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WO2025220380A1 - Système d'analyse automatisé et procédé de diagnostic - Google Patents

Système d'analyse automatisé et procédé de diagnostic

Info

Publication number
WO2025220380A1
WO2025220380A1 PCT/JP2025/010235 JP2025010235W WO2025220380A1 WO 2025220380 A1 WO2025220380 A1 WO 2025220380A1 JP 2025010235 W JP2025010235 W JP 2025010235W WO 2025220380 A1 WO2025220380 A1 WO 2025220380A1
Authority
WO
WIPO (PCT)
Prior art keywords
unit
diagnostic measurement
measurement
diagnostic
quality control
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/JP2025/010235
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English (en)
Japanese (ja)
Inventor
俊輔 佐々木
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hitachi High Tech Corp
Original Assignee
Hitachi High Tech Corp
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Filing date
Publication date
Application filed by Hitachi High Tech Corp filed Critical Hitachi High Tech Corp
Publication of WO2025220380A1 publication Critical patent/WO2025220380A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N35/00—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor

Definitions

  • the present invention relates to an automated analysis system and diagnostic method for analyzing biological samples such as blood.
  • Automated analyzers are devices that automatically analyze samples and output results. These results are used by doctors in hospitals and medical testing facilities for diagnosis, so reliability must be ensured. Therefore, the measurement accuracy of the automated analyzer is managed by periodically measuring quality control samples (hereinafter referred to as quality control measurements) in which the concentrations of target components are known. If the measurement results fall outside a preset tolerance range, the quality control measurement is deemed to have failed and troubleshooting is required.
  • Patent Document 1 discloses an automated analyzer that uses quality control measurements to instruct the user on troubleshooting.
  • the user will typically contact a service center and request a repair.
  • a service engineer from the service center will visit the user's location and repair the automated analyzer.
  • the service engineer will identify the cause of the failed quality control measurement on-site, take measures, and confirm that the quality control measurement passes before handing the automated analyzer over to the user.
  • the service engineer performs the work of investigating the cause, taking measures, and verifying accuracy on-site, the user will not be able to 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 machine in advance or outsource sample analysis to an external organization.
  • service engineers sometimes arrive at the site without any idea of the cause of the malfunction, so even if the cause is identified and, for example, a part needs to be replaced, they may not have the replacement part with them. If the replacement part is not on hand, the service engineer will have to return to the service center to retrieve the replacement part or order the part, which takes even more time before the automatic analyzer can be handed over to the user and increases the service engineer's workload and service costs.
  • Patent Document 1 statistically analyzes the results of quality control measurements from multiple automated analyzers, classifies abnormalities, and outputs troubleshooting instructions, but it is difficult to identify the cause of the abnormality from the various factors, such as equipment and reagents, that affect measurement accuracy.
  • a service engineer is notified of a malfunction by a user, they must visit the site from the stage of identifying the cause.
  • Even if several possible causes are estimated from information about the abnormality before visiting the site, it remains the case that they must visit the site at the stage of identifying the cause in order to accurately identify the cause. Therefore, it is difficult for the technology described in Patent Document 1 to solve the aforementioned issues of reducing downtime and reducing workload and service costs.
  • the objective of the present invention is to provide an automatic analysis system and diagnostic method that can shorten downtime, improve user work efficiency, and reduce the workload of service engineers.
  • the present invention provides an automatic analysis system having an analysis unit that analyzes samples and a control unit that controls the analysis unit, in which the control unit receives diagnostic measurement parameters that define the conditions for diagnostic measurements via a network, controls the analysis unit in accordance with the diagnostic measurement parameters, and automatically performs the diagnostic measurements.
  • This invention can reduce downtime, improve user work efficiency, and reduce the workload of service engineers.
  • FIG. 1 is a diagram showing the main parts of an example of the configuration of an analysis unit and the like 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.
  • 1 is a schematic diagram illustrating an example of the configuration of a network for implementing a diagnostic method for an analysis unit of an automatic analysis system according to a first embodiment of the present invention.
  • 10 is an example of measurement data obtained by measuring a sample in an analysis unit. 1 shows examples of diagnostic measurement parameters used in the present invention.
  • FIG. 10 is an explanatory diagram of an example of analysis of diagnostic measurement results. 10 is a flowchart showing a diagnostic procedure of an analysis unit in the first embodiment of the present invention.
  • FIG. 10 is a flowchart illustrating an example of a procedure for narrowing down the cause of a defect.
  • FIG. 10 is a diagram showing an example of a permission acquisition screen for obtaining permission to perform diagnostic measurements.
  • 10 is a flowchart showing a diagnostic procedure of an analysis unit in a second embodiment of the present invention.
  • FIG. 10 is a diagram showing the main parts 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.
  • FIG. 10 is a conceptual diagram of a learning model used in an automatic analysis system according to a fourth embodiment of the present invention.
  • FIG. 10 is a diagram showing the main parts of an example of the configuration of an analysis unit and the like that constitutes an automatic analysis system according to a fifth embodiment of the present invention.
  • FIG. 10 is a diagram showing the main parts of an example configuration of an analysis unit and the like that constitutes an automatic analysis system according to a fifth embodiment of the present invention.
  • FIG. 10 is a diagram showing the main parts of an example of the configuration of an analysis unit and the like that constitutes an automatic analysis system according to a fifth embodiment of the present invention.
  • FIG. 10 is a diagram showing the main parts of an example of the configuration of an analysis unit and the like that constitutes an automatic analysis system according to a fifth embodiment of the present invention.
  • 4 is another example of a diagnostic measurement parameter used in the present invention.
  • 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.
  • the analysis unit 100 of the automatic analysis system 1 can be a wide variety of devices that analyze samples based on the results of reactions between samples and reagents, including, for example, automatic biochemistry analyzers.
