Gradient condition search method, program, information processing device, and analysis system

Abstract

In liquid chromatography analysis of a sample, the goal is to determine gradient conditions that allow for the separation of specific components from other components. [Solution] The gradient condition search method according to the present disclosure includes: step S12 of receiving information to identify a target component; step S14 of obtaining first and second chromatogram data obtained by analyzing a sample containing two or more components using first and second gradient conditions that are different from each other; step S16 of creating a model that shows the relationship between the gradient conditions and the degree of separation for the target component based on the first and second chromatogram data; step S18 of using the model to calculate the predicted degree of separation for the target component corresponding to each of the multiple gradient conditions; and step S20 of selecting a gradient condition from the multiple gradient conditions that yields the highest predicted degree of separation or a predicted degree of separation that is equal to or greater than a threshold.

Description

Technical Field

[0001] The present disclosure relates to a gradient condition search method, a program, an information processing apparatus, and an analysis system, and more particularly, to determining gradient conditions for separating a specific component from other components.

Background Art

[0002] In a gradient elution method used in liquid chromatography, in which components in a sample are eluted while continuously changing the composition of two or more mobile phases, it is desirable to improve the resolution of peaks derived from a plurality of components appearing in a chromatogram by adjusting gradient conditions that define the time change in the mixing ratio of the two or more mobile phases.

[0003] Japanese Patent No. 7173159 (Patent Document 1) discloses a technique for calculating the resolution for each peak included in a chromatogram using a regression model that describes the relationship between gradient conditions and resolution, and presenting a distribution with the smallest resolution as an index to the user. The resolution is an index indicating how well two adjacent peaks are separated, and it can be said that the larger the value, the more separated the two peaks are. Therefore, the smallest resolution in a chromatogram is a value based on the two closest peaks in the chromatogram. If the smallest resolution in a chromatogram is greater than or equal to a threshold value (generally considered to be completely separated when it is 1.5 or more), it can be said that all the peaks included in the chromatogram are separated.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] According to Patent Document 1, a user can recognize gradient conditions that increase the smallest resolution value in a chromatogram. In the distribution presented in Patent Document 1, if the smallest resolution is greater than or equal to a threshold (for example, 1.5), it can be said that the components contained in the sample are separated. However, especially when there are many components in the sample, the number of peaks in the chromatogram increases, and in any gradient condition, the smallest resolution may fall below the threshold. In such cases, it is difficult to completely separate all peaks.

[0006] In the above case, the user may desire gradient conditions that allow for the separation of specific peaks derived from components of the user's choice, even if not all peaks can be separated. Patent Document 1 does not address such user needs.

[0007] This disclosure is made in view of these circumstances, and its purpose is to determine gradient conditions that can separate specific components from other components in the analysis of a sample by liquid chromatography.

[0008] A gradient condition search method according to a first aspect of this disclosure includes: (a) receiving information from a user to identify a target component; (b) obtaining first and second chromatogram data obtained by analyzing a sample containing two or more components, including the target component, under first and second different gradient conditions; (c) creating a model showing the relationship between the gradient conditions and the degree of separation for the target component based on the first and second chromatogram data; (d) using the model to calculate the predicted degree of separation for the target component corresponding to each of the multiple gradient conditions; and (e) selecting a gradient condition from the multiple gradient conditions that yields the highest predicted degree of separation or a predicted degree of separation equal to or greater than a threshold.

[0009] An information processing device according to a second aspect of this disclosure comprises at least one processor and one or more memory accessible to the processors, the memory storing one or more instructions to be executed by the processors, the processor receiving information from a user to identify a target component by executing one or more instructions, obtaining first and second chromatogram data obtained by analyzing a sample containing two or more components including the target component under mutually different first and second gradient conditions, creating a model showing the relationship between the gradient conditions and the degree of separation for the target component based on the first and second chromatogram data, calculating the predicted degree of separation for the target component corresponding to each of the multiple gradient conditions using the model, and selecting the gradient condition from the multiple gradient conditions that yields the highest predicted degree of separation or a predicted degree of separation equal to or greater than a threshold. [Effects of the Invention]

[0010] According to this disclosure, in the analysis of a sample by liquid chromatography, gradient conditions can be determined that allow for the separation of specific components from other components. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic diagram showing the configuration of the analysis system according to the embodiment. [Figure 2] This figure shows an example of a chromatogram. [Figure 3] This is a diagram illustrating the process for determining gradient conditions. [Figure 4] This is a flowchart showing the process of searching for gradient conditions. [Modes for carrying out the invention]

[0012] The embodiments of this disclosure will be described in detail below with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated.

