Information processing system and server system

Abstract

An object of the present application is to provide a technology capable of flexibly and seamlessly using resources that perform data analysis processing regardless of the type of a network such as a public cloud network or an on-premise network. The present disclosure provides an information processing system including a management system that manages: a program for analyzing at least one of light intensity data and fluorescent marker intensity data acquired by irradiating a biological sample with light; and an analysis server for performing at least one of deployment and execution of the program.

Description

Technical Field

[0001] This disclosure relates to information processing systems and server systems, and more specifically, to information processing systems and server systems for analyzing at least one of light intensity data or fluorescent labeling intensity data obtained by irradiating biological samples with light. Background Technology

[0002] For example, particle groups such as cells, microorganisms, and liposomes are labeled with fluorescent dyes, and each particle in the particle group is irradiated with a laser to measure the intensity and / or pattern of fluorescence generated from the excited fluorescent dye, thereby measuring the characteristics of the particles. A representative embodiment of a particle analysis device for performing the measurement is a flow cytometer.

[0003] As a technology related to the processing of data (specifically, light intensity data) acquired by flow cytometry, for example, Patent Document 1 below discloses a "server system comprising: an automatic analysis processing unit that generates output data by analyzing and processing light intensity data or fluorescent labeling intensity data acquired by irradiating a biological sample with light; an analysis result data storage unit that stores the output data generated based on the light intensity data or the fluorescent labeling intensity data; and an interactive analysis processing unit that analyzes the fluorescent labeling intensity data based on analysis commands of the output data output to an output device and outputs analysis result data."

[0004] Reference List

[0005] Patent documents

[0006] Patent Document 1: WO 2022 / 080102 Summary of the Invention

[0007] The problem to be solved by the present invention

[0008] To process data acquired through flow cytometry, cloud services such as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) can be used. Cloud services reduce costs compared to setting up your own servers or software, as fees are based on usage. Specifically, because data analysis according to this technology requires significant computational processing, the initial and operational costs of servers and software become a substantial burden. Using cloud services can significantly reduce these costs.

[0009] On the other hand, because data acquired through flow cytometry can include personal and confidential information, it is necessary to keep the data in a field environment rather than in a cloud environment. However, as mentioned above, the initial and operating costs of servers and software become a significant burden due to the large amount of computational processing required in data analysis according to this technology.

[0010] Therefore, it is preferable to maximize the advantages of both cloud and field environments and to build a system that combines the advantages of both.

[0011] Therefore, the primary objective of this disclosure is to provide a technique that enables flexible and seamless use of resources to perform data analysis processing, regardless of the type of network (such as a public cloud network or a field network). Note that the purpose of this disclosure is not limited to this; for example, it may address any one or more of the problems described below.

[0012] Solution to the problem

[0013] This disclosure provides

[0014] An information processing system includes a management system that manages a program for analyzing at least one of light intensity data and fluorescence labeling intensity data obtained by irradiating a biological sample with light; and an analysis server for executing at least one of: a deployment program and an execution program.

[0015] The management system may include: The resource management unit manages resource information related to the computing resources of the analytics server. The program management unit manages program information about the program, and A connection unit, connected to at least one of a system and apparatus different from the management system.

[0016] The information processing system may further include: an agent unit connected to the analysis server and a connection unit.

[0017] The management system can connect to the primary information communication network. The agent unit can be connected to a second information communication network, and The first information communication network and the second information communication network can be connected to each other via a communication processing unit.

[0018] The first information and communication network can be a public cloud network, and

[0019] The second information and communication network can be a private cloud network or a site-specific network.

[0020] The agent unit can communicate with the connection unit through long polling.

[0021] The agent unit may include: a resource registration unit, which sends the resource information of the analysis server to the resource management unit.

[0022] The agent unit may include: a system building unit, which executes at least one of a deployment program and an execution program on the analytics server.

[0023] The information processing system may further include a data analysis client that analyzes at least one of light intensity data and fluorescent label intensity data.

[0024] The data analysis client can send analytical information about at least one of the light intensity data and fluorescence label intensity data to the connection unit.

[0025] The connection unit can determine, based on at least one of analysis information, resource information, and program information, a program for performing analysis processing and an analysis server for performing at least one of deployment and execution programs, and send information about the determined analysis server and program to the system construction unit.

[0026] The system building unit can, based on the information received related to the analysis server and the program, execute at least one of the programs deployed on the analysis server and the program executed.

[0027] The connection unit can determine, based on at least one of analysis information, resource information, program information, and information about the usage cost of the analysis server, a program for performing analysis processing and an analysis server for performing at least one of deployment and execution programs, and send information about the determined analysis server and program to the system construction unit.

[0028] The information processing system may further include a data segmentation unit that segments at least one of light intensity data and fluorescent marker intensity data based on resource information, and sends the segmented data to different analysis servers.

[0029] The information processing system may further include a data analysis client that analyzes at least one of light intensity data and fluorescent label intensity data.

[0030] The connection unit can send information about the analysis server used to execute at least one of the deployment and execution procedures to the data analysis client.

[0031] The data analysis client can accept the designation of at least one of the analysis server and the program, and send information about at least one of the analysis server and the program to the connection unit.

[0032] Furthermore, this disclosure provides a server system, including: The system building unit executes at least one of a deployment procedure and an execution procedure, the procedure being used to analyze at least one of light intensity data and fluorescence labeling intensity data obtained by irradiating biological samples with light on an analysis server, wherein... The at least one of the program and analysis server is determined based on a database containing information about at least one of the program and analysis server.

[0033] According to this disclosure, resources for performing data analytics processing can be used flexibly and seamlessly, regardless of the type of network, such as a public cloud network or a site-specific network. It should be noted that the effects described herein are not necessarily limiting and may be any of the effects described in this disclosure. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the configuration of a flow cytometer.

[0035] Figure 2 This is a diagram illustrating an experimental procedure embodiment when the present technology is applied to flow cytometry.

[0036] Figure 3 This is a diagram illustrating an embodiment of the gate arrangement.

[0037] Figure 4 It is a diagram used to describe surface markings.

[0038] Figure 5 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0039] Figure 6 This is an embodiment of a database managed by a resource management unit 71 according to an implementation of the present technology.

[0040] Figure 7 This is an embodiment of a database managed by a program management unit 72 according to an implementation of the present technology.

[0041] Figure 8 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology.

[0042] Figure 9 This is a schematic diagram illustrating an embodiment of a long polling processing flow.

[0043] Figure 10 This is a block diagram illustrating a configuration embodiment of an analysis server 101 according to an implementation of the present technology.

[0044] Figure 11 This is a block diagram illustrating a configuration embodiment of a data analysis client terminal 20 according to an implementation of the present technology.

[0045] Figure 12 This is a block diagram illustrating a configuration embodiment of a data analysis client terminal 20 according to an implementation of the present technology.

[0046] Figure 13This is a diagram illustrating an embodiment of a window from a data analysis client terminal 20 to an output device according to an implementation of the present technology.

[0047] Figure 14 This is a block diagram illustrating a configuration embodiment of a data acquisition client 30 according to an implementation of the present technology.

[0048] Figure 15 This is a schematic diagram illustrating a configuration embodiment of a biological sample analysis device 40 according to an embodiment of the present technology.

[0049] Figure 16 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0050] Figure 17 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology.

[0051] Figure 18 This is a diagram illustrating an embodiment of a window from a data analysis client terminal 20 to an output device according to an implementation of the present technology.

[0052] Figure 19 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0053] Figure 20 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology.

[0054] Figure 21 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0055] Figure 22 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology. Detailed Implementation

[0056] Preferred embodiments for carrying out this disclosure will be described below. It should be noted that the embodiments described below are representative embodiments of this disclosure, and the scope of this disclosure is not limited to these embodiments. It should be noted that this disclosure will be described in the following order.

[0057] 1. The first embodiment of this technology (Example 1 of an information processing system)

[0058] (1) Description of relevant technologies

[0059] (2) Overview of the information processing system

[0060] (3) Management System

[0061] (3-1) Resource Management Unit

[0062] (3-2) Program Management Unit

[0063] (3-3) Connection Unit

[0064] (4) Server system

[0065] (4-1) Agent Unit

[0066] (4-2) Client-server communication

[0067] (4-3) Analyze the server

[0068] (5) Data analysis client

[0069] (6) Data acquisition client terminal

[0070] (7) Biological sample analysis device

[0071] (7-1) Biological samples

[0072] (7-2) Flow channel

[0073] (7-3) Light Illumination Unit

[0074] (7-4) Detection Unit

[0075] (7-5) Information Processing Unit

[0076] (7-6) Sorting Unit

[0077] 2. Second embodiment of this technology (Example 2 of the information processing system)

[0078] 3. The third embodiment of this technology (Example 3 of the information processing system)

[0079] 4. The fourth embodiment of this technology (Example 4 of the information processing system)

[0080] 5. The fifth embodiment of this technology (Example 5 of the information processing system)

[0081] 6. The sixth embodiment of this technology (Example 6 of the information processing system)

[0082] 7. Seventh Implementation of this Technology (Server System Example)

[0083] [1. First embodiment of this technology (Example 1 of an information processing system)]

[0084] [(1) Description of relevant technologies]

[0085] For example, from the perspective of the optical system for fluorescence measurement, flow cytometry can be roughly classified into filter type and spectral type. To extract only the target optical information from the target fluorescent dye, filter-type flow cytometry can employ techniques such as... Figure 1 The configuration shown in Figure 1. Specifically, the light generated by the irradiation of the particles is branched into multiple beams by a wavelength separation unit (DM) such as a dichroic mirror, passed through different filters, and each branch beam is measured by multiple detectors (e.g., photomultiplier tubes, PMTs). That is, in a filter-type flow cytometer, fluorescence detection of multiple colors is performed by using a detector corresponding to each fluorescent dye to perform fluorescence detection for each wavelength band corresponding to each fluorescent dye. In this case, when using multiple fluorescent dyes with close fluorescence wavelengths, fluorescence correction processing can be performed to calculate a more accurate fluorescence amount.

