WO2023189281A1 - Information processing apparatus, information processing method, cell culturing system, and program - Google Patents

Abstract

The present invention provides a technology that enables visual confirmation of a culturing condition of a cell group including different cells. The present technology provides an information processing apparatus comprising a control unit for predicting multiple culturing prediction results for each culturing condition of a cell group including different cells. The control unit performs control so as to visualize, as the culture prediction results, the composition of cultured cells and the proliferative process of the cells. The present technology also provides a cell culturing system having: a cell culturing device comprising a cell culturing unit for culturing a cell group including different cells, and a measurement unit for measuring the cellular composition of the cell group and the proliferative process of the cells; and an information processing apparatus which comprises a control unit for predicting multiple culturing prediction results for each culturing condition of a cell group including different cells, and in which the control unit performs control so as to visualize, as the culturing prediction result, the composition of the cultured cells and the proliferative process of the cells.

Description

Information processing device, information processing method, cell culture system, and program

The present technology relates to an information processing device, an information processing method, a cell culture system, and a program. More specifically, the present invention relates to an information processing device, an information processing method, a cell culture system, and a program that can provide an overview of culture conditions for cell groups including different cells.

Cell production in regenerative medicine requires culturing the required amount of cells at the desired time. In contrast, conventionally, a skilled operator determines the culture conditions and adjusts the culture conditions as necessary by observing the culture state of the cells during culture. However, since it is difficult to stably culture living cells, automatic culture systems are sometimes used.

For example, Cited Document 1 describes a culture support device for culturing cells in a culture tank, and a target, which is a specific growth rate to obtain a target number of cells at a target time, among a plurality of performance data. Set culture conditions, which are culture conditions for obtaining the target specific growth rate, are determined based on a neighboring data group, which is a set of actual data similar to the query point, including the specific growth rate and the culture status of the culture tank. A culture support device comprising a calculation device, wherein each of the plurality of performance data is data regarding culture performed in the past, and includes a specific growth rate and a culture status when the specific growth rate was obtained. is disclosed.

JP2019-41656A

However, although there are conventional methods for classifying different cell types, there is a method that allows for hierarchical classification and a bird's-eye view of predicted results such as cell composition and cell growth process according to culture conditions. The problem was that it didn't exist.

Therefore, the main purpose of this technology is to provide a technology that allows a bird's-eye view of the culture conditions of a cell group containing different cells.

First, the present technology includes a control unit that predicts a plurality of culture prediction results for each culture condition of a cell group including different cells, and the control unit is configured to predict a cultured cell composition and cell growth based on the culture prediction results. An information processing device is provided that controls a process to be visualized.

In addition, the present technology includes a control step of predicting a plurality of culture prediction results for each culture condition of a cell group including different cells, and in the control step, the culture prediction results include the composition of the cultured cells and the growth of the cells. It also provides an information processing method that controls the process to make it visible.

Furthermore, the present technology includes a cell culture device having a cell culture section for culturing cell groups containing different cells, and a measurement section for measuring the cell composition of the cell groups, and a cell culture device for each culture condition of the cell groups containing different cells. a control unit that predicts a plurality of culture prediction results, the control unit comprising an information processing device that controls to visualize the cultured cell composition and cell growth process as the culture prediction results; Cell culture systems are also provided.

In addition, the present technology predicts a plurality of culture prediction results for each culture condition of a cell group containing different cells, and controls to visualize the cultured cell composition and cell growth process as the culture prediction results. A program that causes a computer to execute a process including steps is also provided.

