Multi-sample circular dichroism analyzer

Abstract

The objective is to automate the sequence setting in a multi-sample circular dichroism analyzer. [Solution] The computer of the multi-sample circular dichroism (CD) analyzer is equipped with a sequence setting function that determines the order in which samples are measured. It acquires information about the sample, information about the solvent, and information about the number of samples (N). Using attribute information that distinguishes whether the sample and solvent relate to a standard sample (R) or to the samples to be evaluated (S1, S2, ...), and type information that distinguishes between the sample (S) and the solvent (B), it automatically determines the order in which samples are measured according to the following rules (1) to (3): (1) for each attribute, one sample and one solvent sample are made into one set, and one solvent sample is placed immediately before or after one sample sample; (2) all sets of sample and solvent samples for all attributes are placed in a single row; and (3) the arrangement of the sample sets is repeated for the number of samples (N).

Description

Technical Field

[0001] The present invention relates to an apparatus for measuring circular dichroism spectra for a large number of specimens.

Background Art

[0002] In recent years, due to the increasing interest in antibody pharmaceuticals, there has been a growing need to measure multiple specimens using a circular dichroism (CD) measurement apparatus capable of evaluating the higher-order structure (secondary and tertiary structures) of proteins. Evaluation of the higher-order structure (HOS) is essential in the development of follow-up products (biosimilars) of antibody pharmaceuticals, and it is necessary to evaluate the identity between the pioneer product (innovator) and the follow-up product (for example, see Patent Document 1). In addition to the development of biosimilars, HOS evaluation is also performed in stability evaluation to evaluate whether denaturation or inactivation occurs due to changes in temperature, salt concentration, and pH. At this time, for statistical comparative studies, a large number of samples with slightly different conditions are measured.

[0003] For spectral measurement of multiple specimens, an autosampler is usually used (for example, see Patent Document 2). In a system combining a spectrophotometer, an autosampler, and a flow cell, automatic measurement of multiple specimens is possible by automatically performing a series of operations including conveyance of the sample to the flow cell (suction by a pump), discharge of the sample from the flow cell after measurement is completed (discharge by a pump), and cleaning of the flow cell and the flow path.

[0004] When performing CD measurement on multiple specimens with a single beam, in order to reduce the influence of drift (change over time) of the measurement apparatus, the order of measurement of the specimens, that is, the sequence setting, is important. When there are multiple types of samples such as in stability evaluation, and there are N specimens for each type of sample, instead of measuring the N specimens of the first type of sample and then repeating the measurement of the N specimens of the next type of sample, it is recommended to measure one specimen at a time for each type of sample and repeat this for all types of samples N times.

Prior Art Documents

[0005] [Patent Document 1] Japanese Patent Publication No. 2022-080555 [Patent Document 2] Japanese Patent Publication No. 2007-187474 [Overview of the project] [Problems that the invention aims to solve]

[0006] However, the first problem with conventional CD measuring devices is that when dealing with multiple types of samples, or when the sample size (N) for a single type of sample is large, the user's burden in setting up the sequence increases. This is because the user had to set the measurement order for each sample individually.

[0007] Furthermore, when using samples such as proteins dissolved in a solvent, it is necessary to measure only the solvent (buffer) immediately before or after measuring the sample for baseline correction. For example, when measuring three types of samples A, B, and C with N=3, and the buffers are denoted as Ra, Rb, and Rc, the user needs to set up a complex sequence combining the samples and buffers, such as Ra→A1→Rb→B1→Rc→C1→Ra→A2→Rb→B2→Rc→C2→Ra→A3→Rb→B3→Rc→C3.

[0008] Furthermore, conventional CD measuring devices perform the necessary data processing and spectral analysis on each individual spectral data point. However, in the case of sequence measurements combining several types of samples and their respective buffers, as described above, a second problem arises: the user must read out the desired data point from the numerous spectral data points stored in the computer's memory, and then perform the appropriate data processing and spectral analysis on each individual data point, which is extremely time-consuming. There is also the possibility of errors such as reading out the wrong data. For example, when subtracting spectra during baseline correction, there is a possibility of making mistakes in the combination of spectra or the order in which they are subtracted, or when evaluating identity, there is a possibility of misidentifying the spectrum being evaluated.