  • automatic analysis units such as mass spectrometers used in clinical testing and coagulation analyzers that measure blood clotting times can also be used as the analysis unit 100.
  • the present invention can also be applied to automatic analysis systems that include multiple automatic analysis units of the same or different types that are connected to each other.
  • FIG. 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 FIG. 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.
  • the transport unit 300 includes rack transport lines 301 and 302 that transport rack ⁇ 1.
  • the rack transport line 301 is a feed line that transports rack ⁇ 1 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 ⁇ 1 from the analysis unit 100 toward the quality control sample storage unit 200.
  • Rack ⁇ 1 is installed with a plurality of sample containers ⁇ 1 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 ⁇ 1 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 ⁇ 1 used in the analysis unit 100 is transported via the transport line 302 to the sample recovery unit 304, where the user recovers the rack ⁇ 1.
  • 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/refrigeration mechanism (not shown), and can store racks ⁇ 2, on which multiple sample containers ⁇ 2 containing quality control samples are placed, by cooling and keeping them cold using the cooling/refrigeration mechanism (not shown).
  • the quality control sample transport unit 217 retrieves rack ⁇ 2 from any of the storage units 219, transports it to the transport unit 300, and supplies it to the analysis unit 100.
  • 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.
  • the analysis unit 100 is a mechanical unit that performs analysis operations and includes multiple operating mechanisms used for analyzing samples.
  • 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.
  • the reagent cooling unit 101 functions as a reagent container storage cabinet.
  • the reagent cooling unit 101 holds and keeps cold multiple reagent containers ⁇ containing reagents used in sample analysis.
  • Various types of reagents are stored in the reagent cooling unit 101 depending on 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.
  • the cover 101a is shown partially cut away to show the reagent containers ⁇ inside the reagent cooling unit 101.
  • the incubator disk 102 has a reaction vessel placement section 102b that can accommodate multiple reaction vessels 102a for containing a reaction liquid, which is a mixture of sample and reagent, and a temperature adjustment mechanism 102c that adjusts the temperature of the reaction liquid of sample (including quality control samples) and reagent in the reaction vessels 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.
  • the sample dispensing mechanisms 103A and 103B have a rotation drive mechanism and a vertical drive mechanism (not shown), and use these drive mechanisms to aspirate the sample from sample container ⁇ 1 mounted on rack ⁇ 1 on the rack transport line 301, and dispense the aspirated sample into reaction container 102a held on incubator disk 102.
  • the reagent dispensing mechanisms 104A and 104B also have a rotation drive mechanism and a vertical drive mechanism (not shown), and these drive mechanisms aspirate reagent from the reagent container ⁇ held in the reagent cooling unit 101, and dispense the aspirated reagent into the reaction container 102a held on the incubator disk 102.
  • 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 of directly manipulating the reaction vessel 102a is to rotate the reaction vessel 102a with a rotation mechanism (not shown) to stir the mixture.
  • An example of a method of 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, and then irradiate the mixture with these ultrasound waves to stir it.
  • the stirring unit 105 is configured to allow the stirring strength of the mixture to be adjusted.
  • the BF separation units 106A and 106B are devices that separate and remove impurities contained in a reaction solution obtained by mixing a sample and a reagent from the reaction solution.
  • Detection units 107A and 107B are devices that detect specific components in the sample (including quality control samples) and reagent reaction solution, and are composed of a photomultiplier tube, light source lamp, spectroscope, photodiode, etc. These detection units 107A and 107B have the function of adjusting the temperature of equipment such as the photomultiplier tube, light source lamp, spectroscope, photodiode, etc.
  • the analysis unit 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.
  • sample and reagent are dispensed into reaction vessel 102a by sample dispensing mechanisms 103A, 103B and reagent dispensing mechanisms 104A, 104B.
  • sample dispensing mechanisms 103A, 103B After impurities are removed by BF separation units 106A, 106B and stirring is performed by stirring unit 105, the desired components are detected by detection units 107A, 107B.
  • the cooling mechanism of reagent cooling unit 101, the temperature adjustment mechanism 102c of incubator disk 102, the stirring unit 105, etc. are shared for each sample measurement.
  • sample dispensing mechanisms 103A, 103B In contrast, for devices with multiple identical functions, such as sample dispensing mechanisms 103A, 103B, reagent dispensing mechanisms 104A, 104B, BF separation units 106A, 106B, and detection units 107A, 107B, one of them is selected and used for each sample measurement.
  • sample dispensing mechanisms 103A, 103B, etc. take a relatively long time and become a bottleneck in the sequential measurement of samples, so by providing multiple devices for each, high measurement throughput is ensured.
  • a predetermined combination (system) of instruments used in the sample measurement process may be referred to as a "channel.”
  • instruments that have exactly the same role and are provided in multiple units in the analysis unit 100 such as the sample dispensing mechanisms 103A and 103B, the BF separation units 106A and 106B, and the detection units 107A and 107B, and are used selectively for each measurement, may be referred to as a "channel-specific unit.”
  • 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.”
  • 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
  • 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), controls the analysis unit 100, the quality control sample storage unit 200, the transport unit 300, etc. according to the diagnostic measurement parameters, and has the function of automatically performing diagnostic measurements requested from remote locations via the network NW.
  • diagnostic measurement parameters FIG. 5
  • NW FIG. 3
  • the control unit 400 may be configured as hardware using a dedicated circuit board, or as software executed by a computer connected to the analysis unit 100.
  • the control unit 400 When the control unit 400 is configured as hardware, it can be realized by integrating multiple processing units on a wiring board, semiconductor chip, or package.
  • the control unit 400 When the control unit 400 is configured as software, it can be realized by installing a high-speed general-purpose CPU in the computer and executing a program that performs the desired calculation processing. Existing equipment can also be upgraded using a recording medium on which this program is recorded.
