Information processing system and control method

Abstract

The present invention addresses the problem of creating a highly accurate simulation model for generating a manufacturing condition for manufacturing an object. An information processing system (100) comprises an actual data acquisition unit (14) for acquiring first actual data that contains actual parameters, including a condition which has been set in a manufacturing process for actually manufacturing an object using a first facility, and that contains actual manufacturing data pertaining to the object, a virtual data generation unit (13) for generating virtual data that contains virtual parameters, including a condition which has been set for conducting a simulation based on a simulation model, and that contains virtual manufacturing data pertaining to the object which has virtually been manufactured, a data integration unit (15) for generating first integrated data by integrating the first actual data and the virtual data, and a model update unit (16) for updating the simulation model using at least part of the first integrated data.

Description

Information processing system and control method

[0001] The present invention relates to an information processing system and a method for controlling an information processing system.

[0002] To realize a product with the intended quality, it is necessary to accumulate test result data by conducting tests with various conditions during the research and development stage, and then to explore and determine the optimal conditions for manufacturing a product with the intended quality based on the accumulated test result data. Furthermore, in order to stably supply a product with the intended quality, it is necessary to first accumulate prototype data regarding the relationship between the quality of prototypes actually manufactured using manufacturing processes with various manufacturing conditions and the manufacturing conditions under which those prototypes were manufactured. Then, based on the accumulated prototype data, it is necessary to explore and determine the optimal manufacturing conditions for manufacturing a product with the intended quality.

[0003] For example, the technology described in Patent Document 1 discloses a method for manufacturing medical products using the Quality by Design (QbD) approach. The QbD approach is a method aimed at designing products with appropriate quality and manufacturing processes that can consistently and stably supply products with the intended quality, as outlined in Operational Guidelines Q8 for Safety and Quality Maintenance established by the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH). The QbD approach deepens the scientific understanding of product realization and the product manufacturing process by accumulating information and knowledge obtained from tests conducted during the research and development phase. This makes it possible to establish a design space for manufacturing the product, product specifications, and manufacturing control.

[0004] In addition, Patent Document 2 describes an apparatus parameter setting support system that calculates a change value of PID parameters used in simulation processing in an apparatus simulator. This apparatus parameter setting support system can pass the calculated change value to the apparatus simulator and reflect the change over time and the change in the apparatus state that occur in the actual apparatus in the apparatus simulator by taking the change value into account in the PID parameters.

[0005] International Publication No. WO2019 / 044559, International Publication No. WO2011 / 158339

[0006] When the QbD method is applied to manufacture a product, first, using small-scale equipment for research and development, manufacturing conditions that can consistently and stably supply a product having intended quality are examined, and then, manufacturing conditions in manufacturing using larger-scale equipment are examined. Therefore, it is necessary to repeat experiments and manufacture of prototypes until a product having intended quality can be consistently and stably supplied.

[0007] For example, in a manufacturing process for manufacturing cell products used in regenerative medicine and cell therapy, since the process includes an unstable process such as a cell culture process, there is a possibility that even a product manufactured under predetermined manufacturing conditions may not have intended quality. To determine manufacturing conditions for consistently and stably manufacturing such products, a lot of time and cost may be required from the research stage to the manufacturing stage. Furthermore, it is necessary to continuously adjust the determined manufacturing conditions even after the start of manufacturing to lead to more stable product manufacturing.

[0008] One aspect of the present invention aims to realize an information processing system or the like that can create a simulation model for generating manufacturing conditions for manufacturing an object with high accuracy.

[0009] To solve the above problems, an information processing system according to one aspect of the present invention includes: a real data acquisition unit that acquires first real data including real parameters including conditions set in a manufacturing process carried out by a first entity for actually manufacturing an object using first equipment, and real manufacturing data relating to the object manufactured by the manufacturing process; a virtual data generation unit that generates virtual data including virtual parameters including conditions set for executing a simulation based on a simulation model set for the manufacturing process, and virtual manufacturing data relating to the object virtually manufactured by the simulation; a data integration unit that integrates the first real data and the virtual data to generate first integrated data; and a model update unit that updates the simulation model using at least a part of the first integrated data.

[0010] To solve the above problems, a control method for an information processing system according to one aspect of the present invention is a control method for an information processing system executed by one or more computers, comprising: (1) a real data acquisition step of acquiring first real data including real parameters including conditions set in a manufacturing process carried out by a first entity in order to actually manufacture an object using first equipment, and real manufacturing data relating to the object manufactured by the manufacturing process; a virtual data generation step of generating virtual data including virtual parameters including conditions set in order to execute a simulation based on a simulation model set for the manufacturing process, and virtual manufacturing data relating to the object virtually manufactured by the simulation; a data integration step of integrating the first real data and the virtual data to generate first integrated data; and a model update step of updating the simulation model using at least a part of the first integrated data.

[0011] According to one aspect of the present invention, it is possible to create a highly accurate simulation model for generating manufacturing conditions for producing an object.

[0012] This is a block diagram showing the main components of an information processing system according to one embodiment of the present invention. This diagram illustrates the concepts of manufacturing process, unit process, unit operation, and operation as described herein. This diagram illustrates the target system and the inputs and outputs related to said target system as described herein. This is a flowchart showing an example of processing of an information processing device according to one embodiment of the present invention.

[0013] Hereinafter, one embodiment of the present invention will be described in detail. Figure 1 is a block diagram showing the main components of the information processing system 100 in this embodiment. As shown in Figure 1, the information processing system 100 includes research and development equipment 300, manufacturing equipment 400, product utilization equipment 500, and an information processing device 1. As shown in Figure 1, the research and development equipment 300, manufacturing equipment 400, product utilization equipment 500, and information processing device 1 are able to communicate with each other via a network 900.

