Culture medium monitoring device, culture medium monitoring method, and program

Abstract

To provide a culture medium monitoring device, a culture medium monitoring method, and a program, configured to assist in efficient management of cell culture.SOLUTION: A culture medium monitoring device comprises: an acquisition unit that acquires, in cell culture using a culture medium, at least one of, first information on a measurement value obtained through sensing for the culture medium, second information on an environment of the cell culture, and third information on a facility of the cell culture; and an estimation unit that estimates the condition of the culture medium and / or a method for improving the condition of the culture medium on the basis of the information acquired by the acquisition unit.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a culture medium monitoring device, a culture medium monitoring method, and a program.

Background Art

[0002] In recent years, for the purposes of standardizing operations, improving production efficiency, and stabilizing quality and operation, labor reduction and automation of production management processes have been demanded. In particular, in the production management process of products produced using biotechnology such as cell culture, in addition to artificial operations, multiple factors such as the environment and equipment are involved, so the cost for realizing desirable management is high, and labor reduction and automation are demanded.

[0003] For example, Patent Document 1 discloses a technique related to a cell culture management system that identifies the cause of a nonconformance determination when a nonconformance determination is made in a test using an intermediate product of a product produced by culturing cells.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the technique of Patent Document 1, since the work is analyzed in the operation units of cell culture extracted from instruction manuals and production record books to identify the cause of the nonconformance determination, it is difficult to consider the influence of factors outside the work units.

[0006] There are various factors that cause problems in cell culture, and multiple factors often affect each other. For example, for the factor of contamination caused by chemical components, microorganisms, etc., multiple factors such as the non-uniformity of the reagent lots used, the cryopreservation operation and storage state of the cells used, the number of openings and closings and the opening and closing time of the incubator used, and the deposits on the hands of the operator in the work flow can affect each other.

[0007] Therefore, it is difficult to predict the state of the culture medium that may be caused by a series of work processes related to cell culture. Therefore, there is a need to provide a mechanism to support efficient management suitable for the work of cell culture.

[0008] Therefore, an object of the present invention is to provide a culture medium monitoring device, a culture medium monitoring method, and a program for supporting efficient management of cell culture.

Means for Solving the Problems

[0009] A culture medium monitoring device according to an aspect of the present invention includes an acquisition unit that acquires at least any one of first information regarding a measurement value obtained by sensing the culture medium, second information regarding the environment of the cell culture, and third information regarding the equipment of the cell culture in cell culture using the culture medium, and an estimation unit that estimates the state of the culture medium and / or a method for improving the state of the culture medium based on the information acquired by the acquisition unit.

Effects of the Invention

[0010] According to the present invention, it is possible to provide a culture medium monitoring device, a culture medium monitoring method, and a program for supporting efficient management of cell culture.

Brief Description of the Drawings

[0011]

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Embodiments for Carrying Out the Invention

[0012] Embodiments of the present invention (hereinafter referred to as "the present embodiment") will be described with reference to the accompanying drawings. However, the present invention is not limited thereto, and various modifications can be made without departing from the gist thereof. In each figure, those denoted by the same reference numerals have the same or similar configurations. The dimensional ratios in the drawings are not limited to the illustrated ratios.

[0013] <System Configuration> FIG. 1 is a diagram showing a configuration example of a culture medium monitoring system 1 according to the present embodiment. The culture medium monitoring system 1 shown in FIG. 1 includes a data management server 10, a culture medium monitoring device 20, a culture medium state display device 30, a recording system 40, and one or more sensors D (shown as D0, D1, D2, or Dn in the figure). The data management server 10, the culture medium monitoring device 20, the recording system 40, and the one or more sensors D are communicably connected via a wireless or wired communication network such as the Internet, an intranet, a wireless LAN, or mobile communication. Also, the culture medium monitoring device 20 and the culture medium state display device 30 are communicably connected in the same manner. In the present disclosure, the culture medium monitoring system 1 will be described as including the data management server 10, the culture medium state display device 30, and the recording system 40. However, as long as the culture medium monitoring system 1 includes the culture medium monitoring device 20 and the sensors D, it does not necessarily have to include the configurations of the data management server 10, the culture medium state display device 30, and the recording system 40, and the culture medium monitoring device 20 may perform the functions performed by these configurations.

[0014] In the present disclosure, the "culture medium" is a substance for culturing cells, and may be used interchangeably with the "culture medium" or the "culture solution" regardless of whether it is in a liquid form or a solid form. The type of cells is not limited, and for example, it may be a plant cell, an animal cell, or a microorganism cell.

[0015] In the present disclosure, the "state of the culture medium" is, for example, the state that occurs in the culture medium to be monitored, such as acidity, alkalinity, or overgrowth. Unless otherwise specified, it includes the current state of the culture medium and the future state of the culture medium. The state of the culture medium includes both normal and abnormal states. The state of the culture medium is not necessarily limited to the existence of only one, and a plurality of states may exist simultaneously.

