Automated analysis system and diagnostic method

Abstract

Provided is an automated analysis system comprising an analyzing unit that analyzes a sample, and a control unit that controls the analyzing unit, wherein the control unit receives, via a network, a diagnosis measurement parameter that defines a condition for a diagnosis measurement, and controls the analyzing unit in accordance with the diagnosis measurement parameter to automatically perform the diagnosis measurement. The automated analysis system includes, for example, a quality control sample storage unit that stores quality control samples, and a conveying unit that conveys the quality control samples between the quality control sample storage unit and the analyzing unit, wherein: the diagnosis measurement parameter specifies, as the condition, the quality control sample to be used in the diagnosis measurement; and the control unit controls the quality control sample storage unit, the conveying unit, and the analyzing unit in accordance with the diagnosis measurement parameters, supplies the specified quality control sample to the analyzing unit, and performs the diagnosis measurement.

Description

Automated analysis system and diagnostic method

[0001] The present invention relates to an automatic analysis system and a diagnostic method for analyzing biological samples such as blood as specimens.

[0002] An automated analyzer automatically analyzes samples and outputs results. Since these results are used by doctors in hospitals and medical testing facilities for diagnosis, reliability must be ensured. Therefore, the automated analyzer periodically measures quality control samples (hereinafter referred to as quality control measurements) with known concentrations of target components, and the measurement results are checked to ensure there are no abnormalities, thereby managing the measurement accuracy of the automated analyzer. If the values ​​obtained in the quality control measurements fall outside a preset tolerance range, the quality control measurements are deemed to have failed, requiring troubleshooting. Patent Document 1 discloses an automated analyzer that uses quality control measurements to instruct the user on troubleshooting.

[0003] Japanese Patent Application Laid-Open No. 2017-187473

[0004] However, if the measurement accuracy of an automated analyzer does not improve even after the user performs troubleshooting, the user typically contacts a service center and requests a repair. Upon receiving a user request, a service engineer from the service center visits the user's location to repair the automated analyzer. The service engineer identifies the cause of the failed quality control measurement on-site, takes measures, and confirms that the quality control measurement passes before handing the automated analyzer over to the user. Because the service engineer performs the work of investigating the cause, taking measures, and verifying accuracy on-site, the user cannot use the automated analyzer during this time. If the automated analyzer is unable to analyze patient samples (downtime) for an extended period of time, the user may be burdened with having to prepare a replacement device or outsource sample analysis to an external organization.

[0005] Furthermore, because service engineers sometimes arrive at the site without any idea of ​​the cause of the malfunction, even if the cause is identified and, for example, a part needs to be replaced, they may not necessarily have the replacement part with them. If the replacement part is not available, the service engineer must, for example, return to the service center to retrieve the replacement part or order the part, which increases the time required to deliver the automatic analyzer to the user and increases the workload of the service engineer and service costs.

[0006] The technology described in Patent Document 1 statistically analyzes the results of quality control measurements from multiple automated analyzers, classifies abnormalities, and outputs troubleshooting instructions. However, it is difficult to identify the cause of the abnormality from the various factors, such as equipment and reagents, that affect measurement accuracy. Therefore, when a service engineer receives a malfunction report from a user, they must visit the site from the cause identification stage. Even if several possible causes are estimated from abnormality information before visiting the site, they still must visit the site at the cause identification stage to accurately identify the cause. Therefore, it is difficult for the technology described in Patent Document 1 to solve the aforementioned problems, such as reducing downtime and reducing work load and service costs.

[0007] An object of the present invention is to provide an automatic analysis system and a diagnostic method that can shorten downtime, improve the work efficiency of users, and reduce the work burden on service engineers.

[0008] In order to achieve the above-mentioned object, the present invention provides an automatic analysis system having an analysis unit that analyzes samples and a control unit that controls the analysis unit, wherein the control unit receives diagnostic measurement parameters that define the conditions for diagnostic measurements via a network, controls the analysis unit according to the diagnostic measurement parameters, and automatically performs the diagnostic measurements.

[0009] According to the present invention, it is possible to reduce downtime, improve the work efficiency of users, and reduce the work burden on service engineers.

[0010] FIG. 1 is a diagram showing the main parts of an example configuration of an analysis unit, etc., that constitutes an automatic analysis system according to a first embodiment of the present invention. FIG. 2 is a diagram showing an example of a measurement protocol, which is a condition for the measurement process performed in the analysis unit. FIG. 3 is a schematic diagram showing an example configuration of a network that implements a diagnostic method for the analysis unit of the automatic analysis system according to the first embodiment of the present invention. FIG. 4 is an example of measurement data from sample measurements performed in the analysis unit. FIG. 5 is an example of diagnostic measurement parameters used in the present invention. FIG. 6 is an explanatory diagram of an example analysis of diagnostic measurement results. FIG. 7 is a flowchart showing the flow of diagnosis of the analysis unit in the first embodiment of the present invention. FIG. 8 is a flowchart showing an example of a procedure for narrowing down the causes of defects. FIG. 9 is a diagram showing an example of a permission acquisition screen for obtaining permission to perform diagnostic measurement. FIG. 10 is a flowchart showing the flow of diagnosis of the analysis unit in the second embodiment of the present invention. FIG. 11 is a diagram showing the main parts of an example configuration of an analysis unit, etc., that constitutes an automatic analysis system according to a third embodiment of the present invention. FIG. 12 is a conceptual diagram of a learning model used in an automatic analysis system according to a fourth embodiment of the present invention. FIG. 13 is a diagram showing the main parts of an example configuration of an analysis unit, etc., that constitutes an automatic analysis system according to a fifth embodiment of the present invention. FIG. 14 is a diagram showing the main parts of an example configuration of an analysis unit, etc., that constitutes an automatic analysis system according to the fifth embodiment of the present invention. 10 is a diagram showing the main components of an example of the configuration of an analysis unit, etc., that constitutes an automatic analysis system according to a fifth embodiment of the present invention. 11 is another example of diagnostic measurement parameters used in the present invention.

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0012] In the following embodiment, an automatic analysis system 1 including an automatic immunoanalyzer that analyzes immunological analysis items will be described as an example of the analysis unit 100 to which the present invention is applied. However, a wide variety of devices that analyze samples based on the results of reactions between samples and reagents, including automatic biochemical analyzers, can be used as the analysis unit 100 of the automatic analysis system 1. For example, automatic analyzers such as mass spectrometers used in clinical tests and coagulation analyzers that measure blood clotting time can also be used as the analysis unit 100. The present invention can also be applied to an automatic analysis system that includes multiple automatic analyzers of the same or different types that are connected to each other.

[0013] <First Embodiment> - Schematic Configuration - Figure 1 is a diagram showing the main components of an example configuration of an analysis unit and the like that constitutes an automatic analysis system according to a first embodiment of the present invention. The automatic analysis system 1 illustrated in Figure 1 includes an analysis unit (automatic analyzer) 100, a quality control sample storage unit 200, a transport unit 300, and a control unit 400. The analysis unit 100 is a device that analyzes samples including biological samples from patients and quality control samples for quality control. The quality control sample storage unit 200 is a device that stores quality control samples for quality control measurements. The analysis unit 100 and the quality control sample storage unit 200 are connected via a transport unit 300. The transport unit 300 is a device that transports samples between the quality control sample storage unit 200 and the analysis unit 100. The control unit 400 controls each mechanism that constitutes the automatic analysis system 1, such as the analysis unit 100, the quality control sample storage unit 200, and the transport unit 300.

[0014] -Transport Unit- The transport unit 300 includes rack transport lines 301 and 302 that transport rack β1. The rack transport line 301 is a feed line that transports rack β1 from the quality control sample storage unit 200 toward the analysis unit 100. The rack transport line 302 is a return line that transports rack β1 from the analysis unit 100 toward the quality control sample storage unit 200. Rack β1 is installed with a plurality of sample containers α1 containing biological samples such as patient blood or urine. A sample input unit 303 and a sample recovery unit 304 are connected to the rack transport lines 301 and 302. Rack β1 is input by a user via the sample input unit 303 and supplied to the analysis unit 100 via the rack transport line 301. The rack β1 used in the analysis unit 100 is transported via the transport line 302 to the sample recovery unit 304, and the user recovers the rack β1 from the sample recovery unit 304.

[0015] -Quality control sample storage unit- The quality control sample storage unit 200 includes a quality control sample transport unit 217 and multiple storage units 219. The storage unit 219 includes a cooling / cold insulation mechanism (not shown), and can store racks β2, on which multiple sample containers α2 containing quality control samples are placed, by cooling and keeping them cold using the cooling / cold insulation mechanism (not shown). In the quality control sample storage unit 200, the quality control sample transport unit 217 retrieves rack β2 from any of the storage units 219, transports it to the transport unit 300, and supplies it to the analysis unit 100.

[0016] In this embodiment, the configuration has been described in which racks β1 and β2 are transported between the analysis unit 100 and the quality control sample storage unit 200 via rack transport lines 301 and 302. Here, the quality control sample storage unit 200 may be housed within the housing of the analysis unit 100 and configured as a unit that is part of the analysis unit 100.

[0017] -Analysis Unit- The analysis unit 100 is a mechanical unit that performs analysis operations and has multiple operating mechanisms used for analyzing samples. Specifically, the analysis unit 100 includes a reagent cooling unit 101, an incubator disk (reaction disk) 102, sample dispensing mechanisms 103A and 103B, reagent dispensing mechanisms 104A and 104B, a stirring unit 105, BF separation units 106A and 106B, and detection units 107A and 107B.