[0014] The following description illustrates an example of applying the information processing system 100 to the production of cells. However, the information processing system disclosed herein can also be applied to the production of objects other than cells. Examples of objects other than cells include extracellular vesicles, viruses, proteins, macromolecules (macromolecular compounds), genes, small molecules (small molecule compounds), pharmaceuticals, diagnostic agents, chemical products, food products, agricultural products, and the like.

[0015] Here, we will explain the definitions and concepts of terms used in this specification. Figure 2 is a diagram illustrating the concepts of manufacturing process, unit process, unit operation, and operation as used in this specification. As shown in Figure 2, a manufacturing process consists of multiple unit processes. Figure 2 shows an example in which a manufacturing process consists of 12 unit processes. For example, in the case of a cell manufacturing process, it includes multiple unit processes such as thawing and seeding, amplification and culture (culture process), medium exchange, harvesting and subculturing, detachment and dispensing, freezing, storage, and transport. The thawing and seeding process and the amplification and culture process are part of the cell processing process, which processes cells. In other words, the cell processing process includes the culture process, which cultures cells. A unit process is a series of operations that can be evaluated using control items at completion. Each unit process consists of multiple operations (unit operations). As an example, Figure 2 shows a unit process consisting of six unit operations: two unit operations in the upper row, three unit operations in the lower row, and one unit operation performed after these unit operations. A unit task is the smallest work division consisting of a series of actions that accomplish a single work objective. An action is a work division defined by a single command that can be specified by parameters. Figure 2 shows a unit task composed of four unit actions.

[0016] Next, the "target system" and the inputs and outputs related to the "target system" in this specification will be described. Figure 3 is a diagram illustrating the target system and the inputs and outputs related to the target system in this specification. As shown in Figure 3, the information processing system 100 has a first target system S1, a second target system S2, and a third target system S3 set up as target systems that include a response field that shows a response according to each operation. The first target system S1 is a response field to which cells respond, and the target in the first target system S1 is an individual cell. The second target system is a culture system (e.g., a container) for culturing cells, and the target in the second target system S2 is a group of cells within the culture system. The third target system is an apparatus system for manufacturing cells, and the target in the third target system S3 is a group of culture systems within the apparatus system.

[0017] As shown in Figure 3, the information processing system 100 has settings for operation inputs, operation outputs, response outputs, etc., for the first target system S1, the second target system S2, and the third target system S3. The details of the inputs and outputs for each target system are described below.

[0018] For the third target system S3, the operator's actions become the operation input I1. The operator can be, for example, a person, a robotic arm, a pump, a device, a gear, a motor, etc. The operator's actions are the operator's actions toward an object such as process materials. The object can be in the gas phase, liquid phase, and / or solid phase. In the third target system S3, the gas phase object is, for example, air. In the third target system S3, the liquid phase object is, for example, a culture medium, a buffer solution, a cell suspension, etc. In the third target system S3, the solid phase object is, for example, a culture vessel, a pipette, a centrifuge tube, a tube, a stirring blade, etc. The operation input I1 for the third target system S3 is represented, for example, by a group of variables such as current and voltage, and a group of parameters that fluctuate from that group of variables.

[0019] The operational output O1 from the third object system S3 is represented, for example, by a group of variables relating to the object, such as distance, angle, momentum, energy, and amount of substance, and a group of variable parameters for the said group of variables. In this specification, "group of variables" refers to quantities related to matter, motion, energy, etc., expressed in SI units, and quantities indicating density (concentration) considering space. In this specification, "group of variable parameters" refers to combinations of time, velocity, acceleration, jerk, frequency, cumulative amount, dot product, etc., relating to the group of variables.

[0020] For the second target system S2, the operation of the process material becomes the operation input I2. The operation of the process material is the operation of the process material, which is in the solid phase, with respect to the gaseous, liquid, and / or solid phase objects within the process material. The gaseous object in the second target system S2 is, for example, air. The liquid phase object in the second target system S2 is, for example, culture medium, buffer solution, cell suspension, etc. The solid phase object in the second target system S2 is, for example, culture vessel, pipette, centrifuge tube, culture tank, pump tubing, dispensing nozzle, etc. The operation input I2 for the second target system S2 is represented by, for example, a group of variables such as momentum, energy, and amount of substance, a group of variables related to the amount of substance, movement (including flow) variables of these groups of variables, and a group of parameters that change these groups of variables and the above variables. The operation input I2 may be, for example, airflow rate, pressure, concentration, etc., in the gas phase; time, culture medium flow rate, fresh culture medium component concentration, cell suspension concentration, droplet generation rate, etc., in the liquid phase; and time, travel distance, culture vessel operating speed, dust generation rate, etc., in the solid phase.

[0021] The operational output O2 from the second target system S2 is similar to the set of variables of the operational input I2, but is a more physicochemically organized set of variables than the set of variables of the operational input I2. For example, in the gas phase, the operational output O2 may be air permeability velocity, pressure, mass transfer velocity, etc.; in the liquid phase, it may be time, medium inflow linear velocity, Reynolds number, medium component concentration, cell suspension concentration, droplet generation velocity, etc.; and in the solid phase, it may be travel distance, culture vessel operating speed, dust generation velocity, etc.

[0022] The operational input I3 for the first target system S1 is similar to the set of variables for the operational output O2, but is a more biologically organized set of variables than the set of variables for the operational output O2. For example, the operational input I3 may be pressure, gas composition, etc., if it is in the gas phase; time, shear stress, dissolved oxygen concentration, culture medium component concentration, cell suspension concentration, droplet / particle contamination probability, etc., if it is in the liquid phase; and time, inertial force, cumulative energy amount, etc., if it is in the solid phase. Cell behavior (response) occurs when the operational input I3 is applied to the first target system S1.

