Apparatus, method, and program

Abstract

There is provided an apparatus including: a control parameter setting unit that sets a control parameter for a controller model, the controller model being included in a simulator of a cell culture system that controls an actuator through a controller according to a measurement result of a sensor, and the controller model being a simulation model of the controller; a simulator execution unit that executes the simulator in a state in which the control parameters are set for the controller model; and a delay time setting unit that sets a delay time for a sensor model, which is included in the simulator and is a simulation model of the sensor, in which the sensor model is simulated by the sensor after the delay time has elapsed from a point in time at which a measurement target of the sensor model fluctuates. The simulator execution unit causes the fluctuation to occur in a measurement result of the sensor model.

Description

Technical Field

[0001] The content of the following patent applications is incorporated herein by reference: No. 2023-054856, filed in Japan on March 30, 2023 The present invention relates to an apparatus, a method, and a program. Background Art

[0002] Patent Documents 1-9 and Non-Patent Document 1 disclose "a method for providing an optimized process specification for a cell culture process in a reactor system based on culture data of the cell culture process, including the steps of: obtaining culture data of the cell culture process; and adapting or generating at least one optimized process specification from the obtained culture data by applying a digital twin obtainable by the method according to any one of claims 1-6" (Claim 7 of Patent Document 4). (List of Cited Documents) (Patent Documents) Patent Document 1: International Publication No. 2020252442 Patent Document 2: U.S. Patent Application Publication No. 2019-153381 Patent Document 3: International Publication No. WO2020-238918 Patent Document 4: Japanese translation of PCT International Application Publication No. 2022-537799 Patent Document 5: Japanese Patent Application Publication No. 2019-041656 Patent Document 6: International Publication No. 2020-039683 Patent Document 7: International Publication No. 2021-166824 Patent Document 8: Japanese Patent Application Publication No. 2022-099096 Patent Document 9: Japanese Patent Application Publication No. 2018-049316 (Non-Patent Documents) Non-Patent Document 1: Sei Murakami, "Subcommittee 2, Current status and issues of continuous culture process", Journal of the Society for Biotechnology, Japan, Vol. 97, No. 6, pp. 338-341 Summary of the Invention

[0003] A first aspect of the present invention provides a device, comprising: a control parameter setting unit that sets control parameters for a controller model, the controller model being included in a simulator of a cell culture system, the cell culture system controlling an actuator through a controller according to measurement results of a sensor, and the controller model being a simulation model of the controller; and a simulator execution unit that executes the simulator in a state where the control parameters are set for the controller model. The control parameters may indicate control conditions of the actuator and may be parameters of feedback control.

[0004] The device may further include a delay time setting unit that sets a delay time for a sensor model, the sensor model being included in the simulator and being a simulation model of the sensor, and after a lapse of the delay time from a moment when a measurement target of the sensor model fluctuates, the simulator execution unit may cause the fluctuation to appear in the measurement result of the sensor model. The delay time may be the time between the moment when the measurement target of the sensor model fluctuates and the moment when the measurement result of the sensor model fluctuates, and may be set based on past culture data.

[0005] In any one of the devices, at least one sensor in the cell culture system may be an on-line sensor immersed in a culture solution and measuring a state of the culture solution, and the device may further include a drift parameter setting unit that sets a drift parameter for an on-line sensor model, the on-line sensor model being included in the simulator and being a simulation model of the on-line sensor, and the simulator execution unit may cause the measurement result of the on-line sensor model to drift according to the drift parameter.

[0006] Any one of the devices may further include an uncertainty parameter setting unit that sets one or more uncertainty parameters of a cell state in an incubator model, the incubator model being included in the simulator and being a simulation model of an incubator of the cell culture system, and the simulator execution unit may cause state uncertainty of the cells in the incubator model according to the uncertainty parameters.

[0007] The device may further include a determination unit that, based on the simulator executed multiple times in a state where one of the one or more uncertainty parameters is set, obtains values indicating execution results of each execution to determine whether a distribution of the values satisfies a predetermined condition. The predetermined condition may be a condition according to a control target, and a value of a process value assumed according to the sensor model may be its target value (or within a reference range of the target value).

[0008] Any one of the above-mentioned devices may further include a determination unit, which determines whether a value indicating an execution result satisfies a predetermined condition according to the simulator being executed.

[0009] Any one of the devices having the determination unit may include an output unit, which outputs the control parameter as a set value of the controller according to the determination by the determination unit that the value indicating the execution result satisfies the predetermined condition.

[0010] A second aspect of the present invention provides a method, including: setting a control parameter for a controller model, where the controller model is included in a simulator of a cell culture system, the cell culture system controls an actuator through a controller according to a measurement result of a sensor, and the controller model is a simulation model of the controller; and executing the simulator in a state where the control parameter has been set for the controller model.

[0011] A third aspect of the present invention provides a program that causes a computer to function as: a control parameter setting unit that sets a control parameter for a controller model, where the controller model is included in a simulator of a cell culture system, the cell culture system controls an actuator through a controller according to a measurement result of a sensor, and the controller model is a simulation model of the controller; and a simulator execution unit that executes the simulator in a state where the control parameter has been set for the controller model.

[0012] The abstract clause does not have to describe all the necessary features of the embodiments of the present invention. The present invention may also be a sub-combination of the above features. Brief Description of the Drawings

[0013] Figure 1 Shows a cell culture system 1 according to an embodiment. Figure 2 Shows a control loop 15 of the cell culture system 1. Figure 3 Shows a simulation device 2 according to an embodiment. Figure 4 Shows the operation of the simulation device 2. Figure 5 Shows an example of a computer 2200 that can implement all or part of the aspects of the present invention. Detailed Description of the Embodiments

[0014] Hereinafter, the present invention will be described by way of embodiments of the present invention, but the following embodiments do not limit the present invention according to the claims. In addition, not all combinations of the features described in the embodiments are essential for the solution of the present invention.

[0015] (1. Cell culture system 1) Figure 1 Figure 1 shows a cell culture system 1 according to the present embodiment. The cell culture system 1 performs cultivation to produce a target substance through a biological reaction. The cell culture system 1 can produce, for example, biopharmaceuticals such as antibody drugs, and can culture animal cells such as CHO cells. The cell culture system 1 may include an incubator 10, one or more actuators 11, one or more sensors 12, and a controller 13. The incubator 10, one or more sensors 12, the controller 13, and one or more actuators 11 may form one or more control loops (e.g., a closed control loop or an open control loop), and the cell culture system 1 can control the actuator 11 through the controller 13 based on the measurement results of the sensor 12.