[0013] [Configuration of the analysis system] FIG. 1 is a diagram showing the configuration of an analysis system 100 according to an embodiment. Referring to FIG. 1, the analysis system 100 includes a liquid chromatograph 1, an information processing device 2, an input device 3, and a display device 4. The analysis system 100 measures each component contained in the introduced sample.

[0014] The liquid chromatograph 1 includes a first container 11, a second container 12, a first pump 13, a second pump 14, a mixer 15, an injector 16, a column 17, and a detector 18. The liquid chromatograph 1 has a configuration for supplying a mobile phase according to the gradient elution method. The liquid chromatograph 1 separates and detects the components contained in the sample over time.

[0015] In the liquid chromatograph 1, a first solvent and a second solvent are prepared as solvents constituting the mobile phase. The first container 11 stores the first solvent, and the second container 12 stores the second solvent.

[0016] The first solvent and the second solvent have different elution powers from each other. In one implementation example, the first solvent is water and the second solvent is methanol. The first solvent and the second solvent may contain an acidic solution (e.g., trifluoroacetic acid, formic acid, and ammonium formate) as an additive.

[0017] The first pump 13 sucks the first solvent stored in the first container 11 and feeds it to the analysis flow path at a predetermined flow rate. The second pump 14 sucks the second solvent stored in the second container 12 and feeds it to the analysis flow path at a predetermined flow rate.

[0018] The mixer 15 mixes the first solvent supplied from the first pump 13 and the second solvent supplied from the second pump 14. The information processing device 2 adjusts the flow rates of the first solvent and the second solvent in the mobile phase by controlling the flow rates of the first pump 13 and the second pump 14, thereby adjusting the ratio of the first solvent and the second solvent in the mobile phase.

[0019] The injector 16 injects a predetermined amount of the sample prepared in advance in the flow path of the mobile phase into the liquid chromatograph 1. The sample is introduced from the injector 16 into the mobile phase fed from the first pump 13 and the second pump 14, and the mobile phase containing the sample is introduced into the column 17.

[0020] The column 17 is filled with a stationary phase, and the mobile phase passes through its interior. When passing through the column 17, various components in the sample interact with the mobile phase and the stationary phase, and thus are separated in the time direction. The column 17 may be housed in a column oven (not shown) and the temperature may be maintained at a predetermined temperature.

[0021] The detector 18 is a device for detecting each of the components separated in the column 17. The detector 18 acquires a detection signal based on each of the components separated in the column 17 and transmits the detection signal to the information processing device 2. The detector 18 is, for example, an absorbance detector such as an ultraviolet absorbance detector (UV detector) or a photodiode array detector (PDA detector), a fluorescence detector, a differential refractive index detector, an evaporative light scattering detector, an electrochemical detector, and a conductivity detector. Further, the detector 18 may be a mass spectrometer. In this case, the mass spectrometer analyzes the eluate introduced from the liquid chromatograph 1 and continuously acquires a mass spectrum. The mass spectrum is represented by a graph with the mass-to-charge ratio (m / z) of ions on the horizontal axis and the relative amount of ions on the vertical axis. From the obtained mass spectrum, the molecular weight, mass-to-charge ratio, and base peak mass of each component can be determined.

[0022] Note that the liquid chromatograph 1 according to the present embodiment uses two types of solvents, the first solvent and the second solvent, as the mobile phase, but the number of solvents is not limited to this, and three or more types of solvents may be mixed to form the mobile phase. In this case, the liquid chromatograph 1 includes a pump for supplying each solvent to the mixer 15.

[0023] The information processing device 2 controls the operation of the first pump 13, the second pump 14, and the injector 16, and also performs various calculations and creates chromatogram data based on the detection signal obtained by the detector 18, and searches for gradient conditions.

[0024] The information processing device 2 includes, as its main components, a processor 21, memory 22, a communication interface (I / F) 23, and an input / output I / F 24. Each of these components is connected to each other via a bus so as to be able to communicate. The information processing device 2 is, for example, a computer. Note that the information processing device 2 does not need to be composed of a single computer; it may be composed of multiple computers.

[0025] The processor 21 is an example of an electrical circuit and controls the operation of the information processing device 2 by executing a given program. The program executed by the processor 21 may be stored in memory 22 or in a storage device outside the information processing device 2. The processor is, for example, a CPU (Central Processing Unit).

[0026] Memory 22 non-temporarily stores programs executed by the processor 21 and chromatograms created based on detection signals obtained by the detector 18. The programs and chromatograms stored in memory 22 include reference chromatogram data 221 and a search program 222. Memory 22 includes volatile memory (e.g., RAM (Random Access Memory)) and non-volatile memory (e.g., ROM (Read Only Memory), hard disk drives, and solid-state drives). The above programs and / or chromatograms may also be stored in an external storage device accessible by the processor 21.