[0016] In the present disclosure, the "method for improving the state of a culture medium" is a treatment for improving the state of a culture medium or making the state of the culture medium better by applying it to the culture medium. For example, the method for improving the state of a culture medium includes setting, changing, adding, deleting, or adjusting culture conditions including presenting specific target values or reference values related to cell culture. When the state of the culture medium is normal, the method for improving the state of the culture medium is a treatment for improving the quality of the culture medium, etc.

[0017] In the present disclosure, "culture conditions" are conditions related to biological materials for cell culture such as "cell seeding amount", conditions related to the environment of cell culture such as "temperature inside the incubator", and conditions related to the equipment for cell culture such as "culture medium used". Further, the culture conditions may include conditions related to artificial factors and conditions related to non-artificial factors. Examples of conditions related to artificial factors include, for example, "incubator opening and closing time" and "hygiene status of the hands and clothes of the operator", and examples of conditions related to non-artificial factors include, for example, "temperature inside the incubator" and "culture medium used".

[0018] In the present disclosure, "monitoring" may be used interchangeably with "observing" in some cases.

[0019] The data management server 10 is an information processing device that undertakes some functions of culture medium monitoring, such as managing sensor data (which may be referred to as "feature quantity" in the present disclosure), which is a measured value obtained by sensing by the sensor D, and managing data related to the estimation result. The data management server 10 may be composed of one or more information processing devices, or may be configured using a virtual server (such as a cloud server). The data management server 10 may be configured by a computer. In the present disclosure, when referring to "sensor data", the number and type of sensor data are not particularly limited and may be any number and type of one or more.

[0020] The culture medium monitoring device 20 is an information processing device that estimates the state of the culture medium to be monitored and the method for improving the state of the culture medium using the sensor data obtained by sensing with the sensor D. For example, it acquires information regarding the measured values obtained by sensing with one or more sensors D and information regarding the equipment for cell culture input via the operation of the recording system 40, and estimates the state of the culture medium and the method for improving the state of the culture medium. The culture medium monitoring device 20 may be composed of one or more information processing devices, or may be configured using a virtual server. The culture medium monitoring device 20 may be configured by a computer.

[0021] The culture medium state display device 30 is an information processing device that displays the state of the culture medium estimated by the culture medium monitoring device 20, the method for improving the state of the culture medium, and various sensor data and the like.

[0022] The recording system 40 is an information processing device that manages information regarding cell culture conditions, manages tasks and workflows related to cell culture, analyzes data related to processes, and the like. The recording system 40 may be composed of one or more information processing devices, or may be configured using a virtual server. The recording system 40 may be configured by a computer. The recording system 40 is, for example, a laboratory information management system (LIMS: Laboratory Informatics Software), a supervisory control system (SCADA: Supervisory Control And Data Acquisition), a manufacturing execution system (MES: Manufacturing Execution System), or a clinical laboratory information system (LIS: Laboratory Information System).

[0023] One or more sensors D are devices that perform sensing on the medium to be monitored or sensing on the cell culture environment. The number and type of sensors D used are not particularly limited and may be any number and type of one or more. In FIG. 1, "n" in "sensor Dn" means an arbitrary number. The sensor D is, for example, an imaging device, a pH sensor, an oxygen sensor, a carbon dioxide sensor, a biological imaging sensor, a nutrient component sensor, a temperature sensor, a humidity sensor, a turbidity sensor, an illuminance sensor, a photometric sensor, an image sensor, or a color sensor, etc.

[0024] <Hardware Configuration> FIG. 2 is a diagram showing an example of the hardware configuration of the data management server 10, the medium monitoring device 20, the medium state display device 30, and the recording system 40. The data management server 10, the medium monitoring device 20, the medium state display device 30, and the recording system 40 include a processor 71 such as a CPU (Central Processing Unit) or a GPU (Graphical Processing Unit), a communication IF (Interface) 72 that performs wireless or wired communication, a memory (for example, a RAM (Random Access Memory) or a ROM (Read Only Memory)), a storage device 73 such as an HDD (Hard Disk Drive) and / or an SSD (Solid State Drive), an input device 74 that accepts input operations, and an output device 75 that outputs information. The input device 74 is, for example, a keyboard, a touch panel, a mouse, and / or a microphone, etc. The output device 75 is, for example, a display, a touch panel, and / or a speaker, etc. The processor 71, the communication IF 72, the storage device 73, the input device 74, and the output device 75 are interconnected by one or more communication buses 76.