[0016] (1.1 Incubator 10) The incubator 10 is a container for accommodating a culture medium and cells to culture the cells. To promote cell proliferation, the temperature, pH value, amount of dissolved oxygen (DO), etc. of the culture solution in the incubator 10 can be appropriately managed by the actuator 11. For example, perfusion culture can be performed in the incubator 10, and a culture medium can be continuously supplied to the incubator 10 at a stage when the cells have proliferated to a certain extent (e.g., the second to the third day from the start of cultivation) so that an amount of cell removal solution (harvest solution) equal to the supply amount is recovered from the incubator 10. In this way, the volume of the culture solution in the incubator 10 can be kept constant.

[0017] It should be noted that the incubator 10 may be provided with a manually operated sampling device 101 or a feeding device (not shown). The sampling device 101 can sample the culture solution in the incubator 10, and the feeding device can apply a feeding agent to the incubator 10 to supply a nutrient source. The sampling device 101 and the feeding device can be actuators 11 that are automatically operated.

[0018] (1.2. Actuator 11) Each actuator 11 is a driving device that performs physical movement, and can control at least one of the dissolved oxygen concentration, pH value, temperature, substrate concentration (glucose concentration), cell density, amount of culture solution, stirring speed, pressure, weight, volume, flow rate, etc. of the culture solution. Each actuator can be any one of a valve, a pump, a heater, a fan, a motor, and a switch.

[0019] In the present embodiment, for example, the cell culture system 1 may have a pump P1 for supplying a culture medium to the incubator 10, a pump P2 for supplying glucose to the incubator 10, a pump P3 for supplying an alkali (alkali solution) to the incubator 10, a stirring device 131 for stirring the culture solution in the incubator 10, a pump P4 for discharging the cells and the culture solution together from the incubator 10, and a pump P5 for discharging the harvest solution from the incubator 10 as the actuator 11.

[0020] Among these actuators 11, the pump P5 can discharge the harvest liquid from the incubator 10 via the cell removal device 102 and the flow cell 103. The cell removal device 102 can have a filtering function called TFF (tangential flow filtration) or ATF (alternating tangential flow filtration), and can discharge the harvest liquid from the incubator 10 while keeping the cells in the incubator 10.

[0021] (1.3 Sensor 12) Each sensor 12 measures the state of the incubator 10. Each sensor 12 can measure process values (also called process parameters, PV) indicating the dissolved oxygen concentration, pH value, temperature, substrate concentration (glucose concentration), cell density, culture solution volume, stirring speed, pressure, weight, volume, flow rate, etc. of the culture solution.

[0022] In the present embodiment, for example, the cell culture system 1 can have: a sensor (not shown) for measuring the weight of the incubator 10, sensors (not shown) for measuring the volume and weight of the fluid provided by the pumps P1 to P3, a sensor (not shown) for measuring the cell density, a dielectric spectrometer 121 for measuring the dielectric constant of the culture solution, a near-infrared / infrared / Raman spectrometer 122 for measuring the nutrient components and metabolic components of the culture solution, an analysis device 124 for analyzing the components of the culture solution, and an in-line sensor 120 immersed in the culture solution to measure the state of the culture solution as the sensor 12.

[0023] Among these sensors 12, the dielectric spectrometer 121 can measure the dielectric constant of the culture solution based on the current flowing between the electrodes 1210 inserted in the culture solution, and can further measure the number and viability of cells in the culture solution based on the measured dielectric constant.

[0024] The near-infrared / infrared / Raman spectrometer 122 can irradiate the culture solution with various types of measurement light (near-infrared light, infrared light, monochromatic light) through the light receiving and emitting sensor 1220 inserted in the culture solution to measure the near-infrared spectrum, infrared spectrum, Raman spectrum, etc. of the light transmitted through or reflected from the culture solution; and can further measure glucose, lactate, ammonia, various amino acids, etc. in the culture solution based on the measured spectrum. It should be noted that when the measurement is performed by the near-infrared / infrared / Raman spectrometer 122, the measurement can be performed by the following methods: constructing a calibration model using a solution with a pre-adjusted component concentration; and converting the spectrum obtained from the light receiving and emitting sensor 1220 immersed in the incubator 10 into a component concentration through the calibration model. The light receiving and emitting sensor 1220 can be provided in the flow cell 103.

[0025] The analysis device 124 can be, for example, a high performance liquid chromatography (HPLC) device, a cell culture analysis device, etc. The analysis device 124 can analyze the components of the culture solution sampled from the incubator 10 by the sampling device 101 at a reference time interval (e.g., 24 hours) in an offline state (i.e., away from the incubator 10).

[0026] The on-line sensor 120 can be immersed in the culture solution to measure the state of the culture solution during the cell culture process. For example, the on-line sensor 120 can measure at least one of the basic physical and chemical parameters such as pH value, dissolved oxygen (DO) amount, temperature, gas partial pressure (oxygen partial pressure, carbon dioxide partial pressure, etc.), osmotic pressure, nutrient components, metabolic components, or target product concentration in the culture solution. The electrode 1210 of the dielectric spectrometer 121 and the light receiving and emitting sensor 1220 of the near-infrared / infrared / Raman spectrometer 122 can be the on-line sensor 120. It should be noted that due to the change of the culture environment, drift will occur in the measurement results of the on-line sensor 120. Examples of factors that cause changes in the culture environment include fluctuations in mechanical stress occurring in the culture solution due to stirring or gas ventilation, consumption of nutrients and oxygen in the culture solution, and accumulation of waste products (also called residues, impurities) such as lactate and ammonia generated by cells.

[0027] Among one or more sensors 12 included in the cell culture system 1, at least one sensor 12 can be provided with a noise removal filter for removing noise from the measurement results. The noise removal filter may cause a delay between the moment when fluctuations occur in the measurement target of the sensor 12 and the moment when fluctuations occur in the measurement results of the sensor 12.

[0028] Each sensor 12 can perform measurements within a preset period. Each sensor 12 can provide the measurement results to the controller 13 as process values. Each sensor 12 can perform calibration at any time.

[0029] It should be noted that the process value can be obtained by sampling the culture solution at a reference frequency (e.g., once a day) and performing analysis by the analysis device 124. The cell density measured by the dielectric spectrometer 121 etc. can be calculated by analyzing the images taken by staining the culture solution. The nutrient components / metabolic components measured by the near-infrared / infrared / Raman spectrometer 122 etc. can be measured by using enzyme sensors etc.

[0030] (1.4 Controller 13) The controller 13 can control one or more actuators 11 based on the measurements of one or more sensors 12. For example, the controller 13 can control the actuator 11 by providing a control signal indicating a manipulated variable calculated based on the measurements of the sensor 12 to the actuator 11. The controller 13 can scale (e.g., normalize) the measurements of one or more sensors 12 and then use the scaled measurements to calculate the manipulated variable.