[0009] The present invention aims to automate sequence setting in multi-sample CD measurement, and to automate data processing or spectral analysis of the large number of spectral data obtained in multi-sample CD measurement. [Means for solving the problem]

[0010] In other words, the multi-sample circular dichroism (CD) measuring device of the present invention is a multi-sample circular dichroism (CD) measuring device that measures the circular dichroism (CD) spectra of multiple samples, Flow cell and, An autosampler that transports the samples to the flow cell in the order of measurement and discharges them from the flow cell, A measuring instrument unit for measuring the CD spectrum of the sample in the flow cell, The system includes a computer that controls the autosampler and the measuring instrument unit and processes the CD spectrum from the measuring instrument unit. The aforementioned computer, It includes a sequence setting function that determines the measurement order of the aforementioned samples, The sequence setting function uses the following input information (1) to (3): (1) Sample information (e.g., sample name, identification number, concentration, etc.), (2) Information on the solvent contained in the sample, and (3) Information on the number of samples (N: where N is a natural number of 1 or more) of the above sample, Obtain attribute information (R,S1,S2,...) that distinguishes whether the sample and solvent relate to a standard sample (R) or to one of the samples to be evaluated (S1,S2,...), and type information (S,B) that distinguishes the sample and the solvent, and use the following rules (4)~(6): (4) For each attribute (R, S1, S2, ...), one sample (S) and one solvent (B) are made into a set, and the solvent (B) is placed immediately before or immediately after the sample (S). (5) Arrange the sets of samples of the sample (S) and solvent (B) for all the attributes (R, S1, S2, ...) in a single row, (6) The arrangement of the set of samples is repeated the number of times (N) of the sample. The measurement order of the samples is determined accordingly. It is characterized by functioning in such a way.

[0011] With this configuration of a multi-sample circular dichroism analyzer, the first problem is addressed by inputting "sample information, information on the solvent contained in the sample, and information on the number of samples (N)," which automatically sets the recommended sequence.

[0012] Furthermore, the sequence setting function is In order to determine the positions in which the samples are arranged in the vertical and horizontal planes on the autosampler, the following rules (7), (8) are used using the attribute information (R, S1, S2, ...) and the type information (S, B): (7) The rows of the sample sets in (5) above are arranged vertically, and (8) Samples for which both attribute information and type information are the same are arranged horizontally. The position of the sample in the autosampler is determined accordingly. It is preferable that it functions in this way.

[0013] According to the multi-sample circular dichroism measuring apparatus having the above configuration, an appropriate arrangement diagram of the samples in the autosampler is automatically determined.

[0014] Also, the computer is provided with a storage unit capable of storing the CD spectrum data in a state where the attribute information (R, S1, S2, ···) and the type information (S, B) are attached to or associated with the CD spectrum data. When executing a previously specified data process, it is preferably configured to read out the CD spectrum data to be processed from the storage unit using the attribute information (R, S1, S2, ···) and the type information (S, B).

[0015] Here, it is preferable that the data process includes at least any one of baseline correction, calculation between spectrum data, peak detection, waveform separation, and spectrum analysis. Further, it is preferable that the spectrum analysis is protein identity evaluation or higher-order structure evaluation.

[0016] According to the multi-sample circular dichroism measuring apparatus having the above configuration, with respect to the second problem, when performing various data processes (including spectrum analysis) on a large number of CD spectrum data, the computer can read out the CD spectrum data to be processed from the storage unit using the attribute information (R, S1, S2, ···) and the type information (S, B), so that automation of these data processes becomes possible.

Brief Description of the Drawings

[0017] [Figure 1] It is an overall configuration diagram of a multi-sample CD measuring apparatus according to an embodiment of the present invention. [Figure 2] It is a diagram showing a configuration example of the autosampler of the multi-sample CD measuring apparatus. [Figure 3] It is an explanatory diagram of the search function of the multi-sample CD measuring apparatus. [Figure 4] It is a measurement flowchart of the multi-sample CD measuring apparatus. [Figure 5] An example of the monitor screen (input screen) of the multi-sample CD measurement device shown above. [Figure 6] An example of the monitor screen (sample arrangement diagram) of the multi-sample CD measurement device shown above. [Figure 7] An example of the monitor screen (measurement order list) of the multi-sample CD measurement device shown above. [Figure 8] An example of the monitor screen (at the start of measurement) of the multi-sample CD measurement device shown above. [Figure 9] An example of the monitor screen (during measurement) of the multi-sample CD measurement device shown above. [Figure 10] An example of the monitor screen (evaluation results) of the multi-sample CD measurement device shown above. [Modes for carrying out the invention]