[0018] The reagent cooling unit 101 functions as a reagent container storage cabinet. The reagent cooling unit 101 holds and keeps cold a plurality of reagent containers γ containing reagents used in sample analysis. Various types of reagents are stored in the reagent cooling unit 101 according to the purpose of the analysis. At least a portion of the top surface of the reagent cooling unit 101 is covered by a cover 101a. In FIG. 1, the cover 101a is shown partially cut away in order to illustrate the reagent containers γ inside the reagent cooling unit 101.

[0019] The incubator disk 102 has a reaction vessel arrangement section 102b that can accommodate a plurality of reaction vessels 102a for containing a reaction liquid, which is a mixture of a sample and a reagent, and a temperature adjustment mechanism 102c that adjusts the temperature of the reaction liquid of the sample (including a quality control sample) and the reagent in the reaction vessel 102a to a desired temperature. The temperature adjustment mechanism 102c is not actually shown in the plan view of Figure 1, but for convenience, its location is indicated by a symbol.

[0020] The sample dispensing mechanisms 103A and 103B have a rotation drive mechanism and an up / down drive mechanism (not shown), and use these drive mechanisms to aspirate a sample from a sample container α1 mounted on a rack β1 on the rack transport line 301, and dispense the aspirated sample into a reaction container 102a held on the incubator disk 102.

[0021] Like the sample dispensing mechanisms 103A and 103B, the reagent dispensing mechanisms 104A and 104B also have a rotation drive mechanism and an up-down drive mechanism (not shown), and these drive mechanisms aspirate reagent from the reagent container γ held in the reagent cooling unit 101 and dispense the aspirated reagent into the reaction container 102a held in the incubator disk 102.

[0022] The stirring unit 105 stirs the mixture of reagent and sample dispensed into the reaction vessel 102a. There are several methods that can be used to stir the mixture, including directly manipulating the reaction vessel 102a and applying a force to the mixture from the outside. An example of a method for directly manipulating the reaction vessel 102a is to rotate the reaction vessel 102a using a rotation mechanism (not shown) to stir the mixture. An example of a method for applying a force to the mixture from the outside is to apply a voltage to electrodes arranged on a piezoelectric element (not shown) to generate ultrasound waves, which are then irradiated onto the mixture to stir it. Since the desired stirring intensity may differ for each measurement item, the stirring unit 105 is configured to adjust the stirring intensity of the mixture.

[0023] The BF separation units 106A and 106B are devices that separate and remove impurities contained in a reaction liquid obtained by mixing a sample and a reagent from the reaction liquid.

[0024] The detection units 107A and 107B are devices that detect predetermined components of the reaction solution of the sample (including the quality control sample) and the reagent, and are configured to include a photomultiplier tube, a light source lamp, a spectroscope, a photodiode, etc. These detection units 107A and 107B have the function of adjusting the temperature of the devices such as the photomultiplier tube, light source lamp, spectroscope, photodiode, etc.

[0025] Although not shown, the analysis section 100 also includes a cleaning mechanism for cleaning the probes of the dispensing mechanisms (sample dispensing mechanisms 103A, 103B, reagent dispensing mechanisms 104A, 104B) and a cleaning mechanism for cleaning the BF separation units 106A, 106B.

[0026] In the analysis section 100 configured as described above, sample and reagent dispensing mechanisms 103A and 103B and reagent dispensing mechanisms 104A and 104B dispense samples and reagents into reaction vessels 102a. After impurities are removed by BF separation units 106A and 106B and stirring is performed by stirring unit 105, desired components are detected by detection units 107A and 107B. The cooling mechanism of the reagent cooling unit 101, the temperature adjustment mechanism 102c of the incubator disk 102, the stirring unit 105, and other components are shared for each sample measurement. In contrast, for devices with multiple identical functions, such as sample dispensing mechanisms 103A and 103B, reagent dispensing mechanisms 104A and 104B, BF separation units 106A and 106B, and detection units 107A and 107B, one of them is selected and used for each sample measurement. The steps using these sample dispensing mechanisms 103A, 103B, etc. take a relatively long time in the sequential measurement of samples and become a bottleneck, so by providing a plurality of devices for each step, high measurement throughput is ensured.

[0027] Hereinafter, in this specification, a predetermined combination (system) of instruments used in the sample measurement process may be referred to as a "channel." Furthermore, among the instruments involved in the sample measurement process, instruments such as the sample dispensing mechanisms 103A and 103B, the BF separation units 106A and 106B, and the detection units 107A and 107B, which have the same function and are provided in the analysis unit 100 in multiple units and are selectively used for each measurement, may be referred to as a "channel-specific unit." Furthermore, among the instruments involved in the sample measurement process, instruments other than the channel-specific units, i.e., instruments that can be shared between each measurement, such as the reagent dispensing mechanisms 104A and 104B, the temperature adjustment mechanism 102c, and the stirring unit 105, may be referred to as a "common unit." However, the instruments that fall under the category of channel-specific units and the instruments that fall under the category of common units may differ depending on the size and type of the analysis unit. For example, if multiple sets of reagent dispensing mechanisms 104A and 104B are provided, the reagent dispensing mechanisms may also be channel-specific units.

[0028] -Control Unit- The control unit 400 controls the operation of the entire mechanism, including the analysis unit 100, the quality control sample storage unit 200, and the transport unit 300. The control unit 400 receives diagnostic measurement parameters (FIG. 5) that define the conditions for diagnostic measurements via the network NW (FIG. 3), and controls the analysis unit 100, the quality control sample storage unit 200, the transport unit 300, etc. in accordance with the diagnostic measurement parameters, automatically carrying out diagnostic measurements requested from remote locations via the network NW.

[0029] The control unit 400 may be configured as hardware using a dedicated circuit board, or may be configured as software executed by a computer connected to the analysis unit 100. When the control unit 400 is configured as hardware, it can be realized by integrating multiple arithmetic units that perform processing on a wiring board, a semiconductor chip, or a package. When the control unit 400 is configured as software, it can be realized by installing a high-speed general-purpose CPU in a computer and executing a program that performs the desired arithmetic processing. Existing devices can also be upgraded using a recording medium on which this program is recorded. Furthermore, the devices, circuits, computers, etc. that make up the control unit 400 are connected via a wired or wireless network and transmit and receive data between them. The control unit 400 is also connected to a storage device 401 such as a hard disk or SSD, and an operation unit 402 that inputs analysis requests and outputs results. The operation unit 402 includes, for example, a display unit such as a monitor, and input devices such as a mouse and a keyboard.

[0030] Although an example has been given of a configuration in which the analysis unit 100, quality control sample storage unit 200, etc. are controlled by the same control unit 400, a configuration in which separate control units 400 and operation units 402 are connected to the analysis unit 100 and quality control sample storage unit 200, respectively, is also possible.

[0031] - Measurement Protocol - Figure 2 is a diagram showing an example of a measurement protocol, which is the condition for the measurement process performed by the analysis unit 100. Sample measurement requires multiple cycles. A "cycle" is a unit of time for the analysis unit 100 to perform a series of operations included in sample measurement, such as dispensing, photometry, cleaning, etc., and may be every 8 seconds or 20 seconds, for example.

[0032] 2 represent the following: S1: Sample dispensing by sample dispensing mechanism 103A S2: Sample dispensing by sample dispensing mechanism 103B S1w: Cleaning of sample dispensing mechanism 103A S2w: Cleaning of sample dispensing mechanism 103B R1: Reagent dispensing by reagent dispensing mechanism 104A R2: Reagent dispensing by reagent dispensing mechanism 104B R1w: Cleaning of reagent dispensing mechanism 104A R2w: Cleaning of reagent dispensing mechanism 104B Mix: Mixing of reaction solution by mixing unit 105 BF1: BF separation by BF separation unit 106A BF2: BF separation by BF separation unit 106B BF1w: Cleaning of BF separation unit 106A BF2w: Cleaning of BF separation unit 106B D1: Detection by detection unit 107A D2: Detection by detection unit 107B

[0033] The example in Figure 2 assumes that a new measurement is started in each cycle and multiple measurements are performed in parallel, and primarily shows which mechanisms are driven at what timing. In the example in Figure 2, multiple mechanisms performing different measurements are driven in parallel in the same cycle. In each cycle, the driven mechanisms operate in response to control signals from the control unit 400. Note that different mechanisms are driven for each measurement. Generally, to improve measurement throughput, a combination of channel-specific units used for the same measurement is set. For example, a channel combining the sample dispensing mechanism 103A, BF separation unit 106A, and detection unit 107A is designated "ch1," while a channel combining the sample dispensing mechanism 103A, BF separation unit 106B, and detection unit 107B is designated "ch2." Measurements 1-6 illustrated in Figure 2 are performed alternately using ch1 and ch2. However, some mechanisms, such as the BF separation units 106A and 106B, may not be used depending on the measurement.

[0034] An example of the measurement process will be described using the measurement protocol for measurement 1 in FIG. 2 as an example. Measurement 1 is performed using a channel-specific unit for ch1 and a common unit. In measurement 1, first, in cycle 1, sample dispensing (S1) by sample dispensing mechanism 103A and first reagent dispensing (R1) by reagent dispensing mechanism 104A are performed. Next, in cycle 2, second reagent dispensing (R2) by reagent dispensing mechanism 104B, cleaning (S1w) of sample dispensing mechanism 103A, and cleaning (S2w) of reagent dispensing mechanism 104A are performed. In the following cycle 3, cleaning (R2w) of reagent dispensing mechanism 104B is performed. Although reagent dispensing mechanisms 104A and 104B have the same function, they may have different operational purposes (reagents dispensed) during the same measurement process, and therefore, in this embodiment, they are classified as common units as described above.

[0035] Next, in cycle 4, mixing is performed by the mixing unit 105. The intensity of the mixing operation of the mixing unit 105 can be set differently depending on the measurement item. Cycle 5 is spent promoting the reaction in the incubator disk 102. The temperature of the incubator disk 102 is usually constant, but can be changed by the temperature adjustment mechanism 102c.