[0031] The controller 13 can control the cultivation process in the cell culture system 1 by controlling one or more actuators 11 based on the measurements of one or more sensors 12. For example, the controller 13 can: monitor the state of the culture medium in the incubator 10; perform various controls related to the perfusion culture process (operation control of various pumps, motors, etc. and temperature control, etc.); and control the supply amount, recovery amount, ventilation amount, perfusion rate, etc. in the incubator 10. For example, while controlling basic process values such as the dissolved oxygen concentration, pH value, temperature, substrate concentration (glucose concentration), cell density, culture medium volume, and stirring speed of the culture medium, the controller 13 can add nutrient components contained in the culture medium or promoters that enhance the cell proliferation or production rate.

[0032] In the controller 13, a target value (also referred to as a set value SV) of the process value can be set. When the target value is set, the controller 13 can calculate a manipulated variable that causes the process value to reach the target value (or within the reference range of the target value) and control the actuator 11. When the cell culture system 1 has multiple control loops, target values can be set for each control loop in the controller 13. The target value of the process value can be set by an operator to achieve any control objective.

[0033] The control objective can be an objective related to the steady-state characteristics, and for example, when the state of the incubator 10 is in a steady state, the process value (PV) is within the reference range of the target value (SV). The control objective can be an objective related to the transient characteristics, and for example, the settling time (also referred to as the response delay time) until the process value reaches the target value (or within the reference range of the target value) is less than the reference time. The control objective can be an objective related to the tracking of the target value, and for example, when changing the target value of any process value and performing cell culture, the control objective can be that the rate at which the process value reaches the target value (or within the reference range of the target value) (also referred to as the tracking rate) exceeds the reference rate.

[0034] In the controller 13, control parameters can be set. The control parameters can be parameters indicating the control conditions of the actuator 11 and can be, for example, parameters of feedback control (also referred to as feedback control parameters). For example, the feedback control parameters can be at least one of a proportional gain, an integral gain, or a derivative gain. The control parameters can be parameters indicating the output frequency or control period of the control signal of the actuator 11 (also referred to as frequency parameters) and can be the upper / lower limits of the manipulated variable (also referred to as the manipulated variable of the actuator 11) provided to the actuator 11 for instruction. For example, the upper / lower limits of the manipulated variable can be set to 0 (%) to 100 (%), -50 (%) to 50 (%), etc.

[0035] The controller 13 can maintain the cell density in the incubator 10 within an appropriate range by discharging (wherein cells and the culture solution are discharged from the incubator 10) using the pump P4 according to the cell density reaching the reference value. The controller 13 can have a setting interface for process parameters, a trend display function, a data storage / output function, etc. as a user interface.

[0036] (2. Control loop 15 of the cell culture system 1) Figure 2 The control loop 15 of the cell culture system 1 is shown. The controller 13, actuator 11, incubator 10, and sensor 12 of the cell culture system 1 can form one or more closed control loops 15.

[0037] (3. Simulation device 2) Figure 3 The simulation device 2 according to the present embodiment is shown. The simulation device 2 is an example of a device and performs the simulation of the cell culture system 1. The simulation device 2 can have a storage unit 20, a simulator acquisition unit 21, a setting unit 22, a simulator execution unit 23, a determination unit 24, and a display unit 25.

[0038] (3.1. Storage unit 20) The storage unit 20 stores various types of information. The storage unit 20 according to the present embodiment can store the simulator 3 of the cell culture system 1.

[0039] (3.1.1. Simulator 3) The simulator 3 may have an incubator model 30 as a simulation model of the incubator 10, one or more actuator models 31 as simulation models of the actuators 11, one or more sensor models 32 as simulation models of the sensors 12, and a controller model 33 as a simulation model of the controller 13. The controller model 33, the actuator models 31, the incubator model 30, and the sensor models 32 may form one or more control loops 35 similar to the cell culture system 1. The simulation models may be mathematical models and may be combined according to the input and output relationships of the control loops 35 respectively.

[0040] (3.1.1(1). Incubator Model 30) The incubator model 30 may reproduce the behavior of the incubator 10. The behavior of the incubator 10 may include: the behavior of the culture medium and the like contained in the incubator 10 and the behavior of the cells contained in the culture medium. The incubator model 30 may be constructed considering the biological characteristics peculiar to the cell culture process (for example, the kinetics caused by the cells). For example, the incubator model 30 may be a mechanical model disclosed in References (1) and (2) described below. For the control variables peculiar to the cell culture process, as long as the behavior during the process can be expressed mathematically, the incubator model 30 may be a data-driven model generated by machine learning or a hybrid model (a model obtained by combining a mechanical model and a data-driven model). The parameters indicating the dynamic characteristics of the incubator model 30 may be set based on past culture data or seed discharge data. In the incubator model 30, uncertainty parameters may be set. The uncertainty parameters may indicate the uncertainty of the cell state in the culture medium and may be set as random number components such as normal random numbers of the incubator model 30 disclosed in References (1) and (2). This makes it possible to perform simulations considering the uncertainty of the cell state and even the variations between batches. When the incubator model 30 is provided with a manually operated sampling device 101 and a feeding device, these operating conditions may be defined for the incubator model 30.

[0041] Reference (1): Sara Badr and five other authors, "Integrated Design of Biopharmaceutical Manufacturing Processes: Operation Modes and Process Configurations for Monoclonal Antibody Production", Computers and Chemical Engineering, Vol. 153, p. 107422 (2021)

[0042] Reference (2): Martin Kornecki, Jochen Strube, "Process Analytical Technology for Advanced Process Control in Biologics Manufacturing with the Aid of Macroscopic Kinetic Modeling", Biotechnology, May 2018

[0043] (3.1.1(2). Actuator Model 31) Each actuator model 31 can reproduce the behavior of any actuator 11 that is the simulation target. Each actuator model 31 can operate based on the manipulated variable provided from the controller model 33. Among one or more actuator models 31 included in the simulator 3, at least one actuator model 31 can perform unique processing (e.g., scaling or transformation processing) on the provided manipulated variable and can operate based on the processed manipulated variable.

[0044] (3.1.1(3). Sensor Model 32) Each sensor model 32 can reproduce the behavior of any sensor 12 that is the simulation target. Among one or more sensor models 32 included in the simulator 3, at least one sensor model 32 can add pseudo-noise to the value of the measurement target (also referred to as the true value) calculated by the incubator model 30 and obtain the value with pseudo-noise added thereto as the process value. In the sensor model 32, parameters of the pseudo-noise added to the true value can be set (e.g., the intensity, shape, etc. of the noise). The parameters of the noise can be set based on the specifications of the sensor 12 that is the simulation target or past culture data. When the reliability of the sensor 12 that is the simulation target is high, the parameters of the noise can be set to add Gaussian white noise.