[0027] Reference chromatogram data 221 includes two or more chromatogram data obtained by analyzing the sample targeted for gradient condition exploration under various gradient conditions.

[0028] The search program 222 uses the reference chromatogram data 221 to select gradient conditions that satisfy predetermined criteria. Details of the processing performed by the search program 222 will be described later.

[0029] Communication I / F23 is a communication interface for exchanging various data with external devices. Communication I / F23 is implemented, for example, by a network adapter. The communication method may be wireless communication such as Bluetooth® or Wi-Fi, or it may be wired communication using USB (Universal Serial Bus), etc.

[0030] The input / output interface 24 is an interface for exchanging various types of data between the processor 21 and external devices connected to the input / output interface 24. The external devices include a liquid chromatograph 1, an input device 3, and a display device 4.

[0031] In the analysis system 100 according to this embodiment, the information processing device 2 controls the liquid chromatograph 1. However, another control device (for example, a computer) may be connected to the liquid chromatograph 1, and the liquid chromatograph 1 may be controlled by this control device.

[0032] The input device 3 includes, for example, at least one of a mouse, a keyboard, and a touch panel, and accepts operations on the information processing device 2 and input of information to the information processing device 2. This information is, for example, information that identifies peaks derived from target components that the user wishes to separate in the chromatogram. The information that identifies peaks derived from target components is, for example, information on the area of ​​the peaks derived from the target components, information on the height of the peaks derived from the target components, and the elution order. The information on the area of ​​the peaks derived from the target components is, for example, the ranking of the magnitudes of the peaks derived from the target components among the peaks included in the chromatogram. The information on the heights of the peaks derived from the target components is, for example, the ranking of the heights of the peaks derived from the target components among the peaks included in the chromatogram. Furthermore, if the detector 18 is a PDA, this information may be the wavelength of the peaks of the target components. In addition, if the detector 18 is a mass spectrometer, this information may be the molecular weight, mass-to-charge ratio, or base peak mass of the target components.

[0033] The display device 4 includes, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and displays information according to the instructions of the information processing device 2. This information includes, for example, the gradient conditions for separating the target component of the sample output by the information processing device 2, and the chromatogram that is estimated to be obtained when the sample is analyzed under those gradient conditions.

[0034] [Comparative Example] In analysis using liquid chromatography, even when analyzing the same sample, the resulting chromatogram will vary depending on the analytical conditions, such as the type of solvent used, the type of column, and the temperature during measurement. Gradient conditions are also one of the analytical conditions that affect the chromatogram. Gradient conditions define the time change in the mixing ratio of two or more mobile phases. It is preferable to adjust the gradient conditions to improve the separation of peaks originating from multiple components that appear in the chromatogram.

[0035] Resolution is an index that indicates how well a particular peak is separated from other adjacent peaks. Resolution R is expressed by the following equation (1), where T1 and T2 are the retention times of two adjacent peaks, and W1 and W2 are the peak widths of those two peaks.

[0036]

number

[0037] The greater the degree of separation between two peaks, the more clearly the two peaks are separated. For example, if the value calculated as the degree of separation between a peak and an adjacent peak is 1.5 or higher, the peaks are considered to be completely separated. However, the degree of separation value used here (1.5) is merely an example and may be changed as appropriate depending on the circumstances to which the technology relating to this disclosure is applied. In this specification, the degree of separation of a given component refers to the smaller of the two degrees of separation calculated between the given component and the two components eluted before and after it.

[0038] Patent Document 1 discloses a technique that uses a regression model describing the relationship between gradient conditions and resolution to calculate the resolution for each peak in a chromatogram, and presents to the user a distribution that uses the smallest resolution among the peaks in the chromatogram as an indicator.

[0039] According to Patent Document 1, a user can recognize a gradient condition that maximizes the resolution of the smallest peak in the chromatogram. However, for example, when the sample contains many components, it may not be possible to find a gradient condition in which the smallest resolution is greater than or equal to a threshold (e.g., 1.5). In such cases, it is difficult to completely separate all peaks. In such cases, the user may want a gradient condition that can separate a specific peak, even if it cannot separate all peaks.

[0040] Figure 2 shows an example of a chromatogram obtained by analyzing a sample using liquid chromatography. Figure 2 shows chromatograms obtained by analyzing a sample containing five components a to e under two gradient conditions, gradient condition x and gradient condition y. The peaks originating from components a to e are denoted as peaks A to E, respectively.