[0036] Thereafter, in cycles 6 and 7, BF separation (BF1) is performed by the BF separation unit 106A. The BF separation step requires time for preparation to remove impurities from the reaction solution, and therefore, in the example of FIG. 2, multiple cycles are allocated to this step. This BF separation unit 106A is washed in cycle 8 (BF1w). Also in cycle 8, detection (D1) by the detection unit 107A is initiated. Detection by the detection unit 107A is performed across cycles 8 and 9. Measurement 1 is completed upon completion of detection (D1) by the detection unit 107A.

[0037] As such, the operation of each channel-specific unit takes multiple cycles. For example, in measurement 1, the sample dispensing mechanism 103A consumes cycle 1 for dispensing and cycle 2 for cleaning. The BF separation unit 106A consumes cycles 6-8, and the detection unit 107A consumes cycles 8 and 9. Therefore, for example, the sample dispensing mechanism 103A cannot be used for another measurement during cycles 1 and 2, and the next time the sample dispensing mechanism 103A can be used is cycle 3. To maximize measurement throughput, it is important to start a new measurement every cycle. Therefore, the analysis unit 100 of this embodiment is equipped with multiple channel-specific units, as described above. As a result, in measurement 1, which is started in cycle 1 using the channel-specific unit for ch1, the sample dispensing mechanism 103A cannot be used for measurement 2 in cycle 2, but measurement 2 can be started in cycle 2 by using the channel-specific unit for ch2.

[0038] In the example of FIG. 2 , measurements 1, 2, 3, etc. alternately use the channel-specific units ch1 and ch2. BF separation may not be necessary depending on the measurement item. In the example of FIG. 2 , measurements 4 and 5 do not use a BF separation unit. Even in measurements where some channel-specific units are not used, the combination of channel-specific units constituting the channels used remains unchanged. In this embodiment, parameters for each measurement, including analytical conditions such as the channels used (ch1, ch2) and whether or not BF separation is performed, are referred to as "measurement protocol parameters." In this embodiment, the measurement protocol parameters are expressed as "ch1BF+" when BF separation is performed on ch1, and as "ch2BF-" when BF separation is not performed on ch2, for example.

[0039] - Diagnostic Method of the Analysis Unit - FIG. 3 is a schematic diagram showing an example of the configuration of a network for implementing a diagnostic method of the analysis unit 100 of the automatic analysis system 1. As shown in FIG.

[0040] In the diagnostic method of the analysis unit 100 in this embodiment, diagnostic measurement parameters defining the conditions for the diagnostic measurement are transmitted to the control unit 400 that controls the analysis unit 100 via a network NW such as the Internet, the analysis unit 100 is caused to perform a diagnostic measurement according to the diagnostic measurement parameters, and the results of the diagnostic measurement are viewed on a terminal (e.g., data analysis terminal 502B) installed in a second facility (service center B or a facility connected to service center B via a network NW) that is separate from the first facility (e.g., user facility A) where the control unit 400 is installed, and the location of the malfunction in the analysis unit 100 is estimated. In other words, the service engineer remotely instructs the analysis unit 100 to perform the diagnostic measurement without visiting the user facility A where the analysis unit 100 is operating, and attempts to identify the cause of the malfunction in the analysis unit 100 from the results of the diagnostic measurement before visiting the user facility A.

[0041] In FIG. 3 , user facility A is equipped with an analysis unit 100, a quality control sample storage unit 200, and a control unit 400. As described above, the automated analysis system 1 may include multiple analysis units 100, and the example in FIG. 3 shows an example in which multiple analysis units 100 are installed in user facility A. These multiple analysis units 100 can be diagnostic targets. Furthermore, analysis units 100 installed in locations other than user facility A can also be included as diagnostic targets, as long as they are configured to enable remote exchange of diagnostic measurement parameters and diagnostic measurement results via a network NW. Furthermore, while the example in FIG. 3 illustrates a configuration in which multiple sets of analysis units 100, quality control sample storage units 200, and control units 400 are included, at least one of the quality control sample storage units 200 and the control unit 400 may be shared by multiple analysis units 100.

[0042] In a broad sense, the automated analyzer 1 includes a data transfer terminal 500A installed at a first facility (user facility A in FIG. 3 ) together with the control unit 400, a data server 501B, and data analysis terminals 502B and 503B installed at a second facility (service center B or other facility in FIG. 3 ) separate from the first facility, as needed. The data transfer terminal 500A is, for example, a computer connected to a network NW and is capable of bidirectional communication with the data server 501B and the data analysis terminals 502B and 503B. The data server 501B and the data analysis terminals 502B and 503B can also be configured, for example, by computers connected to the network NW. While the data server 501B is installed at service center B in the example of FIG. 3 , it may be installed at user facility A or at a location other than user facility A and service center B as long as they are connected to the network NW for bidirectional communication. Data analysis terminal 502B is an example of a terminal installed at service center B, and data analysis terminal 503B is an example of a terminal installed at a second facility other than service center B. Control unit 400 transfers measurement data ( FIG. 4 ) of the sample performed in analysis unit 100 to data server 501B via data transfer terminal 500A. The measurement data may be transferred in real time (after each measurement, i.e., every cycle) or in batches at preset times (e.g., once per hour, once per day). A specific example of a diagnostic method for analysis unit 100 using the network configuration of FIG. 3 will be described later using the flowchart of FIG. 7.

[0043] -Measurement Data- Figure 4 shows an example of measurement data from sample measurements performed by the analysis unit 100. The measurement data in Figure 4 is data obtained by measuring a sample in, for example, one or both of the analysis units 100 shown in Figure 3. Although not shown in Figure 4, each measurement data item includes information indicating which analysis unit 100 the data was obtained from. The measurement data includes information such as measurement time D401, measurement type D402, reagent name D403, sample name D404, measurement result D405, measured concentration D406, target concentration D407, target concentration range D408, measurement protocol D409, stirring intensity / reaction temperature D410, remaining reagent amount D411, and remaining QC sample amount D412. This measurement data is recorded in the storage device 401 (Figure 1) by the control unit 400 and transferred to the data server 501B via the data transfer terminal 500A by the control unit 400.

[0044] Each piece of information in the measurement data will be explained. First, the measurement time D401 is the time when the corresponding measurement is completed in the analysis unit 100 and the measurement data is output. The measurement type D402 is information indicating the type of measurement performed, and records, for example, whether it is a regular quality control measurement (QC), a calibration measurement (Calibration), a general measurement (Routine), or a diagnostic measurement (Self-Diagnostic) requested via the network NW. The reagent name D403 is the name of the reagent used in the measurement, and the sample name D404 is the name of the sample used in the measurement. In the example of Figure 4, the sample name D404 is recorded only when the measurement type D402 is QC, Calibration, or Self-Diagnostic, and is not recorded when it is routine.

[0045] The measured concentration D406 is the concentration (measured value) of the target component contained in the measured sample. The target concentration D407 is a target concentration (set reference value) set for each target component for the measured concentration D406. The target concentration range D408 is a normal range set for each target component for the measured concentration D406. In the example of FIG. 4 , the target concentration D407 and target concentration range D408 are set only for the measurement types D402 of QC, Calibration, and Self-Diagnostic, and are not set for the measurement type D402 of Routine.

[0046] The measurement result D405 is a determination result of whether the measured concentration D406 falls within the target concentration range D408. If the measured concentration D406 falls within the target concentration range D408, the measurement result D405 is recorded as "OK." If the measured concentration D406 falls outside the target concentration range D408, the measurement result D405 is recorded as "NG." In the example of FIG. 4 , the measurement result D405 is recorded only in the measurement type D402 for QC, Calibration, and Self-Diagnostic, but not in the measurement type D402 for routine. Note that the determination logic for the measurement result D405 is not limited to whether the measured concentration D406 falls within the target concentration range D408. For example, the value of the measured concentration D406 can be compared with values ​​from the past N measurements (measured values ​​from the same type of measurement) to determine whether the measured concentration D406 exhibits a predetermined trend (such as a monotonically increasing or decreasing trend).

[0047] As mentioned above, the measurement protocol 409 indicates the channel (ch1 / ch2) used in the measurement and whether BF separation was performed (BF+ / BF-). The stirring intensity / reaction temperature 412 indicates the stirring intensity and reaction temperature used in the measurement. The stirring intensity is recorded as a value from 1 to 10, with 10 representing the maximum stirring intensity and 1 representing the minimum stirring intensity. The remaining reagent amount D411 indicates the remaining amount of reagent used in the measurement, and the remaining QC sample amount D412 indicates the remaining amount of quality control sample stored in the quality control sample storage unit 200. For example, if the remaining reagent amount D411 or the remaining QC sample amount D412 is recorded as "N tests," this indicates that there is enough remaining amount to perform N remaining measurements. Furthermore, the remaining QC sample amount D412 is recorded only in measurement types D402 that use quality control samples, i.e., QC and Self-Diagnostic measurement types D402, and is not recorded in measurement types D402 for Calibration and Routine.

[0048] - Diagnostic Measurement Parameters As described above, in this embodiment, analytical conditions such as the channel to be used (ch1, ch2) and information on whether or not BF separation is performed are represented by measurement protocol parameters. As mentioned above, the control unit 400 can perform diagnostic measurements in accordance with the diagnostic measurement parameters via the network NW. These diagnostic measurement parameters are described by measurement protocol parameters, and the control unit 400 can interpret the diagnostic measurement parameters described by the measurement protocol parameters and control the analysis unit 100, the quality control sample storage unit 200, etc. to perform sample measurements. In addition, the control unit 400 can communicate the mechanism used in the measurement to personnel such as service engineers by outputting the measurement protocol D409 as shown in FIG. 4.

