 24... calculation unit, 25... output unit, P1... program, MD... measurement data, PS... peak area ratio data, RM... reaction model, PM... parameter

Claims

1. an acquisition unit that acquires a plurality of measurement data obtained by analyzing a sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; an estimation unit that reads out a reaction model stored in a storage device, models quantitative estimation information of the substance using the reaction model, and estimates parameters of the reaction model by providing the plurality of pieces of quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; a calculation unit that calculates quantitative estimated information of the substance at an arbitrary time based on the parameters estimated by the estimation unit, or calculates information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, A sample analyzer, wherein the reaction model includes an integrated error term that integrates errors from the set values ​​of the temperature and humidity that are set under the plurality of analysis conditions.

2. an acquisition unit that acquires a plurality of measurement data obtained by analyzing a sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; an estimation unit that reads out a reaction model stored in a storage device, models quantitative estimation information of the substance using the reaction model, and estimates parameters of the reaction model by providing the plurality of pieces of quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; a calculation unit that calculates quantitative estimated information of the substance at an arbitrary time based on the parameters estimated by the estimation unit, or calculates information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, A sample analyzer, wherein an additional reaction is set in the reaction model according to an initial value.

3. an acquisition unit that acquires a plurality of measurement data obtained by analyzing a sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; a quantitative information calculation unit that calculates a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; an estimation unit that reads out a reaction model stored in a storage device, models quantitative estimation information of the substance using the reaction model, and estimates parameters of the reaction model by providing the plurality of pieces of quantitative measurement information calculated by the quantitative information calculation unit to the reaction model; a calculation unit that calculates quantitative estimated information of the substance at an arbitrary time based on the parameters estimated by the estimation unit, or calculates information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, A sample analyzer, wherein a time lag for starting analysis is set in the reaction model.

4. 4. The sample analyzer according to claim 1, wherein the reaction model is adapted to the Arrhenius equation or a modified Arrhenius equation.

5. The sample analyzer according to any one of claims 1 to 3, wherein the acceleration factor includes light.

6. The sample analyzer according to any one of claims 1 to 3, wherein a plurality of reaction models are stored in the storage device.

7. The sample analyzer according to any one of claims 1 to 3, wherein the quantitative estimation information of the substance includes a quantitative value, a confidence interval, or a quantile of the substance at any time.

8. The sample analyzer according to any one of claims 1 to 3, wherein the information relating to time includes a value, a confidence interval, or a quantile of the time until the quantitative estimation information of the substance reaches a predetermined threshold.

9. 4. A pharmaceutical analysis apparatus according to claim 1, wherein the sample contains a formulation or a drug substance, and the substance contains an active ingredient or an impurity present in the formulation or the drug substance.

10. acquiring a plurality of measurement data obtained by analyzing a sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; calculating a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; a step of reading out a reaction model stored in a storage device, modeling quantitative estimated information of the substance using the reaction model, and estimating parameters of the reaction model by providing the plurality of pieces of quantitative measurement information to the reaction model; Calculating quantitative estimated information of the substance at any time based on the estimated parameters, or calculating information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, A sample analysis method, wherein the reaction model includes an integrated error term that integrates errors from the set values ​​of the temperature and humidity that are set under the plurality of analysis conditions.

11. acquiring a plurality of measurement data obtained by analyzing a sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; calculating a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; a step of reading out a reaction model stored in a storage device, modeling quantitative estimated information of the substance using the reaction model, and estimating parameters of the reaction model by providing the plurality of pieces of quantitative measurement information to the reaction model; Calculating quantitative estimated information of the substance at any time based on the estimated parameters, or calculating information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, A sample analysis method, wherein an additional reaction is set in the reaction model according to an initial value.

12. acquiring a plurality of measurement data obtained by analyzing a sample in an analytical device under a plurality of analytical conditions including temperature and humidity as acceleration factors; calculating a plurality of quantitative measurement information of substances contained in the sample based on the plurality of measurement data; a step of reading out a reaction model stored in a storage device, modeling quantitative estimated information of the substance using the reaction model, and estimating parameters of the reaction model by providing the plurality of pieces of quantitative measurement information to the reaction model; Calculating quantitative estimated information of the substance at any time based on the estimated parameters, or calculating information regarding the time until the quantitative estimated information of the substance reaches a predetermined threshold, A sample analysis method, wherein a time lag for starting analysis is set in the reaction model.

13. 13. The pharmaceutical analysis method according to claim 10, wherein the sample contains a formulation or a drug substance, and the substance contains an active ingredient or an impurity present in the formulation or the drug substance.

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