[0086] On the other hand, spectral flow cytometry analyzes the fluorescence level of each particle by performing deconvolution (unmixing) on ​​fluorescence data obtained by detecting light generated when particles are illuminated, based on the spectral information of the fluorescent dye used for staining. For example... Figure 1 As shown in Figure 2, spectral flow cytometers use prism dispersive optics with P-dispersive fluorescence. Furthermore, instead of multiple photodetectors in filter-type flow cytometers, spectral flow cytometers include array-type detectors (e.g., array-type photomultiplier tubes, PMTs, etc.) for detecting dispersed fluorescence. Compared to filter-type flow cytometers, spectral flow cytometers are less susceptible to fluorescence leakage and are suitable for analysis using a variety of fluorescent dyes.

[0087] In recent years, to advance comprehensive interpretation in basic and clinical medicine, multicolor analysis using multiple fluorescent dyes has become widespread in flow cytometry. The number of fluorescent dyes used in single multicolor analyses tends to increase. As mentioned above, when a large number of fluorescent dyes are used in a single measurement, in filter-type flow cytometers, fluorescence leakage from fluorescent dyes other than the target dye leaks into various detectors, reducing analytical accuracy. In cases with a large number of colors, the problem of fluorescence leakage can be solved by using spectral flow cytometry.

[0088] The following will refer to Figure 2 Examples of experimental procedures using flow cytometry are described.

[0089] The experimental procedure using flow cytometry is generally divided into experimental planning steps for examining the cells used as experimental subjects. Figure 2 The "1: Plan" in the document describes the method for detecting cells, as well as the preparation steps for preparing fluorescently labeled antibody reagents and the actual staining sample preparation procedures. Figure 2The "2: Preparation" step in the FCM measurement procedure involves preparing cells in a state suitable for measurement and measuring the fluorescence intensity of each stained cell using flow cytometry. Figure 2 The "3: FCM" in the text refers to the data analysis steps involving various data processing to obtain the desired analytical results from the data recorded via FCM measurements. Figure 2 (See "4: Data Analysis" in the document). Then, these steps can be repeated as needed.

[0090] In the experimental planning steps, firstly, based on flow cytometry expression, it is determined which molecules (e.g., antigens, cytokines, etc.) will be used as the basis for identifying the microparticles (primarily cells) to be detected using flow cytometry. That is, the markers used to detect the microparticles are determined. This can be done, for example, based on information such as past experimental results and publications. Next, it is examined which fluorescent dyes will be used to detect the markers. For example, based on information such as the number of markers to be detected simultaneously, the specifications of the available FCM apparatus, commercially available fluorescently labeled reagents, and the spectrum, intensity, price, and delivery date of the fluorescent dyes, the combination of fluorescently labeled antibody reagents necessary for the actual experiment is determined. The method for determining this reagent combination is often referred to as group design in FCM.

[0091] In the sample preparation step, the experimental subjects are first prepared to be in a state suitable for FCM measurement. For example, cell isolation and purification can be performed. For example, for immune cells derived from blood, red blood cells are removed from the blood by hemolysis and density gradient centrifugation, and white blood cells are extracted. The extracted cell population is stained with fluorescently labeled antibodies.

[0092] In the FCM measurement step, when performing optical analysis on particles, firstly, excitation light is emitted from the light source of the flow cytometer's illumination unit, and the excitation light is used to illuminate the particles flowing in the flow channel. Next, the fluorescence emitted from the particles is detected by the flow cytometer's detection unit. Specifically, light with a specific wavelength (target fluorescence) is separated from the light emitted from the particles using only a dichroic mirror, bandpass filter, etc., and the separated light is detected by a detector such as a PMT. At this time, for example, the fluorescence is dispersed using a prism, diffraction grating, etc., and a detector such as a 32-channel PMT detects light with different wavelengths in each channel. Using this configuration, the spectral information of the detected light (fluorescence) can be easily obtained.

[0093] Flow cytometers can record fluorescence information for each particle acquired via FCM measurement, along with scattered light information, time information, and location information in addition to fluorescence information. The recording function is primarily performed by a computer using memory or disk. In normal cell analysis, because thousands to millions of particles are analyzed under a single experimental condition, it is necessary to record multiple pieces of information in an organized manner for each experimental condition.

[0094] In the data analysis step, the light intensity data detected in each wavelength region during the FCM measurement step are equivalently quantified using a computer, and the fluorescence amount (intensity) of each fluorescent dye used is obtained. For this analysis, a calibration method is used, employing a standard calculated from the experimental data. The standard is calculated through statistical processing of two types of measurement data for particles stained with only one fluorescent dye and measurement data for unstained particles. The calculated fluorescence amount can be recorded along with information such as the name of the fluorescent molecule, measurement date, and particle type in a data recording unit set up in the computer. The fluorescence amount (fluorescence spectral data) of the sample estimated through data analysis is retained and displayed for the purpose of analysis, and the fluorescence distribution of the particles is analyzed.

[0095] For example, to analyze fluorescence distribution, gating is typically performed, which allows calculation of the proportion of target cells in the sample. For example, as... Figure 3 As shown, by generating two-dimensional plots of forward scattering (FSC) and side scattering (SSC) and selecting a predetermined range from these plots, the ratio of monocytes to lymphocytes among the blood cells contained in PBMCs can be specified. Furthermore, by setting and expanding the gating of lymphocytes expressing predetermined surface markers, the ratios of B cells, T cells, and NK cells in lymphocytes can be calculated. Additionally, the ratios of memory B cells to other B cells, cytotoxic T cells to helper T cells, and primitive T cells to memory T cells can also be specified. It is known that the surface markers expressed by each cell type vary depending on the cell type, for example, such as... Figure 4 As shown. Therefore, by appropriately selecting antibodies that bind to surface markers and fluorescent dyes that label the antibodies, and by analyzing them using flow cytometry, cells in the sample can be examined.

[0096] The information processing system and components included in the system according to this disclosure can be used for analysis in the data analysis step.

[0097] [(2) Overview of the information processing system]

[0098] In recent years, with advancements in computer and reagent technologies, the number of parameters that can be simultaneously measured using flow cytometry has increased dramatically. Therefore, relative to the increased computational resources required for measurement and analysis, there is a growing trend towards using cloud platforms provided by cloud providers to maintain data and perform analyses in the cloud environment.

[0099] When using cloud services (such as cloud platforms or SaaS), it becomes unnecessary to introduce and build high-performance servers or workstations for analytics that are typically required when performing analytics in a field environment. The advantage of this arrangement is that it eliminates the time and financial costs associated with operational issues such as hardware failures, premature aging, and storage exhaustion.

[0100] On the other hand, because the measurement data obtained by flow cytometry is highly confidential, some companies, research institutions and users prefer to retain and analyze the measurement data in a field environment rather than using a cloud environment, mainly for security reasons.

[0101] As mentioned above, both cloud and on-site environments are required. Therefore, it is preferable to implement a system that supports hybrid configurations combining cloud and on-site environments, thereby allowing for flexible construction of the analysis execution environment and the execution of analyses according to user needs.

[0102] Therefore, this technology provides an information processing system, including: a management system for managing a program for analyzing at least one of light intensity data and fluorescence labeling intensity data obtained by irradiating a biological sample with light; and an analysis server for executing at least one of a deployment program and an execution program.

[0103] Reference Figure 5 This describes a configuration embodiment of an information processing system according to an implementation of the present technology. Figure 5 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0104] like Figure 5 As shown, the information processing system 100 includes a management system 70. The management system 70 manages programs for analyzing at least one of light intensity data and fluorescence labeling intensity data obtained by irradiating a biological sample with light, and an analysis server 101 for executing at least one of a deployment program and an execution program. Note that in this configuration embodiment, one analysis server 101 is shown, but multiple analysis servers 101 may exist. Additionally, an analysis server system may include multiple analysis servers 101.

[0105] Through the management system 70, the program and analytics server 101 included in the server system 10 can be centrally managed, allowing program deployment and other operations regardless of whether the program and analytics server 101 is located in a cloud environment or an on-premises environment. Specific configuration embodiments of the management system 70 will be described later.

[0106] The information processing system 100 also includes a biological sample analysis device 40, a data acquisition client 30, a server system 10, and a data analysis client 20. For example, the biological sample analysis device 40 may be the flow cytometer described above. The data acquisition client 30 acquires light intensity data of the biological sample from the biological sample analysis device 40. The server system 10 primarily analyzes at least one of the light intensity data and the fluorescence labeling intensity data. The data analysis client 20 further analyzes at least one of the light intensity data and the fluorescence labeling intensity data by sending analysis requests to the server system 10 and displaying the analysis results from the server system 10.

[0107] The management system 70 and the server system 10 can be connected to each other via the information communication network 50. Each of the data analysis client terminal 20, the data acquisition client terminal 30, and the server system 10 can be connected, for example, via a wired or wireless connection, or via the information communication network. The biological sample analysis device 40 can be connected, for example, via a wired or wireless connection to the data acquisition client 30.

[0108] [(3) Management System]

[0109] The management system 70 manages a program for analyzing at least one of light intensity data and fluorescence labeling intensity data obtained by irradiating biological samples with light, and an analysis server 101 for executing at least one of deployment and execution programs. The program and analysis server 101 may be included in the server system 10 described above.