[0023] The response output O3 from the first target system S1 is similar to the set of variables in the operational input I3, but is a more biologically organized set of variables than the set of variables in the operational input I3. The response output O3 may be, for example, cell arrangement indicators, cell state indicators, environmental state indicators, three-dimensional structure indicators, spatial state indicators, etc. Cell arrangement indicators may be the spatial coordinate positions of individual cells. Cell state indicators may be biological indicators related to cell behavior, such as cell cycle, cell division and migration, intercellular bonding, cell adhesion, lag time, cell activity, differentiation, aging, methylation frequency, degree of anomaly, adhesion ability, migratory ability, and cell potency (collagen remodeling ability, degree of DNA damage). Environmental state indicators may be environmental indicators such as the amount of culture medium components, the amount of products, the degree of cell encirclement, the amount of culture surface adhesion proteins, the mechanical field, and the concentration of contaminating particles. Three-dimensional structure indicators may be shape indicators representing the structure of the cell population, such as thickness, diameter, roughness, and lumen volume. Spatial condition indicators may include indicators related to the environment of the operating space (airflow conditions in the environment) and indicators related to dust and droplet generation by the operator (e.g., dust generation rate, amount of particles adsorbed in the space, droplet generation rate, droplet flight range and concentration distribution, etc.).

[0024] The response output O4 from the second target system S2 is an output index of the cell population in the culture system, calculated and output using the response output O3 as input I4. The response output O4 is similar to the variable set of the response output O3, and consists of variables such as the spatial distribution and average amount of the variable set of the response output O3, population characteristic indices in the cell population, and their temporal and spatial heterogeneity indices. The response output O4 may be, for example, a spatial cell arrangement (three-dimensional structure) index, a spatial cell state index, a spatial environmental state index, a spatial state index, a population index, or a spatial heterogeneity index. A population index is an index that represents the cell population using representative values ​​such as the population frequency for each cell capability separated by single-cell analysis, etc. A spatial heterogeneity index is an index that represents spatial variability, for example, global heterogeneity and local heterogeneity.

[0025] The response output O5 from the third target system S3 is an output index between culture systems, calculated and output using the response output O4 as input I5. The response output O5 is similar to the variable group of the response output O3 and is an index of variability with respect to the spatial distribution and mean amount of the variable group of the response output O3. The response output O5 may be, for example, a spatial cell arrangement (three-dimensional structure) index, a spatial cell state index, a spatial environmental state index, a spatial state index, a population index, a spatial heterogeneity index, a stability index, an instability index, etc. Stability is an index that represents the stability of the process between batches and between containers, and the instability index is an index that shows deviations that occur occasionally and an index that shows the frequency of outlier occurrences.

[0026] (Overview of Information Processing System 100) First, an overview of the information processing system 100 will be provided. In the information processing system 100, the information processing device 1 determines target parameters, including conditions to be set in the manufacturing process of the target object (cells) carried out in the research and development facility 300 and / or the manufacturing facility 400. The target parameters include, as the above conditions, input parameters for multiple operations included in each unit operation of each unit process in the manufacturing process. Specifically, the information processing device 1 performs a simulation of cell manufacturing based on a simulation model and generates virtual data including virtual parameters set in the simulation and virtual manufacturing data relating to the virtually manufactured object. In other words, the information processing device 1 can be considered as a virtual laboratory and / or virtual factory in the information processing system 100. The information processing device 1 also acquires actual data generated by actually manufacturing or using cells in each of the research and development facility 300, the manufacturing facility 400, and the product utilization facility 500. The information processing device 1 integrates the actual data and virtual data to generate integrated data. Then, the information processing device 1 determines the target parameters based on the integrated data. The details of the information processing device 1 will be described below.

[0027] (Research and Development Facility 300) The research and development facility 300 is a facility for conducting research and development related to cell manufacturing. The research and development facility 300 comprises a first control device 301 and a research and testing device 302 (first facility). The research and testing device 302 may include multiple devices. In the research and development facility 300, the manufacturing process is carried out using the research and testing device 302. In the research and development facility 300, the entity that manufactures cells (first entity) may be a human or a robot, and some operations in the manufacturing process may be performed by a human and other operations by a robot.

[0028] The first control device 301 manages various types of information in the research and development facility 300. For example, the first control device 301 collects first actual data 24, which includes actual parameters including conditions set in the manufacturing process carried out using the research and testing device 302 (hereinafter also referred to as first conditions), and actual manufacturing data related to the cells produced by the manufacturing process (hereinafter also referred to as first actual manufacturing data).

[0029] The first condition described above includes the parameters of the inputs to the first target system S1, the second target system S2, and the third target system S3 in the research and development facility 300, i.e., the parameters of the operation inputs I1 to I3 shown in Figure 3.

[0030] The first actual manufacturing data described above may include, for example, at least one of the quality and yield of cells produced by the manufacturing process in the research and development facility 300. The first actual manufacturing data may also include response outputs O3 to O5 output from the first target system S1, the second target system S2, and the third target system S3 in the research and development facility 300. In other words, the first actual data 24 may include parameters measured and / or generated in the process of actually manufacturing cells using the research and development facility 300.

[0031] The first management device 301 outputs the collected first actual data 24 to the information processing device 1 via the network 900.

[0032] (Manufacturing Equipment 400) Manufacturing equipment 400 is equipment that scales up and carries out cell manufacturing under the manufacturing conditions that were studied and determined in research and development equipment 300. When manufacturing equipment 400 is used, the amount of cells produced in one manufacturing process is greater than when research and development equipment 300 is used. Manufacturing equipment 400 is equipped with a second control device 401 and a manufacturing device 402 (second equipment). The manufacturing device 402 may include multiple devices. In manufacturing equipment 400, the manufacturing process is carried out using the manufacturing device 402.

[0033] In the manufacturing facility 400, the entity that manufactures the cells (second entity) may be a human or a robot, and the human may perform some of the operations in the manufacturing process while the robot performs other operations.