  • the devices, circuits, computers, etc. that make up the control unit 400 are connected via a wired or wireless network and send 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 keyboard.
  • Measurement protocol - 2 is a diagram showing an example of a measurement protocol, which is a 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, and cleaning, and may be, for example, every 8 seconds or every 20 seconds.
  • FIG. 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 stirring 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
  • a channel combining sample dispensing mechanism 103A, BF separation unit 106A, and detection unit 107A is called “ch1,” and a channel combining sample dispensing mechanism 103A, BF separation unit 106B, and detection unit 107B is called “ch2.”
  • Measurements 1-6 shown in Figure 2 are performed alternately using ch1 and ch2. However, some mechanisms, such as BF separation units 106A and 106B, may not be used depending on the measurement.
  • Measurement 1 is performed using the channel-specific unit for ch1 and a common unit.
  • sample dispensing mechanism 103A dispenses a sample (S1) and reagent dispensing mechanism 104A dispenses a first reagent (R1).
  • reagent dispensing mechanism 104B dispenses a second reagent (R2), and sample dispensing mechanism 103A is cleaned (S1w), and reagent dispensing mechanism 104A is cleaned (S2w).
  • reagent dispensing mechanism 104B is cleaned (R2w).
  • Reagent dispensing mechanisms 104A and 104B have the same function, but because their operational purposes (dispensing reagents) can differ in the same measurement process, in this embodiment they are classified as common units as described above.
  • 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.
  • BF separation (BF1) is performed by the BF separation unit 106A.
  • the BF separation process requires time for preparation to remove impurities from the reaction solution, so in the example of Figure 2, multiple cycles are allocated to it.
  • This BF separation unit 106A is washed in cycle 8 (BF1w).
  • detection (D1) by the detection unit 107A begins. 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.
  • each channel-specific unit takes multiple cycles.
  • 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.
  • the analysis unit 100 of this embodiment is equipped with multiple channel-specific units. As a result, when measurement 1 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.
  • measurements 1, 2, 3, etc. alternately use the channel-specific units ch1 and ch2.
  • BF separation may not be necessary depending on the item being measured.
  • 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 that make up the channels used does not change.
  • parameters for each measurement including analysis conditions such as the channels to be used (ch1, ch2) and whether or not BF separation is performed, are called "measurement protocol parameters.”
  • 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.
  • FIG. 3 is a schematic diagram showing an example of the configuration of a network for implementing the diagnostic method of the analysis unit 100 of the automatic analysis system 1.
  • diagnostic measurement parameters defining the conditions for diagnostic measurement are sent to the control unit 400, which controls the analysis unit 100, via a network NW such as the Internet, and the analysis unit 100 is caused to perform diagnostic measurement according to the diagnostic measurement parameters.
  • the results of the diagnostic measurement are viewed on a terminal (e.g., data analysis terminal 502B) installed at a second facility (service base B or a facility connected to service base B via a network NW) 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.
  • a service engineer can remotely instruct the analysis unit 100 to perform diagnostic measurement without visiting user facility A where the analysis unit 100 is operating, and identify the cause of the malfunction in the analysis unit 100 from the results of the diagnostic measurement before visiting user facility A.
  • user facility A is equipped with an analysis unit 100, a quality control sample storage unit 200, and a control unit 400.
  • the automated analysis system 1 may include multiple analysis units 100, and the example in Figure 3 shows an example in which multiple analysis units 100 are installed at user facility A. These multiple analysis units 100 can be the subject of diagnosis. Furthermore, analysis units 100 installed in locations other than user facility A can also be included as the subject of diagnosis, as long as they are configured to enable remote exchange of diagnostic measurement parameters and diagnostic measurement results via the network NW. Furthermore, while the example in Figure 3 illustrates a configuration in which there are multiple sets of analysis units 100, quality control sample storage units 200, and control units 400, at least one of the quality control sample storage units 200 and the control unit 400 may be shared by multiple analysis units 100.
  • the automated analyzer 1 includes a data transfer terminal 500A installed at a first facility (user facility A in Figure 3) along with the control unit 400, as well as a data server 501B and data analysis terminals 502B and 503B installed at a second facility (service base B or other facility in Figure 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 data analysis terminals 502B and 503B.
  • the data server 501B and data analysis terminals 502B and 503B can also be configured, for example, as computers connected to the network NW.
  • the data server 501B is installed at service base B, but it may also be installed at user facility A, or it may be installed at a location other than user facility A and service base B as long as it is connected to enable bidirectional communication via the network NW.
  • Data analysis terminal 502B is an example of a terminal installed at service site B
  • data analysis terminal 503B is an example of a terminal installed at a second facility other than service site B.
  • Control unit 400 transfers sample measurement data (FIG. 4) 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 may be transferred 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.
  • FIG. 4 shows an example of measurement data from sample measurements performed in the analysis unit 100.
  • the measurement data in FIG. 4 is data obtained by measuring a sample in, for example, one or both of the analysis units 100 shown in FIG. 3.
  • 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 ( FIG. 1 ) by the control unit 400 and transferred to the data server 501B via the data transfer terminal 500A by the control unit 400.
  • measurement time D401 is the time when the corresponding measurement was completed in the analysis unit 100 and the measurement data was output.
  • Measurement type D402 is information indicating the type of measurement performed, and records, for example, whether it was a regular quality control measurement (QC), calibration measurement (Calibration), general measurement (routine), or diagnostic measurement (Self-Diagnostic) requested via the network NW.
  • Reagent name D403 is the name of the reagent used in the measurement
  • sample name D404 is the name of the sample used in the measurement. In the example of Figure 4, sample name D404 is recorded only when measurement type D402 is QC, Calibration, or Self-Diagnostic, and is not recorded when it is routine.
  • the measured concentration D406 is the concentration (measured value) of the target component contained in the measured sample.
  • the target concentration D407 is the target concentration (set reference value) set for each target component for the measured concentration D406.