[0018] Hereinafter, an embodiment of the multi-sample circular dichroism (CD) measuring device according to the present invention will be described based on the drawings. Figure 1 is a schematic overall configuration diagram of the multi-sample CD measuring device 10 of this embodiment. The multi-sample CD measuring device 10 comprises a CD measuring instrument unit 14 in which a flow cell holder 12 (with a water-cooled Peltier type temperature control function) is installed in the sample chamber, an autosampler 22 having a nozzle 20 connected to the lower inlet / outlet of the flow cell 16 via a first flow channel 18, a drying unit 26 connected to the upper inlet / outlet of the flow cell 16 via a second flow channel 24, and a syringe pump 30 connected to the drying unit 26 via a third flow channel 28. The drying unit 26 has a three-way valve 32 and a drying pump 34, and the second flow channel 24, the third flow channel 28 and the drying pump 34 are connected to the three-way valve 32.

[0019] Figure 2 shows the vial holder 40, washing solution bottle 42, nozzle wipe 44, and drainage bottle 46 installed in the autosampler 22. The nozzle 20 can be moved in a predetermined order to the desired vials 40A, 40B, ..., washing solution bottle 42, nozzle wipe 44, and drainage bottle 46 on the vial holder 40 by the nozzle moving device of the autosampler 22.

[0020] Using Figure 1, we will explain the process of transporting the sample from the vial to the flow cell 16. As an example, we will explain a series of operations including "washing," "drying," "sample transport," "measurement," "sample discharge," and "drying."

[0021] First, during cleaning, the three-way valve 32 opens the second flow path 24 and the third flow path 28. The nozzle 20 is then inserted into the cleaning solution bottle 42. When the syringe pump 30 is operated in suction mode, a predetermined volume of cleaning solution is transported from the nozzle 20 to the pump. This cleaning solution reaches the flow cell 16, cleaning the first flow path 18 and the flow cell 16.

[0022] Next, move the nozzle 20 to the drainage bottle 46 (or the drainage port leading to the drainage bottle 46). When the syringe pump 30 is operated in discharge mode, the cleaning solution is pushed towards the nozzle 20, and the cleaning solution that returns to the nozzle 20 is discharged into the drainage bottle 46. Once discharge is complete, stop the syringe pump 30.

[0023] During drying, the solenoid valve of the three-way valve 32 is switched to open the drying pump 34 and the second flow path 24. The nozzle 20 can remain in the position of the drainage bottle 46. By running the drying pump 34 for a predetermined time, air (or nitrogen gas) from the drying pump 34 is sent into the second flow path 24, so that the inside of the second flow path 24, the flow cell 16 and the first flow path 18 are dried. The above is an example of one cycle of operation when cleaning the flow cell 16.

[0024] When using multiple types of cleaning solutions, repeat the above cleaning and drying process for each type of cleaning solution. Note that when moving the nozzle 20, there is a step to remove residue from the nozzle tip with the nozzle wipe 44, but this will not be explained here.

[0025] After washing the nozzle 20, the first channel 18, and the flow cell 16 a predetermined number of times, the nozzle 20 is moved to a desired vial (e.g., 40A). By inserting the nozzle 20 into vial 40A and aspirating the sample, the sample is transported to the flow cell (resulting in the state shown in Figure 1).

[0026] In this embodiment, the timing of a sample's arrival at the flow cell 16 can be detected (search function) by monitoring the adjustment voltage (HT voltage) applied to the detector 36 that detects transmitted light from the flow cell 16. The HT voltage, which is the monitored signal here, is a voltage used to adjust the gain of the detector 36 so that the amount of light received by the detector 36 remains constant. When the HT voltage is monitored during sample transport, the HT voltage remains relatively high until the sample arrives at the flow cell 16 (there is air inside the flow cell 16), and then decreases at the moment the sample arrives at the flow cell 16. This is because the presence of the sample inside the flow cell 16 increases the amount of light transmitted through the flow cell 16. When performing this search function, it is advisable to set the wavelength of the light transmitted through the flow cell 16 to a wavelength band outside the absorbance band of the sample in order to avoid the influence of the sample's absorbance.