[0034] The second control device 401 manages various types of information in the manufacturing equipment 400. For example, the second control device 401 collects second actual data 25, which includes actual parameters including conditions set in the manufacturing process carried out using the manufacturing device 402 (hereinafter also referred to as second conditions), and actual manufacturing data related to the cells produced by the manufacturing process (hereinafter also referred to as second actual manufacturing data).

[0035] The second condition described above includes the parameters of the inputs to the first target system S1, the second target system S2, and the third target system S3 in the manufacturing equipment 400, i.e., the parameters of the operation inputs I1 to I3 shown in Figure 3.

[0036] The second actual manufacturing data described above may include, for example, at least one of the quality and yield of cells produced by the manufacturing process in the manufacturing equipment 400. The second actual manufacturing data may also include response outputs O3 to O5 output from the first target system S1, the second target system S2, and the third target system S3 in the manufacturing equipment 400. In other words, the second actual data 25 may include parameters measured and / or generated in the process of actually manufacturing cells using the manufacturing equipment 400.

[0037] The second management device 401 outputs the collected second actual data 25 to the information processing device 1 via the network 900.

[0038] (Product Utilization Facility 500) The product utilization facility 500 is a facility that utilizes cells manufactured in the manufacturing facility 400. The product utilization facility 500 may be, for example, a hospital or a clinical trial facility. In the product utilization facility 500, cells manufactured in the manufacturing facility 400 are used by users, and actual effect data showing the effects of using the cells is obtained. Hereafter, this actual effect data will also be referred to as the third actual data 26.

[0039] The product utilization equipment 500 is equipped with a third management device 501. The third management device 501 collects third actual data 26 and outputs the collected third actual data 26 to the information processing device 1 via the network 900.

[0040] (Information Processing Device 1) The information processing device 1 comprises an input unit 2 for receiving input to the information processing device 1, a display unit 3 for displaying various types of information, a storage unit 20, and a control unit 10.

[0041] The storage unit 20 stores various data used by the information processing device 1. For example, the storage unit 20 stores a group of simulation models 21. The group of simulation models 21 includes a first model 211, a second model 212, a third model 213, a fourth model 214, and a fifth model 215.

[0042] The first model 211 is a model of an operation model set for operations performed in a manufacturing process using the research and development equipment 300 or the manufacturing equipment 400. The first model 211 consists of a group of cell behavior modules that can represent cell characteristics and / or raw material characteristics, a group of environment modules that can represent the cell culture environment, and a group of culture operation modules that can reflect work characteristics. The first model 211 models the first target system S1, the second target system S2, and the third target system S3 shown in Figure 3. By inputting operation inputs I1 to I3 as input values ​​to the first model 211, response outputs O3 to O5 are virtually output.

[0043] The second model 212 is a second model set for the environment and / or space of the facility where the manufacturing process using the research and development facility 300 or the manufacturing facility 400 is carried out. The second model 212 is a simulation model that outputs a group of parameters indicating a person and / or a movement path (conducting wire) in the facility where the manufacturing process is carried out, as well as a group of space parameters for a sterile environment, by inputting space coordinates for the external (and internal if necessary) structure of facilities, devices, etc. in the space, the space movement speed of people and machines (including robots) performing operations, etc. By the second model 212, a person and / or a movement path (conducting wire) in the facility where the manufacturing process is carried out can be represented, and the movement time and / or the fluctuation of the sterile environment at that time can be evaluated.

[0044] The third model 213 is a model set for the costs and / or time required to carry out the manufacturing process using the research and development facility 300 or the manufacturing facility 400. The third model 213 is designed to output, as output, a group of parameters related to manufacturing costs (hereinafter also referred to as a manufacturing cost parameter group) for each of the first model 211 and the second model 212. From the manufacturing cost parameter group output from the third model 213, labor costs, consumable costs, construction costs, manufacturing risk costs, etc. can be obtained. Thereby, the cost calculation during research and development in the research and development facility 300 and / or the cost during the development and actual manufacturing of the manufacturing process in the manufacturing facility 400 can be calculated, and business judgment can be supported.

[0045] The fourth model 214 is a model generated based on the correlation between cell quality data and treatment results. The fourth model 214 outputs a virtual treatment result by a virtual cell by inputting parameters of the quality data of the virtual cell. By using the fourth model, it is possible to carry out the development for doctors and / or patient support.

[0046] The fifth model 215 is a model determined by the model determination unit 12 described later. Details of the fifth model 215 will be described later.

[0047] In addition, the storage unit 20 stores (1) integrated data 22 generated by a data integration unit 15 described later, (2) virtual data 23 generated by a virtual data generation unit 13 described later, and (3) first actual data 24, second actual data 25, and third actual data 26 acquired by an actual data acquisition unit 14 described later.

[0048] The control unit 10 comprehensively controls each unit of the information processing apparatus 1. The control unit 10 includes a request reception unit 11, a model determination unit 12, a virtual data generation unit 13, an actual data acquisition unit 14, a data integration unit 15, a model update unit 16, and a condition determination unit 17.

[0049] The request reception unit 11 receives requests from the user. The request reception unit 11 may receive from the user a request for generating conditions to be set in the manufacturing process performed in the research and development facility 300 in order to manufacture cells having a predetermined quality using the research and development facility 300. The request reception unit 11 may receive from the user a request for generating conditions to be set in the manufacturing process performed in the research and development facility 300 in order to manufacture cells at a predetermined yield (in other words, at a yield equal to or higher than a predetermined yield) using the research and development facility 300. The request reception unit 11 may receive from the user a request for generating conditions to be set in the manufacturing process performed in the manufacturing facility 400 in order to manufacture cells having a predetermined quality using the manufacturing facility 400. The request reception unit 11 may receive from the user a request for generating conditions to be set in the manufacturing process performed in the manufacturing facility 400 in order to manufacture cells at a predetermined cost using the manufacturing facility 400.