[0110] Note that the management system 70 can be a centralized management system that centrally manages programs and data on a specific server, or it can be a system using distributed ledger technology (blockchain technology) that utilizes multiple nodes (computers) participating in network recording and data sharing. In the following description, the management system 70 will be described as an embodiment of a centralized management system. The management system 70 includes a resource management unit 71, a program management unit 72, and a connection unit 73.

[0111] [(3-1) Resource Management Unit]

[0112] Resource management unit 71 is a service that manages and analyzes resource information related to the computing resources of server 101. This resource information can be managed using, for example, a database. (See reference...) Figure 6 Describe the database. Figure 6This is an embodiment of a database managed by a resource management unit 71 according to an implementation of the present technology.

[0113] like Figure 6 As shown, the database includes columns such as "Server ID", "Group ID", "Server Name", "Server URL", "Server Type", "Server Specification", "Connection Status", and "Usage Status".

[0114] The "Server ID" is an ID used to uniquely identify the analysis server 101 registered in the server system 10.

[0115] "Group ID" is an ID used to identify the group to which a user with the corresponding analytics server 101 belongs. For example, a group ID can be assigned to each user based on the company they belong to.

[0116] "Server Name" is the name of analysis server 101.

[0117] The "server URL" is information indicating the location of the analysis server 101 on the information communication network.

[0118] "Server Type" is information used to specify the environment in which the resources of the analysis server 101 reside. Examples of "Server Type" include "Cloud on Demand", "Cloud Dedicated", and "On-site".

[0119] "Cloud video-on-demand" refers to a form of computing resource allocation where the analytics server 101 exists in a public cloud network, and users reserve computing resources on demand. On-demand computing resource allocation means that computing resources are allocated only when needed, rather than continuously.

[0120] "Cloud-dedicated" means that the analytics server 101 exists in a public cloud network and the user continuously retains computing resources.

[0121] "Field" refers to the form in which the analysis server 101 exists within the field network.

[0122] "Server Specifications" refers to information about the specifications of Server 101.

[0123] "Connection Status" indicates whether the data analysis client terminal 20 is connected to the analysis server 101. "Online" indicates that the data analysis client terminal 20 is connected to the analysis server 101.

[0124] "Usage Status" indicates whether a user is using analytics server 101. "In Use" indicates that a specific user is using analytics server 101. "Idle" indicates that all users are not using analytics server 101.

[0125] Resource management unit 71 manages this resource information, allowing users to flexibly specify computing resources that meet their needs. For example, an analysis execution request from data analysis client terminal 20 may include information such as "analysis will be performed using an analysis server owned by a user belonging to user group 100, operating within the field network, currently unused, and having a specification higher than a certain level."

[0126] Note that the resource management unit 71 can manage not only the resources of the analytics server 101, but also resources related to data storage and databases. In that case, possible approaches include building multiple resource management tables for each type of resource to be managed, or extending existing tables to manage multiple resource types. This enables flexible system configurations, such as building data storage within a field network and performing analytical processing on the analytics server 101 within a public cloud network.

[0127] The data analysis client terminal 20 only needs to connect to the analysis server 101 returned from the management system 70 as the connection destination. Therefore, the data analysis client terminal 20 can perform analysis processing without knowing the physical location of the computing resources.

[0128] [(3-2) Program Management Unit]

[0129] The program management unit 72 is a service for managing program information related to the program to be analyzed. This program information can be managed using, for example, a database. (See reference...) Figure 7 Describe the database. Figure 7 This is an embodiment of a database managed by a program management unit 72 according to an implementation of the present technology.

[0130] like Figure 7 As shown, the database includes columns such as "Program Version", "I / F Version", "Program URL", and "Tag".

[0131] "Program Version" refers to information about the program version. It is assumed that each program version is uniquely managed. Program versions can be managed in single-digit increments or in a multi-digit versioning format that includes major, minor, and maintenance versions.

[0132] "I / F version" is information used to manage the version of the interface between the server and the client. For example, "I / F version" can be the version of an application programming interface (API).

[0133] A "program URL" is information indicating the location where a program is stored on an information communication network. For example, an agent unit, described later, can obtain a program based on this information and deploy the program on a predetermined analysis server 101.

[0134] "Labels" are information that indicates the attributes or characteristics of a program. For example, "latest" means that the program is the latest version.

[0135] The program management unit 72 manages such program information, thereby enabling a flexible system architecture. For example, an analysis execution request from the data analysis client terminal 20 may include information such as "execute the analysis using the latest program among the programs with a predetermined I / F version".

[0136] Note that the program management unit 72 can manage multiple programs based on the analysis content. In this case, multiple databases can be built for managing the programs, or the databases can be expanded.

[0137] [(3-3) Connection Unit]

[0138] The connection unit 73 is connected to at least one of a system or device different from the management system 70. Figure 5 In the configuration embodiment shown, the connection unit 73 is connected to each of the data acquisition client 30, the server system 10, and the data analysis client 20.

[0139] The connection unit 73 receives analysis execution requests from the data analysis client terminal 20, selects and reserves a suitable analysis server 101, selects a suitable program, and deploys the program on the analysis server 101. Furthermore, the connection unit 73 notifies the data analysis client terminal 20 of the connection destination of the analysis server 101. These operations are implemented in cooperation with the resource management unit 71, the program management unit, and the agent unit 80, which will be described later.

[0140] For example, the connection unit 73 can select an analysis server 101 with appropriate computing performance based on the size of the target data (the number of events and the number of dimensions).

[0141] [(4) Server System]

[0142] Server system 10 includes agent unit 80 and analysis server 101.

[0143] [(4-1) Agent Unit]

[0144] Each of the management system 70 and the server system 10 can be connected to a different information communication network. The management system 70 can be connected to a first information communication network, and the server system 10 can be connected to a second information communication network. The first and second information communication networks can be connected to each other via the communication processing unit 60.

[0145] The communication processing unit 60 can be, for example, a router. Because a router has a firewall function that blocks specific communications, it can protect the server system 10 from unauthorized access, malware, etc.

[0146] The management system 70, which centrally manages servers and programs, is preferably connected to a public cloud network. That is, the first information communication network can be a public cloud network. Therefore, the management system 70 can be accessed from the server system 10.

[0147] On the other hand, primarily for security reasons, server system 10 can be connected to a field network. That is, the second information communication network can be a private cloud network or a field network. In this case, although communication from server system 10 to management system 70 is possible, communication processing unit 60 prevents communication from management system 70 to server system 10.

[0148] Therefore, preferably, the program used as the starting point for communication to the management system 70 exists in the field network. The information processing system according to an embodiment of the present technology further includes a proxy unit 80 and a connection unit 73 connected to the analysis server 101. The proxy unit 80 is connected to a second information communication network. The proxy unit 80 has a crucial function for coordination between the management system 70 and the analysis server 101. The presence of the proxy unit 80 allows management of the analysis server 101 regardless of whether the analysis server 101 is connected to a public cloud network or a field network.

[0149] The agent unit 80 can be a resident program installed on any computer connected to the second information communication network. The agent unit 80 includes a resource registration unit 81. The resource registration unit 81 sends the resource information of the analysis server 101 to the resource management unit 71 via the connection unit 73 included in the management system 70. Using this configuration, the resource management unit 71 of the management system 70 can manage the resource information of the analysis server 101, for example, located within a field network.

[0150] Furthermore, agent unit 80 includes system building unit 82. System building unit 82 executes at least one of the programs to be analyzed that are deployed or executed on analysis server 101. (See reference...) Figure 8 Describe the processing flow at this point. Figure 8 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology.

[0151] like Figure 8 As shown, firstly, in step S101, the data analysis client terminal 20 sends analysis information regarding the analysis processing of at least one of the light intensity data and the fluorescence marker intensity data to the connection unit 73 in the analysis execution request.

[0152] Next, in step S102, the connection unit 73 determines, based on at least one of analysis information, resource information, and program information, a program for performing analysis processing and an analysis server 101 for performing at least one of a deployment program and an execution program. Program information regarding the program is managed by the program management unit 72. Resource information regarding the analysis server 101 is managed by the resource management unit 71.

[0153] Next, in step S103, the connection unit 73 sends information about the determined analysis server 101 and program to the system construction unit 82.

[0154] Next, in step S104, the system building unit 82 accesses the computer holding the program based on information about the program in order to obtain the program.

[0155] Next, in step S105, the system building unit 82 deploys the acquired program on the predetermined analysis server 101 based on information related to the analysis server 101. Thus, the server system 10 is constructed.

[0156] Next, in step S106, the connection unit 73 sends information for connecting to the analysis server 101 to the data analysis client terminal 20. That is, the connection unit 73 sends information about the analysis server 101 used to perform at least one of the deployment or execution programs to the data analysis client terminal 20.

[0157] Finally, in step S107, the data analysis client terminal 20 connects to the analysis server 101 based on information used to connect to the analysis server 101. Through this arrangement, the data analysis client terminal 20 can analyze at least one of light intensity data and fluorescence marker intensity data.

[0158] It should be noted that the data in the analysis server 101 can be deleted when the analysis process is complete. This prevents unauthorized access to the data.

[0159] In one embodiment of the processing flow, system building unit 82 deploys a program in analysis server 101, but this program may already be deployed. For example, different programs may already be deployed on each of the multiple analysis servers 101. In this case, system building unit 82 can execute a predefined program from the different programs. Using this configuration, the time for deploying programs can be reduced when an analysis execution request exists.