[0027] By using the search function described above, it is possible to stop the syringe pump 30 when the sample reaches the flow cell 16 without having to accurately determine in advance the amount of gas that the nozzle 20 should aspirate after aspirating the sample, i.e., the air volume required to transport the sample to the flow cell 16 (air volume for delivery). This ensures that the CD measurement is performed with the sample reliably present in the flow cell 16. Therefore, even when measuring samples with different viscosities, there is no need to readjust the air volume. Even when samples with multiple viscosities are included, there is no need to readjust the air volume each time the viscosity of the sample changes, saving time and effort. When automatically measuring multiple samples consisting of samples of various viscosities in a single sequence, the search function may be executed for each sample, or the air volume may be set for each group of samples, such as setting a certain air volume for a certain range of samples. Alternatively, a delivery test using the search function may be performed before the actual measurement to determine the air volume for delivery (see Figure 3). As shown in Figure 3, the monitor signal (HT voltage) during the delivery test may be displayed graphically in real time. In this example, the HT voltage drops when the air volume (horizontal axis) drawn in by the syringe pump 30 reaches 1140 μL, so this air volume is set as the air volume for fluid delivery.

[0028] Furthermore, by saving the HT voltage monitoring signal along with the measurement data, the monitoring signal can be used to investigate the cause of problems. For example, if there is a problem where measurement was not performed, the monitoring signal can be used to determine whether the cause was that there was no sample in the flow cell, or another equipment malfunction, or which sample number is faulty.

[0029] After the measurement is complete, the sample is discharged and dried as follows: To discharge the sample, move the nozzle 20 to the drain bottle 46 (or the drain port leading to the drain bottle 46). When the syringe pump 30 is operated in dispensing mode, the sample in the flow cell is pushed towards the nozzle, and the sample that returns to the nozzle 20 is discharged into the drain bottle 46. Once discharge is complete, stop the syringe pump 30.

[0030] During drying after measurement, the three-way valve 32 opens the drying pump 34 and the second flow path 24, similar to the drying before measurement. The nozzle 20 can remain in the position of the drainage bottle 46. By running the drying pump 34 for a predetermined time, air (or nitrogen gas) from the drying pump 34 is sent into the second flow path 24, so that the inside of the second flow path 24, the flow cell 16, and the first flow path 18 are dried. The above steps, from washing to sample discharge and drying, represent one example of the operation of a single cycle when measuring one sample in a flow cell.

[0031] Figure 4 shows the overall operation flow of the multi-sample CD measurement device. This operation flow is the operation flow of the CD measurement program, which is executed by a computer connected to the CD measurement device unit 14 (capable of simultaneously measuring CD spectra and fluorescence spectra), autosampler 22, drying unit 26, and syringe pump 30. When the program is executed, the computer displays confirmation input screens for each step on a display device or the like, so that the user can proceed with the measurement while confirming (and inputting information as needed) according to the procedure.

[0032] In Step 1, the user selects whether to perform spectrum acquisition or identity verification testing. This section describes the operation flow of identity verification testing, which allows evaluation of the identity between the sample under evaluation and a standard sample based on their respective spectral data. Identity evaluation can be performed using either CD spectra or fluorescence spectra.

[0033] In the system setup in step 2, the system automatically recognizes the detectors connected to the CD measuring instrument unit 14, and displays a list of available detectors (name, serial number, etc.) along with information on previously connected detectors. The user can easily select the detector to use on the screen. Similarly, connected accessories (cell units, external accessories, etc.) are also automatically recognized and displayed in a list. The names and serial numbers of the detectors and accessories used for measurement are added to the measurement data.

[0034] In step 3, setting the conditions, you can choose to open an existing conditions file or create a new one. If you open an existing conditions file, proceed to step 9, the liquid delivery test. If you create a new one, name the conditions file and set the save location. Since the measurement data for both CD spectra and fluorescence spectra will be saved together in this location, set the file names for the spectral data to be saved. The spectral files to be saved include raw (unprocessed) spectral files, integrated spectral files, baseline-corrected spectral files, data-processed spectral files, reference model files, and identity verification test result files. For raw spectral files, set it so that the raw spectral file for baseline correction (i.e., the solvent) and the raw spectral data of the sample itself are saved separately.