[0025] <Functional Block Configuration> (Medium Monitoring Device) FIG. 3 is a diagram showing an example of a functional block configuration of the culture medium monitoring device 20. The culture medium monitoring device 20 includes a storage unit 201, an acquisition unit 202, a model construction unit 203, an estimation unit 204, and an output unit 205. The storage unit 201 can be realized using a storage device 73 included in the culture medium monitoring device 20. The acquisition unit 202, the model construction unit 203, the estimation unit 204, and the output unit 205 can be realized by a processor 71 included in the culture medium monitoring device 20 executing a program stored in the storage device 73. Further, the program can be stored in a storage medium. The storage medium storing the program may be a non-transitory computer readable medium. The non-transitory storage medium is not particularly limited, and may be, for example, a storage medium such as a USB (Universal Serial Bus) memory or a CD-ROM (Compact Disc Read-Only Memory). In the present disclosure, the culture medium monitoring device 20 is described as having the model construction unit 203. However, the culture medium monitoring device 20 does not necessarily have the model construction unit 203, and a different information processing device may perform the functions of the model construction unit 203, and the culture medium monitoring device 20 may use a model constructed in the different information processing device.

[0026] <Storage unit> The storage unit 201 stores various data necessary for the culture medium monitoring device to perform culture medium monitoring.

[0027] <Acquisition unit> The acquisition unit 202 has a function of acquiring at least one of first information regarding a measurement value obtained by sensing the culture medium, second information regarding the environment of cell culture, and third information regarding the equipment for cell culture.

[0028] In the present disclosure, the first information regarding the measurement value obtained by sensing the culture medium is information regarding the measurement value obtained by sensing with various sensors D for the culture medium.

[0029] In the present disclosure, a "measurement value" is a value obtained by measurement, and a "set value" is a value obtained by user input or setting without measurement. Neither value is limited to being a numerical value. The measurement value may be, for example, a pH value, a temperature, or a hue. The set value may be, for example, the cells used (cultured cells), the type of medium used, the incubator used, or the set temperature inside the incubator. In the present disclosure, "information regarding the measurement value" includes the measurement value, information based on the measurement value obtained by processing or analyzing the measurement value, and information inferred based on the measurement value.

[0030] The first information may be, for example, imaging information for acquiring the hue of the medium or the cell occupancy rate, or optical sensing information for acquiring the pH, turbidity, or concentration change of a predetermined substance of the medium. The first information may be, for example, a pH value measured by a pH sensor, a pH value inferred based on a hue value measured by a color sensor, and the like. The acquisition unit 202 may acquire the first information from the sensor D, or may acquire it via communication with an information processing device different from the medium monitoring device 20 such as the data management server 10.

[0031] In the present disclosure, the second information regarding the cell culture environment is information regarding the measurement value obtained by sensing the cell culture environment, or information regarding various set values input via the input device 74 of the recording system 40 or the medium monitoring device 20. The information regarding the measurement value obtained by sensing the cell culture environment is, for example, information regarding the temperature of the culture environment such as a temperature change inside the incubator, or information regarding humidity, carbon dioxide concentration, or oxygen concentration. The information regarding various set values is information determined by artificial setting, and is, for example, the temperature inside the incubator. The acquisition unit 202 may acquire the second information from the sensor D, or may acquire it via communication with an information processing device different from the medium monitoring device 20 such as the recording system 40 or the data management server 10.

[0032] In the present disclosure, the third information regarding the equipment for cell culture is information regarding the equipment and devices used for cell culture. For example, information regarding equipment (including devices, equipment, and biological materials) such as the incubator (storage) used, the medium used, the type of cells (cultured cells) used, or the reagents used, information regarding the usage status of these equipment such as the cell culture method, and information regarding the hygiene status of the operator's hands and clothes. The third information includes at least either information regarding measured values or information regarding set values.

[0033] The acquisition unit may acquire various types of information together with time-series data regarding the time series when the information was acquired. Thereby, it becomes possible to monitor the medium along the time series of cell culture.

[0034] <Model construction unit> The model construction unit 203 has a function of constructing a mathematical model (hereinafter also referred to as a "model") based on the information acquired by the acquisition unit 202. As an example, the model construction unit 203 constructs a mathematical model for statistical causal analysis such as a Bayesian network model, a multiple regression analysis model, or a decision tree model based on the information acquired by the acquisition unit 202. The information used by the model construction unit 203 for model construction may refer to the information stored in the storage unit 201 as existing information regarding cell culture. By inputting at least any one of the first information, the second information, and the third information acquired by the acquisition unit 202 into the model constructed by the model construction unit 203, it is possible to estimate the state of the medium generated under the influence of the input information, and it is possible to calculate the probability that the estimated state of the medium is appropriate.