[0160] System building unit 82 can install programs not only on computers connected to the field network but also on computers connected to the public cloud network. Using this configuration, the analysis server 101 connected to the public cloud network can also be registered in the management system 70. In this case, while reserving computing resources on demand in response to analysis execution requests from the data analysis client terminal 20, it is generally possible to specify the programs that can be executed when the analysis server 101 is activated.

[0161] [(4-2) Client-server communication]

[0162] The communication between the management system 70 and the agent unit 80 is client-server communication between the management system 70 as a server and the agent unit 80 as a client. In client-server communication, typically, the server returns a response in response to a request from the client. For example, in the resource registration process described above, the agent unit 80, acting as a client, sends a request to the management system 70, and the management system 70 responds to the request by performing the necessary processing.

[0163] On the other hand, there are also situations where the management system 70, acting as a server, needs to communicate with the client from the starting point. In this case, communication is performed from the management system 70 in the public cloud network to the agent unit 80 in the field network. Therefore, considering the presence of the communication processing unit 60, there are technical problems in the implementation method.

[0164] Typically, communication between a server and a client originates from the server and is called server push, and several technologies exist, such as polling, long polling (COMET), and WebSocket. WebSocket is a technology capable of bidirectional communication, but it also requires communication outside the framework of the HTTP (HTTPS) protocol. Therefore, considering the existence of HTTP proxies, connectivity issues arise.

[0165] In normal client-server communication, when a client requests data from a server, the server returns the data accordingly. However, if the server always needs to send data, the client needs to periodically request data from the server. This is called polling.

[0166] Polling has the advantage of always receiving data from the server, but it also has the disadvantage of increasing the load on the server. Furthermore, it consumes bandwidth because network communication occurs every time a client sends a data request to the server.

[0167] Long polling can overcome these shortcomings of traditional polling. Long polling is a client-server communication method where the server periodically sends data to the client. Long polling is suitable for communication between the system 70 and the agent unit 80.

[0168] Reference Figure 9 Describe long polling. Figure 9 This is a schematic diagram illustrating an embodiment of a long polling processing flow. For example... Figure 9 As shown, in long polling, the client (the agent unit 80 in this embodiment) sends an HTTP request to the server (the management system 70 in this embodiment) and then waits for data from the server. When data is updated, the server sends the data to the client.

[0169] Long polling offers advantages such as reduced server load and bandwidth savings. Furthermore, the waiting time from when the server receives data to be notified to the client to when the server returns a response to the client is shorter in long polling than in traditional polling. Moreover, unlike WebSocket, long polling is suitable for communication between the system 70 and the proxy unit 80 because communication is performed solely via the HTTP (HTTPS) protocol. Therefore, the proxy unit 80 preferably communicates with the connection unit 73 via long polling. Note that the communication method is not limited to long polling.

[0170] An embodiment of the scenario where a request is pushed from the management system 70 to the agent unit 80 includes processing when an analysis execution request from the data analysis client terminal 20 is used with the analysis server 101. The analysis execution request received by the connection unit 73 of the management system 70 is notified to the appropriate analysis server 101 via a server push based on the content of the request. The agent unit 80 obtains the necessary programs according to the content of the request, deploys the programs on the analysis server 101, performs automatic analysis processing or initiates interactive analysis processing, and waits for a connection from the data analysis client terminal 20. The data analysis client terminal 20 connects to the connection destination of the analysis server 101 returned by the connection unit 73 and performs automatic analysis result acquisition and interactive analysis processing.

[0171] [(4-3) Analyze the server]

[0172] Analysis server 101 performs analysis processing in response to requests from data analysis client terminal 20. Because the amount of data from the biological sample analysis device is large and there are limitations on the analysis in data analysis client terminal 20, it is preferable to perform the analysis in analysis server 101.

[0173] The analysis server 101 has multiple services. In this configuration embodiment, the analysis server 101 includes services such as an automatic analysis processing unit 11, an interactive analysis processing unit 12, an output data generation unit 13, a connection unit 14, an optical data storage unit 15, an analysis result data storage unit 16, and a database 17. These services can be implemented by the agent unit 80 of the deployment program.

[0174] In one embodiment of this disclosure, the automated analysis and processing unit 11 can calculate fluorescent label intensity data from light intensity data acquired by illuminating a biological sample. The light intensity data can be light intensity data sent from the data acquisition client 30 to the analysis server 101. The light intensity data can be stored in the optical data storage unit 15. The automated analysis and processing unit 11 can acquire the light intensity data from the optical data storage unit 15.

[0175] The automatic analysis and processing unit 11 performs processes such as fluorescence correction or unmixing on the light intensity data to calculate the fluorescence labeling intensity data. Unmixing is also known as fluorescence separation.

[0176] The automatic analysis and processing unit 11 preferably performs demixing processing using spectral reference data. The spectral reference data used in the demixing process includes spectral data of fluorescence generated when the fluorescent dye of the labeled particles is irradiated with a predetermined excitation light. The spectral reference data used in the demixing process may include spectral data of fluorescence generated when the fluorescent dye of the labeled particles is irradiated with light having a predetermined wavelength and spectral data of fluorescence generated when the fluorescent dye of the labeled particles is irradiated with light having a different wavelength from the predetermined wavelength.

[0177] The spectral reference data can be pre-stored in any storage unit or database within the analysis server 101, and for example, in database 17. For instance, the automatic analysis processing unit 11 can retrieve the spectral reference data from database 17 and perform demixing processing using the retrieved spectral reference data.

[0178] The automatic analysis and processing unit 11 analyzes and processes the fluorescence label intensity data. The automatic analysis and processing unit 11 generates analysis result data through the analysis and processing. Output data can be generated based on the analysis result data. The output data is sent to the data analysis client terminal 20, and then the data analysis client terminal 20 causes an output device to output the output data. The output device can be, for example, a display device. The output device can be configured to allow the user to input analysis commands, which will be described later.

[0179] It should be noted that in this specification, "analysis result data" refers to the data generated through analysis processing in the analysis server 101. "Output data" is a part of the analysis result data, and specifically, it is the data used to output the analysis results in the data analysis client terminal 20.

[0180] Preferably, in response to light intensity data stored in the optical data storage unit 15, the automatic analysis processing unit 11 performs processing to calculate fluorescent label intensity data from the light intensity data. Then, the automatic analysis processing unit 11 can analyze the fluorescent label intensity data to generate analysis result data. Additionally, the automatic analysis processing unit 11 can generate output data based on the analysis result data. For example, the automatic analysis processing unit 11 can start automatic analysis processing in response to light intensity data being stored in the optical data storage unit 15. That is, the automatic analysis processing unit 11 can perform event-driven analysis processing triggered by the memory.

[0181] The automatic analysis and processing unit 11 reserves computing resources for automatic analysis and processing in response to the light intensity data being stored in the optical data storage unit 15. That is, the automatic analysis and processing unit 11 can regard the memory as receiving an analysis start command and responding to receiving and allocating calculations in the analysis server 101. The automatic analysis and processing unit 11 can perform calculation processing of fluorescence label intensity data, analysis processing of fluorescence label intensity data, and processing of output data generated from analysis result data by using the reserved computing resources.

[0182] The interactive analysis processing unit 12 can analyze the fluorescence label intensity data based on the analysis command of the output data to the output device to generate analysis result data. The output data can be the output data generated by the automatic analysis processing unit 11, or it can be the output data acquired or generated by the output data generation unit 13, which will be described later.

[0183] The interactive analysis processing unit 12 can perform processing to calculate fluorescent label intensity data from light intensity data. Then, it can analyze the calculated fluorescent label intensity data based on analysis commands to generate analysis result data. The interactive analysis processing unit 12 can then generate output data from the generated analysis result data.

[0184] In response to receiving an analysis start command, the interactive analysis processing unit 12 may reserve computing resources for processing performed by itself. After reserving computing resources, the interactive analysis processing unit 12 waits until an analysis command is sent from the data analysis client terminal 20.

[0185] As described above, the automatic analysis processing unit 11 can reserve computing resources for processing by the automatic analysis processing unit in response to receiving an analysis start command, and the interactive analysis processing unit 12 can also reserve computing resources for processing by the interactive analysis processing unit 12 in response to receiving an analysis start command. Therefore, in this disclosure, the processing of the automatic analysis processing unit and the processing of the interactive analysis processing unit can be performed on different computing resources.

[0186] In response to receiving an analysis command sent from the data analysis client terminal 20, the interactive analysis processing unit 12 can perform calculation processing of fluorescence label intensity data, analysis processing of fluorescence label intensity data, and processing of output data generated from the analysis result data. These processes can be event-driven analysis processes triggered by the receipt of the analysis command. That is, the interactive analysis processing according to this technology can be event-driven analysis processing.

[0187] The interactive analysis and processing unit 12 can perform the calculation and processing of fluorescent label intensity data, the analysis and processing of fluorescent label intensity data, and the processing of output data from the analysis results data in the same manner as the automatic analysis and processing unit 11.

[0188] The connection unit 14 is a functional element for executing remote procedure calls (RPCs) in the interactive processing between the analysis server 101 (particularly the interactive analysis processing unit 12) and the data analysis client terminal 20. For example, the connection unit 14 causes the analysis server 101 to execute analysis commands input to the data analysis client terminal 20.

[0189] The output data generation unit 13 generates output data based on the analysis result data stored in the analysis result data storage unit 16. Then, the output data generation unit 13 sends the output data to the data analysis client terminal 20.

[0190] The output data generation unit 13 requires relatively small computing resources. Therefore, the operating cost of the analysis server 101 can be reduced.