[0049] Figure 5 shows examples of diagnostic measurement parameters. In Figure 5, symbols such as S1, S2, R1, R2, Mix, BF1, BF2, D1, and D2 correspond to the same symbols explained in Figure 2. The stirring intensity and reaction temperature are also as explained in Figure 4.

[0050] The measurement protocol parameters P10 and P20 shown in the top two rows of Figure 5 are measurement protocol parameters (ch1BF+, ​​ch2BF+) when a routine measurement using a patient's biological sample is performed using ch1 and ch2, respectively. In both examples of the measurement protocol parameters P10 and P20, the stirring intensity is 3 and the reaction temperature is 37°C. Furthermore, the measurement protocol parameters P10 and P20 are measurement protocol parameters when BF separation is performed; the measurement protocol parameters (ch1BF-, ch2BF-) when no BF separation is performed are not shown in Figure 5. The analysis unit 100 performs a routine measurement based on the measurement protocol parameters P10 and P20.

[0051] In contrast, the third and subsequent lines in Figure 5 represent diagnostic measurement parameters P11-P15 and P21-P25. Diagnostic measurement parameters P11-P15 are parameters that remotely instruct the control unit 400 via the network NW to perform diagnostic measurements in the analysis unit 100 to identify the cause of a malfunction or other problem when, for example, a failure occurs in a routine quality control measurement (QC in Figure 4) for a measurement related to measurement protocol parameter P10 but the user is unable to resolve the issue. Similarly, diagnostic measurement parameters P21-P25 are parameters that remotely instruct the control unit 400 via the network NW to perform diagnostic measurements when a failure occurs in a measurement related to measurement protocol parameter P20.

[0052] An operator, such as a service engineer, uses the data analysis terminal 502B or 503B to review the measurement data, such as those shown in FIG. 4 , transmitted from the control unit 400 and selects, inputs, or otherwise sets diagnostic measurement parameters P11-P15, P21-P25, etc., that are relevant to cause identification. The diagnostic measurement parameters are arbitrarily set on the data analysis terminal 502B or 503B and transmitted to the control unit 400 via the network NW in response to an operator's operation. The diagnostic measurement parameters set by the service engineer specify the quality control sample to be used in the diagnostic measurement as a condition. While the quality control sample is not shown in FIG. 5 , typically, the same reagent as used in the routine quality control measurement (QC) in which the malfunction occurred is specified in the diagnostic measurement parameters. For example, when identifying the cause of an abnormality occurring in the measurement data second from the top in FIG. 4 , the reagent named FT4 is specified in the diagnostic measurement parameters. Furthermore, as described below, the diagnostic measurement parameters specify as a condition that the operating mechanisms (dispensing mechanism, BF separation unit, detection unit, etc.) to be used in each step of the diagnostic measurement must be different from the operating mechanisms used in the quality control measurement in which the malfunction occurred.

[0053] Upon receiving the diagnostic measurement parameters, the control unit 400 controls the quality control sample storage unit 200, the transport unit 300, and the analysis unit 100 according to the received diagnostic measurement parameters, supplies the quality control sample specified by the diagnostic measurement parameters to the analysis unit 100, and performs diagnostic measurement using each specified operating mechanism. The control unit 400 transmits the results of the diagnostic measurement to a connected computer (data server 501B) via the network NW. The "Self-Diagnostic" at the bottom of Figure 4 is an example of diagnostic measurement data performed using the diagnostic measurement parameters. A service engineer or the like can check the diagnostic measurement results received from the control unit 400 on the data analysis terminal 502B or 503B, or access the data server 501B from the data analysis terminal 502B or 503B to check the diagnostic measurement results and estimate and identify the cause of the malfunction.

[0054] -Analysis of diagnostic measurement results- Fig. 6 is an explanatory diagram of an example of analysis of diagnostic measurement results. Fig. 6 shows an example of analysis when a problem occurs in the measurement using ch1.

[0055] For diagnostic measurement parameters, the conditions for the failed quality control measurement and some of the processes are changed. For example, a different operating mechanism (dispensing mechanism, etc.) from that used in the quality control measurement where the problem occurred is specified as a condition for the diagnostic measurement.

[0056] For example, in the example of FIG. 5 , if a malfunction occurs during a routine quality control (QC) measurement using channel 1 associated with measurement protocol parameter P10, diagnostic measurement parameter P11 is a parameter for determining whether the malfunction is caused by sample dispensing mechanism 103A. This diagnostic measurement parameter P11 specifies, as a condition, a sample dispensing mechanism 103B (S2) that is different from sample dispensing mechanism 103A (S1) specified by measurement protocol parameter P10 as the dispensing mechanism to be used in the diagnostic measurement. Analysis example 61A shown in the topmost column of FIG. 6 illustrates the determination of the results of a diagnostic measurement performed based on diagnostic measurement parameter P11. As shown in analysis example 61A, if the result of the diagnostic measurement using sample dispensing mechanism 103B specified by diagnostic measurement parameter P11 is changed to OK by control unit 400, it can be determined that a malfunction is likely occurring in sample dispensing mechanism 103A. Conversely, if the result of the diagnostic measurement using the sample dispensing mechanism 103B remains NG, it can be determined that there is a high possibility that a malfunction has occurred in a process other than the sample dispensing mechanism 103A. To confirm whether the malfunction has been resolved, the result is determined using the same criteria as in the measurement during the malfunction, such as the target concentration and target concentration range. In this case, the target concentration D407 and target concentration range D408 may be the ranges used in quality control measurement (QC) or calibration measurement, or the target concentration D407 and target concentration range D408 for the diagnostic measurement may be set independently.

[0057] Similarly, the diagnostic measurement parameter P12 in the example of FIG. 5 is a parameter for determining whether the malfunction is caused by the BF separation unit 106A. This diagnostic measurement parameter P12 specifies, as a condition, the BF separation unit to be used in the diagnostic measurement, namely, the BF separation unit 106B (BF2), which is different from the BF separation unit 106A (BF1) set in the measurement protocol parameter P10. Analysis example 62A shown in the second column from the top of FIG. 6 represents the determination of the results of the diagnostic measurement performed based on the diagnostic measurement parameter P12. As shown in analysis example 62A, if the result of the diagnostic measurement using the BF separation unit 106B changes to OK, it can be determined that there is a high possibility that a malfunction has occurred in the BF separation unit 106A. Conversely, if the result of the diagnostic measurement using the BF separation unit 106B remains NG, it can be determined that there is a high possibility that a malfunction has occurred in a process other than the BF separation unit 106A.

[0058] Furthermore, the diagnostic measurement parameter P13 in the example of FIG. 5 is a parameter for determining whether the malfunction is caused by the detection unit 107A. This diagnostic measurement parameter P13 specifies, as a condition, the detection unit to be used in the diagnostic measurement, which is detection unit 107B (D2), which is different from detection unit 107A (D1) set in the measurement protocol parameter P10. Analysis example 63A shown in the third column from the top of FIG. 6 represents the determination of the results of the diagnostic measurement performed based on the diagnostic measurement parameter P13. As shown in analysis example 63A, if the result of the diagnostic measurement using detection unit 107B changes to OK, it can be determined that there is a high possibility that a malfunction has occurred in detection unit 107A. Conversely, if the result of the diagnostic measurement using detection unit 107B remains NG, it can be determined that there is a high possibility that a malfunction has occurred in a process other than detection unit 107A.

[0059] Furthermore, the diagnostic measurement parameter P14 in the example of FIG. 5 is a parameter for determining whether the malfunction is caused by the agitation unit 105. This diagnostic measurement parameter P14 specifies a condition for the agitation operation intensity of the agitation unit 105, which is different from the intensity (3) set in the measurement protocol parameter P10. Analysis example 64A shown in the fourth column from the top of FIG. 6 represents the determination of the results of a diagnostic measurement performed with the agitation intensity changed based on the diagnostic measurement parameter P14. As shown in analysis example 64A, if the result of the diagnostic measurement performed at agitation intensity (7) changes to OK, it can be determined that the agitation unit 105 is likely operating normally. Conversely, if the result of the diagnostic measurement performed at agitation intensity (7) remains NG, it can be determined that the agitation unit 105 is not operating normally and that a malfunction may be occurring in the agitation unit 105.

[0060] Furthermore, the diagnostic measurement parameter P15 in the example of FIG. 5 is a parameter for determining whether the malfunction is caused by the incubator disk 102. This diagnostic measurement parameter P15 specifies 35°C as the condition for the temperature of the reaction solution controlled by the temperature adjustment mechanism 102c of the incubator disk 102, which is different from the 37°C set by the measurement protocol parameter P10. Analysis example 65A shown in the fifth column from the top of FIG. 6 represents the determination of the results of a diagnostic measurement performed after adjusting the temperature of the reaction solution based on the diagnostic measurement parameter P15. As shown in analysis example 65A, if the result of the diagnostic measurement performed at 35°C changes to OK, it can be determined that the incubator disk 102 is likely operating normally. Conversely, if the result of the diagnostic measurement performed at a temperature of 35°C remains NG, it can be determined that the incubator disk 102 is not operating normally and that a malfunction may have occurred in the incubator disk 102.

[0061] The judgments in each of analysis examples 61A-65A can be made manually by a service engineer or the like based on the results of diagnostic measurements, or can be made automatically by a computer such as control unit 400 or data analysis terminals 502B, 503B. For example, control unit 400 can be made to sequentially perform diagnostic measurements related to diagnostic measurement parameters P11-P15, and the cause of the malfunction in channel 1 can be automatically estimated by control unit 400 or data analysis terminals 502B, 503B.