[0041] The smallest resolution of the peaks in the chromatogram X obtained under gradient condition x is higher than that under other gradient conditions, but it is not above the threshold. Therefore, it is difficult to separate the five components a to e contained in the sample.

[0042] Here, when measuring component c in a sample, the user may want to search for a gradient condition that can separate peak C derived from component c, even if it is not possible to separate all components contained in the sample. In such cases, for example, as shown in Figure 2, a gradient condition y is sought that increases the degree of separation of component c. Since the degree of separation of peak C in chromatogram Y obtained by gradient condition y is greater than the degree of separation of peak C in chromatogram X, it can be said that gradient condition y is a gradient condition more suitable for separating component c than gradient condition x.

[0043] Patent Document 1 does not discuss comparing multiple gradient conditions using the degree of separation of a specific peak derived from the target component as an indicator.

[0044] [Analysis system according to an embodiment] Therefore, in the analytical system according to the embodiment, a model is created showing the relationship between gradient conditions and the degree of separation for the target component using chromatogram data obtained by analyzing the sample under various gradient conditions, and gradient conditions are searched for that can separate the peak originating from the target component from other peaks.

[0045] According to the analysis system of this embodiment, gradient conditions can be determined that allow the peak derived from the target component to be separated from other peaks, and the target component can be measured by analyzing the sample under these gradient conditions.

[0046] In this specification, the resolution of a predetermined peak refers to the resolution of the lesser of the two resolutions calculated between the predetermined peak and the peaks before and after it. Furthermore, if a predetermined component corresponds to the earliest or latest elution order in the chromatogram, the resolution of the predetermined component refers to the resolution between the peak corresponding to that predetermined component and the adjacent peak.

[0047] The process by which the analysis system 100 according to this embodiment selects gradient conditions will be described below. Figure 3 is a block diagram illustrating the procedure by which the analysis system 100 searches for gradient conditions.

[0048] As shown in Figure 3, the information processing device 2 executes the search program 222. First, the information processing device 2 retrieves the reference chromatogram data 221 from the memory 22. The reference chromatogram data 221 includes chromatogram data obtained by analyzing the sample for which the analysis system 100 determines the gradient conditions, under two or more different gradient conditions.

[0049] The information processing device 2 receives information from the user to identify the target component via the input device 3. The target component is not limited to a single compound and may include multiple compounds. The information processing device 2 may also read the information identifying the target component from the memory 22.

[0050] The target component is a component in the sample that the user wishes to separate from other components. The information used to identify the target component is necessary to identify the peak derived from the target component in the reference chromatogram data 221, and includes, for example, information on the area of ​​the peak corresponding to the target component, information on the height of the peak corresponding to the target component, and the elution order of the target component. The information on the area of ​​the peak corresponding to the target component is, for example, the ranking of the magnitudes of the peaks derived from the target component among the peaks included in the chromatogram. The information on the height of the peak corresponding to the target component is, for example, the ranking of the heights of the peaks derived from the target component among the peaks included in the chromatogram. Furthermore, if the detector 18 is a PDA, this information may also be the wavelength of the peak of the target component. In addition, if the detector 18 is a mass spectrometer, this information may also be the molecular weight of the target component, the mass-to-charge ratio of the target component, or the base peak mass of the target component.

[0051] Next, the information processing device 2 identifies a peak contained in one of the chromatogram data from the reference chromatogram data 221. The peak is detected, for example, by peak waveform processing. The detected peak is associated with a corresponding peak in the other reference chromatogram data 221. Specifically, the association of each peak detected in each of the two or more chromatogram data contained in the reference chromatogram data 221 is made based on, for example, the elution order, peak waveform, peak area, peak height, spectral information if the detector 18 is a PDA, and mass spectral information if the detector 18 is a mass spectrometer.

[0052] Each peak in the reference chromatogram data 221 originates from each component present in the sample. Therefore, the above processing identifies the peaks of each component in the sample under each gradient condition. This allows for the identification of the peak of the target component in the reference chromatogram data 221.

[0053] The information processing device 2 extracts the retention time and peak width for each component under each gradient condition from the reference chromatogram data 221.

[0054] Next, the information processing device 2 creates a model that shows the relationship between gradient conditions and resolution for the target component. Specifically, based on the retention time and peak width of the target component and the components eluted before and after the target component under each gradient condition, it predicts the retention time and peak width of the target component and the components eluted before and after the target component under multiple unmeasured gradient conditions, and creates a model to calculate the predicted resolution, which is a predicted value of the resolution of the target component under those multiple unmeasured gradient conditions, from these predictions.