  • the target concentration range D408 is the normal range set for each target component for the measured concentration D406. In the example of Figure 4, the target concentration D407 and target concentration range D408 are set only for the QC, Calibration, and Self-Diagnostic measurement types D402, and are not set for the routine measurement type D402.
  • the measurement result D405 is the result of determining 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 Figure 4, the measurement result D405 is recorded only in the measurement types D402 of QC, Calibration, and Self-Diagnostic, and is not recorded in the measurement type D402 of 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.
  • the value of the measured concentration D406 can be compared with the values of the past N measurements (measured values of the same type) to determine whether the measured concentration D406 is showing a predetermined trend (such as a monotonic increase or decrease). This can also be applied to the measurement result D405.
  • 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 between 1 and 10, with 10 representing the maximum stirring intensity and 1 representing the minimum stirring intensity.
  • the remaining reagent amount D411 is the remaining amount of reagent used in the measurement
  • the remaining QC sample amount D412 is 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.
  • the remaining QC sample amount D412 is recorded only for measurement types D402 that use quality control samples, i.e., QC and Self-Diagnostic measurement types D402, and is not recorded for Calibration and routine measurement types D402.
  • 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.
  • Figure 5 shows an example of diagnostic measurement parameters.
  • 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.
  • 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.
  • the stirring intensity is 3 and the reaction temperature is 37°C.
  • measurement protocol parameters P10 and P20 are measurement protocol parameters when BF separation is performed; measurement protocol parameters (ch1BF-, ch2BF-) when BF separation is not performed are not shown in Figure 5.
  • the analysis unit 100 performs a routine measurement based on the measurement protocol parameters P10 and P20.
  • diagnostic measurement parameters P11-P15 and P21-P25 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 and the user is unable to resolve the issue.
  • 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.
  • An operator such as a service engineer uses data analysis terminal 502B or 503B to check the measurement data sent from control unit 400, such as the example shown in Figure 4, and selects, inputs, etc., diagnostic measurement parameters P11-P15, P21-P25, etc., that are relevant to cause identification.
  • Diagnostic measurement parameters are set arbitrarily on data analysis terminal 502B or 503B and are sent to control unit 400 via network NW in response to operator 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. Although the quality control sample is not shown in Figure 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.
  • QC routine quality control measurement
  • the reagent named FT4 is specified in the diagnostic measurement parameters.
  • the diagnostic measurement parameters specify as a condition that the operating mechanisms (dispensing mechanism, BF separation unit, detection unit, etc.) 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.
  • the control unit 400 which has received the diagnostic measurement parameters, controls the quality control sample storage unit 200, transport unit 300, and 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.
  • 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 deduce and identify the cause of the malfunction.
  • -Analysis of diagnostic measurement results- 6 is an explanatory diagram of an example of analysis of diagnostic measurement results, which shows an example of analysis when a problem occurs in measurement using ch1.
  • diagnostic measurement parameters for example, 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 the operating mechanism used in the quality control measurement where the problem occurred is specified as a condition for the diagnostic measurement.
  • diagnostic measurement parameter P11 is a parameter used to determine whether the malfunction is caused by sample dispensing mechanism 103A.
  • This diagnostic measurement parameter P11 specifies, as a condition, that the dispensing mechanism to be used in the diagnostic measurement is sample dispensing mechanism 103B (S2), which is different from sample dispensing mechanism 103A (S1) set by measurement protocol parameter P10.
  • Analysis example 61A shown in the first column from the top of Figure 6, illustrates the determination of the results of the diagnostic measurement performed based on diagnostic measurement parameter P11.
  • the results are determined using the same criteria as the measurement during the malfunction, such as the target concentration and target concentration range.
  • the target concentration D407 and target concentration range D408 may use the ranges used during quality control measurement (QC) or calibration measurement, or the target concentration D407 and target concentration range D408 for diagnostic measurement may be set independently.
  • the diagnostic measurement parameter P12 in the example of FIG. 5 is a parameter used to determine whether the malfunction is caused by the BF separation unit 106A.
  • This diagnostic measurement parameter P12 specifies, as a condition, that the BF separation unit to be used in the diagnostic measurement be 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 in FIG. 6 represents the determination of the results of the diagnostic measurement performed based on the diagnostic measurement parameter P12.
  • the diagnostic measurement parameter P13 in the example of Figure 5 is a parameter used to determine whether the malfunction is caused by detection unit 107A.
  • This diagnostic measurement parameter P13 specifies as a condition that the detection unit to be used in the diagnostic measurement 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 in Figure 6 represents the determination of the results of the diagnostic measurement performed based on 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.
  • the diagnostic measurement parameter P14 in the example of Figure 5 is a parameter used to determine whether the malfunction is caused by the agitation unit 105.
  • This diagnostic measurement parameter P14 specifies a condition for the intensity of the agitation operation of the agitation unit 105, a different intensity (7) from the intensity (3) set in the measurement protocol parameter P10.
  • Analysis example 64A shown in the fourth column from the top in Figure 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 have occurred in the agitation unit 105.
  • the diagnostic measurement parameter P15 in the example of Figure 5 is a parameter used to determine 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 set by the temperature adjustment mechanism 102c of the incubator disk 102, which is different from the 37°C set in the measurement protocol parameter P10.
  • Analysis example 65A shown in the fifth column from the top in Figure 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.
  • each analysis example 61A-65A can be made manually by a service engineer or the like based on the results of the diagnostic measurements, or they can be made automatically by a computer such as the control unit 400 or data analysis terminals 502B, 503B.
  • the control unit 400 can be made to sequentially perform diagnostic measurements related to diagnostic measurement parameters P11-P15, and the cause of the problem in channel 1 can be automatically estimated by the control unit 400 or data analysis terminals 502B, 503B.