[0035] FIG. 4 is a diagram showing an example of the structure of the Bayesian network model constructed by the model construction unit 203. The four ellipses are nodes indicating each event. In the model constructed by the model construction unit 203, for example, the model can be constructed using a learning engine from 1000 pieces of training data created based on existing information on cell culture. Among the 1000 pieces of training data, 800 are "normal or other states (node 101)", and 200 are "state 1 (e.g., overgrowth) (node 102)". Among the 800 pieces of training data of "normal or other states", 106 are "10.0 < sensor D1 value < 20.0 (node 103)", and 8 are "250.0 < sensor Dn value < 300.0 (node 104)". Also, among the 200 pieces of training data of "state 1", 6 are "10.0 < sensor D1 value < 20.0 (node 103)", and 195 are "250.0 < sensor Dn value < 300.0 (node 104)". In the example of the model shown in FIG. 4, when the "sensor Dn value < 300.0", the probability of being in "state 1" is estimated to be 0.96.

[0036] FIG. 5 is a diagram showing an example of the structure of the Bayesian network model constructed by the model construction unit 203. In the same manner as in the case of FIG. 4, in the model constructed by the model construction unit 203, from each event (node 204, node 205, node 206, and node 207 in FIG. 5) regarding a predetermined parameter based on all sensor data and set values, the estimated probability of each event (node 201, node 202, and node 203 in FIG. 5) indicating the state of the culture medium can be obtained. In the example of the model shown in FIG. 5, for example, when the sensor data is "10.0 < sensor D1 value < 20.0 (node 204)", the probability that the state of the culture medium is "normal (node 201)" is 0.13, the probability that the state of the culture medium is "state 1 (node 202)" is 0.09, and the probability that the state of the culture medium is "state 2 (node 203)" is 0.92.

[0037] FIG. 6 is a diagram showing an example of the structure of the Bayesian network model constructed by the model construction unit 203. In the model constructed by the model construction unit 203, it is also possible to obtain the estimated probability regarding the causal relationship between each event (in FIG. 6, node 304, node 305, node 306, and node 307) regarding a predetermined parameter based on all sensor data and setting values.

[0038] FIG. 7 is a diagram showing an example of the structure of the Bayesian network model constructed by the model construction unit 203. As described with reference to FIG. 6, in the model constructed by the model construction unit 203, it is possible to obtain the estimated probability regarding the causal relationship between each event regarding a predetermined parameter based on all sensor data and setting values. In the example of the model shown in FIG. 7, out of 1000 pieces of training data, 782 pieces are "10.0 < sensor D1 value < 20.0 (node 404)". Out of the 782 pieces of training data with "10.0 < sensor D1 value < 20.0", 203 pieces are "250.0 < sensor D2 value < 300.0 (node 405)", 586 pieces are "700.0 < sensor D3 value < 750.0 (node 406)", and 113 pieces are "1000.0 < sensor D4 value < 1100.0 (node 407)". Out of the 113 pieces of training data with "1000.0 < sensor D4 value < 1100.0", 78 pieces are "state 2 (node 403)", 30 pieces are "state 1 (node 402)", and 13 pieces are "normal (node 401)". In the example of the model shown in FIG. 7, when the sensor data is the measured value shown in table10, the state of the culture medium is estimated as "state 2", "state 1", and "normal" in descending order of the probability of being appropriate.

[0039] FIG. 8 is a flowchart showing an example of a procedure for constructing a Bayesian network model by the model construction unit 203. Various sensors D for sensing the medium to be monitored are installed in an incubator or a clean bench (step S101). Various types of data are registered in the medium management DB 101a (step S102). Sensor data sensed by various sensors D and set values input to the recording system 40 are collected and stored in various databases (step S103). An estimation result is labeled for each sensor data (step S104). Each sensor data that is a continuous value is discretized (step S105). A Bayesian network model is constructed from the discretized sensor data (step S106). Conditions to be applied to the Bayesian network model (for example, no arrow is emitted from event A, etc.) are selected (step S107). If there is known know-how such as a rule of thumb regarding cell culture, the know-how is reflected as a condition to be applied to the Bayesian network model (step S108: YES). If there is no know-how, the construction of the Bayesian network model is completed (step S108: NO).

[0040] The model construction unit 203 may perform preprocessing for adjusting the information acquired by the acquisition unit 202 based on time-series data. The model construction unit 203 may construct a model of the Bayesian network model based on the information acquired by the acquisition unit 202 that has performed the preprocessing.

[0041] The model construction unit 203 may perform preprocessing for adjusting the information acquired by the acquisition unit 202 based on the measured values and set values of the sensor data. The model construction unit 203 may construct a Bayesian network model based on the information acquired by the acquisition unit 202 that has performed the preprocessing.

[0042] The model construction unit 203 may construct a Bayesian network model based on the information on the rules of thumb regarding cell culture input by the user. For example, even when there is no sensor data, the user may manually set the probabilities. Thereby, even if there is no sensor data, a model incorporating the knowledge of experts can be constructed. In the present disclosure, the rules of thumb regarding cell culture include, for example, the rules of thumb based on the passage number of cell culture, the rules of thumb based on the culture period (adhesion period, induction period, logarithmic growth period, stationary period, etc.) of cell culture, and the like.