[0055] An example of a model creation method is shown below. In one embodiment, the model for calculating the predicted separation of the target component is created using the target component and the measured retention times and peak widths of components eluted before and after the target component in the chromatogram data of reference chromatogram data 221. The predicted retention times and peak widths for each component are obtained using model equations that show the relationship between gradient conditions and retention time, and model equations that show the relationship between gradient conditions and peak width. That is, creating the model involves calculating the coefficients in those model equations for the target component and the components eluted before and after the target component from the measured elution times and peak widths of each peak in the reference chromatogram data 221, and the model includes the model equations.

[0056] First, let's explain the model equation for predicting retention time. The migration rate of a compound can be expressed as the reciprocal of the retention coefficient, and the retention time t R The relationship between the retention coefficient k(t) at each time step is given by the dwell time and t. D Let t0 be the dead time, and the equation (2) below expresses this.

[0057]

number

[0058] t D k(0) is calculated as system capacity / flow rate, and t0 is calculated as column capacity / flow rate. k(0) represents the retention coefficient for the mobile phase composition before time 0. It is assumed that the mobile phase composition is fixed and the retention coefficient remains unchanged until the start of the analysis.

[0059] Furthermore, the relationship between the organic solvent concentration and the retention coefficient during reversed-phase analysis is expressed by the following equation (3), where φ(t) is the ratio of the organic solvent in the mobile phase at each time step, and k0 is the retention coefficient when the organic solvent ratio is 0.

[0060]

number

[0061] In equation (3), S1 and S2 are coefficients, and these vary depending on the type of sample, mobile phase, and column.

[0062] The information processing device 2 determines k0, S1, and S2 by fitting the time evolution of peak retention times and organic solvent ratios in the acquired reference chromatogram data 221, and creates a model equation relating to retention time for each component. By substituting arbitrary gradient conditions into the created model equation, it is possible to obtain predicted values ​​for the retention time of each component under those gradient conditions.

[0063] Next, we will explain the model equation for predicting peak width. In reverse-phase gradient analysis, it is known that the peak width tends to change with respect to the retention time, and this is called peak compression. Peak compression is expressed as follows: the compression coefficient G is the peak width W, and k(t) R With ) as the retention coefficient during elution and N as the number of theoretical plates in the column, it can be expressed by the following equation (4).

[0064]

number

[0065] Note that the retention coefficient k(t R ) can be calculated based on equation (3). The compression coefficient G is expressed by the following equation (5) using the retention coefficient.

[0066]

number

[0067] Similar to the creation of the retention time model equation, the information processing device 2 determines each coefficient by fitting based on the acquired reference chromatogram data 221 and creates a model equation relating to the peak width for each component. By substituting an arbitrary gradient condition into the created model equation, a predicted value of the peak width of the peak under that gradient condition can be obtained.

[0068] Furthermore, the model equations used to create the model equations are not limited to the formulas described above. The model equations used to estimate retention time and peak width may be exponential functions, polynomials, or kernel regressions such as Gaussian kernel regression. Also, the model equations used to estimate retention time and peak width may be functions of the same shape or functions of different shapes.

[0069] Furthermore, while a model equation was used to predict retention time and peak width in the above-described embodiment, the method is not limited to this, and retention time and peak width may also be predicted by machine learning, for example.

[0070] Under predetermined gradient conditions, the predicted separation rate of the target component can be determined using the predicted retention time and peak width of the target component and the components eluted before and after it.

[0071] In the above-described example, to calculate the predicted separation of the target component, the predicted retention time and peak width of components eluted before and after the target component in one of the reference chromatogram data 221 were used. However, components eluted before and after the target component in one chromatogram data may not necessarily be eluted before and after the target component in different chromatogram data. Therefore, the predicted separation of the target component may be determined by predicting the retention time and peak width for all components contained in the sample, or the predicted retention time and peak width of components eluted within the 5th position before and after the target component in one of the reference chromatogram data 221 may be used. The fewer the predicted retention time and peak width values ​​used to calculate the predicted separation of the target component, the less burden it places on the information processing device 2 for model creation.

[0072] The information processing device 2 calculates the predicted separation rate of the target component for each of several gradient conditions with different gradient conditions, using the created model. The multiple gradient conditions may be specified by the user or predetermined. For example, the multiple gradient conditions are gradient conditions in which the initial organic solvent concentration is shifted by 5%, such as 0%, 5%, 10%, etc., in the gradient condition from which one chromatogram data of the reference chromatogram data 221 was obtained.

[0073] The information processing device 2 selects from among the multiple gradient conditions the gradient condition that yields the highest predicted separation of the target component, or the gradient condition that results in a predicted separation of the target component being equal to or greater than a threshold. This threshold is, for example, 1.5.