  • Figure 6 explains an example of an analysis to identify the cause when a problem occurs in a routine quality control measurement (QC) using ch1 associated with measurement protocol parameter P10 ( Figure 5). However, if a problem occurs in a routine quality control measurement (QC) using ch2 associated with measurement protocol parameter P20 ( Figure 5), the diagnostic measurement parameters P21-P25 ( Figure 5) can be used as appropriate to perform a similar analysis to identify the cause.
  • diagnostic measurement parameters are not limited to the diagnostic measurement parameters P11-P15 and P21-P25 illustrated in Figure 5.
  • the cause of the malfunction is the cleaning process.
  • 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 measurement (QC), and whether the cleaning mechanism for the sample dispensing mechanism is operating normally can be inferred based on whether the measurement result changes to OK or remains NG.
  • 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. If 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.
  • FIG. 7 is a flowchart showing the flow of diagnosis by the analysis unit 100 in this embodiment.
  • the service engineer receives notification of the malfunction from the user (step S701) and confirms the malfunction by receiving the measurement data ( Figure 4) from the control unit 400 (step S702).
  • 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 obtains the measurement data from the data server 501B using the data analysis terminal 502B or 503B.
  • the transmission path L1 for the measurement data output from the analysis unit 100 is shown by the dashed line in Figure 3.
  • the service engineer identifies the reagent name D403 and measurement protocol D409 for the measurement in which the malfunction occurred from the measurement data ( Figure 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 this confirmed data, the service engineer sets diagnostic measurement parameters on the data analysis terminal 502B or 503B (step S703).
  • Figure 7 will use 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 Figure 5.
  • 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 Figure 5.
  • the service engineer transmits the diagnostic measurement parameters P11-P15 set on data analysis terminal 502B or 503B as a measurement request to control unit 400 via network NW (step S704).
  • the set diagnostic measurement parameters are transmitted from data analysis terminal 502B or 503B via network NW and transmitted to control unit 400 via data transfer terminal 500A.
  • the transmission path L2 for these diagnostic measurement parameters is shown by the two-dot chain line in Figure 3.
  • the control unit 400 which has received the diagnostic measurement parameters, displays a permission acquisition screen (e.g., Figure 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 that permission was not obtained. The procedure then returns to step S704, for example. 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 on the GUI makes it easier to schedule diagnostic measurements.
  • a permission acquisition screen e.g., Figure 9
  • the procedure of obtaining permission on the GUI of the operation unit 402 is not required; for example, the service engineer may contact the user by phone or email to obtain user permission in advance.
  • the scheduled time to perform diagnostic measurements is a time that conforms to rules previously set for diagnostic measurements. For example, if there is a predetermined amount of free time 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 is scheduled, such as at night.
  • 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).
  • 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 are the same as those used in the quality control measurement (QC) where the malfunction occurred.
  • step S708 An example of the procedure for narrowing down the cause of the malfunction in step S708 is shown in the flowchart of Figure 8.
  • Figure 8 shows an example of the logic for narrowing down the cause of a malfunction related to the measurement of ch1BF+.
  • diagnostic measurement parameters in this example, diagnostic measurement parameters P11-P15 in Figure 5
  • P11-P15 diagnostic measurement parameters
  • step S703 the measurement results for each diagnostic measurement parameter are confirmed in step S707.
  • the presence or absence of a malfunction in the common unit is determined.
  • step S708A the results of the diagnostic measurement, for example, for diagnostic measurement parameter P11, are analyzed as shown in analysis example 61A of Figure 6 (step S708A). If the measurement result for diagnostic measurement parameter P11 changes to OK, it is presumed that the malfunction is in 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 results of the diagnostic measurement, for example, for diagnostic measurement parameter P12 are analyzed as shown in analysis example 62A of Figure 6 (step S708B). If the measurement result for diagnostic measurement parameter P12 changes to OK, it is presumed that the malfunction is in BF separation unit 106A (step S708b).
  • step S708C If the measurement result for diagnostic measurement parameter P12 remains NG, BF separation unit 106A is excluded from the cause of the malfunction, and the diagnostic measurement result for diagnostic measurement parameter P13 is analyzed, for example, as shown in analysis example 63A in Figure 6 (step S708C). If the measurement result for diagnostic measurement parameter P13 changes to OK, it is assumed that the malfunction is in detection unit 107A (step S708c). If the measurement result for diagnostic measurement parameter P13 remains NG, detection unit 107A is excluded from the cause of the malfunction. The order of steps S708A-S708C can be changed as desired. If the results of steps S708A-S708C show that no abnormalities are found in the channel-specific units, the common unit is diagnosed next.
  • step S708D the results of the diagnostic measurement related to the diagnostic measurement parameter P14 are analyzed as shown in analysis example 64A of Figure 6 (step S708D). If no change is observed in the measurement result related to the diagnostic measurement parameter P14 with increased stirring intensity (NG), considering that the channel-specific units are presumed to be normal, it is suspected that the stirring unit 105 is not operating normally (step S708d). Conversely, if the measurement result related to the diagnostic measurement parameter P14 changes (changes to OK), it is presumed that the stirring unit 105 is operating normally.
  • NG stirring intensity
  • 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 Figure 6 (step S708E). If no change is observed in the measurement result for the diagnostic measurement parameter P15 when the reaction temperature is changed (NG), then 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).
  • step S708f if the measurement result for the 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 the diagnostic measurement parameters P11-P15, and something other than these operating mechanisms (for example, a quality control sample or reagent) is suspected as the cause of the malfunction (step S708f).
  • the evaluation target is separated by diagnostic measurements related to diagnostic measurement parameters P11-P15, and the cause of the malfunction in the analysis unit 100 is identified from the data of each diagnostic measurement.