[0050] The model determination unit 12 determines an integrated model (hereinafter also referred to as the fifth model 215), which is a simulation model including at least any one of the first model 211, the second model 212, the third model 213, and the fourth model 214 stored in the storage unit 20, in response to the request received by the request reception unit 11. In other words, the model determination unit 12 generates the fifth model 215.

[0051] For example, if the model determination unit 12 is asked to determine parameters for producing cells of a predetermined quality using the research and development equipment 300, it may determine the first model 211 as the fifth model 215.

[0052] As another example, if the model determination unit 12 is requested to provide conditions for establishing a new facility in the manufacturing facility 400 to produce cells of a desired quality, it may determine a fifth model 215 by integrating the first model 211, the second model 212, and the third model 213. By including the second model 212 and the third model 213 in the fifth model 215, a simulator can be performed that takes into account the layout of the manufacturing apparatus 402, manufacturing risks, and manufacturing costs. Furthermore, by integrating the first model 211, the second model 212, and the third model 213 into a fifth model 215, it is possible to simulate the spatial design and manufacturing process design of the manufacturing facility 400 based on data obtained in the research and development facility 300. When integrating multiple models, the model determination unit 12 may integrate them using correlation parameters between the parameter groups of each model. The model determination unit 12 stores the determined fifth model 215 in the storage unit 20.

[0053] The virtual data generation unit 13 generates virtual data 23 by performing a simulation based on the fifth model 215 determined by the model determination unit 12 and stored in the storage unit 20. The virtual data 23 includes virtual parameters, including the conditions set for executing the simulation based on the fifth model 215, and virtual manufacturing data relating to cells virtually manufactured by the simulation. The virtual data generation unit 13 stores the generated virtual data 23 in the storage unit 20.

[0054] The actual data acquisition unit 14 acquires data from the research and development equipment 300, the manufacturing equipment 400, and the product utilization equipment 500. In other words, the actual data acquisition unit 14 collects data from the research and development equipment 300, the manufacturing equipment 400, and the product utilization equipment 500. The actual data acquisition unit 14 comprises a first actual data acquisition unit 141, a second actual data acquisition unit 142, and a third actual data acquisition unit 143.

[0055] The first real data acquisition unit 141 acquires the first real data 24 from the research and development equipment 300 (more specifically, the first control device 301). The first real data acquisition unit 141 stores the acquired first real data 24 in the storage unit 20.

[0056] The second actual data acquisition unit 142 acquires the second actual data 25 from the manufacturing equipment 400 (more specifically, the second control device 401). The second actual data acquisition unit 142 stores the acquired second actual data 25 in the storage unit 20.

[0057] The third actual data acquisition unit 143 acquires the third actual data 26 from the product utilization equipment 500 (more specifically, the third management device 501). In this embodiment, as shown in Figure 1, the third actual data acquisition unit 143 is configured to acquire the third actual data 26 via the manufacturing equipment 400, but the third actual data 26 may also be acquired directly from the third management device 501. The third actual data acquisition unit 143 stores the acquired third actual data 26 in the storage unit 20.

[0058] The data integration unit 15 integrates at least one of the first real data 24, the second real data 25, and the third real data 26 with the virtual data 23 to generate integrated data 22. For example, the data integration unit 15 may generate integrated data 22 (first integrated data) by integrating the first real data 24 and the virtual data 23. Alternatively, the data integration unit 15 may generate integrated data 22 (second integrated data) by integrating the first real data 24, the second real data 25, and the virtual data 23. Furthermore, the data integration unit 15 may generate integrated data 22 (third integrated data) by integrating the first real data 24, the third real data 26, and the virtual data 23. The data integration unit 15 stores the generated integrated data 22 in the storage unit 20.

[0059] The data integration unit 15 updates the integrated data 22 to include the newly acquired data when it acquires at least one of the first actual data 24, second actual data 25, and third actual data 26. Furthermore, the data integration unit 15 updates the integrated data 22 to include the newly generated virtual data when it generates virtual data 23.

[0060] The model update unit 16 updates the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 using at least a portion of the integrated data 22. The model update unit 16 may also update the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 when the integrated data 22 is updated by the data integration unit 15. As a result, the model update unit 16 can update the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 when new virtual data 23 is generated by newly acquiring at least one of the first real data 24, second real data 25, and third real data 26.

[0061] As described above, the integrated data 22 includes real data (first real data 24, second real data 25, and third real data 26) and virtual data 23. Therefore, the model update unit 16 can update the model using more data than when updating the model using only real data. As a result, the model update unit 16 can update the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 to models with high simulation accuracy. In other words, to update the simulation model group 21, the model update unit 16 uses integrated data 22, which has an increased amount of data due to the virtual data 23 generated using the simulation model group 21 compared to the case using only real data. This allows the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 to be updated to models with high accuracy and precision.

[0062] The condition determination unit 17 determines a first target parameter that includes conditions to be set in the manufacturing process of the research and development equipment 300 or manufacturing equipment 400, in accordance with the request received by the request reception unit 11. For example, the condition determination unit 17 may determine the first target parameter based on the correlation between (1) actual manufacturing data and virtual manufacturing data and (2) actual parameters and virtual parameters in the integrated data 22. For example, the condition determination unit 17 may determine the first target parameter based on the above correlation for the purpose of optimizing efficiency, optimizing stability, or minimizing instability in cell manufacturing.

[0063] The condition determination unit 17 may, for example, perform sensitivity analysis on the actual manufacturing data, virtual manufacturing data, actual parameters, and virtual parameters included in the integrated data 22 to calculate the degree of influence of the input parameters on efficiency and / or variability, thereby determining the priority of the parameters to be determined as the first target parameters. This reduces the number of trials required to determine suitable conditions in the research and development facility 300 and / or the manufacturing facility 400. This reduces the time and cost required for development.