[0043] The model construction unit 203 may construct a Bayesian network model based on the information on cell culture that contributed to the state of the medium estimated by the estimation unit 204, even if the information acquired by the acquisition unit 202 does not include measured values or set values. Thereby, even if the facility environment in which all the factors that can contribute to the state of the medium cannot necessarily be monitored, the factors that can contribute to the state of the medium can be comprehensively utilized for model construction.

[0044] <Estimation unit> The estimation unit 204 has a function of estimating the state of the medium and a method for improving the state of the medium based on the information acquired by the acquisition unit 202. The information acquired by the acquisition unit 202 used by the estimation unit 204 includes measured values and / or set values. The information acquired by the acquisition unit 202 used by the estimation unit 204 includes at least any one of the first information, the second information, and the third information. In addition to the function of estimating the state of the medium and a method for improving the state of the medium, the estimation unit 204 has a function of estimating the probability that the state of the medium and a method for improving the state of the medium are reasonable.

[0045] In the present disclosure, "estimating a method for improving the state of the culture medium" means specifying a method for improving the state of the culture medium using the result of the estimation by the estimation unit 204. For example, it may be to specify a method for improving the state of the culture medium having a predetermined reasonable probability from a list of methods for improving the state of the culture medium registered in advance according to the state of the culture medium, the sensing item, or the numerical value of the sensor data estimated by the estimation unit 204. For example, it may be to specify a predetermined method for improving the state of the culture medium based on the factor information contributing to the state of the culture medium estimated by the estimation unit 204.

[0046] The estimation unit 204 may estimate the state of the culture medium and the method for improving the state of the culture medium by using a mathematical model used for statistical cause analysis such as a Bayesian network model constructed by the model construction unit 203.

[0047] FIG. 9 is a flowchart showing an example of a procedure when the estimation unit 204 performs estimation. Sensor data sensed by various sensors D and set values input to the recording system 40 are collected and stored in various databases (step S201). The collected sensor data is input to the Bayesian network model (step S202). The state of the culture medium is estimated from the calculated estimation probability (step S203). Each data and the estimated result are stored in the estimation result data TSDB101e (step S204). Information on the estimated cause (state) is displayed in a ranking format from the culture medium state information DB101b (step S205). A countermeasure (improvement method) for the cause (state) with the highest rank is executed (step S206). Based on the sensor data collected after the execution of the countermeasure, the state of the culture medium is estimated, and it is determined whether the state of the culture medium has been improved (step S207). If it is determined that the improvement has not occurred, the process returns to step S204 (step S207: NO). If it is determined that the improvement has occurred, the process proceeds to step S208 (step S207: YES). It is determined whether to apply the estimation result data to the training data of the model (step S208).

[0048] In addition to the function of estimating the state of the culture medium and the method for improving the state of the culture medium, the estimation unit 204 may have a function of estimating the factor information that contributed to the state of the culture medium among the information based on the measured values or set values acquired by the acquisition unit 202.

[0049] In addition to the function of estimating the state of the culture medium and the method for improving the state of the culture medium, the estimation unit 204 may have a function of estimating the factor information that contributed to the state of the culture medium even if the information acquired by the acquisition unit 202 does not include measured values or set values. As a result, even if the facility environment cannot necessarily monitor all factors, it becomes possible to comprehensively estimate the factors that caused the state of the culture medium.

[0050] The estimation unit 204 may estimate the state of the culture medium and the method for improving the culture medium based on information on rules of thumb related to cell culture input by the user. As a result, even if there is no sensor data, it becomes possible to make an estimation considering the knowledge of experts.

[0051] <Output unit> The output unit 205 has a function of outputting information regarding the state of the culture medium and the method for improving the state of the culture medium estimated by the estimation unit 204. The output method by the output unit 205 is not particularly limited, and may be a display output to a display device or the like, or may be an audio output to a speaker or the like. The output unit 205 has a display control unit 205a that controls the display of the output device 75.

[0052] The output of the "state of the culture medium" may include the name of the state of the culture medium and the description of the state of the culture medium. The description of the state of the culture medium may include a still image or a moving image. In the example of FIG. 10, a name column d101 indicating the name of the state of the culture medium, a summary column d102 indicating the description of the state of the culture medium, and a photo column d103 of the state of the culture medium are provided.

[0053] The output of the "method for improving the state of the culture medium" may include the content of the improvement method and information regarding the sensed items and sensor data, such as "the measurement value by sensor D1 is less than or equal to the recommended value". The content of the improvement method may be output based on the sensed items and information regarding the sensor data. In the example of FIG. 10, the content d201 of the improvement method and advice d202 on the culture operation for improving the state of the culture medium based on the feature quantity (sensor data) are output.