  • step S708 it is determined whether the cause of the malfunction narrowed down in step S708 lies in the operating mechanism of the analysis unit 100 (channel-specific unit or common unit), or in the quality control sample or reagent (step S709). If the cause of the malfunction is presumed to be the quality control reagent or sample, the service engineer notifies the user via an appropriate communication means such as email or telephone requesting that the reagent or quality control sample be replaced with a new one and that quality control measurements be performed on the operating mechanism under the same conditions as when the malfunction occurred (step S710), and the procedure in Figure 7 is completed.
  • an appropriate communication means such as email or telephone requesting that the reagent or quality control sample be replaced with a new one and that quality control measurements be performed on the operating mechanism under the same conditions as when the malfunction occurred (step S710), and the procedure in Figure 7 is completed.
  • the service engineer prepares replacement parts for the operating mechanism identified as the cause of the malfunction in step S706, visits user facility A, and performs 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 satisfactory and it is confirmed that the malfunction has been resolved, the service engineer ends the procedure in Figure 7. On the other hand, if the malfunction is not resolved even after maintenance, the service engineer performs an additional detailed diagnosis of the analysis unit 100 on-site to identify the cause of the malfunction (step S715).
  • 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.
  • the diagnostic measurement parameters are specialized for identifying the cause of the malfunction, allowing for the isolation of processes that are potential causes 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.
  • a service engineer who receives a notification from a user about 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 and travel 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.
  • the number of times that the user has to travel back and forth between the site and the service center B is reduced, and the time required to deal with problems is also shortened, which reduces the workload of the service engineer and reduces service costs.
  • the downtime of the analysis unit 100 is shortened, improving the user's work efficiency and reducing the workload of the service engineer.
  • a quality control sample storage unit 200 for storing quality control samples 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 will be automatically performed in the analysis unit 100.
  • diagnostic measurement 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.
  • the control unit 400 automatically transmits the results of the diagnostic measurement to a connected computer, such as data server 501B, via the network NW.
  • the destination may be data analysis terminal 502B or 503B.
  • the service engineer can also inquire about the results of the diagnostic measurement from the user via email or telephone, but by automatically notifying the results of the diagnostic measurement in this way via the network NW, the burden on the user of responding to inquiries and the burden on the service engineer of inquiring about the results can be reduced, and the service engineer can smoothly begin work on identifying the cause of the malfunction.
  • 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).
  • CBM condition-based maintenance
  • 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.
  • diagnostic measurements are performed automatically (e.g., periodically) at pre-set times.
  • the automated analysis system 1 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 automatically perform diagnostic measurements based on the received diagnostic measurement parameters according to a predetermined schedule. This allows the diagnostic measurement data to be accumulated, the health of the analysis unit 100 to be periodically confirmed, and abnormalities or signs of abnormalities in the analysis unit 100 to be quickly detected without user notification, allowing for quick response to the abnormalities or prevention of malfunctions.
  • the service engineer determines a schedule for performing diagnostic measurements on the data analysis terminal 502B or 503B based on, for example, information about the analysis unit 100 usage schedule provided by the user (step S901).
  • the diagnostic measurement schedule may be daily, weekly, etc., or may specify at least one day or date and time. If a date and time is 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.
  • the service engineer also sets diagnostic measurement parameters on data analysis terminal 502B or 503B (step S902).
  • the diagnostic measurement parameter to be set can be selected from a plurality of pre-set diagnostic measurement parameters, such as diagnostic measurement parameters P11-P15 and P21-P25, as previously illustrated in FIG. 5. Unlike the first embodiment, this embodiment occurs before a malfunction occurs. Therefore, by setting more diagnostic measurement parameters than in the first embodiment, it is possible to collect status diagnostic data for more operating mechanisms. However, it is not necessary to comprehensively collect data for 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 subset of the operating mechanisms to be monitored.
  • Data analysis terminal 502B or 503B determines whether the measurement date and time set in step S901 has arrived (step S903), and if so, transfers the diagnostic measurement parameters set in step S902 and the measurement request to control unit 400 via transmission path L2 ( Figure 3) (step S904).
  • 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 transmission path L1 (step S905).
  • the processing content of the control unit 400 is the same as in the first embodiment (step S706). At this time, processing equivalent to step S705 in the first embodiment is executed, and the user may be allowed to select whether or not to carry out the measurement request.
  • the service engineer analyzes the diagnostic measurement data (step S906) and determines whether any of the diagnosed parts in the analysis unit 100 have 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 accuracy control positioning.
  • the measured concentration D406 is evaluated in step S907 using criteria different from those in the first embodiment in order to detect signs 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 slightly from the target concentration D407, meaning that although there is no malfunction at this stage, there is a possibility that a malfunction may occur in the near future).
  • 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 the reference range, it can be determined that there is a sign of a malfunction.
  • 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, and 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, if at least one indicator falls outside the set range, it is determined that there is a sign of a malfunction. 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.
  • step S908 the service engineer determines the need for additional diagnostic measurements. Additional diagnostic measurements are performed when the state of the analysis unit 100 cannot be fully determined using the acquired measurement data, when the diagnostic measurement needs to be retried, or when a new diagnostic measurement under different conditions needs to be performed. If it is determined that additional diagnostic measurements are not necessary, the procedure proceeds to step S911. If it is determined that additional diagnostic measurements are necessary, the service engineer sets additional diagnostic measurement parameters and sends them to the control unit 400 (step S909), causing the analysis unit 100 to perform the additional diagnostic measurement (step S910). The service engineer obtains the data from this additional diagnostic measurement via the network NW and takes the additional diagnostic measurement data into consideration to improve the accuracy of the failure sign diagnosis.
  • step S910 the service engineer narrows down the areas that may be showing signs of a malfunction (step S911). This narrowing down process may be performed in the same manner as step S708 in FIG. 7, or may be performed based on the determination of whether the indicator described above in step S907 has deviated from the set range.