[0064] The condition determination unit 17 may determine, for example, a first target parameter for producing cells of a predetermined quality using the research and development equipment 300 or the manufacturing equipment 400. Alternatively, the condition determination unit 17 may determine a first target parameter for producing cells at a predetermined yield using the research and development equipment 300 or the manufacturing equipment 400. The condition determination unit 17 may determine the first target parameter using machine learning such as deep learning.

[0065] The condition determination unit 17 includes a test condition determination unit 171 and a manufacturing condition determination unit 172. The test condition determination unit 171 determines a first target parameter including the conditions to be set in the manufacturing process of the research and development equipment 300. The manufacturing condition determination unit 172 determines a first target parameter including the conditions to be set in the manufacturing process of the manufacturing equipment 400.

[0066] (An example of processing performed by the information processing device 1) Next, an example of processing (control method) in the information processing device 1 will be described. Figure 4 is a flowchart of an example of processing performed by the information processing device 1. In this example, it will be explained that the user has requested the generation of conditions to be set in the manufacturing process carried out in the research and development equipment 300 in order to produce cells with a predetermined yield using the research and development equipment 300.

[0067] First, as a premise, it is assumed that the first model 211, the second model 212, the third model 213, and the fourth model 214, which were generated in advance using predetermined parameters, are stored in the storage unit 20.

[0068] In this example, as shown in Figure 4, first, the request receiving unit 11 receives a request from the user (step S11).

[0069] Next, the model determination unit 12 determines an integrated model (i.e., the fifth model 215) for generating the conditions to be set in the manufacturing process carried out in the research and development facility 300 (step S12). Specifically, the model determination unit 12 determines the fifth model 215 by integrating the models necessary to generate the above conditions from the first model 211, second model 212, third model 213, and fourth model 214 stored in the storage unit 20.

[0070] Next, the actual data acquisition unit 14 acquires the first actual data 24, the second actual data 25, and the third actual data from the research and development equipment 300, the manufacturing equipment 400, and the product utilization equipment 500, respectively (step S13, actual data acquisition step). Note that the processing in step S13 may be performed before step S11.

[0071] Next, the virtual data generation unit 13 performs simulations based on the first model 211, the second model 212, the third model 213, the fourth model 214, and the fifth model 215, and generates virtual data 23 (step S14, virtual data generation step). Note that step S14 may be performed before step S13.

[0072] Next, the data integration unit 15 integrates the first actual data 24, the second actual data 25, and the third actual data 26 with the virtual data 23 to generate integrated data 22 (step S15, data integration step).

[0073] Next, the model update unit 16 updates the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 using at least a portion of the integrated data 22 (step S16, model update step). The model update unit 16 may update all of the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215, or it may update only some of them.

[0074] In one aspect of this disclosure, the processing from step S12 may be repeated after step S16. That is, a simulation may be performed based on the updated first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 to generate new virtual data 23. Then, the integrated data 22 may be updated using the generated virtual data 23, and the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 may be updated using the updated integrated data 22. This makes it possible to further improve the accuracy of the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215.

[0075] Next, the condition determination unit 17 determines the conditions (first target parameters) to be set in the manufacturing process carried out at the research and development facility 300 based on the correlation between (1) actual manufacturing data and virtual manufacturing data and (2) actual parameters and virtual parameters in the integrated data 22 (step S17).

[0076] As described above, the information processing device 1 in this embodiment updates the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 using integrated data 22, which is obtained by integrating actual data (first actual data 24, second actual data 25, third actual data 26) acquired by the actual data acquisition unit 14 from the research and development equipment 300, manufacturing equipment 400, and product utilization equipment 500, with virtual data 23 generated by performing simulations based on the model. With the above configuration, since the model is updated using integrated data 22 which is obtained by integrating actual data and virtual data 23, the data used to update the model can be theoretically based data. Therefore, the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 can be created with high accuracy. Then, the first target parameters can be determined based on the integrated data 22, which includes virtual data generated by performing simulations based on the highly accurate first model 211, second model 212, third model 213, fourth model 214, and fifth model 215. This allows the first target parameters to be set with high accuracy.

[0077] Furthermore, in the information processing system 100 of this embodiment, an instability index can be included as the output of the first model 211, making the first model 211 a model capable of representing fluctuations. As a result, by using the first model 211, it is possible to optimize not only product quality and yield, but also the stabilization of product manufacturing and / or the suppression of instability.

[0078] Furthermore, in the information processing system 100 of this embodiment, the data integration unit 15 generates integrated data 22 (second integrated data) by integrating the first real data 24, the second real data 25, and the virtual data 23, and the model update unit 16 may update the first model 211, the second model 212, the third model 213, the fourth model 214, and the fifth model 215 using at least a part of the second integrated data. This makes it possible to update each model with integrated data that includes the manufacturing results obtained at the research and development facility 300 and the manufacturing results obtained at the manufacturing facility 400. As a result, it is possible to consistently predict and manage cell production from research and development at the research and development facility 300 to actual production at the manufacturing facility 400.

[0079] Furthermore, in the information processing system 100 of this embodiment, the data integration unit 15 may generate integrated data 22 (third integrated data) by integrating the first integrated data and the third actual data 26 (actual effect data), and the model update unit 16 may update the first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 using at least a part of the third integrated data. This makes it possible to create first model 211, second model 212, third model 213, fourth model 214, and fifth model 215 in which the quality of the cells to be manufactured is associated with the treatment results. In this case, the condition determination unit 17 may determine target parameters (second target parameters) including conditions to be set in the manufacturing process in order to manufacture cells whose effect from use is above a predetermined level, based on the correlation between (1) actual manufacturing data and virtual manufacturing data, (2) actual parameters and virtual parameters, and (3) actual effect data in the third integrated data.