[0191] The processing of the output data generation unit 13 can be performed by a continuously operating virtual server in the analysis server 101. Because the virtual server operates continuously, output data acquisition processing can be performed at high speed without the waiting time associated with server activation. Furthermore, the output data generation unit 13 can be configured in a serverless architecture.

[0192] The optical data storage unit 15 stores light intensity data and / or fluorescent label intensity data. The optical data storage unit 15 may include two units: a light intensity data storage unit for storing light intensity data and a fluorescent label intensity data storage unit for storing fluorescent label intensity data.

[0193] The analysis result data storage unit 16 stores the analysis result data generated by the automatic analysis processing unit 11 based on the fluorescence label intensity data and / or the analysis result data generated by the interactive analysis processing unit 12 based on the fluorescence label intensity data. Additionally, the analysis result data storage unit 16 stores the output data generated from these analysis result data.

[0194] The analysis server 101 can be configured as a single server unit or a system comprising multiple server units. These multiple server units can reside in a single data center, or they can be distributed and deployed across multiple data centers located in different places or countries.

[0195] Reference Figure 10 This describes an example of the hardware configuration of the analysis server 101. Figure 10 This is a block diagram illustrating a configuration embodiment of an analysis server 101 according to an implementation of the present technology. Figure 10 As shown, the analysis server 101 includes a central processing unit (CPU) 1001, RAM 1002, and ROM 1003. The CPU 1001, RAM 1002, and ROM 1003 are interconnected via a bus 1004. An input / output interface 1005 is further connected to the bus 1004.

[0196] The communication device 1006, storage device 1007, driver 1008, output unit 1009, and input unit 1010 are connected to the input / output interface 1005.

[0197] Communication device 1006 connects analysis server 101 to network 1011 via wired or wireless means. Communication device 1006 enables analysis server 101 to acquire various types of data (e.g., image data) via network 1011. The acquired data can be stored, for example, in storage device 1007. The type of communication device 1006 can be appropriately selected by those skilled in the art.

[0198] Storage device 1007 may store an operating system, programs for enabling analysis server 101 to implement the information processing method according to the present disclosure, various other programs, image data, various data used in the information processing method according to the present disclosure, and various other data. The operating system may be, for example, a UNIX-based OS, particularly LINUX (registered trademark) or a Windows-based OS.

[0199] The driver 1008 can read data (e.g., light intensity data, fluorescence marker intensity data, analysis result data, output data, etc.) or programs recorded on the recording medium and output the data or programs to the RAM 1003. The recording medium is, for example, an HDD, SSD, microSD memory card, SD memory card, or flash memory, but is not limited to these.

[0200] The output unit 1009 can be connected to an output device, such as a display device. The input unit 1010 can accept input for operating the analysis server 101.

[0201] [(5) Data Analysis Client Terminal]

[0202] The data analysis client terminal 20 analyzes at least one of the following: light intensity data or fluorescent label intensity data. (Refer to...) Figure 11 Describe an example configuration of the data analysis client terminal 20. Figure 11 This is a block diagram illustrating a configuration embodiment of a data analysis client terminal 20 according to an implementation of the present technology. (See diagram for example.) Figure 11 As shown, the data analysis client terminal 20 includes a processing unit 21, an analysis instruction unit 22, a connection unit 23, an output data storage unit 24, and a communication unit 25.

[0203] The processing unit 21 performs processing to cause the output device attached to the data analysis client terminal 20 to output the output data sent from the analysis server 101. Specifically, the output data is displayed in a window on the screen displayed on the output device (specifically, the display device). That is, the data analysis client may include an output device that outputs the output data.

[0204] The analysis instruction unit 22 sends the start request for the above-mentioned interactive analysis processing to the analysis server 101.

[0205] Furthermore, the analysis instruction unit 22 accepts input of analysis commands used in the aforementioned interactive analysis processing, and then sends the analysis commands to the analysis server 101. The analysis commands may include the aforementioned worksheet setting data. The interactive analysis processing unit 12 performs analysis processing with reference to the worksheet setting data, thereby generating output data corresponding to the worksheet setting data. As described above, the data analysis client terminal according to this disclosure can be configured to send analysis commands for outputting output data to an output device to the analysis server 101. Furthermore, the data analysis client terminal according to this disclosure can be configured to cause the output device to output a window displaying the output data, and to accept input of analysis commands within the window.

[0206] The connection unit 23 is a functional element for executing remote procedure calls (RPCs) in the interactive processing between the analysis server 101 (particularly the interactive analysis processing unit 12) and the data analysis client terminal 20 (particularly the analysis instruction unit 22). For example, the combination of the connection unit 23 of the data analysis client terminal 20 and the connection unit 14 of the analysis server 101 enables analysis commands entered in the data analysis client terminal 20 to be sent to the analysis server 101 and executed by the analysis server 101.

[0207] The output data storage unit 24 stores the output data sent from the analysis server 101.

[0208] The communication unit 25 receives output data created by the analysis server 101 based on the fluorescence label intensity data from the analysis server 101.

[0209] Reference Figure 12 Describe the hardware configuration of the data analysis client terminal 20. Figure 12 This is a block diagram illustrating a configuration embodiment of a data analysis client terminal 20 according to an embodiment of the present technology. It should be noted that, for example, the terminal may be a general information processing device (specifically, a computer).

[0210] exist Figure 12 The information processing device 1100 shown includes a central processing unit (CPU) 1101, RAM 1102, and ROM 1103. The CPU 1101, RAM 1102, and ROM 1103 are interconnected via a bus 1004. An input / output interface 1105 is further connected to the bus 1104.

[0211] Communication device 1106, storage device 1107, driver 1108, output unit 1109 and input unit 1110 are connected to input / output interface 1105.

[0212] Communication device 1106 connects information processing device 1100 to network 1111 via wired or wireless means. Communication device 1106 enables information processing device 1100 to send or receive various types of data via network 1111. For example, communication device 1106 sends various types of data to server system 10 or receives various types of data from server system 10. The type of communication device 1106 can be appropriately selected by those skilled in the art.

[0213] Storage device 1107 may store an operating system, a program for causing the output data output unit to output output data, a program for implementing interactive analysis processing and other various programs, various data used in information processing according to this disclosure, and various other data. The operating system may be, for example, a UNIX-based OS, particularly LINUX (registered trademark) or a Windows-based OS.

[0214] The driver 1108 can read data (e.g., output data, etc.) or programs recorded on a recording medium and output the data or programs to RAM 1103. The recording medium is, for example, an HDD, SSD, microSD memory card, SD memory card, or flash memory, but is not limited to these.

[0215] Output unit 1109 causes the output device to output output data. The output device may be, for example, a display device. For example, input unit 1110 accepts input of analysis commands in interactive analysis processing. Input devices such as keyboards or mice may be connected to input unit 1110, and analysis commands may be input by these input devices.

[0216] The data analysis client terminal 20 (specifically, the processing unit 21) causes the output device to output data. Figure 13 An example of output data to an output device is shown. Figure 13 This is a diagram illustrating an embodiment of a window from a data analysis client terminal 20 to an output device according to an implementation of the present technology.

[0217] like Figure 13 As shown, a window displaying the output data is displayed on the output device. Seven plotted images are displayed in the lower left corner of the window. Additionally, a cluster image is displayed on the right side of the window. Furthermore, statistics for each gate (number of events, parent percentage, total percentage) are displayed in the upper left corner of the window. In this way, image data and / or statistics based on the output data can be displayed in the window. The image data may include one or more plotted images and / or one or more clustered images as described above. Furthermore, the statistics may include one or more statistical data points.

[0218] [(6) Data acquisition client terminal]

[0219] Reference Figure 14 Describe the data acquisition client 30. Figure 14 This is a block diagram illustrating a configuration embodiment of a data acquisition client 30 according to an implementation of the present technology. For example... Figure 14 As shown, the data acquisition client 30 includes a data acquisition unit 31, a sending unit 32, a data processing unit 33, and a data storage unit 34.

[0220] The data acquisition unit 31 acquires measurement data sent from the biological sample analysis device 40. The measurement data includes light intensity data processed by the automatic analysis and processing unit 11. The light intensity data can be obtained by illuminating the biological sample with light.

[0221] The sending unit 32 sends measurement data (including light intensity data) acquired by the data acquisition unit 31 or measurement data processed by the data processing unit 33 (described below) to the analysis server 101 (specifically, the optical data storage unit 15 of the analysis server 101). In addition to measurement data, the sending unit 32 can also send analysis setting data to the analysis server 101. Preferably, the sending unit 32 sends light intensity data or light intensity data and analysis setting data to the analysis server 101 in response to the acquisition of light intensity data. For example, the sending unit 32 can automatically begin sending measurement data or processed measurement data (and analysis setting data) in response to the acquisition of measurement data. As described above, the data client according to this disclosure can send light intensity data to the analysis server 101. Furthermore, the data acquisition client according to this disclosure can be configured to send light intensity data (and analysis setting data) to the analysis server 101 in response to the acquisition of light intensity data.

[0222] Furthermore, in one embodiment of this disclosure, the data acquisition client 30 can perform calculation processing to calculate fluorescent label intensity data from light intensity data. The calculation processing can be performed as described above (3-1), and can be, for example, fluorescence correction processing or demixing processing. In this embodiment, the sending unit 32 can send the fluorescent label intensity data (or the fluorescent label intensity data processed by the data processing unit 33 described below) to the analysis server 101 (specifically, the optical data storage unit 15 of the analysis server 101). As described above, the data client according to this disclosure can send fluorescent label intensity data to the analysis server 101. Furthermore, the data acquisition client according to this disclosure can be configured to send fluorescent label intensity data to the analysis server 101 in response to acquiring fluorescent label intensity data.