[0054] The output unit 205 may output the state of the culture medium and the method for improving the state of the culture medium estimated by the estimation unit 204 according to the probability that the state of the culture medium and the method for improving the state of the culture medium are reasonable. For example, the state of the culture medium and the method for improving the state of the culture medium may be output in a ranking format according to the probability that the state of the culture medium and the method for improving the state of the culture medium are reasonable. For example, the state of the culture medium and the method for improving the state of the culture medium may be output together with a numerical value or a label indicating the probability that the state of the culture medium and the method for improving the state of the culture medium are reasonable. In the example of FIG. 10, a list screen d301 of rankings according to the probability of occurrence of the state of the culture medium is output. Also, in the example of FIG. 10, when the name column d101 indicating the name of the state of the culture medium for which details are to be confirmed is selected from the list of the states of the culture medium output in a ranking format, a screen d302 showing the details of the selected state of the culture medium is output. In the present disclosure, "probability of being reasonable" may be used interchangeably with "probability of occurrence".

[0055] The output unit 205 may output factor information, which is information among the information acquired by the acquisition unit 202 that contributed to the state of the culture medium estimated by the estimation unit 204. The factor information may be output as information based on the values of sensor data such as "sensor D1 value: 15" or "10.0 < sensor D1 value < 20.0", and may also be output as the item name of factors such as "cell culture temperature" or "temperature inside the incubator". In the example of FIG. 10, among the information acquired by the acquisition unit 202, a graph d401 showing the data of feature quantity 1 is output as factor information that contributed to the state of the culture medium.

[0056] The output unit 205 may output by associating the state of the culture medium estimated by the estimation unit 204 and the method for improving the state of the culture medium with factor information that is information contributing to the state of the culture medium or the method for improving the state of the culture medium among the measured values or set values acquired by the acquisition unit. For example, when there is a state of the culture medium of "overgrowth" estimated by the estimation unit 204, the state of the culture medium of "overgrowth" may be output by associating it with the information of "cell culture temperature exceeds the recommended value", which is factor information contributing to the occurrence of the state of the culture medium of "overgrowth" among the information acquired by the acquisition unit 202. Thereby, even in the operation of cell culture where multiple factors are intricately intertwined, the user can efficiently grasp the factors causing the state of the culture medium and the method for improving the state of the culture medium.

[0057] The output unit 205 may output by associating the state of the culture medium and the method for improving the culture medium estimated by the estimation unit 204 with information related to cell culture that does not have measured values or set values but is estimated by the estimation unit 204 to contribute to the state of the culture medium. For example, when there is a state of the culture medium of "overgrowth" estimated by the estimation unit 204, even when there are no measured values or set values regarding "cell culture temperature", if it is estimated by the estimation unit 204 via a model that "cell culture temperature exceeding the recommended value" contributes to the state of the culture medium of "overgrowth", the state of the culture medium of "overgrowth" may be output by associating it with the information of "cell culture temperature exceeds the recommended value". In this case, it may be output in a manner that enables the user to recognize that it is a factor estimated by the estimation unit 204 but has no measured values or set values. Thereby, even if the user is not in a facility environment where all factors can necessarily be monitored in the operation of cell culture where multiple factors are intricately intertwined, the user can comprehensively grasp the factors causing the state of the culture medium and the method for improving the state of the culture medium.

[0058] The causal information may be output according to the probability of contributing to the state of the medium and the method of improving the medium. For example, the causal information contributing to the state of the medium may be output in a ranking format according to the probability of contributing to the state of the medium and the method of improving the state of the medium. For example, the causal information contributing to the state of the medium and the method of improving the state of the medium may be output together with a numerical value or a label indicating the probability of contributing to the state of the medium and the method of improving the state of the medium. For example, it may be output as a Bayesian network model diagram including a node indicating the causal information contributing to the state of the medium and a node indicating the state of the medium, with the nodes connected by arrows indicating the causality between the nodes. FIG. 12 is a diagram showing an example of the output of the Bayesian network model diagram.

[0059] In the Bayesian network model diagram, the direction and strength of the causality may be expressed using the direction of the arrow, the type of line, the color of the line, or the thickness of the line, etc. Thereby, the strength of the causal relationship can be visualized, and it becomes possible to identify the factors that should be preferentially improved.

[0060] In the Bayesian network model diagram, only the objects indicating a probability equal to or higher than a predetermined threshold value may be output. Thereby, it becomes possible to efficiently grasp the fundamental factors.