[0080] Furthermore, in the information processing system 100 of this embodiment, if all operations in the manufacturing process of the research and development equipment 300 and / or the manufacturing equipment 400 are performed by robots, in other words, automatically, the first target parameters determined by the condition determination unit 17 can be used as setting conditions (in other words, parameters for each of the above operations) to be input to each device installed in the research and development equipment 300 and / or the manufacturing equipment 400, thereby enabling unmanned and automated cell production.

[0081] In one embodiment of the information processing system 100 of this disclosure, when the request receiving unit 11 receives a request from a user to generate conditions to be set for manufacturing a new cell different from conventional cells from the research and development equipment 300 or other research and development equipment, the model determination unit 12 may determine a new fifth model 215 by modifying the fifth model 215 that was determined (generated) before the request was received, using the difference between the manufacturing of conventional cells and the manufacturing of new cells as a new element. This makes it possible to reduce the time and cost required from research and development of new cells to actual manufacturing.

[0082] [Example of implementation by software] The functions of the information processing device 1 (hereinafter referred to as "device") can be realized by a program that causes the device to function as a computer, and by a program that causes each control block of the device (especially each part included in the control unit 10) to function as a computer.

[0083] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., memory) as hardware for executing the program. By executing the program using this control device and storage device, the functions described in each of the embodiments are realized.

[0084] The above program may be recorded on one or more computer-readable recording media, not temporary ones. These recording media may or may not be provided by the above device. In the latter case, the program may be supplied to the above device via any wired or wireless transmission medium.

[0085] Furthermore, some or all of the functions of each of the above-mentioned control blocks can also be realized by logic circuits. For example, an integrated circuit in which logic circuits functioning as each of the above-mentioned control blocks are formed is also included in the scope of the present invention. In addition, it is also possible to realize the functions of each of the above-mentioned control blocks by, for example, a quantum computer. The present invention is not limited to the embodiments described above, and various modifications are possible within the scope of the claims, and embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention.

[0086] [Summary] An information processing system according to Embodiment 1 of the present disclosure includes: a real data acquisition unit that acquires first real data including real parameters including conditions set in a manufacturing process carried out by a first entity for actually manufacturing an object using first equipment, and real manufacturing data relating to the object manufactured by the manufacturing process; a virtual data generation unit that generates virtual data including virtual parameters including conditions set for executing a simulation based on a simulation model set for the manufacturing process, and virtual manufacturing data relating to the object virtually manufactured by the simulation; a data integration unit that integrates the first real data and the virtual data to generate first integrated data; and a model update unit that updates the simulation model using at least a part of the first integrated data.

[0087] The information processing system according to aspect 2 of the present disclosure may, in aspect 1, further include parameters measured and / or generated in the process of actually manufacturing the object using the first equipment.

[0088] The information processing system according to aspect 3 of the present disclosure further comprises a condition determination unit that determines a first target parameter including conditions to be set in the manufacturing process for (1) to manufacture the object having a predetermined quality using the first equipment, and / or (2) to manufacture the object with a predetermined yield using the first equipment, wherein the condition determination unit may be configured to determine the first target parameter based on the correlation between (1) the actual manufacturing data and the virtual manufacturing data and (2) the actual parameter and the virtual parameter in the first integrated data.

[0089] The information processing system according to aspect 4 of the present disclosure may be configured such that, in any of aspects 1 to 3 above, the actual data acquisition unit further acquires actual parameters including conditions set in the manufacturing process carried out by a second entity in order to actually manufacture the object using a second piece of equipment different from the first equipment, and second actual data including actual manufacturing data relating to the object manufactured by the manufacturing process; the data integration unit integrates the first actual data, the second actual data, and the virtual data to generate second integrated data; and the model update unit updates the simulation model using at least a portion of the second integrated data.

[0090] The information processing system according to aspect 5 of this disclosure may be configured such that, in aspect 4, the amount of the object produced in one manufacturing process is greater than when the first equipment is used, when the second equipment is used.

[0091] In the information processing system according to aspect 6 of this disclosure, the first entity may be a human or a robot in any of aspects 1 to 5 described above.

[0092] The information processing system according to Embodiment 7 of the present disclosure may further include a model determination unit that determines the simulation model, which in any of Embodiments 1 to 6 above includes at least one of the following: (1) a first model set for an operation model set for an operation performed in the manufacturing process; (2) a second model set for the environment and / or space of the facility where the manufacturing process is carried out; and (3) a third model set for the costs and / or time required to carry out the manufacturing process.

[0093] The information processing system according to aspect 8 of the present disclosure may, in aspect 3 above, include a manufacturing process which is performed by a predetermined device, and the first target parameter may include setting conditions which are input to the predetermined device.

[0094] In any of the embodiments 1 to 8 described above, the information processing system according to aspect 9 of this disclosure is such that the subject object may be at least one of the following: extracellular vesicles, viruses, proteins, macromolecules, genes, small molecules, pharmaceuticals, diagnostic agents, chemical products, food products, or agricultural products.

[0095] The information processing system according to aspect 10 of this disclosure may be configured such that, in any of aspects 1 to 9 above, the object is a cell, and the manufacturing process includes a cell processing step for processing the cell.

[0096] The information processing system according to aspect 11 of this disclosure may be configured such that the cell processing step includes a culture step for culturing the cells, in aspect 10 described above.

[0097] In any of the embodiments 1 to 11, the information processing system according to embodiment 12 of this disclosure is such that the actual manufacturing data may include data that includes at least one of the quality and yield of the object manufactured by the manufacturing process.