[0223] Furthermore, in this disclosure, the sending unit 32 can send both the measurement data and the fluorescence label intensity data to the analysis server 101.

[0224] The data acquisition client 30 has a sending unit 32 independent of the data acquisition unit 31, thereby allowing data acquisition processing and upload processing to be performed separately. Using this configuration, measurement data (including light intensity data), fluorescence labeling intensity data calculated from the measurement data, or both, can be uploaded to the analysis server 101 without affecting the data acquisition processing from the biological sample analysis device 40.

[0225] The data processing unit 33 can perform predetermined processing on the measurement data and / or fluorescent label intensity data acquired by the data acquisition unit 31. This processing can be compression, data processing (e.g., format conversion), etc. Through data processing, the measurement data and / or fluorescent label intensity data can be converted into a form suitable for information processing in the analysis server 101, making the processing in the analysis server 101 more efficient. As described above, the data acquisition client according to this disclosure can be configured to perform predetermined processing on the light intensity data or fluorescent label intensity data in response to the acquisition of light intensity data or fluorescent label intensity data, and send the processed light intensity data or fluorescent label intensity data to the analysis server 101.

[0226] The data storage unit 34 is capable of storing measurement data or processed measurement data. The data storage unit 34 can store fluorescent label intensity data or processed fluorescent label intensity data.

[0227] The hardware configuration embodiment of the data acquisition client 30 is the same as that described for the data analysis client 20. It should be noted that, for example, the data acquisition client 30 can also be a general information processing device (specifically, a computer).

[0228] [(7) Biological sample analysis device]

[0229] For example, a biological sample analysis device can be a flow cytometer as described above, but is not limited to this. (See also...) Figure 15 Describe an embodiment of the configuration of a biological sample analysis device. Figure 15 This is a schematic diagram illustrating a configuration embodiment of a biological sample analysis device 40 according to an embodiment of the present technology.

[0230] like Figure 15 As shown, the biological sample analysis device 40 includes a light irradiation unit 41, a detection unit 42, and an information processing unit 43. The light irradiation unit 41 uses light to irradiate the biological sample S flowing through the flow channel C. The detection unit 42 detects the light generated by the irradiation, and the information processing unit 43 processes information about the light detected by the detection unit. Embodiments of the biological sample analysis device 40 include flow cytometers and imaging cytometers. The biological sample analysis device 40 may include a sorting unit 44 for classifying specific biological products P in the biological sample. As an embodiment of the biological sample analysis device 40 including a sorting unit, a cell sorter may be exemplified, for example.

[0231] [(7-1) Biological Samples]

[0232] Biological sample S can be a liquid sample containing biological products. Biological products are, for example, cellular or non-cellular biological products. Cells can be living cells, and more specific embodiments include blood cells (e.g., red blood cells and white blood cells) and germ cells (e.g., sperm and fertilized eggs). Cells can be collected directly from a sample such as whole blood, or can be cultured cells obtained after culturing. Embodiments of non-cellular biological products include extracellular vesicles, particularly exogenous bodies and microvesicles. Biological products can be labeled with one or more labeling substances (e.g., dyes (especially fluorescent dyes) and antibodies labeled with fluorescent dyes). It should be noted that the biological sample analysis apparatus of this disclosure can analyze particles other than biological products, or can analyze beads, etc., for calibration, etc.

[0233] [(7-2) Flow channel]

[0234] Flow channel C can be configured to allow the biological sample to flow, and specifically, to form a flow in which biological articles contained in the biological sample are arranged in a substantially single row. The flow channel structure including flow channel C can be designed to form laminar flow, and specifically, to form a laminar flow in which the flow of the biological sample (sample flow) is enveloped by a flow of sheath fluid. The design of the flow channel structure can be suitably chosen by those skilled in the art, and known flow channel structures can be employed. Flow channel C can be formed as a flow channel structure (specifically, a flow channel structure performing focusing), such as a microchip (a chip with micron-scale flow channels) or a flow cell. The width of flow channel C is 1 mm or less, and can particularly be 10 μm or greater and 1 mm or less. Flow channel C and the flow channel structure including flow channel C can comprise materials such as plastic or glass.

[0235] The apparatus disclosed herein can be configured to irradiate a biological sample, particularly a biological product within the biological sample, flowing in a flow channel C with light from an irradiation unit. The apparatus can be configured such that the light irradiation point (probing point) relative to the biological sample is located within a flow channel structure in which the flow channel C is formed, or it can be configured such that the light irradiation point is located outside the flow channel structure. As an embodiment of the former, a configuration in which the flow channel C in a microchip or flow cell is irradiated with light may be mentioned. In the latter, the biological product after exiting the flow channel structure (particularly its nozzle portion) can be irradiated with light, and embodiments thereof include flow cytometers with air jet systems.

[0236] [(7-3) Light Illumination Unit]

[0237] The light illumination unit 41 includes a light source unit that emits light and a light-guiding optical system that guides the light to the flow channel C. The light source unit includes one or more light sources. The type of light source can be, for example, a laser light source or an LED. The wavelength of the light emitted from each light source can be any wavelength of ultraviolet, visible, or infrared light. For example, the light-guiding optical system includes optical components such as a beam splitter group, a lens group, or an optical fiber. In addition, the light-guiding optical system may include a lens group for collecting light and may include, for example, an objective lens. The biological sample can be illuminated with light at one or more illumination points. The light illumination unit 41 can be configured to collect light emitted from one or more different light sources to one illumination point.

[0238] [(7-4) Detection Unit]

[0239] Detection unit 42 includes at least one photodetector that detects light generated by illuminating the particle with light by the light irradiation unit. The light to be detected is, for example, fluorescence or scattered light (e.g., any one or more of forward-scattered light, back-scattered light, and side-scattered light). Each photodetector includes one or more light-receiving elements, such as an array of light-receiving elements. Each photodetector may include one or more PMTs (photomultiplier tubes) and / or photodiodes such as APDs and MPPCs as light-receiving elements. The photodetector includes, for example, an array of PMTs, wherein multiple PMTs are arranged in a one-dimensional direction. Furthermore, the detection unit may include an imaging element such as a CCD or CMOS. The detection unit can acquire images of the biological product (e.g., bright-field images, dark-field images, fluorescence images, etc.) through the imaging element.

[0240] The detection unit includes a detection optical system that directs light with a predetermined detection wavelength to a corresponding photodetector. The detection optical system includes a dispersive unit such as a prism or diffraction grating, or a wavelength separation unit such as a dichroic mirror or filter. For example, the detection optical system may be configured to disperse light from a biological product and detect light in different wavelength ranges by multiple photodetectors, in numbers greater than the number of fluorescent dyes. Flow cytometers including such detection optical systems are called spectral flow cytometers. Furthermore, for example, the detection optical system may be configured to separate light corresponding to the fluorescence wavelength range of the fluorescent dye from the light from the biological product, and to cause the separated light to be detected by corresponding photodetectors.

[0241] Furthermore, the detection unit may include a signal processing unit that converts the electrical signal obtained by the photodetector into a digital signal. The signal processing unit may include an A / D converter as the device performing the conversion. The digital signal obtained by the signal processing unit can be sent to the information processing unit. The digital signal processing unit can treat the digital signal as light-related data (hereinafter also referred to as "optical data"). For example, optical data may be optical data including fluorescence data. More specifically, optical data may be light intensity data, and light intensity may be light intensity data including fluorescence (which may include characteristic quantities such as area, height, and width).

[0242] [(7-5) Information Processing Unit]

[0243] The information processing unit 43 includes a processing unit that performs processing of various types of data (e.g., optical data) and a storage unit that stores various types of data.

[0244] In the case where the biological sample analysis apparatus includes a sorting unit described later, the information processing unit can determine whether to sort the biological products based on optical data and / or morphological information. The information processing unit then controls the sorting unit based on the determination result, and the sorting unit can sort the biological products.

[0245] The information processing unit can be configured as a general-purpose computer and can be configured as an information processing device including, for example, a CPU, RAM, and ROM. The information processing unit can be included within a housing in which the light irradiation unit and the detection unit are disposed, or it can be located outside the housing. For example, the information processing unit can be implemented via a data acquisition client 30.

[0246] [(7-6) Sorting Unit]

[0247] For example, sorting unit 44 can perform sorting of biological products based on the determination result of information processing unit. Sorting methods may include generating droplets containing biological products through vibration, applying charge to the droplets to be sorted, and controlling the direction of droplet movement via electrodes. Sorting methods may also include controlling the direction of travel of biological products in a flow channel structure to perform sorting. For example, the flow channel structure may be provided with a control mechanism for pressure (injection or suction) or loading. Embodiments of the flow channel structure include a chip with a flow channel structure (e.g., the chip described in Japanese Patent Application Publication No. 2020-76736), in which the flow channel C branches into a collection channel and a waste liquid channel on its downstream side, and in this flow channel structure, specific biological products are collected into the collection channel.

[0248] For example, the biological sample analysis apparatus 40 can be a microscope apparatus for performing multicolor fluorescence imaging, specifically a fluorescence microscope apparatus. In recent years, the number of phosphors used in fluorescence imaging has tended to increase, and the information processing system of this disclosure can process light intensity data acquired through the microscope apparatus.

[0249] Provided there are no technical contradictions, the above-described content of the information processing system according to the first embodiment of this technology can be applied to other embodiments of this technology.