[0062] In addition, Figure 6 explains an example of an analysis to identify the cause when a malfunction occurs in a regular quality control measurement (QC) using ch1 related to the measurement protocol parameter P10 (Figure 5). However, if a malfunction occurs in a regular quality control measurement (QC) using ch2 related to the measurement protocol parameter P20 (Figure 5), an analysis to identify the cause can be performed in the same manner as above, using the diagnostic measurement parameters P21-P25 (Figure 5) as appropriate.

[0063] In addition, diagnostic measurement parameters are not limited to the diagnostic measurement parameters P11-P15 and P21-P25 illustrated in FIG. 5 . For example, the cause of the malfunction may be the cleaning process. In this case, diagnostic measurement parameters are set that change the cleaning intensity of the sample dispensing mechanism 103A cleaning (S1w) and the reagent dispensing mechanism 104B cleaning (S2w) from the normal quality control (QC) measurement, and whether the cleaning mechanism for the sample dispensing mechanism is operating normally can be estimated based on whether the measurement result changes to OK or remains NG. In this case, it is effective to set the cleaning intensity of the diagnostic measurement parameter to, for example, 0 (zero), thereby setting a condition in which cleaning is not performed. By intentionally performing a diagnostic measurement that omits the cleaning process, it is possible to determine whether ineffective cleaning is the cause of the malfunction when sample carryover occurs. Similarly, by setting diagnostic measurement parameters that change the cleaning strength or cleaning time of the cleaning (R1w) of reagent dispensing mechanism 104A, the cleaning (R2w) of reagent dispensing mechanism 104B, the cleaning (BF1w) of BF separation unit 106A, and the cleaning (BF2w) of BF separation unit 106B, it is possible to estimate whether the cleaning mechanisms for the reagent dispensing mechanisms and the BF separation units are operating normally. It is also possible to set diagnostic measurement parameters that swap the reagents dispensed by reagent dispensing mechanisms 104A and 104B, and estimate whether the reagent dispensing mechanisms are operating normally based on whether the measurement result changes to OK or remains NG. When only one type of reagent is used in the measurement, it is also possible to set diagnostic measurement parameters that change the reagent dispensing mechanism used.

[0064] -Diagnostic Procedure- FIG. 7 is a flowchart showing the diagnostic procedure of the analysis unit 100 in this embodiment.

[0065] The service engineer receives notification of the malfunction from the user (step S701) and confirms the malfunction by receiving the measurement data ( FIG. 4 ) from the control unit 400 (step S702). At this time, as shown in FIG. 3 , the measurement data obtained by the analysis unit 100 is transferred from the control unit 400 of the analysis unit 100 to the data transfer terminal 500A and then stored in the data server 501B via the network NW. The service engineer acquires the measurement data from the data server 501B using the data analysis terminal 502B or 503B. The transmission path L1 of the measurement data output from the analysis unit 100 is shown by the dashed line in FIG. 3 . In step S702, the service engineer identifies the reagent name D403 and measurement protocol D409 for the measurement in which the malfunction occurred from the measurement data ( FIG. 4 ). The measurement protocol D409 identifies the channel (ch1 / ch2) of the channel-specific unit and the presence or absence of a BF separation process (BF+ / BF-). Based on the confirmed data, the service engineer sets diagnostic measurement parameters on the data analysis terminal 502B or 503B (step S703).

[0066] For ease of explanation, FIG. 7 will be described using an example in which the measurement protocol D409 for the measurement in which a malfunction was detected is ch1BF+, ​​i.e., the measurement protocol parameter P10 in FIG. 5 . In this case, the mechanism used in the measurement in which the malfunction occurred was ch1, and the BF separation process was also performed. Therefore, in step S703, the diagnostic measurement parameters P11-P15 for ch1 are selected from the diagnostic measurement parameters P11-P15 and P21-P25 illustrated in FIG. 5 . The service engineer transmits the diagnostic measurement parameters P11-P15 set on the data analysis terminal 502B or 503B as a measurement request to the control unit 400 via the network NW (step S704). At this time, as shown in FIG. 3 , the set diagnostic measurement parameters are transmitted from the data analysis terminal 502B or 503B via the network NW and transmitted to the control unit 400 via the data transfer terminal 500A. The transmission path L2 for these diagnostic measurement parameters is shown by the two-dot chain line in FIG. 3 .

[0067] Upon receiving the diagnostic measurement parameters, the control unit 400 displays a permission acquisition screen (e.g., FIG. 9 ) on the operation unit 402 to obtain user permission to perform diagnostic measurements from the service engineer and determines whether the user has given permission (step S705). If the user's permission is not obtained, the control unit 400 replies via transmission path L1 indicating that permission was not obtained. The procedure returns to, for example, step S704. If the user's permission is obtained, the control unit 400 waits for the scheduled time and sequentially performs diagnostic measurements based on the diagnostic measurement parameters (step S706). In step S705, obtaining user permission via the GUI facilitates scheduling of diagnostic measurements. Note that the procedure of obtaining permission via the GUI of the operation unit 402 is not essential; for example, the service engineer may contact the user by phone, email, or the like to obtain user permission in advance. Furthermore, the scheduled time for performing diagnostic measurements is a time that conforms to a rule previously set for diagnostic measurements. For example, if there is a free time of a predetermined length or more in the measurement schedule scheduled by the analysis unit 100, the diagnostic measurement may be performed using that free time, or the diagnostic measurement may be performed at a time when no measurement schedule is scheduled, such as at night.

[0068] When the diagnostic measurement is completed in the analysis unit 100, the measurement data is transferred from the control unit 400 to the data server 501B via transmission path L1. The service engineer checks the measurement data on the data analysis terminal 502B or 503B (step S707). For example, as shown in the example at the bottom of Figure 4, the measurement data from the diagnostic measurement is recorded as "Self-Diagnostic" in the measurement type D402, and the reagent name D403, sample name D404, and other analysis conditions are recorded in the same way as for regular quality control measurement (QC) and calibration measurement (Calibration). The quality control samples and reagents used in the diagnostic measurement (Self-Diagnostic) are the same as those used in the quality control measurement (QC) where the malfunction occurred.

[0069] After checking the measurement data, the service engineer analyzes the cause of the problem as described in FIG. 5 and narrows down the possible causes of the problem, such as a breakdown (step S708). An example of the procedure for narrowing down the cause of the problem in step S708 is shown in the flowchart of FIG. 8. FIG. 8 shows an example of logic for narrowing down the cause of the problem related to the measurement of ch1BF+. In this case, diagnostic measurement parameters (in this example, diagnostic measurement parameters P11-P15 in FIG. 5) are prepared for each channel-specific unit and common unit that are candidates for the problem location in step S703, and the measurement results for each diagnostic measurement parameter are confirmed in step S707. In this example, after determining whether or not there is a problem in the channel-specific unit, if no abnormality is found in the channel-specific unit, the presence or absence of a problem in the common unit is determined.

[0070] When the procedure of step S708 is started, the result of the diagnostic measurement, for example, for diagnostic measurement parameter P11, is analyzed as shown in analysis example 61A of FIG. 6 (step S708A). If the measurement result for diagnostic measurement parameter P11 changes to OK, the malfunction is presumed to be sample dispensing mechanism 103A (step S708a). If the measurement result for diagnostic measurement parameter P11 remains NG, sample dispensing mechanism 103A is excluded from the cause of the malfunction, and the result of the diagnostic measurement, for example, for diagnostic measurement parameter P12 is analyzed as shown in analysis example 62A of FIG. 6 (step S708B). If the measurement result for diagnostic measurement parameter P12 changes to OK, the malfunction is presumed to be BF separation unit 106A (step S708b). If the measurement result for the diagnostic measurement parameter P12 remains unchanged and is NG, the BF separation unit 106A is excluded from the cause of the malfunction, and the diagnostic measurement result for the diagnostic measurement parameter P13 is analyzed, for example, as shown in analysis example 63A of FIG. 6 (step S708C). If the measurement result for the diagnostic measurement parameter P13 changes to OK, the malfunction is presumed to be the detection unit 107A (step S708c). If the measurement result for the diagnostic measurement parameter P13 remains unchanged and is NG, the detection unit 107A is excluded from the cause of the malfunction. The order of steps S708A-S708C can be arbitrarily changed. If the results of steps S708A-S708C show that no abnormality is found in the channel-specific units, the common unit is next diagnosed.

[0071] When the diagnosis of the common unit begins, for example, the results of the diagnostic measurement related to the diagnostic measurement parameter P14 are analyzed as shown in analysis example 64A of FIG. 6 (step S708D). If the measurement results related to the diagnostic measurement parameter P14 with increased stirring intensity show no change (NG), it is suspected that the stirring unit 105 is not operating normally, considering that the channel-specific units are assumed to be normal (step S708d). Conversely, if the measurement results related to the diagnostic measurement parameter P14 change (change to OK), it is assumed that the stirring unit 105 is operating normally. In this case, the stirring unit 105 is excluded from the cause of the malfunction, and the results of the diagnostic measurement related to the diagnostic measurement parameter P15 are analyzed as shown in analysis example 65A of FIG. 6 (step S708E). If the measurement result for diagnostic measurement parameter P15 changes after changing the reaction temperature (NG), it is assumed that the channel-specific units and stirring unit 105 are normal, and it is suspected that the temperature adjustment mechanism 102c of the incubator disk 102 is not operating normally (step S708e). Conversely, if the measurement result for diagnostic measurement parameter P15 changes (changes to OK), no abnormality is found in the channel-specific units or common units that are the subject of diagnosis for diagnostic measurement parameters P11-P15, and a mechanism other than these operating mechanisms (for example, a quality control sample or reagent) is suspected as the cause of the malfunction (step S708f).

[0072] As in this example, the evaluation target is divided by diagnostic measurements related to diagnostic measurement parameters P11-P15, and the cause of the malfunction of analysis unit 100 is identified from the data of each diagnostic measurement.