[0098] The information processing system according to aspect 13 of the present disclosure may be configured such that, in aspect 3, the actual data acquisition unit further acquires actual effect data showing the effect of using the object by a user who has used the object; the data integration unit integrates the first integrated data and the actual effect data to generate third integrated data; and the condition determination unit determines a second target parameter, which includes conditions to be set in the manufacturing process in order to manufacture the object whose effect is above a predetermined level, based on the correlation between (1) the actual manufacturing data and the virtual manufacturing data, (2) the actual parameters and the virtual parameters, and (3) the actual effect data in the third integrated data.

[0099] A control method for an information processing system according to aspect 14 of the present disclosure is a control method for an information processing system executed by one or more computers, comprising: (1) a real data acquisition step of acquiring first real data including real parameters including conditions set in a manufacturing process carried out by a first entity in order to actually manufacture an object using first equipment, and real manufacturing data relating to the object manufactured by the manufacturing process; a virtual data generation step of generating virtual data including virtual parameters including conditions set in order to execute a simulation based on a simulation model set for the manufacturing process, and virtual manufacturing data relating to the object virtually manufactured by the simulation; a data integration step of integrating the first real data and the virtual data to generate first integrated data; and a model update step of updating the simulation model using at least a portion of the first integrated data.

[0100] 1 Information Processing Device 12 Model Determination Unit 13 Virtual Data Generation Unit 14 Actual Data Acquisition Unit 15 Data Integration Unit 16 Model Update Unit 17 Condition Determination Unit 22 Integrated Data 23 Virtual Data 24 First Actual Data 25 Second Actual Data 26 Third Actual Data 100 Information Processing System 211 First Model 212 Second Model 213 Third Model 214 Fourth Model 215 Fifth Model 300 Research and Development Equipment 400 Manufacturing Equipment 500 Product Utilization Equipment

Claims

1. An information processing system comprising: a real data acquisition unit that acquires first real data including real parameters including conditions set in a manufacturing process carried out by a first entity for actually manufacturing an object using first equipment, and real manufacturing data relating to the object manufactured by the manufacturing process; a virtual data generation unit that generates virtual data including virtual parameters including conditions set for executing a simulation based on a simulation model set for the manufacturing process, and virtual manufacturing data relating to the object virtually manufactured by the simulation; a data integration unit that integrates the first real data and the virtual data to generate first integrated data; and a model update unit that updates the simulation model using at least a portion of the first integrated data.

2. The information processing system according to claim 1, wherein the actual parameters further include parameters measured and / or generated in the process of actually manufacturing the object using the first equipment.

3. The information processing system according to claim 1, further comprising a condition determination unit that determines a first target parameter including conditions to be set in the manufacturing process for (1) to manufacture the object having a predetermined quality using the first equipment, and / or (2) to manufacture the object at a predetermined yield using the first equipment, wherein the condition determination unit determines the first target parameter based on the correlation between (1) the actual manufacturing data and the virtual manufacturing data and (2) the actual parameter and the virtual parameter in the first integrated data.

4. The information processing system according to claim 1, wherein the actual data acquisition unit further acquires actual parameters including conditions set in the manufacturing process carried out by a second entity in order to actually manufacture the object using a second piece of equipment different from the first equipment, and second actual data including actual manufacturing data relating to the object manufactured by the manufacturing process; the data integration unit integrates the first actual data, the second actual data, and the virtual data to generate second integrated data; and the model update unit updates the simulation model using at least a portion of the second integrated data.

5. The information processing system according to claim 4, wherein when the second equipment is used, the amount of the object produced in one manufacturing process is greater than when the first equipment is used.

6. The information processing system according to claim 1, wherein the first entity is a human or a robot.

7. The information processing system according to claim 1, further comprising: a model determination unit that determines the simulation model which includes at least one of: (1) a first model set out for an operation model set out for an operation performed in the manufacturing process; (2) a second model set out for the environment and / or space of a facility in which the manufacturing process is carried out; and (3) a third model set out for the costs and / or time required to carry out the manufacturing process.

8. The information processing system according to claim 3, wherein the manufacturing process includes a process to be performed by a predetermined device, and the first target parameter includes setting conditions to be input to the predetermined device.

9. The information processing system according to claim 1, wherein the object is at least one of extracellular vesicles, viruses, proteins, macromolecules, genes, small molecules, pharmaceuticals, diagnostic agents, chemical products, food products, or agricultural products.

10. The information processing system according to claim 1, wherein the object is a cell, and the manufacturing process includes a cell processing step for processing the cell.

11. The information processing system according to claim 10, wherein the cell processing step includes a culture step of culturing the cells.

12. The information processing system according to claim 1, wherein the actual manufacturing data includes data relating to at least one of the quality and yield of the object manufactured by the manufacturing process.

13. The information processing system according to claim 3, wherein the actual data acquisition unit further acquires actual effect data showing the effect of using the object on a user who has used the object; the data integration unit integrates the first integrated data and the actual effect data to generate third integrated data; and the condition determination unit determines a second target parameter, which includes conditions to be set in the manufacturing process in order to manufacture the object whose effect is greater than or equal to a predetermined level, based on the correlation between (1) the actual manufacturing data and the virtual manufacturing data, (2) the actual parameters and the virtual parameters, and (3) the actual effect data in the third integrated data.

14. A method for controlling an information processing system performed by one or more computers, comprising: (1) a real data acquisition step of acquiring first real data including real parameters including conditions set in a manufacturing process performed by a first entity in order to actually manufacture an object using first equipment, and real manufacturing data relating to the object manufactured by the manufacturing process; a virtual data generation step of generating virtual data including virtual parameters including conditions set in order to perform a simulation based on a simulation model set for the manufacturing process, and virtual manufacturing data relating to the object virtually manufactured by the simulation; a data integration step of integrating the first real data and the virtual data to generate first integrated data; and a model update step of updating the simulation model using at least a portion of the first integrated data.

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