  • the service engineer determines whether the cause of the symptom identified in step S911 lies in the operating mechanism of the analysis unit 100 (channel-specific unit or common unit), or in the quality control sample or reagent (step S912). If the cause is suspected 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 Figure 10 ends.
  • the service engineer prepares replacement parts for the operating mechanism identified as the symptom location in step S911 and visits user facility A, the site, to perform maintenance on the analysis unit 100, such as replacing the parts (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 may decide 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).
  • this embodiment is the same as the first embodiment.
  • CBM can be used to prevent malfunctions from occurring in advance. 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 if it were possible 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 when troubleshooting, but this can be achieved according to this embodiment.
  • Third Embodiment 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.
  • 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.
  • the automated 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 prepare them for analysis, a quality control sample storage unit 200 that stores quality control samples, a transport unit 300 that transports sample containers ⁇ 1 and ⁇ 2 ( Figure 1), multiple analysis units 100 (three in Figure 11) arranged along a rack transport line 301' of the transport unit 300, and a control unit 400 that controls the operation of the sample pretreatment system 600, quality control sample storage unit 200, transport unit 300, and analysis unit 100.
  • the sample pretreatment system 600 is composed of multiple processing units 601-609 for pretreatment of samples contained in sample containers ⁇ 1.
  • sample container ⁇ 1 is placed in processing unit 601, and centrifugation to separate serum and clots is performed in processing unit 602.
  • Processing unit 603 performs the uncapping operation to remove the cap from sample container ⁇ 1
  • processing unit 604 performs the dispensing operation to transfer the serum portion from sample container ⁇ 1 to another container.
  • a secondary sample container into which the serum portion has been dispensed can also be sample container ⁇ 1.
  • Processing unit 605 holds sample container ⁇ 1 retrieved from rack transport line 301' via sample transfer unit 305.
  • rack ⁇ 1 Figure 1 carrying sample container ⁇ 1 is transported between processing units 601-609 via a rack transport line (not shown).
  • Sample container ⁇ 1 pretreated by the sample pretreatment system 600 and sample container ⁇ 2 stored in the quality control sample storage unit 200 are transported to the rack transport line 301' by the sample transfer unit 305, and are 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 ⁇ 2 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.
  • the multiple analysis units 100 are each connected to the transport unit 300 via a sample rack buffer unit 306, and sequentially analyze samples in sample containers ⁇ 1 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.
  • 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' is configured to transport racks ⁇ 1 and ⁇ 2 in both directions along a single path, but it may also be configured with two transport lines forming an outbound path and a return path, as in the first embodiment.
  • 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 that identifies 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, as in the first or second embodiment.
  • the present invention can also be applied to an automated analysis system 1 configured so that multiple analysis units 100 share the same quality control sample storage unit 200, and similar effects can be obtained.
  • Fourth Embodiment 12 is a conceptual diagram of a learning model used in an automated analysis system according to a fourth embodiment of the present invention.
  • a service engineer sets diagnostic measurement parameters based on quality control measurement data from the analysis unit 100.
  • 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.
  • diagnostic measurement parameters are set using learning model 120.
  • 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 data analysis terminals 502B and 503B or in a storage device on network NW.
  • a computer such as data analysis terminals 502B and 503B sets diagnostic measurement parameters using learning model 120.
  • Data input to the input layer of the learning model 120 may include, for example, NG data, measurement protocol parameters, assay features, troubleshooting history, alarm history, and units/components that affect measurement.
  • NG data is, for example, data that was determined to be NG in a quality control measurement or calibration measurement previously performed by the analysis unit 100, and includes information such as whether the data was high or low relative to the target concentration range D408, and how far it deviated.
  • Measurement protocol parameters are the measurement protocol parameters applied to the measurement that was determined to be NG, and include information on the 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 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 that was determined to be NG, and corresponds to corrective training 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 the 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, whose status affects the measured concentration D406.
  • the learning model 120 has already learned the relationship between this input data and the diagnostic measurement parameters, 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 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.
  • the learning model 120 can be used, for example, to set diagnostic measurement parameters in step S703 ( Figure 7), steps S902, and S909 ( Figure 10), and to evaluate the measurement data for diagnostic measurements in step S708 ( Figure 7), steps S906, and S911 ( Figure 10). Furthermore, the input of quality control measurement data that has been determined to be NG into 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.
  • This embodiment is similar to the first, second, or third embodiment, except that AI is used to set parameters and evaluate measurement data.
  • Fifth Embodiment 13 to 16 are diagrams 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, 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 already explained in Figures 13 to 16 are given the same reference numerals as in the previously mentioned drawings, and explanations thereof will be omitted as appropriate.
  • This embodiment is similar to the first embodiment except for the configuration of the quality control sample storage unit 200, which will be described below.
  • the quality control sample storage unit 200 of this embodiment can also be applied to the second to fourth embodiments.
  • sample container ⁇ 2 is individually removed from rack ⁇ 2 on the transport unit 300 by the container gripping mechanism 211 and stored individually in the storage unit 219.
  • the quality control sample storage unit 200 of this embodiment differs from the quality control sample storage unit 200 shown in Figure 1.
  • the quality control sample storage unit 200 illustrated in Figures 13-16 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 and 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 sample container ⁇ 2 with a mechanism (not shown) including claws, and move in a planar direction while gripping sample container ⁇ 2 using the X-direction transport mechanism 212 and Y-direction transport mechanism 213.
  • the quality control sample transport unit 217 is used as a place to store empty rack ⁇ required for transporting sample container ⁇ 2 from the storage unit 219.