[0045] Among one or more sensor models 32 included in the simulator 3, at least one sensor model 32 can be provided with a simulation model (not shown) of a noise removal filter that removes noise from the acquired process value. In the sensor model 32 provided with the noise removal filter, parameters of the noise removal filter can be set. The parameters of the noise removal filter can be set based on the specifications of the noise removal filter provided in the sensor 12 that is the simulation target or past culture data. The simulation model of the noise removal filter may cause a delay between when there is a fluctuation in the measurement target of the sensor model 32 and when there is a fluctuation in the measurement result of the sensor model 32.

[0046] In at least one of the one or more sensor models 32 included in the simulator 3, a delay time can be set between when a measurement target of the sensor model 32 fluctuates and when a measurement result of the sensor model 32 fluctuates. The delay time can be set based on past cultivation data or the like.

[0047] In the one or more sensor models 32 included in the simulator 3, at least one sensor model 32 can be an online sensor model 320 that is an analog model of the online sensor 120. The online sensor model 320 may cause drift in the true value and acquire the drifted true value as a process value. In at least one online sensor model 320, a parameter of the drift (also referred to as a drift parameter) can be set. For example, the parameter of the drift can indicate the magnitude of the drift that occurs according to an increase or decrease in the amount of waste in the culture solution by a unit amount; can indicate the magnitude of the drift that occurs per unit time; or can indicate the amplitude of the drift that occurs according to an increase or decrease in temperature, pressure, etc. by a unit amount. The parameter of the drift can be set by adjusting the coefficient of the function expression used to calculate the process value of the online sensor model 320. In the sensor model 32, the time and method of calibration can be set.

[0048] In each sensor model 32, a measurement period can be set. The measurement period can be set based on the specifications of the sensor 12 that is the simulation target.

[0049] (3.1.1(4). Controller Model 33) The controller model 33 can reproduce the behavior of the controller 13. The controller model 33 can control one or more actuator models 31 based on the measurement results of one or more sensor models 32. For example, the controller model 33 can control the actuator model 31 by providing a control signal indicating a manipulated variable to the actuator model 31, and the manipulated variable is calculated based on the measurement results of the sensor model 32. The controller model 33 can scale (e.g., normalize) the measurement results of one or more sensors 12 and then use the scaled measurement results to calculate the manipulated variable.

[0050] In the controller model 33, a target value (SV) of the process value can be set, and the controller model 33 can calculate a manipulated variable that causes the process value to reach the target value (or within the reference range of the target value) and control the actuator model 31. When the simulator 3 has multiple control loops 35, target values can be set for each control loop 35 in the controller model 33.

[0051] In the controller model 33, control parameters can be set. The control parameters can be parameters indicating control conditions for the actuator model 31; for example, they can be feedback control parameters; they can be frequency parameters; or they can be the upper / lower limits of the manipulated variable of the actuator 11.

[0052] In the controller model 33, conditions for starting and ending control can be set. When considering the influence of control loops 35 on each other or when reducing the influence of known disturbances, the amount of adjustment of the manipulated variable by feedforward can be set in the controller model 33.

[0053] (3.2. Simulator acquisition unit 21) The simulator acquisition unit 21 acquires the simulator 3. The simulator acquisition unit 21 can acquire the simulator 3 generated by an external device, or can generate the simulator 3 according to the operation of an operator. For example, the simulator 3 can be generated in the development environment of MATLAB (registered trademark) / Simulink, but can also be generated in other development environments. The simulator acquisition unit 21 can cause the storage unit 20 to store the acquired simulator 3.

[0054] (3.3. Setting unit 22) The setting unit 22 can set various operating conditions for at least one of the controller model 33, actuator model 31, sensor model 32, or incubator model 30 of the simulator 3 according to the operation of an operator.

[0055] (3.3.1. Content of setting the controller model 33) The setting unit 22 can set a target value for the process value for the controller model 33. In the case of setting target values for multiple process values measured by multiple sensor models 32, the setting unit 22 can set a unified target value for each process value, or can set different target values for at least two process values. The setting unit 22 can appropriately set the target value when the simulator 3 is executed, or can preset the target value before the simulator 3 is executed.

[0056] The setting unit 22 can be an example of a control parameter setting unit and can set the control parameters of the controller model 33. The setting unit 22 can preset the control parameters before executing the simulator 3.

[0057] For example, the setting unit 22 can set the feedback control parameter as the control parameter. When multiple control loops 35 are formed in the simulator 3, the setting unit 22 can set the feedback control parameter for at least one control loop 35. In the case of setting the feedback control parameter for multiple control loops 35, the setting unit 22 can set a unified feedback control parameter for each control loop 35, or can set different feedback control parameters for at least two control loops 35.

[0058] The setting unit 22 can set the frequency parameter as a control parameter. When multiple actuator models 31 are included in the simulator 3, the setting unit 22 can set the frequency parameter for at least one actuator model 31. In the case of setting the frequency parameter for multiple actuator models 31, the setting unit 22 can set a unified frequency parameter for each actuator model 31, or can set different frequency parameters for at least two actuator models 31.

[0059] The setting unit 22 can set the upper / lower limit of the manipulated variable of the actuator model 31 as a control parameter. When multiple actuator models 31 are included in the simulator 3, the setting unit 22 can set the upper / lower limit of the manipulated variable for at least one actuator model 31. In the case of setting the upper / lower limit of the manipulated variable for multiple actuator models 31, the setting unit 22 can set a unified upper / lower limit of the manipulated variable for each actuator model 31, or can set different upper / lower limits of the manipulated variable for at least two actuator models 31.

[0060] The setting unit 22 can set the adjustment amount of the manipulated variable by feedforward. In the case of setting the adjustment amount for multiple actuator models 31, the setting unit 22 can set a unified adjustment amount for each actuator model 31, or can set different adjustment amounts for at least two actuator models 31. The setting unit 22 can preset the adjustment amount before executing the simulator 3.

[0061] (3.3.2. Contents of setting the sensor model 32) The setting unit 22 can set the noise parameter for at least one sensor model 32. In the case of setting the noise parameter for multiple sensor models 32, the setting unit 22 can set a unified parameter for each sensor model 32, or can set different parameters for at least two sensor models 32. The setting unit 22 can preset the noise parameter before executing the simulator 3.

[0062] The setting unit 22 can set the parameter of the noise removal filter for at least one sensor model 32. In the case of setting the parameter of the noise removal filter for multiple sensor models 32, the setting unit 22 can set a unified parameter for each sensor model 32, or can set different parameters for at least two sensor models 32. The setting unit 22 can preset the parameter of the noise removal filter before executing the simulator 3.