[0035] Note that only the final spectrum file (the spectrum file after data processing) with all data processing such as integration and baseline correction performed should remain; intermediate files such as the raw spectrum file can be deleted once data processing is complete. Next, proceed to setting the conditions in steps 4-8.

[0036] In step 4, mode selection, choose the measurement mode according to the type of sample. Sample type here refers to, for example, proteins and nucleic acids. Measurement modes include, for example, protein (secondary structure), protein (tertiary structure), nucleic acid, and advanced mode. Depending on the measurement mode, appropriate measurement parameters (measurement wavelength, data interval, response, etc.) for the sample are automatically set. When measuring samples other than proteins and nucleic acids, or when measuring fluorescence that is not derived from the sample (such as fluorescent labeling) even if it is a protein or nucleic acid, select the advanced mode (where all settings can be arbitrarily selected).

[0037] In step 5, setting up the identity verification test, you will define the conditions for the identity verification test. When evaluating the identity between the standard sample and the sample to be evaluated, you will choose whether to use the spectrum of one sample to be evaluated or the spectra of multiple samples to be evaluated. You will also set the significance level and other parameters. Furthermore, you will set the calculation of spectral distance, including the method for correcting concentration errors and the type of weighting used.

[0038] In step 6, the sequence setup determines the placement of the samples on the autosampler 22 (multiple sample placement diagram) based on sample information. The computer first processes the following input information (1) to (3): (1) Sample information (e.g., sample name, identification number, concentration, etc.), (2) Information on the solvent contained in the sample, and (3) Information on the number of samples (N: where N is a natural number greater than or equal to 1), The computer obtains the data and determines the measurement order for all samples. Next, the computer determines the positions in the autosampler 22 for arranging the samples in a vertical and horizontal plane.

[0039] The computer uses attribute information (R, S1, S2, ...) and type information (S, B) to determine the measurement order. Attribute information distinguishes whether the sample and solvent relate to the standard sample (R) or to one of the samples to be evaluated (S1, S2, ...), while type information distinguishes between the sample (S) and the solvent (B). Attribute information (R, S1, S2, ...) and type information (S, B) are assigned to input information (1) and input information (2) respectively by the user on the input screen. Figure 5 shows an example of the input screen.

[0040] In the upper part of Figure 5, there is an input field for the number of groups. The number of groups indicates how many types of samples are being evaluated, and here we will explain using a group number of 3. This group number indicates, for example, how many types of biosimilars there are for an original antibody drug (innovator), or how many types of samples have been modified by adding changes such as temperature, salt concentration, and pH to a standard sample (e.g., native). The group number is different from the number of samples (N). Both the standard sample and the samples being evaluated are in a mixed state of the substance of the sample itself and some kind of solvent (buffer). Based on the group number, input fields for the standard sample and the samples being evaluated are formed. In the first column of the input field, the attribute information field displays "R" to indicate the standard sample and "S1~S3" to indicate the 1st to 3rd sample groups. In the second column, the type information field, the sample (S) and solvent (B) fields are formed in two rows for each attribute (R, S1~S3). From the third column onward, input fields are formed for entering information about the samples (samples or solvents) that are distinguished by the attribute information and type information. Information about the specimen (sample or solvent) includes, for example, the name of the specimen, identification number, concentration, unit of concentration, and the name of the specimen (or solvent).

[0041] Therefore, the first row of the input field contains information about the solvent of the standard sample, distinguished by attribute R and type B; the second row contains information about the standard sample, distinguished by attribute R and type S; the third row contains information about the solvent of the first sample group, distinguished by attribute S1 and type B; and the fourth row contains information about the sample of the first sample group, distinguished by attribute S1 and type S. Similarly, information about the solvent and sample for each sample group is entered sequentially in the subsequent rows.

[0042] In Figure 5, the "Reference (or Sample Group) Baseline" in the sample name column means that the sample consists only of the solvent (buffer). This is because the spectral data of the solvent is necessary when baseline correction of the spectrum of the standard sample or the sample being evaluated.

[0043] The upper limit on the number of groups may be set so that the value expressed as "((number of groups) + 1) × 2" does not exceed the number of samples that can be arranged in one row using one or more multi-sample trays (such as the vial holder 40 in Figure 2) installed on the autosampler 22 (for example, the number of wells in one row).