[0250] [2. Second embodiment of the present technology (Example 2 of the information processing system)]

[0251] When a program and analysis server 101 are determined to perform analysis processing, instead of analysis information or other than analysis information, the connection unit 73 may determine the program and analysis server 101 to perform analysis processing based on information about the usage cost of the analysis server 101. That is, the connection unit may determine the program for performing analysis processing and the analysis server 101 for performing at least one of the following: analysis information, resource information, program information, or information about the usage cost of the analysis server 101, and send information about the determined analysis server 101 and program to the system construction unit.

[0252] Reference Figure 8 Let us describe an embodiment of the processing flow at this time again. In step S102, the connection unit 73 determines the analysis server 101 and the program. At this time, the connection unit 73 may determine the program for performing analysis processing and the analysis server 101 for performing at least one of the following: analysis information, resource information, program information, or information about the usage cost of the analysis server 101.

[0253] According to this embodiment, the operating cost of the analysis server 101 can be reduced. The cost of using an analysis server 101 with high resource performance tends to increase. Therefore, if the analysis server 101 with high resource performance performs analysis processing that does not require high resource performance, cost-performance deteriorates. Therefore, by determining the analysis server 101 based on at least one of analysis information, resource information, program information, or information regarding the usage cost of the analysis server 101, operating costs and processing time can be balanced.

[0254] Provided there are no technical contradictions, the above-described content of the information processing system according to the second embodiment of this technology can be applied to other embodiments of this technology.

[0255] [3. Third embodiment of this technology (Example 3 of the information processing system)]

[0256] Reference Figure 16 This describes a configuration embodiment of an information processing system according to an implementation of the present technology. Figure 16 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0257] like Figure 16As shown, the information processing system 100 may further include a data segmentation unit 90. The data segmentation unit 90 segments at least one of light intensity data or fluorescent marker intensity data based on resource information and sends the segmented data to different analysis servers (e.g., a first analysis server 10111, a second analysis server 10122, and a third analysis server 103). For example, the data segmentation unit 90 can segment data on an event-by-event basis. Using this configuration, processing time can be reduced compared to a single analysis server 101 analyzing and processing a large amount of data.

[0258] It should be noted that in this configuration embodiment, the server system 10 includes a data segmentation unit 90, but for example, the communication processing unit 60 may include a data segmentation unit 90.

[0259] Furthermore, although not shown, for example, the data segmentation unit 90 can segment the analysis result data or the output data.

[0260] Provided there are no technical contradictions, the above-described content of the information processing system according to the third embodiment of this technology can be applied to other embodiments of this technology.

[0261] [4. Fourth embodiment of this technology (Example 4 of the information processing system)]

[0262] At least one of the analysis server 101 or the program used for analysis processing can be determined by the connection unit 73, or by the user via the data analysis client terminal 20. (See reference...) Figure 17 An example of the processing flow at this time is described. Figure 17 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology.

[0263] like Figure 17 As shown, firstly, in step S201, the data analysis client terminal 20 accepts a designation for at least one of the analysis server 101 or the program.

[0264] Next, in step S202, the data analysis client terminal 20 sends information about at least one of the analysis server 101 or the program, along with the analysis information, to the connection unit 73. Subsequent processing can be... Figure 8 The flowchart shown is similar.

[0265] When at least one of the analysis server 101 or program is selected in step S201, the output device of the data analysis client terminal 20 can display a list of the selected analysis server 101 and program. (Refer to...) Figure 18 Describe the embodiment displayed at this time. Figure 18This is a diagram illustrating an embodiment of a window from a data analysis client terminal 20 to an output device according to an implementation of the present technology.

[0266] like Figure 18 As shown, multiple analysis servers 101 and multiple programs are displayed in the list. The list of analysis servers 101 displays attribute information such as "Server Name," "Server Type," "Server Specifications," and "Usage Fee." Attribute information such as "Program Version" and "I / F Version" are displayed in the program list. Note that it is not necessary to display both analysis servers 101 and programs; at least one of them can be displayed.

[0267] In the list of analytics servers 101, preferably, only analytics servers 101 owned by the user's group are displayed based on "Group ID". Furthermore, preferably, only unused analytics servers 101 are displayed based on "Usage Status".

[0268] The data analysis client terminal 20 can have a search function. For example, by allowing searches by server name or program version, users can easily find the necessary programs or servers. The search function can be enhanced by providing text boxes for entering program versions or server names, or by offering filtering functionality.

[0269] Furthermore, the data analytics client terminal 20 can have a categorization function. For example, by enabling sorting by server specifications in descending order or by usage fees in ascending order, users can easily find the necessary programs or servers.

[0270] Provided there are no technical contradictions, the above-described content of the information processing system according to the fourth embodiment of this technology can be applied to other embodiments of this technology.

[0271] [5. Fifth embodiment of the present technology (Example 5 of the information processing system)]

[0272] Analysis server 101 can connect to a field network or a public cloud network. Figure 5 In the configuration embodiment shown, the analysis server 101 is connected to the field network. (Refer to...) Figure 19 This describes a configuration example of how server 101 connects to a public cloud network. Figure 19 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0273] like Figure 19As shown, in the services provided by the analysis server 101, the automatic analysis processing unit 11, the interactive analysis processing unit 12, the output data generation unit 13, and the connection unit 141 are connected to the public cloud network. In the services provided by the analysis server 101, the connection unit 141, the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 are connected to the field network. Note that the analysis server connected to the public cloud network is defined as the first analysis server 1011. The analysis server connected to the field network is defined as the second analysis server 1012.

[0274] With this configuration, the data and database reside within the field network. Therefore, highly confidential measurement data can be protected from unauthorized access, information leaks, and other threats.

[0275] Reference Figure 20 Describe the processing flow at this point. Figure 20 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology.

[0276] like Figure 20 As shown, firstly, in step S301, the data analysis client terminal 20 sends analysis information regarding the analysis processing of at least one of the light intensity data or the fluorescence marker intensity data to the connection unit 73 in the analysis execution request.

[0277] Next, in step S302, the connection unit 73 determines, based on at least one of analysis information, resource information, or program information, a program for performing analysis processing and an analysis server for deploying or executing at least one of the programs. Program information regarding the program is managed by the program management unit 72. Resource information regarding the analysis server is managed by the resource management unit 71.

[0278] Next, in step S303, the connection unit 73 sends information about the determined analysis server and program to the system construction unit 82.

[0279] Next, in step S304, the system building unit 82 accesses the computer holding the program based on information about the program in order to obtain the program.

[0280] Next, in step S305, the system construction unit 82 deploys the acquired program on a predetermined analysis server based on information related to the analysis server. This enables the formation of the server system 10.

[0281] Next, in step S306, the connection unit 73 sends information for connecting to the first analysis server 1011 and the second analysis server 1012 to the data analysis client terminal 20.

[0282] Next, in step S307, the data analysis client terminal 20 connects to the first analysis server 1011 based on the information used to connect to the first analysis server 1011.

[0283] Next, in step S308, the data analysis client terminal 20 notifies the first analysis server 1011 (specifically, the connection unit 141) of information for connecting to the second analysis server 1012.

[0284] Next, in step S309, the first analysis server 1011 (specifically, the connection unit 141) sends a data information acquisition request to the second analysis server 1012. At this time, the proxy unit 80 preferably communicates with the connection unit 73 through long polling.

[0285] Finally, in step S310, the second analysis server 1012 (specifically, the connection unit 142) sends the data stored in the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 to the first analysis server 1011. Through this arrangement, the data analysis client terminal 20 can analyze at least one of the light intensity data or the fluorescence marker intensity data.

[0286] Note that in the embodiment of the processing flow, the system building unit 82 deploys programs in the analysis server 101, but programs may already be deployed. For example, different programs may already be deployed on each of the multiple analysis servers 101. In this case, the system building unit 82 can execute predetermined programs from different programs.

[0287] Provided there are no technical contradictions, the above-described content of the information processing system according to the fifth embodiment of this technology can be applied to other embodiments of this technology.

[0288] [6. Sixth Embodiment of the Technology (Embodiment 6 of the Information Processing System)]

[0289] Reference Figure 21 Describes another configuration embodiment of the analysis server 101 connected to a public cloud network. Figure 21 This is a block diagram illustrating a configuration embodiment of an information processing system 100 according to an embodiment of the present technology.

[0290] like Figure 21As shown, in the services provided by the analysis server 101, the connection unit 141, the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 are connected to the public cloud network. In the services provided by the analysis server 101, the automatic analysis processing unit 11, the interactive analysis processing unit 12, the output data generation unit 13, and the connection unit 142 are connected to the field network. Note that the analysis server connected to the public cloud network is defined as the first analysis server 1011. The analysis server connected to the field network is defined as the second analysis server 1012.

[0291] The first analytics server 1011, connected to the public cloud network, can increase or decrease its resources based on usage, allowing it to flexibly respond to sudden increases in data volume.

[0292] Reference Figure 22 Describe the processing flow at this point. Figure 22 This is a flowchart illustrating an embodiment of the processing flow of an information processing system 100 according to an implementation of the present technology.

[0293] like Figure 22 As shown, firstly, in step S401, the data analysis client terminal 20 sends analysis information regarding the analysis processing of at least one of the light intensity data or the fluorescence marker intensity data to the connection unit 73.

[0294] Next, in step S402, the connection unit 73 determines, based on at least one of analysis information, resource information, or program information, a program for performing analysis processing and an analysis server for performing at least one of deployment or execution programs. Program information regarding the program is managed by the program management unit 72. Resource information regarding the analysis server is managed by the resource management unit 71.

[0295] Next, in step S403, the connection unit 73 sends information about the determined analysis server and program to the system construction unit 82.

[0296] Next, in step S404, the system building unit 82 accesses the computer holding the program based on information about the program in order to obtain the program.