[0074] Furthermore, the information processing device 2 may search for gradient conditions that result in a higher predicted separation of the target component than the multiple gradient conditions used to calculate the predicted separation of the target component. For example, the information processing device 2 may search for the gradient condition that maximizes the predicted separation of the target component using Bayesian optimization.

[0075] Furthermore, the information processing device 2 may select gradient conditions based on evaluation values ​​obtained by applying the derived predicted separation values ​​to a function whose variable is the separation value of the target component. In particular, when the target component includes multiple compounds, the predicted separation values ​​calculated for each compound can be applied to the function, and gradient conditions that can separate the multiple compounds can be searched for based on the evaluation values ​​obtained. Specifically, for example, the larger the evaluation value derived from the function, the more favorable the corresponding gradient condition is. The function may also use the minimum separation value in the corresponding gradient condition as a variable. The information processing device 2 derives evaluation values ​​for multiple gradient conditions and searches for the gradient condition that maximizes the evaluation value using Bayesian optimization. The information processing device 2 selects the gradient condition that maximizes the evaluation value as the gradient condition for separating the target component.

[0076] A function whose variable is the resolution of the target component may further include at least one of the following variables: final peak elution time, initial organic solvent concentration of the mobile phase, final organic solvent concentration of the mobile phase, and confidence level. The confidence level indicates the robustness of the predicted resolution calculated by the model and includes information such as whether the gradient conditions are linear or step gradient. Generally, linear gradients are more robust in predicting the resolution of the target component than step gradients, so the confidence level will be higher. Furthermore, the confidence level may be scored differently depending on the number of steps in the step gradient. Generally, fewer steps in the step gradient are more robust in predicting the resolution of the target component, so the confidence level will be higher.

[0077] The information processing device 2 selects gradient conditions for separating the target components, and then displays the gradient conditions and the chromatogram estimated to be obtained when the sample is analyzed under those gradient conditions on the display device 4.

[0078] By analyzing the sample under the gradient conditions displayed on the display device 4, the user can separate the target component from other components using liquid chromatography and measure the target component.

[0079] Furthermore, chromatogram data obtained by measuring the sample under the selected gradient conditions may be added to the reference chromatogram data 221, and the search for gradient conditions may be performed again. This process can improve the prediction accuracy of the model.

[0080] [flowchart] Figure 4 is a flowchart illustrating the process related to the search for gradient conditions. The information processing device 2 performs the process shown in this flowchart by having the processor 21 execute the search program 222.

[0081] Referring to Figure 4, in step S10, the processor 21 detects an operation to start the search for gradient conditions. For example, if a user uses the input device 3 to start the search for gradient conditions, that operation is detected in step S10.

[0082] In step S12, the processor 21 receives information from the user to identify the target component. The information to identify the target component includes, for example, at least one of the following: information on the area of ​​the peak derived from the target component, information on the height of the peak derived from the target component, the wavelength of the PDA of the target component, the molecular weight of the target component, the mass-to-charge ratio of the target component, and the base peak mass of the target component. The target component is not limited to one compound and may include multiple compounds.

[0083] In step S14, the processor 21 reads and acquires reference chromatogram data 221 from memory 22. The reference chromatogram data 221 includes multiple chromatogram data obtained by analyzing a sample containing two or more components under one or more different gradient conditions.

[0084] In step S16, the processor 21 creates a model showing the relationship between gradient conditions and resolution for the target component based on the reference chromatogram data 221.

[0085] In step S18, the processor 21 uses the model created in step S16 to calculate the predicted separation, which is a predicted value of the separation of the target component corresponding to each of several different gradient conditions.

[0086] In step S20, the processor 21 selects from the predicted separation values ​​calculated in step S18 the gradient condition that yields the highest predicted separation value, or the gradient condition in which the predicted separation value is equal to or greater than a threshold. This threshold may be specified by the user or may be predetermined, for example, 1.5.

[0087] In step S22, the processor 21 displays the selected gradient conditions and the chromatogram obtained by measuring the sample under those gradient conditions on the display device 4. After that, the processor 21 completes the series of processes shown in Figure 4.

[0088] According to the gradient condition search method of this embodiment, when measuring a sample using liquid chromatography with two or more solvents as mobile phases, it is possible to search for gradient conditions that can separate specific components contained in a sample from other components.

[0089] [Aspect] Those skilled in the art will understand that the above-described exemplary embodiments are specific examples of the following embodiments.