[0044] Next, we will explain how the computer determines the order of sample measurements, using Figure 7. The computer follows the following rules (4) to (6): (4) For each attribute (R, S1, S2, ...), one sample (S) and one solvent (B) should be arranged as one set, with the solvent (B) placed immediately before or after the sample (S). (5) Arrange the sample sets of all attributes (R, S1, S2, ...) and solvents (B) in a single row, and (6) The arrangement of the sample sets is repeated the number of times equal to the number of samples (N). The measurement order for all samples is determined accordingly.

[0045] The image in Figure 7 displays a list of the measurement order for all samples, with N=10 being the number of samples in each sample group. The first column of the list displays attribute information in different colors, and the second column displays the position information of the samples to be placed on the autosampler 22.

[0046] The samples in the first and second rows of the list belong to attribute R, and their columns are colored, for example, "pink." Samples of solvent B are in the first row, and samples of sample S are in the second row. For visibility, the attribute column displays "B" to indicate the solvent and "R" to indicate the standard sample. The samples in the third and fourth rows of the list belong to attribute S1, and their columns are, for example, "orange". Samples of solvent B are in the third row, and samples of sample S are in the fourth row. For visibility, the attribute column displays "B" to indicate the solvent and "S1" to indicate the first sample group. The samples in the 5th and 6th rows of the list belong to attribute S2, and their columns are, for example, "green". Samples of solvent B are in the 5th row, and samples of sample S are in the 6th row. For visibility, the attribute column displays "B" to indicate the solvent and "S2" to indicate the second sample group. The samples in the 7th and 8th rows of the list belong to attribute S3, and their columns are, for example, "blue". Samples of solvent B are in the 7th row, and samples of sample S are in the 8th row. For visibility, the attribute column displays "B" to indicate the solvent and "S3" to indicate the third sample group.

[0047] In this way, the first eighth row contains the first sample set (solvent B and sample S) for each attribute (R, S1, S2, ...), which is eight samples in total. From the ninth to the sixteenth row, the second eighth sample set for each attribute is arranged in the same manner as from the first to the eighth row. This arrangement is repeated from the seventeenth row onward, until finally, the tenth eighth sample set for each attribute is arranged.

[0048] In this way, the computer, based on the sample and solvent information in the input fields, uses attribute information (R, S1, S2, ...) and type information (S, B) to arrange a total of 80 samples (= (3 + 1) × 2 × 10) according to predetermined rules so that the number of samples in each sample group is N = 10, and determines the measurement order for all samples.

[0049] Next, we will explain, using Figure 6, how the computer determines the arrangement of all samples on the autosampler 22. The computer follows the following rules (7), (8): (7) The columns of the sample sets in rule (5) are arranged vertically, and (8) Samples with the same attribute information and type information are arranged horizontally. Accordingly, the position of all samples in the autosampler 22 is determined using the measurement order determined above. Here, we will explain the case where the multi-sample plate of the autosampler 22 is a microplate that can arrange a total of 96 samples in 8 rows vertically and 12 columns horizontally. The vertical position of the microplate is represented by A to H, and the horizontal position is represented by 1 to 12. For example, the position information of the 2nd row, 3rd column is shown as "B3".

[0050] The image in Figure 6 displays the positions of the samples determined by rules (7) and (8) above in a planar layout. The second column of the table in Figure 7 also displays the information of the determined positions. Specifically, the first eight samples (1st to 8th) are placed in the first column of the microplate, the ninth to sixteenth samples (8) are placed in the second column, and similarly, the seventeenth to twenty-fourth samples (8) are placed in the third column. This arrangement is repeated from the fourth column onwards, with the 73rd to 80th (last) samples placed in the tenth column. This automatic setup of the sample layout significantly reduces the user's sequence setting burden. The determined layout is designed to minimize the effects of drift in the measuring device and to allow for the shortest possible measurement time. Furthermore, by displaying the sample information on the layout diagram (the position of a single well) when the mouse cursor hovers over it, the user can more easily access and review the sample information.