[0063] The setting unit 22 can be an example of a delay time setting unit and can set a delay time for at least one sensor model 32. In the case of setting delay times for multiple sensor models 32, the setting unit 22 can set a unified delay time for each sensor model 32, or can set different delay times for at least two sensor models 32. The setting unit 22 can preset the delay time before executing the simulator 3.

[0064] The setting unit 22 can be an example of a drift parameter setting unit and can set a drift parameter for at least one online sensor model 320. In the case of setting drift parameters for multiple online sensor models 320, the setting unit 22 can set a unified drift parameter for each online sensor model 320, or can set different drift parameters for at least two online sensor models 320. The setting unit 22 can preset the drift parameter before executing the simulator 3.

[0065] (3.3.3. Contents for setting the incubator model 30) The setting unit 22 can be an example of an uncertainty parameter setting unit and can set an uncertainty parameter for the cell state in the incubator model 30 for the incubator model 30. The setting unit 22 can set the number of execution times of the simulation to which the uncertainty parameter is applied together with the uncertainty parameter. The setting unit 22 can preset these contents before executing the simulator 3.

[0066] (3.3.4. Other setting contents) The setting unit 22 can set the control target of the simulation through the operation of the operator.

[0067] For example, the control target can be a target related to the stability characteristic, and for example, when the state of the incubator model 30 is in a steady state, the process value (PV) is within the reference range of the target value (SV). In this case, the setting unit 22 can set the reference range of the process value to be maintained when the state of the incubator model 30 is in a steady state.

[0068] The control target can be a target related to the transient characteristic, and for example, the stabilization time (also called the response delay time) until the process value reaches the target value (or within the reference range of the target value) is less than the reference time. The control target can be a target related to the followability of the target value, and for example, when the target value of any process value is changed and cell culture is performed, the control target can be that the follow-up rate at which the process value reaches the target value (or within the reference range of the target value) exceeds the reference rate. In these cases, the setting unit 22 can set the reference time below which the stabilization time should be, and can set the reference rate that the follow-up rate should exceed.

[0069] The setting unit 22 can set the environment of the simulator 3 through the operation of an operator. For example, the setting unit 22 can set the type of solver used by the simulator 3 (e.g., Euler method, Runge-Kutta method, etc.), or can set the global variables used by multiple simulation models (e.g., simulation period (i.e., culture cycle)).

[0070] The setting unit 22 can provide the set content to the simulator 3, or can provide the set content to the simulator execution unit 23. The setting unit 22 can provide the set content of the control target to the determination unit 24.

[0071] (3.4. Simulator Execution Unit 23) The simulator execution unit 23 executes the simulator 3.

[0072] The simulator execution unit 23 can execute the simulator 3 in a state where the target value (SV) of the process value is set for the controller model 33. The simulator execution unit 23 can cause the controller model 33 to drive the actuator model 31 so that the process value measured by the sensor model 32 approaches the target value.

[0073] The simulator execution unit 23 can execute the simulator 3 in a state where control parameters are set for the controller model 33. The simulator execution unit 23 can cause the controller model 33 to perform feedback control according to the set feedback control parameters. The simulator execution unit 23 can cause a control signal to be output from the controller model 33 to the actuator model 31 at an output frequency or control period according to the set frequency parameter. The simulator execution unit 23 can output a control signal indicating the manipulated variable from the controller model 33 to the actuator model 31 according to the upper / lower limits of the set manipulated variable.

[0074] The simulator execution unit 23 can execute the simulator 3 in a state where a feedforward adjustment amount is set for the controller model 33. The simulator execution unit 23 can cause a control signal indicating the manipulated variable according to the set content to be output from the controller model 33 to the actuator model 31.

[0075] The simulator execution unit 23 can execute the simulator 3 in a state where uncertainty parameters are set for the incubator model 30. The simulator execution unit 23 can cause the state of the cells in the incubator model 30 to be uncertain according to the uncertainty parameters. The simulator execution unit 23 can execute the simulator 3 a predetermined number of times by the setting unit 22 according to the set uncertainty parameters.

[0076] The simulator execution unit 23 can execute the simulator 3 in a state where noise parameters are set for the sensor model 32. The simulator execution unit 23 can cause the sensor model 32 to obtain a process value obtained by adding noise to the true value of the measurement target calculated by the incubator model 30 according to the noise parameters.

[0077] The simulator execution unit 23 can execute the simulator 3 in a state where noise removal filter parameters are set for the sensor model 23. The simulator execution unit 23 can cause the sensor model 32 to obtain a process value obtained by removing noise according to the noise removal filter parameters.

[0078] The simulator execution unit 23 can execute the simulator 3 in a state where a delay time is set for the sensor model 32. After the elapse of the delay time from the moment when fluctuations occur in the measurement target of the sensor model 32, the simulator execution unit 23 can cause the fluctuations to appear in the measurement result of the sensor model 32.

[0079] The simulator execution unit 23 can execute the simulator 3 in a state where drift parameters are set for the online sensor model 320. The simulator execution unit 23 can cause the measurement result of the online sensor model 320 to drift according to the drift parameters.

[0080] The simulator execution unit 23 can execute the simulator 3 in a state where a measurement period is set for the sensor model 32. The simulator execution unit 23 can cause each sensor model 32 to obtain a process value within the measurement period.

[0081] The simulator execution unit 23 can execute the simulator 3 according to the environment settings set by the setting unit 22. For example, when the type of solver is set, the simulator execution unit 23 can perform calculations by using the set solver. When a simulation section is set, the simulation can be performed within the set simulation section.

[0082] The simulator execution unit 23 can cause the storage unit 20 to store the execution result of the simulation of the simulator 3. The execution result of the simulation can include time series data obtained by each simulation model and the setting content of the simulation model.

[0083] (3.5. Decision unit 24) The decision unit 24 determines whether the value indicating the execution result satisfies a predetermined condition according to the simulator 3 being executed. The predetermined condition can be a condition according to the control target and is also referred to as the target condition. The decision unit 24 can obtain the value indicating the execution result from the simulator 3.

[0084] When the state of the incubator 10 is in a steady state, the value indicating the execution result can be a value based on the process value (e.g., the process value itself) measured by one or more sensor models 32. In this case, the target condition can be that the process value is its target value (or within the reference range of the target value).

[0085] The value indicating the execution result can be the stabilization time until the process value reaches the target value (or within the reference range of the target value). In this case, the target condition can be that the stabilization time is less than the reference time, can be that the stabilization time is less than the stabilization time when the simulator 3 was previously executed, or can be that the stabilization time is less than the stabilization time in the case of cell culture performed in the cell culture system 1.

[0086] The value indicating the execution result can be the following rate at which the process value reaches the target value (or within the reference range of the target value) when the target value of any process value is changed and the simulator 3 is executed. In this case, the target condition can be that the following rate exceeds its reference rate, can be that the following rate exceeds the following rate when the simulator 3 was previously executed, or can be that the following rate exceeds the following rate in the case of cell culture performed in the cell culture system 1.