[0073] 7, it is determined whether the cause of the problem narrowed down in step S708 lies in the operating mechanism (channel-specific unit or common unit) of the analysis unit 100, or in the quality control sample or reagent (step S709). If the cause of the problem is presumed to be the quality control reagent or sample, the service engineer notifies the user by appropriate communication means such as email or telephone of a request to replace the reagent or quality control sample with a new one and to perform quality control measurement on the operating mechanism under the same conditions as when the problem occurred (step S710), and the procedure in FIG. 7 is terminated.

[0074] If it is determined that the cause of the malfunction is in the channel-specific unit or the common unit, the service engineer prepares replacement parts for the operating mechanism identified as the cause of the malfunction in step S706 and visits the user facility A, which is the site, to perform maintenance on the analysis unit 100, such as replacing the parts (step S711).The service engineer then performs quality control measurements under the same conditions as when the malfunction occurred (step S712), checks the measurement data (step S713), and determines whether the malfunction has been resolved (step S714).If the measurement data is found to be satisfactory and the malfunction has been resolved, the service engineer terminates the procedure of FIG. 7.On the other hand, if the malfunction remains after maintenance, the service engineer performs an additional detailed on-site diagnosis of the analysis unit 100 to identify the cause of the malfunction (step S715).

[0075] -Effects- (1) In this embodiment, the control unit 400 receives diagnostic measurement parameters defining the conditions for diagnostic measurement via the network NW and controls the analysis unit 100 according to the received diagnostic measurement parameters to automatically perform diagnostic measurement. The diagnostic measurement parameters change the conditions for failed quality control measurements and for some processes. Unlike normal quality control measurements, the diagnostic measurement parameters are specialized for identifying the cause of the malfunction, allowing the process to be identified as a potential cause of the malfunction. A service engineer can achieve the same online effect as visiting user facility A and diagnosing the analysis unit 100 on-site. With this configuration, for example, a service engineer notified by a user of a malfunction in the analysis unit 100 can set diagnostic measurement parameters based on the malfunction before visiting user facility A, remotely instruct the control unit 400 to perform a diagnostic measurement, and based on the measurement results, can estimate the cause of the malfunction before visiting the site. Therefore, appropriate replacement parts can be arranged or brought with them in advance to the site. This reduces the need to return to service center B to retrieve or order replacement parts after visiting the site, shortening the time it takes to make the analysis unit 100 operational and deliver it to the user. Furthermore, fewer trips between the site and service center B are required, shortening the time it takes to address malfunctions, reducing the workload on the service engineer and lowering service costs. This reduces the downtime of the analysis unit 100, improving the user's operational efficiency and reducing the workload on the service engineer.

[0076] (2) Furthermore, if a quality control sample storage unit 200 for storing quality control samples is provided on-site, conditions can be specified using diagnostic measurement parameters, including the quality control sample to be used in the diagnostic measurement, and the diagnostic measurement using the specified quality control sample can be automatically performed in the analysis unit 100. If quality control samples stocked in the quality control sample storage unit 200 can be used in this way, there is no need to separately prepare quality control samples for the diagnostic measurement, and there is no need to ask the user to load the specified quality control samples into the analysis unit 100. Therefore, diagnostic measurements can be performed at night or on holidays when there are no users, reducing the burden on the user and increasing the flexibility of scheduling diagnostic measurements.

[0077] (3) The control unit 400 automatically transmits the results of the diagnostic measurement to a connected computer, such as the data server 501B, via the network NW. The transmission destination may be the data analysis terminal 502B or 503B. The service engineer can also inquire about the results of the diagnostic measurement from the user by email or telephone, but by automatically notifying the results of the diagnostic measurement via the network NW in this way, the burden on the user in responding to inquiries and the burden on the service engineer inquiring about the results can be reduced, and the service engineer can smoothly begin work on identifying the cause of the malfunction.

[0078] Second Embodiment FIG. 10 is a flowchart illustrating the flow of diagnostics of the analysis unit in a second embodiment of the present invention. This embodiment relates to condition-based maintenance (CBM). In the first embodiment, a service engineer sets diagnostic measurement parameters based on the nature of a malfunction occurring in the analysis unit 100 and remotely instructs the control unit 400 to perform diagnostic measurements. However, in this embodiment, diagnostic measurements are performed automatically (e.g., periodically) at pre-set times. The automated analysis system 1 according to this embodiment is configured such that the control unit 400 automatically receives diagnostic measurement parameters according to a set schedule and performs diagnostic measurements. The control unit 400 may also be configured to automatically perform diagnostic measurements related to the received diagnostic measurement parameters according to a predetermined schedule. This allows the diagnostic measurement data to be accumulated and the health of the analysis unit 100 to be periodically confirmed, quickly detecting abnormalities or signs of abnormalities in the analysis unit 100 without user notification, and quickly addressing the abnormalities or preventing malfunctions from occurring.

[0079] In the process of Figure 10, the service engineer determines a schedule for performing diagnostic measurements on the data analysis terminal 502B or 503B based on, for example, information on the usage schedule of the analysis unit 100 provided by the user (step S901). The diagnostic measurement schedule may be daily, weekly, or the like, or may specify at least one day or date and time. If the date and time are specified, when the user matches the timing to the scheduled date and time for the quality control measurement, the quality control sample transported from the quality control sample storage unit 200 to the analysis unit 100 for the quality control measurement can be used for the diagnostic measurement. In this case, there is no need to remove the quality control sample from the quality control sample storage unit 200 just for the diagnostic measurement, and deterioration of the quality control sample due to temperature changes, etc. can be suppressed.

[0080] The service engineer then sets diagnostic measurement parameters on the data analysis terminal 502B or 503B (step S902). The diagnostic measurement parameters can be set by selecting at least one from a plurality of pre-set diagnostic measurement parameters, such as the diagnostic measurement parameters P11-P15 and P21-P25 illustrated in FIG. 5 . Unlike the first embodiment, this embodiment is performed before a malfunction occurs. Therefore, by setting more diagnostic measurement parameters than in the first embodiment, it is possible to collect data on the status of more operating mechanisms. However, it is not necessary to comprehensively collect data on all operating mechanisms during a single diagnostic measurement. It is sufficient to change one or more operating mechanisms to be diagnosed for each diagnostic measurement, and periodically diagnose each operating mechanism or a portion of the operating mechanisms to be monitored.

[0081] The data analysis terminal 502B or 503B determines whether the measurement date and time set in step S901 has arrived (step S903), and if the measurement date and time has arrived, transfers the diagnostic measurement parameters set in step S902 and the measurement request to the control unit 400 via transmission path L2 (Figure 3) (step S904).

[0082] The control unit 400, which has received the diagnostic measurement parameters, performs a diagnostic measurement according to the diagnostic measurement parameters and returns the measurement data via the transmission path L1 (step S905). The processing content of the control unit 400 is the same as that of the first embodiment (step S706). At this time, a process equivalent to step S705 of the first embodiment is executed, and the user may be allowed to select whether or not to execute the measurement request.

[0083] The service engineer analyzes the diagnostic measurement data (step S906) and determines whether any of the diagnosed parts in the analysis unit 100 has a malfunction or a sign of a malfunction (step S907). In the first embodiment, whether the malfunction has recurred or been resolved was determined based on whether the measured concentration D406 fell within the target concentration range D408 for quality control positioning. In this embodiment, however, in step S907, the measured concentration D406 is evaluated using criteria different from those in the first embodiment in order to detect a sign of a malfunction that may occur in the future (for example, a state in which the measured concentration D406 falls within the target concentration range D408 but deviates somewhat from the target concentration D407, and thus no malfunction is currently present but a malfunction may occur in the near future). For example, the time-series data of the measured concentration D406 can be used to calculate the slope over a certain period up to the present, and if the slope is outside a reference range, it can be determined that there is a sign of a malfunction. Alternatively, measurement data from a period when no malfunctions have occurred in the operating mechanism being diagnosed can be used as normal data, and an indicator can be calculated and set using machine learning using this as training data. The presence or absence of a sign of a malfunction can be determined based on whether the indicator is within a set range. Multiple indicators may be used, and different indicators may be used for each operating mechanism being diagnosed, such as an indicator that can capture events specific to diagnosing the condition of the detection unit. When multiple indicators are used, it is determined that there is a sign of a malfunction if at least one indicator falls outside its set range. If no sign of a malfunction is detected in step S907, the procedure returns to step S903, and the analysis unit 100 is re-diagnosed using the measurement data from the next diagnostic measurement.

[0084] If a malfunction is detected in step S907, the service engineer determines whether an additional diagnostic measurement is necessary (step S908). An additional diagnostic measurement is performed when the acquired measurement data is insufficient to determine the state of the analysis unit 100, when the service engineer wishes to retry the diagnostic measurement, or when the service engineer wishes to perform a new diagnostic measurement under different conditions. If the service engineer determines that an additional diagnostic measurement is unnecessary, the procedure proceeds to step S911. If the service engineer determines that an additional diagnostic measurement is necessary, the service engineer sets additional diagnostic measurement parameters and transmits them to the control unit 400 (step S909), causing the analysis unit 100 to perform the additional diagnostic measurement (step S910). The service engineer acquires the additional diagnostic measurement data via the network NW and takes the additional diagnostic measurement data into consideration to improve the accuracy of the malfunction prediction diagnosis. By performing the additional diagnostic measurement in this manner, unnecessary service engineer visits can be reduced. After obtaining the necessary measurement data through step S908 or step S910, the service engineer narrows down the location of the malfunction (step S911). This narrowing down process may be performed in the same manner as in step S708 in FIG. 7, or may be performed based on the determination of whether the indicator has deviated from the set range as explained above in step S907.