[0297] Next, in step S405, the system construction unit 82 expands the acquired program onto a specified analysis server based on the information from the analysis server. This enables the construction of the server system 10.

[0298] Next, in step S406, the connection unit 73 sends information for connecting to the first analysis server 1011 and the second analysis server 1012 to the data analysis client terminal 20.

[0299] Next, in step S407, the data analysis client terminal 20 connects to the second analysis server 1012 based on the information used to connect to the second analysis server 1012.

[0300] Next, in step S408, the data analysis client terminal 20 notifies the second analysis server 1012 (specifically, the connection unit 142) of information for connecting to the first analysis server 1011.

[0301] Next, in step S409, based on the information used to connect to the first analysis server 1011, the second analysis server 1012 (specifically, the connection unit 142) connects to the first analysis server 1011.

[0302] Finally, in step S410, the second analysis server 1012 (specifically, connection unit 142) acquires data stored in the optical data storage unit 15, the analysis result data storage unit 16, and the database 17 stored in the first analysis server 1011. Through this arrangement, the data analysis client terminal 20 can analyze at least one of the light intensity data and the fluorescence marker intensity data.

[0303] Note that in the embodiment of the processing flow, the system building unit 82 deploys programs in the analysis server 101, but programs may already be deployed. For example, different programs may already be deployed on each of the multiple analysis servers 101. In this case, the system building unit 82 can execute predetermined programs from different programs.

[0304] Provided there are no technical contradictions, the above-described content of the information processing system according to the sixth embodiment of this technology can be applied to other embodiments of this technology.

[0305] [7. Seventh Embodiment of the Technology (Server System Example)]

[0306] This technology provides a server system, including: a system building unit that executes at least one of a program for deploying or executing an analysis server for analyzing at least one of light intensity data or fluorescent label intensity data obtained by irradiating a biological sample with light, wherein the at least one of the program or analysis server is determined based on a database having information about at least one of the program or analysis server.

[0307] Reference Figure 5 The configuration example of the server system will be described again. For example... Figure 5As shown, the server system 10 according to an embodiment of the present technology includes a system building unit 82. The system building unit 82 executes at least one of a program for analyzing at least one of light intensity data or fluorescent label intensity data obtained by irradiating a biological sample with light on an analysis server.

[0308] At least one of the programs or analytics servers is identified based on a database that stores information about at least one of the programs or analytics servers. This database may, for example, be centrally managed by a management system 70. Alternatively, the database may be configured using distributed ledger technology (blockchain technology), in which multiple nodes (computers) participating in the network record and share data.

[0309] Provided there are no technical contradictions, the above content of the server system according to the seventh embodiment of this technology can be applied to other embodiments of this technology.

[0310] It should be noted that this disclosure may also have the following configurations. [1]

[0312] An information processing system includes: a management system for managing a program for analyzing at least one of light intensity data and fluorescence labeling intensity data obtained by irradiating a biological sample with light; and an analysis server for executing at least one of: a deployment program and an execution program. [2]

[0314] According to the information processing system in [1], in which, The management system includes: The resource management unit manages resource information related to the computing resources of the analytics server. The program management unit manages program information about the program, and A connection unit, connected to at least one of a system and apparatus different from the management system. [3]

[0316] According to the information processing system of [2], it also includes: The agent unit connects to the analysis server and the connection unit. [4]

[0318] According to the information processing system in [3], among which, The management system connects to the first information communication network. The agent unit is connected to the second information communication network, and The first information communication network and the second information communication network are connected to each other via a communication processing unit. [5]

[0320] According to the information processing system in [4], in which, The first information and communication network is a public cloud network, and The second information and communication network is a private cloud network or a site-specific network. [6]

[0322] According to any one of [3] to [5], in the information processing system, The agent unit and the connection unit communicate through long polling. [7]

[0324] According to any one of [3] to [6], the information processing system, wherein, The agent unit includes a resource registration unit, which sends the resource information of the analysis server to the resource management unit. [8]

[0326] According to any one of [3] to [7], the information processing system, wherein, The agent unit includes a system building unit, which performs at least one of the following: deploying a program on the analytics server and executing a program on the analytics server. [9]

[0328] According to the information processing system of [8], it also includes: The data analysis client analyzes at least one of light intensity data and fluorescent label intensity data, wherein, The data analysis client sends analysis information regarding at least one of the light intensity data and fluorescence label intensity data to the connection unit. The connection unit, based on at least one of analysis information, resource information, or program information, determines the program for performing the analysis processing and the analysis server for performing at least one of the following: a deployment program and an execution program, and sends information about the determined analysis server and program to the system construction unit. Based on the information received about the analysis server and the program, the system building unit performs at least one of the following: deploying the program on the analysis server and executing the program on the analysis server.

[10]

[0330] According to the information processing system in [9], in which, The connection unit determines, based on at least one of analysis information, resource information, program information, and information about the usage cost of the analysis server, a program for performing analysis processing and an analysis server for performing at least one of the following: a deployment program and an execution program, and sends information about the determined analysis server and program to the system construction unit.

[11]

[0332] The information processing system according to any one of [2] to

[10] also includes: The data segmentation unit segments at least one of the light intensity data and the fluorescence label intensity data based on resource information, and sends the segmented data to different analysis servers.

[12]

[0334] The information processing system according to any one of [2] to

[11] also includes: The data analysis client analyzes at least one of light intensity data and fluorescent label intensity data, wherein, The connection unit sends information about the analysis server used to perform at least one of the following to the data analysis client: the deployment program and the execution program.

[13]

[0336] According to the information processing system of

[12] , in which, The data analysis client accepts a designation of at least one of the analysis server and the program, and sends information about at least one of the analysis server or the program to the connection unit.

[14]

[0338] A server system includes system building units that execute at least one of the following on an analysis server: a deployment program and an execution program, the program being used to analyze at least one of light intensity data and fluorescence labeling intensity data obtained by irradiating a biological sample with light, wherein... The at least one of the program and analysis server is determined based on a database containing information about at least one of the program and analysis server.

[0339] Reference Symbol List

[0340] 10 Server Systems

[0341] 20 Data Analysis Clients

[0342] 30 Data Acquisition Clients

[0343] 40 Biological Sample Analysis Device

[0344] 60 Communication Processing Units

[0345] 70 Management System

[0346] 71 Resource Management Unit

[0347] 72 Program Management Unit

[0348] 73 Connection Unit

[0349] 80 Agent Units

[0350] 81 Resource Registration Unit

[0351] 82 System Building Units

[0352] 90 data partitioning units

[0353] 100 Information Processing System

[0354] 101 Analysis Server.

Claims

1. An information processing system, comprising: A management system that manages programs for analyzing at least one of light intensity data and fluorescent labeling intensity data obtained by irradiating biological samples with light; And an analysis server for performing at least one of the following: deploying the program and executing the program.

2. The information processing system according to claim 1, wherein, The management system includes: The resource management unit manages resource information regarding the computing resources of the analysis server. The program management unit manages program information about the program, and A connection unit is connected to at least one of a system and device that is different from the management system.

3. The information processing system according to claim 2, further comprising: The proxy unit is connected to the analysis server and the connection unit.

4. The information processing system according to claim 3, wherein, The management system is connected to the first information communication network. The agent unit is connected to the second information communication network, and The first information communication network and the second information communication network are connected to each other via a communication processing unit.

5. The information processing system according to claim 4, wherein, The first information communication network is a public cloud network, and The second information and communication network is a private cloud network or a site-specific network.

6. The information processing system according to claim 3, wherein, The proxy unit and the connection unit communicate through long polling.

7. The information processing system according to claim 3, wherein, The agent unit includes a resource registration unit, which sends the resource information of the analysis server to the resource management unit.

8. The information processing system according to claim 3, wherein, The agent unit includes a system building unit that performs at least one of the following: deploying the program on the analysis server and executing the program on the analysis server.

9. The information processing system according to claim 8, further comprising: The data analysis client analyzes at least one of the light intensity data and the fluorescent label intensity data, wherein, The data analysis client sends analysis information regarding the processing of at least one of the light intensity data and the fluorescent label intensity data to the connection unit. The connection unit, based on at least one of the analysis information, the resource information, and the program information, determines a program for performing the analysis processing and an analysis server for performing at least one of the following: deploying the program and executing the program, and sends information about the determined analysis server and the program to the system construction unit. Based on the received information about the analysis server and the program, the system building unit performs at least one of the following: deploying the program on the analysis server and executing the program on the analysis server.

10. The information processing system according to claim 9, wherein, The connection unit determines, based on at least one of the analysis information, the resource information, the program information, and information about the usage cost of the analysis server, the program for performing the analysis processing and the analysis server for performing at least one of the following: deploying the program and executing the program, and sends information about the determined analysis server and the program to the system construction unit.

11. The information processing system according to claim 2, further comprising: The data segmentation unit segments at least one of the light intensity data and the fluorescence label intensity data based on the resource information, and sends the segmented data to different analysis servers.

12. The information processing system according to claim 2, further comprising: The data analysis client analyzes at least one of the light intensity data and the fluorescent label intensity data, wherein, The connection unit sends information about the analysis server for performing at least one of the following: deploying the program and executing the program.

13. The information processing system according to claim 12, wherein, The data analysis client accepts a designation for at least one of the analysis server and the program, and sends information about at least one of the analysis server and the program to the connection unit.

14. A server system comprising a system building unit that performs at least one of the following on an analysis server: deploying a program and executing the program, the program being used to analyze at least one of light intensity data and fluorescence labeling intensity data acquired by irradiating a biological sample with light, wherein, The program and the analysis server are determined based on a database containing information about at least one of the program and the analysis server.

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