[0090] (Section 1) A gradient condition search method in one embodiment may include the steps of: receiving information to identify a target component; obtaining first and second chromatogram data obtained by analyzing a sample containing two or more components under first and second gradient conditions that are different from each other; creating a model showing the relationship between the gradient conditions and the degree of separation for the target component based on the first and second chromatogram data; using the model to calculate the predicted degree of separation for the target component corresponding to each of the plurality of gradient conditions; and selecting a gradient condition from the plurality of gradient conditions that yields the largest predicted degree of separation or a predicted degree of separation equal to or greater than a threshold.

[0091] According to the gradient condition search method described in paragraph 1, it is possible to determine gradient conditions that can separate specific components from other components in the analysis of a sample by liquid chromatography.

[0092] (Clause 2) In the gradient condition search method described in paragraph 1, the step of creating the model comprises the steps of calculating coefficients in a first model equation showing the relationship between the gradient condition and retention time for the target component, and calculating coefficients in a second model equation showing the relationship between the gradient condition and peak width for the target component, wherein the model may include the first and second model equations.

[0093] According to the gradient condition search method described in Section 2, a model is created that shows the relationship between the gradient conditions and the degree of separation of the target component, using model equations that show the relationship between the gradient conditions and the retention time and peak width, respectively.

[0094] (Clause 3) In the gradient condition search method described in paragraph 1 or 2, the selection step may include a step of calculating an evaluation value by applying the predicted separation value to a function whose variable is the separation value of the target component.

[0095] According to the gradient condition search method described in Section 3, the gradient condition is searched based on an evaluation value obtained by applying the predicted separation value to a function whose variable is the separation value of the target component.

[0096] (Clause 4) In the gradient condition search method described in Clause 3, the function may further include at least one of the following variables: final peak elution time, initial organic solvent concentration of the mobile phase, final organic solvent concentration of the mobile phase, and confidence level.

[0097] According to the gradient condition search method described in Section 4, gradient conditions can be searched using a function that reflects at least one of the following values: final peak elution time, initial organic solvent concentration of the mobile phase, final organic solvent concentration of the mobile phase, and confidence level.

[0098] (Clause 5) In the gradient condition search method described in Clause 4, the confidence level may include the number of steps allowed in the step gradient.

[0099] According to the gradient condition search method described in Section 5, the function used to search for the gradient condition is based on confidence, and this confidence includes information about the number of steps allowed in a step gradient. Specifically, a gradient condition that does not include a step gradient is treated as a more preferable condition than a gradient condition that includes a step gradient.

[0100] (Clause 6) In the gradient condition search method described in any one of Clauses 3 to 5, the selection step may further include a step of searching for the gradient condition that minimizes the evaluation value from the plurality of gradient conditions by Bayesian optimization.

[0101] According to the gradient condition search method described in Section 6, the gradient condition that maximizes the evaluation value is searched for using Bayesian optimization. By using Bayesian optimization, the efficiency of searching for the gradient condition is improved.

[0102] (Section 7) In the gradient condition search method described in any one of Sections 1 to 6, the target component may include two or more compounds.

[0103] According to the gradient condition search method described in Section 7, gradient conditions for separating target components containing two or more compounds can be searched.

[0104] (Clause 8) In the gradient condition search method described in any one of Clauses 1 to 7, the information for identifying the target component may include at least one of the following: information on the area of ​​the peak derived from the target component, information on the height of the peak derived from the target component, the molecular weight of the target component, the mass-to-charge ratio of the target component, and the base peak mass of the target component.

[0105] According to the gradient condition search method described in Section 8, the target component is identified based on at least one of the following: information on the peak area, information on the peak height, the molecular weight of the target component, the mass-to-charge ratio, and the base peak mass.

[0106] (Clause 9) The gradient condition search method described in any one of Clauses 1 to 8 may further include a step of displaying a chromatogram that is estimated to be obtained by measuring the sample under the gradient conditions selected in the selection step.

[0107] According to the gradient condition search method described in Section 9, the user can easily recognize the chromatogram that is estimated to be obtained by measuring the sample. Based on this chromatogram, the user can decide whether to measure the sample under the determined gradient conditions or to continue searching for gradient conditions.

[0108] (Clause 10) In one embodiment, the program may be executed by a processor installed in a computer, thereby causing the computer to execute the gradient condition search method described in any one of paragraphs 1 to 10.

[0109] According to the program described in Section 10, gradient conditions can be determined that allow for the separation of specific components from other components in the analysis of a sample by liquid chromatography.