[0051] Returning to the operation flow in Figure 4, in step 7, the measurement and data processing settings, you set the measurement conditions for the CD spectrum and fluorescence spectrum (such as the number of integrations), and whether to turn the temperature control ON or OFF. You also set the data processing to be applied. For example, you can display a list of various types of data processing (e.g., smoothing, FFT filtering, peak detection, waveform separation) for the user to select from. Essential data processing such as integration and baseline correction does not need to be displayed in the list.

[0052] In step 8, the autosampler settings are configured to set the conditions for the autosampler 22 (sample volume, sample aspiration rate, washing solution, drying time, etc.).

[0053] In the liquid delivery test in step 9, the sample (or washing solution) is actually transported to the flow cell 16 according to the conditions set in step 8, and the timing of arrival is detected using the search function to determine the volume of air used for liquid delivery during measurement.

[0054] In step 10, the measurement of multiple samples is performed using the autosampler 22. The display screen at the start of the measurement is shown in Figure 8. The display screen shows the arrangement of samples for each plate, the position of the washing solution, and the position of the nozzle wipe (NW). The user sets all samples on the plates based on the arrangement diagram. Here, the arrangement diagram uses only plate 1, but if there are many sample groups, the arrangement diagram determined using both plates 1 and 2 will be displayed. The user also sets the washing solution (for example, three types: commercially available alkaline detergent for cells, ultrapure water, and ethanol) and nozzle wipe (NW) according to the display screen. When the user presses the start measurement button, the multi-sample measurement begins.

[0055] Figure 9 shows an example of the display screen during measurement, with a diagram of the sample arrangement on the left and a graph of the spectrum being measured on the far right. For example, as shown in Figure 9, the sample being measured and the sample that has been measured can be displayed in different colors to make it easier for the user to understand the progress of multi-sample measurement. In this example, it can be seen that the sample at position "A5" on plate 1 is being measured.

[0056] In this embodiment, the CD measuring instrument unit simultaneously measures both the CD spectrum and the fluorescence spectrum of a sample in the flow cell. Therefore, the computer processes the CD spectrum data and the fluorescence spectrum data separately. The computer also acquires data on the HT voltage value for each scanning wavelength applied to the detector for the CD spectrum. The CD measuring instrument unit performs spectral measurements a set number of times for each sample transported to the flow cell. The computer performs multiple data processing operations, such as "integration," "baseline correction," and "smoothing," on the raw spectral data from the CD measuring instrument unit.

[0057] Returning to the operation flow in Figure 4, in step 11, the raw spectral data acquired for each sample is integrated for the specified number of integration steps. In the baseline correction step 12, baseline correction is performed on the integrated spectral data. In step 13, if smoothing is selected, the other data processing steps involve smoothing the baseline-corrected spectral data. Other data processing steps (e.g., optical constant calculations) may also be performed.

[0058] Steps 11-13, which involve data processing, are performed for each spectral data set from a single sample, and will therefore be repeated for each sample. If you wish to further analyze the spectral data obtained through this data processing, you may transfer this data to another analysis program.

[0059] In step 14, the reference model is created based on the processed standard sample spectral data once the data processing of the standard sample spectral data is complete.

[0060] In the identity verification test in step 15, the spectral distances of the reference model and the sample under evaluation are calculated under conditions set based on the spectral data of the reference model and the sample under evaluation, and the identity between the standard sample and the sample under evaluation is statistically evaluated.

[0061] In this embodiment, the computer assigns or associates attribute information (R,S1,S2,...) and type information (S,B) to the measured spectral data (raw spectral data) and the spectral data obtained through each data processing and analysis, and then stores this spectral data. When executing a pre-specified data processing, the computer can smoothly read the spectral data to be processed from the storage unit using the attribute information (R,S1,S2,...) and type information (S,B). Therefore, even when measuring a large amount of spectral data from multiple samples, it becomes possible to automate the pre-specified data processing and analysis.

[0062] In the results display in step 16 (for example, Figure 10), the results of the identity verification test for each sample being evaluated are displayed. For example, if you want to analyze the higher-order structure (HOS) of a protein in more detail, you can transfer the spectral data obtained from the data processing and identity verification test up to this point to another analysis program.

[0063] If a search error occurs during the transport of a sample to the flow cell 16, the measurement data will be saved with error information, and multi-sample measurement will continue. The sample with the search error may be clearly indicated in the results display column of Figure 10. Alternatively, the sample data with the search error may not be used for data processing such as integration.