[0061] The output unit 205 may output the relationship between the factor information that contributed to the state of the culture medium estimated by the estimation unit 204. For example, among the information based on the measured values or set values acquired by the acquisition unit 202, the relationship such as the causal relationship between a plurality of factor information that is the information contributing to the state of the culture medium may be output. Thereby, the user can understand the relationship structure of the factors and can expect improvement in culture efficiency and culture medium quality. In the example of FIG. 11, a list screen d311 of factor information indicating a plurality of factors affecting the state of the culture medium is output. When a factor (feature amount A: value of cell density) for which details are to be confirmed is selected from the list of factor information, a screen d312 showing the details of the selected factor (feature amount A: value of cell density) is output. When the user selects the label d411 after discretization of the corresponding sensor data for the selected factor, a ranking d412 of factor information showing other factors that affected the value range of the sensor data is output. For example, when the value of the sensor data of the feature amount A (value of cell density) is 685.0, when the user selects the label d411, a ranking d412 of factor information showing other factors that contributed to the numerical value of the feature amount A (value of cell density) is displayed. In the present disclosure, "contributing to the state of the culture medium" and "affecting the state of the culture medium" may be used interchangeably.

[0062] The output unit 205 may output information regarding the index of the target cell culture. The information regarding the index of the target cell culture may be information indicating the cell culture environment when the culture is successful or failed, may be information obtained by comparing the cell culture environment under monitoring with the cell culture environment when the culture is successful or failed, or may be the target numerical value range of the sensor data. The information regarding the index of the target cell culture may include still images or moving images. Thereby, the user can grasp the state of the culture medium more objectively and can expect improvement in culture efficiency and culture medium quality. In the example of FIG. 10, the reference normal value range d501 of the sensor data is displayed. In the example of FIG. 11, the reference value range d511 of the sensor data is displayed.

[0063] The output unit 205 may output the sensor data constituting the cause information as time-series data reflecting the time series when the data was acquired. As a result, the user can recognize and analyze the period when the sensor data constituting the cause information contributed as a cause. In the example of FIG. 10, the feature quantity 1, the feature quantity 2, etc., which are sensor data, are displayed as a graph d401 reflecting a time series with the horizontal axis as the time axis.

[0064] The output unit 205 may output, in a recognizable manner to the user, the number of cell culture samples estimated to have a predetermined medium state with respect to the total number of cell culture samples. As a result, the user can review and improve the cell culture operation in consideration of the occurrence rate of the predetermined medium state with respect to the entire sample, and it becomes possible to provide an improvement in an efficient cell culture environment.

[0065] The output unit 205 may output, in a distinguishable manner to the user, information regarding system errors (errors based on non-human factors) and information regarding human errors (errors based on human factors) among the cause information. For example, among the cause information whose probability of contributing to the medium state is equal to or greater than a predetermined value, the display colors used for information regarding system errors such as "temperature inside the incubator" and information regarding human errors such as "forgetting to tighten the lid of the culture vessel" are made different, etc., to make the output modes different. As a result, the user can efficiently grasp the cause information that contributed to the occurrence of the medium state.

[0066] The output unit 205 may output information regarding the timing of medium replacement or medium recovery together with the state of the medium and the method for improving the state of the medium. As a result, the user can grasp the state of the medium and can also grasp whether the state of the medium requires medium replacement or recovery.

[0067] (Data management server) The data management server 10 has at least a storage unit 101. The storage unit 101 stores various sensor data obtained by sensing with one or more sensors D and various information related to the cell culture equipment input via the operation of the recording system 40. The data stored by the data management server 10 in the storage unit 101 is stored in a medium management DB (Data Base) 101a, a medium state information DB 101b, a sensor data TSDB (Time Series Data Base) 101c, a pH value data TSDB 101d, and an estimation result data TSDB 101e.

[0068] FIG. 13 is a diagram showing a specific example of the data stored by the data management server 10. The medium management DB 101a manages the product ID of the medium, lot number, name, ID of the sensor D, etc. The product ID of the medium is, for example, an identifier for specifying the medium in units of products, and is stored in association with the type of the medium, product name, etc. The lot number is, for example, an identifier for specifying the medium in units of lots, and is stored in association with the manufacturing date, materials, etc. of the medium. The ID of the sensor D is, for example, used for the purpose of managing the configuration of the system, and is an identifier for specifying the sensor used when the medium is sensed by various sensors. Also, the ID of the sensor D may be an identifier for specifying the information (name, model, resolution, etc.) of the sensor in use, and sensor data obtained when the medium is sensed may be stored in association therewith.

[0069] The medium state information DB 101b manages the name of the state of the medium, the symptoms occurring in the medium (for example, acidification or alkalization, etc.), the color development by the pH indicator of the state of the medium (for example, color development by phenol red), the explanation of the state of the medium (for example, cell metabolites, mainly lactic acid is accumulating in the medium, etc.), and the countermeasure method for the state of the medium (for example, centrifuge at 150×g for about 5 minutes, seed into a new medium at a cell density higher than the recommended concentration, add about 10 to 20% of the acclimation medium, etc.).

[0070] In the present disclosure, the "countermeasure method" may be used interchangeably with the "improvement method" in some cases.

[0071] The sensor data TSDB101c manages various sensor data obtained by sensing with the sensor D together with the acquisition date and time of those data.