[0087] The determination unit 24 can, in a state where an uncertainty parameter is set by the setting unit 22, obtain the values indicating the execution results of each execution based on the simulator 3 executed multiple times, to determine whether the distribution of the values satisfies a predetermined condition (also referred to as a distribution condition). The distribution condition can be that the value indicating the execution result remains within a preset reference range, additionally or instead of this, can be that the variance or standard deviation of the value indicating the execution result remains within a preset reference range. The determination unit 24 can provide the determination result to the display unit 25.

[0088] (3.6. Display Unit 25) The display unit 25 displays various types of information. The display unit 25 can display in combination the value indicating the execution result of the simulator 3 and the determination result of the determination unit 24. The display unit 25 can be an example of an output unit, and can display the control parameter set by the setting unit 22 as the set value of the controller 13 according to the determination unit 24 that determines that the value indicating the execution result of the simulator 3 satisfies the target condition.

[0089] Using the above-described simulation device, the simulator 3 is executed in a state where control parameters are set for the controller model 33 of the simulator 3 included in the cell culture system 1. Therefore, by adjusting the control parameters and executing the simulator 3, appropriate control parameters for achieving any target can be specified, and the specified appropriate control parameters can be applied to the controller 13 of the cell culture system 1. In addition, compared with the case of changing control parameters in the cell culture system 1 and repeating cell culture, the time, raw materials, labor, etc. required for specifying appropriate control parameters can be reduced.

[0090] In addition, after a delay time has elapsed since a delay time is set for the sensor model 32 which is a simulation model of the sensor 12 and a measurement target of the sensor model 32 fluctuates, the fluctuation appears in the measurement result of the sensor model 32. Therefore, the simulator 3 can be executed in a state where the delay time of the sensor model 32 is suitable for the state of the actual sensor 12.

[0091] In addition, a drift parameter is set for the on-line sensor model 320 which is a simulation model of the on-line sensor 120, and a drift according to the drift parameter appears in the measurement result of the line sensor model 320. Therefore, the simulator 3 can be executed in a state where the drift due to waste or the like occurring during the culture process is suitable for the real environment.

[0092] In addition, an uncertainty parameter of the cell state is set for the incubator model 30 which is a simulation model of the incubator, and an uncertainty of the state according to the uncertainty parameter appears. Therefore, the simulator 3 can be executed in a state where the cell state in the incubator model 30 is suitable for the uncertainty of the cell state in the real environment.

[0093] In addition, based on the simulator 3 being executed, it is determined whether a value indicating the execution result satisfies a predetermined target condition. Therefore, when cell culture is performed in the real environment, it is possible to pre-check whether the culture result satisfies the target condition.

[0094] In addition, based on the determination that the value indicating the execution result of the simulator 3 satisfies the target condition, the control parameters are output as the set value of the controller 13. Therefore, the control parameters that satisfy the target condition can be applied to the controller 13 of the cell culture system 1 and cell culture can be performed in the real environment.

[0095] In addition, based on the simulator 3 executed multiple times in a state where one uncertainty parameter is set, values indicating the execution result of each execution are obtained, and it is determined whether the distribution of the values satisfies a predetermined distribution condition. Therefore, when cell culture is performed multiple times in the real environment, it is possible to pre-check whether the multiple culture results as a whole satisfy the distribution condition.

[0096] In addition, the simulation models included in the simulator 3 are combined with each other according to the input and output relationships, so that by grasping the influence between the simulation models, the influence between the components of the cell culture system 1 to be simulated (in this embodiment, for example, the controller 13, the actuator 11, the incubator 10, and the sensor 12) can be grasped. In addition, for each simulation model, the degree of influence on the control performance of the control loop 35 can be grasped, and the grasped influence is used to set the control parameters, so that the control parameters can be easily set.

[0097] (4. Operation) Figure 4 The operation of the simulation device 2 is shown. The simulation device 2 simulates the cell culture system 1 by executing the processes of steps S11 to S25, and determines the control parameters for achieving the desired control target. It should be noted that in this embodiment, for example, the description will be made based on the assumption that the simulator 3 has been previously acquired by the simulator acquisition unit 21 of the simulation device 2.

[0098] In step S11, the setting unit 22 sets the control target of the simulation according to the operation of the operator. The setting unit 22 can set one or more control targets. In this way, the target conditions can be set according to the control target. The setting unit 22 can also set the distribution target that characterizes the distribution conditions of the values indicating the execution results of the simulator 3 according to the operation of the operator. In this way, the distribution conditions can be set according to the distribution target. The setting unit 22 can also further set the environment of the simulator according to the operation of the operator.

[0099] In step S13, the setting unit 22 sets the characteristics of each simulation model according to the operation of the operator. The setting unit 22 can set one or more control parameters (for example, feedback control parameters, frequency parameters, or upper / lower limits of the manipulated variable) for the controller model 33; can set the delay time for the sensor model 32; can set the drift parameter for the on-line sensor model 320; and can set the uncertainty parameter for the incubator model 30.

[0100] In step S15, the simulator execution unit 23 executes the simulator 3. The simulator execution unit 23 can execute the simulator 3 in a state where the setting contents are set through steps S11 and S13. For example, the simulator execution unit 23 can execute the simulator 3 in a state where the control parameters are set for the controller model 33. When the uncertainty parameter is set in step S13, the simulator execution unit 23 can execute the simulator 3 multiple times in a state where the uncertainty parameter is set.

[0101] In step S21, the determination unit 24 determines whether the value indicating the execution result of step S15 satisfies the target conditions. When the simulator 3 is executed multiple times with the state of an uncertainty parameter set in step S15, the determination unit 24 can acquire the value indicating the execution result of each execution, and further determine whether the distribution of the value satisfies the distribution condition. The determination unit 24 can cause the display unit 25 to display the determination result and the execution result of the simulator 3 in combination.

[0102] If it is determined in step S21 that the control condition is not satisfied (step S21; No), the process can proceed to step S23. If it is determined in step S21 that the control condition is satisfied (step S21; Yes), the process can proceed to step S25.

[0103] In step S23, the determination unit 24 determines whether the operator has performed an operation to reduce the effect of the control target. If it is determined that the operation to reduce the effect of the control target has not been performed (step S23; No), the process can proceed to step S13 above. In this way, the characteristics of each simulator model are reset, and the simulator 3 is executed. If it is determined that the operation to reduce the effect of the control target has been performed (step S23; Yes), the process can proceed to step S11 above. In this way, the control target is reset to low so that the control target can be achieved, and the simulator 3 is executed.