[0064] The data measured by the multi-sample CD measuring device 10 of this embodiment may include CD spectra, fluorescence spectra, HT spectra, absorbance spectra calculated from HT, etc., and these are displayed as multi-channel data. By acquiring spectral data from multiple samples using the sequence setting method of this embodiment, it is possible to precisely set what kind of data processing to perform on each channel of the spectrum, and furthermore, the conditions for data processing and analysis can be easily set all at once for the vast amount of spectral data from multiple samples, and such data processing and analysis can be executed smoothly.

[0065] In this embodiment, a CD measuring instrument capable of simultaneously measuring CD spectra and fluorescence spectra was used. However, the instrument may also be configured to enable ultraviolet-visible spectroscopy (UV-vis) measurement, or it may be configured as a multi-sample optical measuring device capable of measuring one or more optical spectral data from CD spectra, fluorescence spectra, and UV-vis spectra. [Explanation of symbols]

[0066] 10. Multi-sample circular dichroism (CD) measurement device 12 Flow cell holder 14 CD Measuring Instruments Section 16 Flow Cells 18. First channel 20 nozzles 22 Autosamplers 24 Second channel 26 Drying Unit 28 Third channel 30 Syringe pumps 32 Three-way valve 34 Drying pump 36 detectors 40 vial holders 42 cleaning solution bottles 44 Nozzle Wipes 46 Drainage bottles

Claims

1. A multi-sample circular dichroism (CD) analyzer that measures the circular dichroism (CD) spectra of multiple samples, Flow cell and, An autosampler that transports the samples to the flow cell in the order of measurement and discharges them from the flow cell, A measuring instrument unit for measuring the CD spectrum of the sample in the flow cell, The system includes a computer that controls the autosampler and the measuring instrument unit and processes the CD spectrum from the measuring instrument unit. The aforementioned computer, It includes a sequence setting function that determines the measurement order of the aforementioned samples, The sequence setting function uses the following input information (1) to (3): (1) Sample information, (2) Information on the solvent contained in the sample, and (3) Information on the number of samples of the above sample (N: where N is a natural number of 1 or more), Obtain attribute information (R, S1, S2, ...) that distinguishes whether the sample and solvent relate to a standard sample (R) or to any of the samples to be evaluated (S1, S2, ...), and type information (S, B) that distinguishes the sample and the solvent, and use the following rules (4) to (6): (4) For each attribute (R, S1, S2, ...), one sample (S) and one solvent (B) are made into a set, and the solvent (B) is placed immediately before or immediately after the sample (S). (5) Arrange the sets of samples of all attributes (R, S1, S2, ...) of the sample (S) and the solvent (B) in a single row, (6) The arrangement of the set of samples is repeated the number of samples (N) of the sample. The measurement order of the samples is determined accordingly. A multi-sample circular dichroism measuring device characterized by functioning in such a way.

2. The sequence setting function described above is In order to determine the positions in which the samples are arranged in the vertical and horizontal planes on the autosampler, the following rules (7), (8) are used using the attribute information (R, S1, S2, ...) and the type information (S, B): (7) The rows of the sample sets in (5) are arranged vertically, and (8) Samples for which both attribute information and type information are the same are arranged horizontally. The position of the sample in the autosampler is determined accordingly. The multi-sample circular dichroism measuring device according to claim 1, characterized in that it functions in such a way.

3. The aforementioned computer, The system includes a storage unit capable of storing the CD spectral data with the attribute information (R, S1, S2, ...) and type information (S, B) attached to or associated with the CD spectral data. When performing pre-specified data processing, the CD spectral data to be processed is read from the storage unit using the attribute information (R, S1, S2, ...) and the type information (S, B). The multi-sample circular dichroism measuring device according to claim 1, characterized in that it is configured as described above.

4. The aforementioned data processing includes at least one of the following: baseline correction, calculations between spectral data, peak detection, waveform separation, and spectral analysis. The multi-sample circular dichroism measuring device according to claim 3, characterized in that it is a multi-sample circular dichroism measuring device.

5. The spectral analysis is for evaluating the identity or higher-order structure of the protein. The multi-sample circular dichroism measuring device according to claim 4, characterized in that it is a multi-sample circular dichroism measuring device.

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