[0072] The pH value data TSDB101d manages the pH value data of the culture medium obtained by sensing with the sensor D together with the acquisition date and time of those data. The pH value data TSDB101d may also manage the product ID of the culture medium.

[0073] FIG. 14 is a diagram showing a specific example of data stored in the data management server 10. The estimated result data TSDB101e manages the estimated result of the state of the culture medium together with the estimation date and time, the lot number of the culture medium, the product ID, the sensor data by the sensor D, the pH value, etc. The estimated state of the culture medium is stored in the estimated result.

[0074] FIG. 15 is a diagram showing a detailed example of data stored in the culture medium state information DB101b. In the example of FIG. 15, the culture medium state information DB101b manages the presumed cause and the identification method for each occurrence regarding the pH change of acidification or alkalization.

[0075] In the present disclosure, "cause" and "factor" may be used interchangeably in some cases.

[0076] 3. Operation FIG. 16 is a flowchart showing an example of a processing procedure when the culture medium monitoring device executes culture medium monitoring. The culture medium monitoring device 20 acquires at least any one of the first information, the second information, and the third information by the acquisition unit 202 (step S301). The culture medium monitoring device 20 constructs a model for estimating the state of the culture medium based on the information acquired by the acquisition unit 202 by the model construction unit 203 (step S302). The culture medium monitoring device 20 inputs the information acquired by the acquisition unit 202 into the model constructed by the model construction unit 203, and estimates the state of the culture medium and a method for improving the state of the culture medium by the estimation unit 204 (step S303). The culture medium monitoring device 20 outputs information regarding the state of the culture medium and a method for improving the state of the culture medium estimated by the estimation unit 204 by the output unit 205 (step S304).

[0077] 4. Program A program according to an aspect of the present invention causes, in cell culture using a culture medium, at least any one of first information including measurement values obtained by sensing the culture medium, second information regarding the environment of the cell culture, and third information regarding the equipment of the cell culture to be acquired, and causes the state of the culture medium and / or a method for improving the state of the culture medium to be estimated based on the information acquired by the acquisition unit to be executed.

Explanation of Reference Numerals

[0078] 1... Culture medium monitoring system, 10... Data management server, 20... Culture medium monitoring device, 201... Storage unit, 202... Acquisition unit, 203... Model construction unit, 204... Estimation unit, 205... Output unit, 205a... Display control unit, 30... Culture medium state display device, 40... Recording system, 71... Processor, 72... Communication IF, 73... Storage device, 74... Input device, 75... Output device, 76... Communication bus, D... Sensor

Claims

1. In cell culture using a medium, an acquisition unit that acquires at least any one of first information regarding a measurement value obtained by sensing the medium, second information regarding the environment of the cell culture, and third information regarding the equipment for the cell culture; An estimation unit that estimates the state of the medium and / or a method for improving the state of the medium based on the information acquired by the acquisition unit, A medium monitoring device.

2. The estimation unit estimates the state of the medium and / or a method for improving the state of the medium by statistical cause analysis based on the information acquired by the acquisition unit. The medium monitoring device according to Claim 1.

3. Further comprising an output unit that outputs the state of the medium and / or a method for improving the state of the medium estimated by the estimation unit. The medium monitoring device according to Claim 1.

4. The first information includes at least one of imaging information of the medium and optical sensing information of the medium. The second information includes at least one of information regarding the temperature of the culture environment, information regarding the humidity, information regarding the carbon dioxide concentration, and information regarding the oxygen concentration. The third information includes at least one of information regarding the type of the medium, information regarding the cultured cells, and information regarding the culture method. The medium monitoring device according to Claim 1.

5. The method for improving the state of the medium includes culture conditions including a target value of the cell culture. The medium monitoring device according to Claim 1.

6. The output unit outputs the state of the medium and / or a method for improving the state of the medium according to the probability that the state of the medium estimated by the estimation unit occurs and / or the probability that the improvement method is appropriate. The medium monitoring device according to Claim 3.

7. The output unit outputs information among the information acquired by the acquisition unit that contributes to the state of the medium and / or the method for improving the medium estimated by the estimation unit. The medium monitoring device according to Claim 3.

8. A medium monitoring device In cell culture using a medium, a step of acquiring at least any one of first information including a measurement value obtained by sensing the medium, second information regarding the environment of the cell culture, and third information regarding the equipment for the cell culture; A step of estimating the state of the medium and / or a method for improving the state of the medium based on the information acquired in the acquiring step; Executing A medium monitoring method.

9. In a medium monitoring device In cell culture using a medium, a step of obtaining at least any one of first information including a measurement value obtained by sensing the medium, second information regarding the environment of the cell culture, and third information regarding the equipment for the cell culture; a step of estimating the state of the medium and / or a method for improving the state of the medium based on the information obtained in the obtaining step; and causing to execute a program.

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