[0085] The service engineer determines whether the cause of the symptom identified in step S911 is in the operating mechanism (channel-specific unit or common unit) of the analysis unit 100, or in the quality control sample or reagent (step S912). If the cause is estimated to be the quality control reagent or sample, the service engineer notifies the user by appropriate communication means such as email or telephone to request that the reagent or quality control sample be replaced with a new one (step S913), and the procedure in FIG. 10 is terminated.

[0086] If the cause is determined to be in the channel-specific unit or the common unit, the service engineer prepares replacement parts for the operating mechanism identified as the symptom location in step S911 and visits the user facility A, which is the site, to perform maintenance on the analysis unit 100, such as part replacement (step S914). Thereafter, as in the first embodiment, the service engineer performs quality control measurements under the same conditions as when the symptom was discovered (step S915), checks the measurement data (step S916), and determines whether the measurement accuracy has improved (step S917). The determination in step S917 can be made using the same logic as the determination in step S907. If the measurement data has improved, the service engineer terminates the procedure in FIG. 10. On the other hand, if the measurement accuracy has not sufficiently improved even after maintenance, the service engineer determines whether to perform an additional detailed on-site diagnosis of the analysis unit 100 to identify the cause of the malfunction or to wait and see for a certain period of time (step S918).

[0087] Except for the points described above, this embodiment is similar to the first embodiment.

[0088] As described above, according to this embodiment, CBM can be used to prevent malfunctions from occurring. While the first embodiment's reduction in the time required for troubleshooting after a malfunction occurs in the analysis unit 100 is a significant benefit for users, it would be even more desirable to be able to avoid downtime caused by dealing with the malfunction in the first place. Anticipating malfunctions that may occur in the future and identifying the factors that could be causing them is just as difficult as identifying the cause during troubleshooting, but this embodiment makes it possible.

[0089] 11 is a diagram showing the main components of an example of the configuration of an analysis unit and the like that constitutes an automatic analysis system according to a third embodiment of the present invention. In Fig. 11, elements that are similar to or correspond to those in the previously described embodiments are given the same reference numerals as those in the previously described drawings, and descriptions thereof will be omitted as appropriate.

[0090] The automatic analysis system 1 shown in Figure 11 includes a sample pretreatment system 600 that performs pretreatment on samples (samples derived from the patient's living body) to make them ready for analysis, a quality control sample storage unit 200 that stores quality control samples, a transport unit 300 that transports sample containers α1 and α2 (Figure 1), multiple (three in Figure 11) analysis units 100 arranged along the rack transport line 301' of the transport unit 300, and a control unit 400 that controls the operation of the sample pretreatment system 600, the quality control sample storage unit 200, the transport unit 300, and the analysis unit 100.

[0091] The sample pretreatment system 600 includes multiple processing units 601-609 for pretreatment of samples contained in sample containers α1. Detailed descriptions of the processing units 601-609 are omitted, but to briefly explain some of them, the sample container α1 is placed in processing unit 601, and centrifugal separation to separate serum and blood clots is performed in processing unit 602. Processing unit 603 performs an uncapping operation to remove the cap from the sample container α1, and processing unit 604 performs a dispensing operation to transfer the serum portion from the sample container α1 to another container. A secondary sample container into which the serum portion has been dispensed can also be the sample container α1. Processing unit 605 holds the sample container α1 retrieved from the rack transport line 301' via the sample transfer unit 305. In the sample pretreatment system 600, rack β1 ( FIG. 1 ) carrying the sample container α1 is transported between the processing units 601-609 via a rack transport line (not shown).

[0092] Sample container α1 pretreated by the sample pretreatment system 600 and sample container α2 stored in the quality control sample storage unit 200 are transferred to the rack transport line 301′ by the sample transfer unit 305, and are also collected from the rack transport line 301′. If the quality control sample requires pretreatment such as dilution or mixing, the quality control sample in sample container α2 may also be pretreated by the sample pretreatment system 600. The pretreated quality control sample may be transported to and stored in the quality control sample storage unit 200, or may be transported to the analysis unit 100 without being stored in the quality control sample storage unit 200 and used for quality control measurements or diagnostic measurements.

[0093] The multiple analysis units 100 are each connected to the transport unit 300 via a sample rack buffer unit 306, and sequentially analyze the samples in the sample containers α1 supplied via the sample rack buffer unit 306. The automated analysis system 1 of this embodiment is configured so that the multiple analysis units 100 share the same quality control sample storage unit 200.

[0094] The transport section 300 includes a sample transfer unit 305, a rack transport line 301′, and a sample rack buffer unit 306. The rack transport line 301′ of this embodiment is configured to be able to transport racks β1 and β2 in both directions along a single path, but may also be configured with two transport lines forming an outbound path and a return path, as in the first embodiment.

[0095] The control unit 400 receives diagnostic measurement parameters via the network NW, as in the first or second embodiment. The diagnostic measurement parameters also include information for identifying the analysis unit 100 to be diagnosed. The control unit 400 automatically transports the quality control sample to be used from the quality control sample storage unit 200 in accordance with the diagnostic measurement parameters, supplies the quality control sample to the analysis unit 100 to be diagnosed among the multiple analysis units 100 via the rack transport line 301′ of the transport unit 300, and controls the analysis unit 100 to perform diagnostic measurements in the same manner as in the first or second embodiment.

[0096] In this way, the present invention can also be applied to an automatic analysis system 1 configured so that multiple analysis sections 100 share the same quality control sample storage section 200, and similar effects can be obtained.

[0097] 12 is a conceptual diagram of a learning model used in an automated analysis system according to a fourth embodiment of the present invention. In the first to third embodiments, an example was described in which a service engineer sets diagnostic measurement parameters based on quality control measurement data from the analysis unit 100. However, in this embodiment, the diagnostic measurement parameters are generated by machine learning using past data accumulated for the analysis unit 100 by a computer, such as a data analysis terminal 502B or 503B.

[0098] 12 , in this embodiment, diagnostic measurement parameters are set using a learning model 120. The learning model 120 is a neural network generated by, for example, using an AI program to learn learning data through machine learning, and is stored, for example, in the memory of the data analysis terminals 502B and 503B or in a storage device on the network NW. For example, a computer such as the data analysis terminals 502B and 503B sets diagnostic measurement parameters using the learning model 120.

[0099] Possible data input to the input layer of the learning model 120 include, for example, NG data, measurement protocol parameters, assay features, troubleshooting history, alarm occurrence history, and units / components that affect measurement. NG data is, for example, data determined to be NG in quality control measurements or calibration measurements previously performed by the analysis unit 100, and includes information such as whether the data was low or high relative to the target concentration range D408 and how far it deviated. Measurement protocol parameters are the measurement protocol parameters applied to the measurement determined to be NG, including information on measurement conditions such as which channel (ch1 / ch2 in the first embodiment) was used and whether a BF separation process was performed. Assay features include, for example, information on characteristics such as the tendency for the measured concentration D406 to decrease when water is mixed into the reaction solution, or the responsiveness of the measured concentration D406 to changes in reaction temperature. Troubleshooting history is information on how the measurement result D405 was changed to OK for a measurement determined to be NG, and corresponds to corrective teacher data for the measurement protocol parameters. The alarm occurrence history is a history of alarms that have occurred in the analysis unit 100 most recently (during a set period up to the present), and is different from the NG measurement result D405. The units / components that affect the measurement are a list of the operating mechanisms and components that make up the analysis unit 100, the status of which affects the measured concentration D406.

[0100] The learning model 120 has already learned the relationship between this input data and the diagnostic measurement parameters, the candidate operating mechanisms that caused the NG, indicators specific to the operating mechanisms that caused the NG, etc. If the measurement result D405 is NG in the quality control measurement, the learning model 120 can set the candidate operating mechanisms that caused the NG (the operating mechanism to be diagnosed) based on the NG data and measurement protocol parameters related to the quality control measurement, the diagnostic measurement parameters to be applied to the diagnostic measurement, indicators to evaluate the results of the diagnostic measurement, etc.

[0101] The learning model 120 can be used, for example, to set diagnostic measurement parameters in step S703 (FIG. 7) or steps S902 and S909 (FIG. 10), or to evaluate the measurement data for diagnostic measurements in step S708 (FIG. 7) or steps S906 and S911 (FIG. 10). Furthermore, the input of quality control measurement data determined to be NG to the learning model 120 and the transmission of diagnostic measurement parameters and the like output by the learning model 120 to the control unit 400 may be performed manually or automatically.

[0102] This embodiment is similar to the first, second, or third embodiment except that AI is used to set parameters and evaluate measurement data.

[0103] By utilizing AI in this way, benefits such as further reducing the burden on service engineers, lowering service costs, and reducing human errors in judgment can be achieved.

[0104] 13 to 16 are diagrams showing the main components of an example of the configuration of an analysis unit and the like that make up an automatic analysis system according to a fifth embodiment of the present invention, and each diagram shows the operation process of the quality control sample storage unit provided in the analysis unit. Elements that are the same as or correspond to elements that have already been explained in Figs. 13 to 16 are given the same reference numerals as in the previously mentioned drawings, and explanations thereof will be omitted as appropriate.

[0105] This embodiment is similar to the first embodiment except for the configuration of the quality control sample storage unit 200 described below. The quality control sample storage unit 200 according to this embodiment can also be applied to the second to fourth embodiments. In the quality control sample storage unit 200 of this embodiment, the sample container α2 is individually removed from the rack β2 on the transport unit 300 by the container gripping mechanism 211 and stored individually in the storage unit 219. In this respect, the quality control sample storage unit 200 of this embodiment differs from the quality control sample storage unit 200 shown in FIG. 1.