[0104] In step S25, the determination unit 24 determines whether the operator has performed an operation to increase the effect of the control target. If it is determined that the operation to increase the effect of the control target has been performed (step S25; Yes), the process can proceed to step S11 above. In this way, the control target is reset to high so that the control target is strict, and the simulator 3 is executed. If it is determined that the operation to increase the effect of the control target has not been performed (step S25; No), the operation can end. In this way, the control parameters and characteristics of the simulation model that can achieve the desired control target can be specified. It should be noted that when changing the characteristics of the simulation model, etc. and performing the simulation, this operation can be executed again from the beginning.

[0105] (5. Modification Example) It should be noted that in the above-described embodiment, it has been described that the simulation device 2 includes the simulator acquisition unit 21, the determination unit 24, and the display unit 25; however, the simulation device 2 may not include any of these.

[0106] In addition, an example in which the display unit 25 is described as an output unit has been given; however, other configurations can be used as the output unit as long as the control parameter is output as a set value of the controller. For example, the output unit can be a control device of the controller 13; and it can be determined according to the determination unit 24 that the value indicating the execution result of the simulator 3 satisfies the target condition, and the set control parameter is output to the controller 13 as a set value so as to execute the control according to the control parameter. In this case, the simulator 3 can be used as a digital twin of the cell culture system 1, and the result of cell culture of the cell culture system 1 can be predicted by inputting actual data (such as a process value indicating the state of the cell culture system 1) and performing a simulation. When the prediction result is not good, the control parameter of the controller 13 of the cell culture system 1 can be adjusted, or the sensor 12 can be calibrated.

[0107] In addition, the controller 13 has been described as determining the manipulated variable by feedback control; however, additionally or instead of this, the manipulated variable can be determined by model predictive control in which a prediction model (for example, the incubator model 30 of the simulator 3) for predicting the behavior of the prediction incubator 10 is used. For example, the controller 13 can determine the manipulated variable for optimizing the reward value determined by a preset reward function. The reward function can be a function having one or more measured values as variables, or can be a function having a settling time as a variable. When the controller 13 performs model predictive control, the setting unit 22 can set at least one of the weight coefficient of the reward function, the prediction section (prediction range) for obtaining an output from the prediction model, or the control section (control range) for controlling the input to the prediction model, as a control parameter of the controller model 33. In this case, the simulator execution unit 23 can execute the simulator 3 in a state where these control parameters are set for the controller model 33. For example, the simulator execution unit 23 can cause the controller model 33 to perform model predictive control to determine the manipulated variable for optimizing the reward value determined by the reward function for which the weight coefficient is set. The simulator execution unit 23 can cause the controller model 33 to perform model predictive control according to the set prediction interval and control interval.

[0108] In addition, the cell culture system 1 has been described as performing perfusion culture; however, the culture can be performed by other methods (such as fed-batch culture or continuous culture).

[0109] In addition, the cell culture system 1 has been described as culturing animal cells such as CHO cells; however, vertebrate cells other than CHO cells can be cultured, cells of shellfish, insects, etc. can be cultured, and human cells, plant cells, and microbial cells can be cultured.

[0110] Additionally, flowcharts and block diagrams can be referred to for illustrating various embodiments of the present invention, where block diagrams can be used as (1) stages in the process of performing operations, or (2) parts of a device having the function of performing operations. Certain stages and parts can be implemented by dedicated circuits, programmable circuits provided with computer-readable instructions stored on a computer-readable medium, and / or processors provided with computer-readable instructions stored on a computer-readable medium. The dedicated circuits can include digital and / or analog hardware circuits, and can include integrated circuits (ICs) and / or discrete circuits. The programmable circuits can include reconfigurable hardware circuits having logical AND, logical OR, logical XOR, logical NAND, logical NOR, and other logical operations, memory elements such as flip-flops, registers, field-programmable gate arrays (FPGAs), and programmable logic arrays (PLAs), etc.

[0111] The computer-readable medium can include any tangible device capable of storing instructions to be executed by a suitable device. Thus, a computer-readable medium storing instructions thereon includes a manufactured article containing the instructions, which can be executed to create a means for performing the operations specified in the flowchart or block diagram. Examples of the computer-readable medium can include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of the computer-readable medium can include floppy (registered trademark) disks, magnetic disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray (registered trademark) disc, memory stick, integrated circuit card, etc.

[0112] The computer-readable instructions can include: assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status-setting data; or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk (registered trademark), JAVA (registered trademark), C++, etc., and conventional procedural programming languages such as the "C" programming language or similar programming languages.

[0113] The computer-readable instructions can be provided locally or via a local area network (LAN), a wide area network (WAN) such as the Internet, etc., to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, or provided to a programmable circuit, to execute the computer-readable instructions to create a means for performing the operations specified in the flowchart or block diagram. Examples of the processor include a computer processor, a processing unit, a microprocessor, a digital signal processor, a controller, a microcontroller, etc.

[0114] Figure 5 FIG. shows an example of a computer 2200 in which aspects of the present invention may be implemented in whole or in part. Programs installed in the computer 2200 may cause the computer 2200 to act as an operation associated with a device according to an embodiment of the present invention or act as one or more parts of the device, or may cause the operation or one or more parts to be performed, and / or may cause the computer 2200 to execute a process according to an embodiment of the present invention or a stage of the process. Such a program may be executed by the CPU 2212 so that the computer 2200 performs certain operations associated with some or all of the blocks in the flowcharts and block diagrams described in this specification.

[0115] The computer 2200 according to the present embodiment includes a CPU 2212, a RAM 2214, a graphics controller 2216, and a display device 2218 interconnected by a host controller 2210. The computer 2200 also includes input / output units such as a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an IC card drive, which are connected to the host controller 2210 via an input / output controller 2220. The computer also includes conventional input / output units such as a ROM 2230 and a keyboard 2242, which are connected to the input / output controller 2220 via an input / output chip 2240.

[0116] The CPU 2212 operates according to programs stored in the ROM 2230 and the RAM 2214 to control each unit. The graphics controller 2216 acquires image data generated by the CPU 2212 on a frame buffer or the like set in the RAM 2214 or itself, and causes the image data to be displayed on the display device 2218.

[0117] The communication interface 2222 communicates with other electronic devices via a network. The hard disk drive 2224 stores programs and data used by the CPU 2212 in the computer 2200. The DVD-ROM drive 2226 reads programs or data from the DVD-ROM 2201 and provides the programs or data to the hard disk drive 2224 via the RAM 2214. The IC card drive reads programs and data from an IC card, and / or writes programs and data to the IC card.

[0118] A boot program or the like executed by the computer 2200 when activated and / or a program depending on the hardware of the computer 2200 are stored in the ROM 2230. The input / output chip 2240 may also connect various input / output units to the input / output controller 2220 via a parallel port, a serial port, a keyboard port, a mouse port, etc.