[0110] (Clause 11) An information processing device in one embodiment includes at least one processor and a memory accessible from the one or more processors, wherein the memory stores one or more instructions to be executed by the processor, and the processor receives information to identify a target component by executing the one or more instructions, obtains first and second chromatogram data obtained by analyzing a sample containing two or more components under mutually different first and second gradient conditions, creates a model showing the relationship between the gradient conditions and the degree of separation for the target component based on the first and second chromatogram data, calculates the predicted degree of separation for the target component corresponding to each of the plurality of gradient conditions using the model, and may select a gradient condition from the plurality of gradient conditions that yields the largest predicted degree of separation or a predicted degree of separation equal to or greater than a threshold.

[0111] According to the information processing device described in paragraph 11, gradient conditions can be determined in which specific components can be separated from other components during the analysis of a sample by liquid chromatography.

[0112] (Clause 12) An analytical system in one embodiment may include the information processing device described in paragraph 11 and a liquid chromatograph.

[0113] According to the analytical system described in Section 12, gradient conditions can be determined in the analysis of a sample by liquid chromatography that can separate specific components from other components.

[0114] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of this disclosure is indicated by the claims rather than by the description of the embodiments above, and all modifications within the meaning and scope equivalent to the claims are intended to be included. Furthermore, each technology in the embodiments is intended to be practiced individually or, as far as possible, in combination with other technologies in the embodiments. [Explanation of symbols]

[0115] 1 Liquid chromatograph, 2 Information processing device, 3 Input device, 4 Display device, 11 First container, 12 Second container, 13 First pump, 14 Second pump, 15 Mixer, 16 Injector, 17 Column, 18 Detector, 21 Processor, 22 Memory, 23 Communication I / F, 24 Input / Output I / F, 100 Analysis system, 221 Reference chromatogram data, 222 Search program.

Claims

1. A step to receive information to identify the target ingredient, The steps include obtaining first and second chromatogram data obtained by analyzing a sample containing two or more components under first and second gradient conditions that are different from each other, Based on the first and second chromatogram data, a model is created to show the relationship between gradient conditions and resolution for the target component. Using the aforementioned model, the steps include: calculating the predicted separation rate of the target component corresponding to each of the multiple gradient conditions; A gradient condition search method comprising the step of selecting a gradient condition from the plurality of gradient conditions that yields the highest predicted separation or a gradient condition that yields a threshold or higher.

2. The step of creating the aforementioned model is: The steps include calculating the coefficients in the first model equation that shows the relationship between gradient conditions and retention time for the aforementioned target component, The process includes the step of calculating the coefficients in a second model equation that shows the relationship between gradient conditions and peak width for the aforementioned target component. The gradient condition search method according to claim 1, wherein the model includes the first and second model equations.

3. The gradient condition search method according to claim 1 or 2, wherein the selection step comprises the step of calculating an evaluation value by applying the predicted separation value to a function whose variable is the separation value of the target component.

4. The gradient condition search method according to claim 3, wherein the function further has at least one of the following as variables: final peak elution time, initial organic solvent concentration of the mobile phase, final organic solvent concentration of the mobile phase, and confidence level.

5. The gradient condition search method according to claim 4, wherein the reliability includes the number of steps allowed in the step gradient.

6. The gradient condition search method according to claim 3, wherein the selection step further comprises a step of searching for the gradient condition that maximizes the value of the evaluation value from the plurality of gradient conditions by Bayesian optimization.

7. The gradient condition search method according to claim 1 or claim 2, wherein the target component comprises two or more compounds.

8. The gradient condition search method according to claim 1 or claim 2, wherein the information identifying the target component includes at least one of the following: information on the area of ​​the peak derived from the target component, information on the height of the peak derived from the target component, the molecular weight of the target component, the mass-to-charge ratio of the target component, and the base peak mass of the target component.

9. A method for searching for gradient conditions according to claim 1 or 2, further comprising the step of displaying a chromatogram that is estimated to be obtained by measuring the sample under the gradient conditions selected in the selection step.

10. A program that, when executed by a processor installed in a computer, causes the computer to execute the gradient condition search method described in claim 1 or claim 2.

11. At least one processor, The system includes memory that can access one or more processors, The memory stores one or more instructions to be executed by the processor, The processor executes one or more instructions, We accept information to identify the target ingredient. First and second chromatogram data are obtained by analyzing a sample containing two or more components under two different first and second gradient conditions. Based on the first and second chromatogram data, a model was created showing the relationship between gradient conditions and resolution for the target component. Using the aforementioned model, the predicted separation rate of the target component corresponding to each of the multiple gradient conditions is calculated. An information processing device that selects from the above-mentioned plurality of gradient conditions the gradient condition that yields the highest predicted separation degree, or the gradient condition that yields the predicted separation degree above a threshold.

12. An analysis system comprising the information processing device described in claim 11 and a liquid chromatograph.

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