[0106] The quality control sample storage unit 200 illustrated in Figures 13 to 16 has three storage positions (left, center, and right) aligned in the X direction (left-right direction in the figures) and multiple storage positions aligned in the Y direction (up-down direction in the figures), but the number of storage positions in the X and Y directions can be changed as appropriate. The container gripping mechanism 211 is configured to grip the sample container α2 with a mechanism (not shown) including claws, etc., and move the sample container α2 in a planar direction while gripping it with the X-direction transport mechanism 212 and the Y-direction transport mechanism 213. In this embodiment, the quality control sample transport unit 217 is used as a place to store empty racks β required to transport the sample container α2 from the storage unit 219.

[0107] In this embodiment, when sample container α2 is transported from rack β2 on the transport line 301 to the quality control sample storage unit 200, the container gripping mechanism 211 first moves toward rack β2 on the transport line 301 using the Y-direction transport mechanism 213 as shown in FIG. 13 and grips one sample container α1 loaded on rack β2 on the transport line 301 ( FIG. 14 ). Then, while holding sample container α2, the container gripping mechanism 211 moves in the Y direction using the Y-direction transport mechanism 213, and then (while moving) moves in the X direction using the X-direction transport mechanism 212 to access the target storage position in the storage unit 219 ( FIG. 15 ), and places sample container α2 in storage position j, completing storage ( FIG. 16 ). The container gripping mechanism 211 can also grip the target sample container α2 in the storage unit 219, remove it from the storage unit 219, and place it on rack β2 in the quality control sample transport unit 217.

[0108] In this way, the present invention can be applied even when the storage form of the sample container α2 in the quality control sample storage unit 200 is different, and the same effects can be achieved.

[0109] <Additional Remarks> The present invention is not limited to the above-described embodiments and may include various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those including all of the described configurations. It is possible to delete some of the configurations of the above-described embodiments or replace them with other configurations, or to add other configurations. For example, as mentioned above, the shared server 40, etc., can be omitted. It is also possible to combine multiple embodiments.

[0110] Furthermore, some or all of the configurations, functions, processes, processing means, etc. of the above embodiments may be implemented by hardware, such as an integrated circuit. The above configurations, functions, etc. may be implemented by software, with a processor interpreting and executing a program that implements each function. Information such as programs, tables, and files that implement each function may be stored in various storage media. Examples of various storage media include recording devices such as memory, hard disks, and solid-state drives (SSDs), as well as flash memory cards and digital versatile disks (DVDs). Furthermore, in the above embodiments, the information input / output lines (e.g., Figures 1 and 2 ) indicate those considered necessary for explanation and do not necessarily represent all lines in the product. In reality, all components may be considered to be interconnected.

[0111] Furthermore, although a quality control sample owned by the user can be used for diagnostic measurements performed at user facility A, there are cases where it is undesirable to use a quality control sample, which is the user's asset, for diagnostic measurements. Therefore, a quality control sample (for diagnostic measurements) for identifying the cause of an abnormality can be arranged at service site B, which is the entity performing the diagnostic measurements, and stored in advance in the quality control sample storage unit 200 of the automated analysis system 1 at user facility A. When necessary, such as when an abnormality occurs, the diagnostic measurements can be performed using the quality control sample for cause identification arranged at service site B, rather than the quality control sample owned by the user used for regular quality control measurements. It is more desirable for the quality control sample for cause identification to be a multi-calibrator compatible with multiple analysis items.

[0112] It is also possible to select and set parameters so that a specific area in the quality control sample storage unit 200 is allocated as a dedicated storage area for quality control samples for cause identification, and when a diagnostic measurement is requested, the designated quality control sample is transported from the dedicated storage area to the analysis unit 100 for the diagnostic measurement. In this case, as shown in FIG. 17, for example, the measurement protocol parameters include parameters (QC1 and QC2 in the illustrated example) that identify the quality control sample (or its storage area) to be used, so that the quality control sample designated by the measurement protocol parameters is used for the measurement. FIG. 17 adds QC1 and QC2 to the measurement protocol parameters shown in FIG. 5, but omits some parameters such as BF1. In the example of FIG. 17, the measurement protocol parameters P19 and P29 for the routine quality control measurement (QC) specify the user's quality control sample (QC1), and the diagnostic measurement parameters P11-P15 and P21-P25 specify the quality control sample (QC2) for cause identification described above. In Figure 17, a simple example is shown in which quality control samples are distinguished by two parameters QC1 and QC2, but it goes without saying that a wider variety of quality control samples can be prepared and one can be selected from among them using the measurement protocol parameters. Also, apart from the predetermined measurement protocol parameters (Figure 5) that specify the sample dispensing mechanism, etc., it is also possible to adopt an instruction form in which the quality control sample to be used in the measurement is separately selected and set.

[0113] In addition, as a method of identifying quality control samples for cause identification in the analysis section 100, in addition to setting up a dedicated storage area as described above and identifying them by their address within the quality control sample storage section 200, it is also possible to attach a barcode to each sample container α2 and identify them based on the barcode reading information.

[0114] 1...automatic analysis system, 100...analysis unit, 102c...temperature adjustment mechanism (operating mechanism), 103A, 103B...sample dispensing mechanism (operating mechanism), 105...stirring unit (operating mechanism), 106A, 106B...separation unit (operating mechanism), 107A, 107B...detection unit (operating mechanism), 120...learning model, 200...quality control sample storage unit, 300...transport unit, 400...control unit, 502B, 503B...data analysis terminal (terminal), NW...network, P11-P15, P21-P25...diagnostic measurement parameters, α1...sample container (sample), α2...sample container (sample, quality control sample)

Claims

1. An automatic analysis system having an analysis unit that analyzes samples and a control unit that controls the analysis unit, wherein the control unit receives diagnostic measurement parameters that define conditions for diagnostic measurements via a network, controls the analysis unit in accordance with the diagnostic measurement parameters, and automatically performs the diagnostic measurements.

2. An automatic analysis system according to claim 1, comprising: a quality control sample storage unit for storing quality control samples; and a transport unit for transporting the quality control samples between the quality control sample storage unit and the analysis unit; wherein the diagnostic measurement parameters specify the quality control samples to be used in the diagnostic measurement as the conditions; and the control unit controls the quality control sample storage unit, the transport unit, and the analysis unit according to the diagnostic measurement parameters, supplies the specified quality control samples to the analysis unit, and carries out the diagnostic measurement.

3. An automatic analysis system according to claim 2, further comprising a terminal installed in a second facility separate from the first facility where the control unit is installed, wherein the diagnostic measurement parameters are arbitrarily set on the terminal and transmitted to the control unit via the network in response to an operator's operation.

4. An automatic analysis system according to claim 2, wherein the control unit is configured to automatically receive the diagnostic measurement parameters according to a set schedule.

5. An automatic analysis system according to claim 2, wherein the control unit transmits the results of the diagnostic measurement to a computer connected via the network.

6. An automatic analysis system according to claim 2, wherein the analysis unit has a plurality of operating mechanisms used to analyze the sample, the diagnostic measurement parameters specify as conditions an operating mechanism to be used in each step of the diagnostic measurement that is different from the operating mechanism used in the measurement in which the malfunction occurred, and the control unit carries out the diagnostic measurement using each operating mechanism specified by the diagnostic measurement parameters.

7. An automatic analysis system according to claim 6, wherein the analysis unit has a plurality of dispensing mechanisms, the diagnostic measurement parameters specify the dispensing mechanisms to be used in the diagnostic measurement as the conditions, and the control unit carries out the diagnostic measurement using the dispensing mechanisms specified by the diagnostic measurement parameters.

8. An automatic analysis system according to claim 6, wherein the analysis section has a plurality of detection units for detecting predetermined components in the reaction solution of the quality control sample and the reagent, the detection units to be used in the diagnostic measurement are specified as the conditions in the diagnostic measurement parameters, and the control section carries out the diagnostic measurement using the detection units specified by the diagnostic measurement parameters.

9. An automatic analysis system according to claim 6, wherein the analysis section has a plurality of separation units that separate and remove impurities contained in the reaction solution of the quality control sample and reagent from the reaction solution, the diagnostic measurement parameters specify the separation units to be used in the diagnostic measurement as the conditions, and the control section carries out the diagnostic measurement using the separation units specified by the diagnostic measurement parameters.

10. An automatic analysis system according to claim 6, wherein the analysis section has a stirring unit that stirs the mixture of the quality control sample and reagent, the diagnostic measurement parameters specify the strength of the stirring action of the stirring unit on the mixture as the condition, and the control section controls the stirring unit to stir the mixture at the strength specified by the diagnostic measurement parameters, thereby performing the diagnostic measurement.

11. An automatic analysis system according to claim 6, wherein the analysis unit has a temperature adjustment mechanism for adjusting the temperature of the reaction solution of the quality control sample and reagent, the temperature of the reaction solution adjusted by the temperature adjustment mechanism is specified as the condition in the diagnostic measurement parameters, and the control unit controls the temperature adjustment mechanism to adjust the temperature of the reaction solution to the temperature specified by the diagnostic measurement parameters, thereby carrying out the diagnostic measurement.

12. An automatic analysis system according to claim 2, characterized in that it comprises a plurality of said analysis units, and is configured so that the same quality control sample storage unit is shared by the plurality of said analysis units.

13. An automatic analysis system according to claim 2, wherein the diagnostic measurement parameters are generated by machine learning past data accumulated for the analysis unit.

14. A diagnostic method for an analysis unit that analyzes samples, comprising the steps of: transmitting diagnostic measurement parameters that define the conditions for diagnostic measurement to a control unit that controls the analysis unit via a network; causing the analysis unit to carry out the diagnostic measurement in accordance with the diagnostic measurement parameters; and viewing the results of the diagnostic measurement on a terminal installed in a second facility separate from the first facility where the control unit is installed, and estimating the location of a defect in the analysis unit.

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