[0119] The program is provided by a computer-readable medium such as a DVD-ROM 2201 or an IC card. The program is read from a computer-readable medium, such as a hard disk drive 2224 which is also an example of a computer-readable medium, a RAM 2214, or a ROM 2230, and is executed by a CPU 2212. The information processing written in these programs is read by a computer 2200, and cooperation between the provided programs and the various types of hardware resources described above is provided. The apparatus or method may be configured by implementing operations or processing of information according to the use of the computer 2200.

[0120] For example, in the case of performing communication between the computer 2200 and an external device, the CPU 2212 may execute a communication program loaded in the RAM 2214, and instruct the communication interface 2222 to perform communication processing based on the procedures written in the communication program. Under the control of the CPU 2212, the communication interface 2222 reads transmission data set in a transmission buffer processing area in a recording medium such as the RAM 2214, a hard disk drive 2224, a DVD-ROM 2201, or an IC card, sends the read transmission data to the network, or writes the received data received from the network into a reception buffer processing area set in the recording medium, etc.

[0121] In addition, the CPU 2212 may cause the RAM 2214 to read all or a necessary part of a file or database stored in an external recording medium such as a hard disk drive 2224, a DVD-ROM drive 2226 (DVD-ROM 2201), an IC card, etc., and may perform various types of processing on the data on the RAM 2214. Then, the CPU 2212 writes the processed data back to the external recording medium.

[0122] Various types of information such as various types of programs, data, tables, and databases can be stored in the recording medium and information processing can be performed. The CPU 2212 may perform various types of processing on the data read from the RAM 2214 to write the result back to the RAM 2214. This processing is described throughout the present disclosure, is specified by an instruction sequence of a program, and includes various types of operations, information processing, conditional determination, conditional branch, unconditional branch, information search / replacement, etc. In addition, the CPU 2212 may search for information in files, databases, etc. in the recording medium. For example, when a plurality of entries (each entry having an attribute value of a first attribute associated with an attribute value of a second attribute) are stored in the recording medium, the CPU 2212 may search for an entry that matches the condition specifying the attribute value of the first attribute from the plurality of entries, and read the attribute value of the second attribute stored in the entry, thereby obtaining the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0123] The above programs or software modules can be stored in a computer-readable medium on or near the computer 2200. Additionally, a recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can be used as the computer-readable medium to provide the program to the computer 2200 via the network.

[0124] Although the present invention has been illustrated by way of embodiments, the technical scope of the present invention is not limited to the above embodiments. It will be apparent to those skilled in the art that various substitutions or improvements can be made to the above embodiments. It can also be clearly seen from the description of the claims that embodiments incorporating such substitutions or improvements can be included within the technical scope of the present invention.

[0125] Note that the operations, processes, steps, and stages of each process performed by the devices, systems, programs, and methods shown in the claims, embodiments, or drawings can be executed in any order, provided that the order is not indicated by "previously", "before", etc., and provided that the output from a previous process is not used in a subsequent process. Even if phrases such as "first" or "next" are used in the claims, specification, or drawings to describe the operation flow, it does not necessarily mean that the process must be executed in this order. List of Reference Numerals

[0126] 1: Cell culture system; 2: Simulation device; 3: Simulator; 10: Incubator; 11: Actuator; 13: Controller; 15: Control loop; 20: Storage unit; 21: Simulator acquisition unit; 22: Setting unit; 23: Simulator execution unit; 24: Judgment unit; 25: Display unit; 30: Incubator model; 31: Actuator model; 32: Sensor model; 33: Controller model; 35: Control loop; 101: Sampling device; 102: Cell removal device; 103: Flow cell; 120: Online sensor; 121: Dielectric spectrometer; 122: Near-infrared / infrared / Raman spectrometer; 124: Analysis device; 131: Stirring device; 1210: Electrode; 1220: Light receiving and emitting sensor; 2200: Computer; 2201: DVD-ROM; 2210: Host controller; 2212: CPU; 2214: RAM; 2216: Graphics controller; 2218: Display device; 2220: Input / output controller; 2222: Communication interface; 2224: Hard disk drive; 2226: DVD-ROM drive; 2230: ROM; 2240: Input / output chip; 2242: Keyboard.

Claims

1. A device comprising: a control parameter setting unit that sets control parameters for a controller model, the controller model being included in a simulator of a cell culture system, the cell culture system controlling an actuator through a controller according to a measurement result of a sensor, and the controller model being a simulation model of the controller; and A simulator execution unit executes the simulator in a state where the control parameters are set for the controller model.

2. The apparatus according to claim 1, further comprising: a delay time setting unit, which sets a delay time for a sensor model, the sensor model being included in the simulator and being a simulation model of the sensor, wherein The simulator execution unit causes the fluctuation to appear in the measurement result of the sensor model after the delay time has elapsed from a time when the fluctuation of the measurement target of the sensor model appears.

3. The device according to claim 1, wherein At least one sensor in the cell culture system is an online sensor immersed in the culture solution and measuring the state of the culture solution, The apparatus further comprises a drift parameter setting unit for setting a drift parameter for an online sensor model, the online sensor model being included in the simulator and being a simulation model of the online sensor; wherein The simulator execution unit causes the measurement result of the online sensor model to drift according to the drift parameter.

4. The apparatus according to claim 1, further comprising: an uncertainty parameter setting unit, which sets one or more uncertainty parameters of the cell state in the incubator model for the incubator model, wherein the incubator model is included in the simulator and is a simulation model of the incubator of the cell culture system, The simulator execution unit causes the cells in the incubator model to experience state uncertainty according to the uncertainty parameter.

5. The apparatus according to claim 4, further comprising: A determination unit acquires a value indicating an execution result of each execution based on the simulator being executed multiple times in a state where one of the one or more uncertainty parameters is set, to determine whether a distribution of the value satisfies a predetermined condition.

6. The apparatus according to claim 1, further comprising: A determination unit determines whether a value indicating an execution result satisfies a predetermined condition based on the simulator being executed.

7. The apparatus according to claim 6, further comprising: An output unit outputs the control parameter as a set value of the controller according to the determination by the determination unit that the value indicating the execution result satisfies the predetermined condition.

8. A method comprising: setting control parameters for a controller model, the controller model being included in a simulator of a cell culture system, the cell culture system controlling an actuator via a controller according to a measurement result of a sensor, and the controller model being a simulation model of the controller; and The simulator is executed in a state where the control parameters are set for the controller model.

9. A program for causing a computer to: a control parameter setting unit that sets control parameters for a controller model that is included in a simulator of a cell culture system that controls an actuator through a controller based on a measurement result of a sensor, and that is a simulation model of the controller; and The simulator execution unit executes the simulator in a state where the control parameters are set for the controller model.

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