  • the container gripping mechanism 211 when sample container ⁇ 2 is transported from rack ⁇ 2 on the transport line 301 to the quality control sample storage unit 200, the container gripping mechanism 211 first moves toward rack ⁇ 2 on the transport line 301 using the Y-direction transport mechanism 213 as shown in FIG. 13 and grips one sample container ⁇ 1 loaded on rack ⁇ 2 on the transport line 301 (FIG. 14). The container gripping mechanism 211 then moves in the Y direction using the Y-direction transport mechanism 213 while gripping sample container ⁇ 2, and then moves in the X direction using the X-direction transport mechanism 212 (or while moving), accessing the desired storage position in the storage unit 219 (FIG. 15), and placing sample container ⁇ 2 at that storage position j to complete storage (FIG. 16). The container gripping mechanism 211 can also grip the desired sample container ⁇ 2 in the storage unit 219, remove it from the storage unit 219, and place it on rack ⁇ 2 in the quality control sample transport unit 217.
  • the present invention can be applied even when the storage format of sample container ⁇ 2 in the quality control sample storage unit 200 is different, and the same effects can be achieved.
  • the present invention is not limited to the above-described embodiments and may include various modifications.
  • the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is 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.
  • the shared server 40, etc. can be omitted. It is also possible to combine multiple embodiments.
  • the various configurations, functions, processes, processing means, etc. of the above embodiments may be realized in part or in whole by hardware such as an integrated circuit.
  • the various configurations, functions, etc. above may also be realized by software, with a processor interpreting and executing a program that realizes each function.
  • Information such as programs, tables, and files that realize each function can be stored on various storage media. Examples of various storage media include recording devices such as memory, hard disks, and SSDs (Solid State Drives), as well as flash memory cards and DVDs (Digital Versatile Disks).
  • the information input/output lines e.g., Figures 1 and 2 show those that are considered necessary for explanation, and do not necessarily show all of the lines in the product. In reality, all components may be considered to be interconnected.
  • service center B which performs diagnostic measurements, can arrange for quality control samples (for diagnostic measurements) to be used to identify the cause of abnormalities and store them in advance in the quality control sample storage unit 200 of the automated analysis system 1 at user facility A.
  • diagnostic measurements can be performed using the quality control samples for cause identification arranged by service center B, rather than the quality control samples owned by the user that are used for regular quality control measurements. It is more desirable for the quality control samples for cause identification to be multi-calibrators compatible with multiple analysis items.
  • the measurement protocol parameters include parameters (QC1, QC2 in the example shown) 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.
  • Figure 17 adds QC1 and QC2 to the measurement protocol parameters shown in Figure 5, but omits some parameters such as BF1.
  • the measurement protocol parameters P19 and P29 for routine quality control measurements specify the user's quality control sample (QC1)
  • the diagnostic measurement parameters P11-P15 and P21-P25 specify the quality control sample (QC2) for cause identification described above.
  • Figure 17 shows a simple example 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 default measurement protocol parameters ( Figure 5) that specify the sample dispensing mechanism, etc., it is also possible to adopt an instruction form that separately selects and sets the quality control sample to be used in the measurement.
  • 1...Automated analysis system 100...Analysis unit, 102c...Temperature control mechanism (operating mechanism), 103A, 103B...Sample dispensing mechanism (operating mechanism), 105...Mixing 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, ⁇ 1...Sample container (sample), ⁇ 2...Sample container (sample, quality control sample)

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Abstract

L'invention concerne un système d'analyse automatisé comprenant une unité d'analyse qui analyse un échantillon, et une unité de commande qui commande l'unité d'analyse, l'unité de commande recevant, par l'intermédiaire d'un réseau, un paramètre de mesure de diagnostic qui définit une condition pour une mesure de diagnostic, et commande l'unité d'analyse conformément au paramètre de mesure de diagnostic pour effectuer automatiquement la mesure de diagnostic. Le système d'analyse automatisé comprend, par exemple, une unité de stockage d'échantillon de contrôle qualité qui stocke des échantillons de contrôle qualité, et une unité de transport qui transporte les échantillons de contrôle qualité entre l'unité de stockage d'échantillon de contrôle qualité et l'unité d'analyse, le paramètre de mesure de diagnostic spécifiant, en tant que condition, l'échantillon de contrôle qualité à utiliser dans la mesure de diagnostic ; et l'unité de commande commandant l'unité de stockage d'échantillon de contrôle qualité, l'unité de transport et l'unité d'analyse conformément aux paramètres de mesure de diagnostic, fournissant l'échantillon de contrôle qualité spécifié à l'unité d'analyse, et effectuant la mesure de diagnostic.
PCT/JP2025/010235 2024-04-19 2025-03-17 Système d'analyse automatisé et procédé de diagnostic Pending WO2025220380A1 (fr)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007108136A (ja) * 2005-10-17 2007-04-26 Mitsubishi Kagaku Bio-Clinical Laboratories Inc 分析精度管理システム
JP2014199211A (ja) * 2013-03-29 2014-10-23 シスメックス株式会社 検体分析方法、検体分析システム、コンピュータプログラム、検体測定方法、及び復旧方法
JP2018124171A (ja) * 2017-01-31 2018-08-09 シスメックス株式会社 精度管理方法、精度管理システム、管理装置、分析装置および精度管理異常判定方法
JP2022524808A (ja) * 2019-03-12 2022-05-10 ラジオメーター・メディカル・アー・ペー・エス 生体試料分析装置

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007108136A (ja) * 2005-10-17 2007-04-26 Mitsubishi Kagaku Bio-Clinical Laboratories Inc 分析精度管理システム
JP2014199211A (ja) * 2013-03-29 2014-10-23 シスメックス株式会社 検体分析方法、検体分析システム、コンピュータプログラム、検体測定方法、及び復旧方法
JP2018124171A (ja) * 2017-01-31 2018-08-09 シスメックス株式会社 精度管理方法、精度管理システム、管理装置、分析装置および精度管理異常判定方法
JP2022524808A (ja) * 2019-03-12 2022-05-10 ラジオメーター・メディカル・アー・ペー・エス 生体試料分析装置

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