FIG. 1 is a schematic diagram showing an example of an embodiment of a cell culture system according to a first embodiment. It is a schematic diagram of a sample holding part. FIG. 2 is a schematic diagram of an immobilized first molecule. FIG. 2 is a schematic diagram showing an example of the configuration of a cell processing container. FIG. 3 is a schematic diagram showing an example of the configuration of an optical control section. 1 is a diagram schematically showing the overall configuration of a microscope system. 1 is a diagram schematically showing the overall configuration of a biological sample analyzer. FIG. 3 is a flow diagram of an information processing method according to a second embodiment. It is a flow diagram of a control process. It is a flow diagram of a processing process. It is a figure showing an example of a culture prediction result. 12 is a diagram showing an example of culture prediction results different from FIG. 11. FIG. 12 is a diagram showing an example of culture prediction results different from FIGS. 11 and 12. FIG. 13 is a diagram showing an example of culture prediction results different from FIGS. 11 to 13. FIG. 14 is a diagram showing an example of culture prediction results different from FIGS. 11 to 14. FIG. FIG. 16 is a diagram showing an example of culture prediction results different from FIGS. 11 to 15. FIG.

Hereinafter, preferred forms for implementing the present technology will be described with reference to the drawings. The embodiment described below shows an example of a typical embodiment of the present technology, and any embodiment can be combined. Furthermore, the scope of the present technology should not be interpreted narrowly due to these. Note that the explanation will be given in the following order.

1. First embodiment (cell culture system 1000 and information processing device 2)
(1) Overall configuration (2) Cell culture device 1
(2-1) Cell culture section 10
(2-2) Measuring section 3
(2-2-1) Microscope system 5000
(2-2-2) Biological sample analyzer 6100
(3) Information processing device 2
2. Second embodiment (information processing method)
(1) Overall configuration (2) Sample preparation process S100
(3) Information acquisition step S110 regarding cells before treatment
(4) Control process S120
(5) Processing step S130
(6) Information acquisition step S140 regarding cells after treatment
(7) Learning process

1. First embodiment (cell culture system 1000 and information processing device 2)

(1) Overall composition

With reference to FIG. 1, the overall configuration of a cell culture system 1000 according to a first embodiment of the present technology will be described. The cell culture system 1000 according to this embodiment includes at least a cell culture device 1 and an information processing device 2. Additionally, other devices and parts may be included as necessary. Note that each device and each part may be stored in the same housing, or may be stored in separate housings and connected via a wired or wireless network.
Hereinafter, each device and each part of the cell culture system 1000 will be explained in detail.

(2) Cell culture device 1

The cell culture device 1 includes at least a cell culture section 10 for culturing a cell group containing different cells, and a measurement section 3 for measuring the cell composition of the cell group and the cell growth process. In addition, other parts may be included as necessary.

As used herein, "cell" may be any of human-derived cells, immune cells, animal-derived cells, plant-derived cells, microbial-derived cells, cancer cells, normal cells, stem cells, and epithelial cells. For example, in the case of animal cells, examples of the cells include cells in blood and cells collected from living tissue. Further, the cells may be either adherent cells or non-adherent cells. Furthermore, the number of types of cells contained in the sample may be one or more, and the term "cell" includes cell clusters, such as spheroids, organoids, and the like.

(2-1) Cell culture section 10

A schematic diagram of the sample holding section 100 of the cell culture section 10 is shown in FIG. 2. A first molecule 104 capable of binding to cells is immobilized on the sample holding part 100 via a degradable linker 103. Degradable linker 103 may be fixed to the bottom of container 101, as shown in FIG. The sample holder 100 may be variable so that its volume increases or decreases. When cells are introduced into the culture container 101, the sample holding unit 100 captures the cells using the first molecules 104 immobilized therein. The captured cells are cultured within the culture container 101.

A first molecule 104 is immobilized inside the culture container 101 of the sample holding unit 100 via a polymer 102 and a degradable linker 103, for example. Note that the degradable linker 103 may directly immobilize the first molecule 104 without using the polymer 102. Immobilization is not limited to the bottom surface of the culture vessel 101, but may be on the inner wall, or, if a planar or three-dimensional internal structure exists inside the culture vessel 101, the surface of the structure. may be immobilized. Note that the inner surface of the culture container 101 is preferably coated with a substance suitable for cell survival (eg, collagen, fibroblast, etc.).

When the polymer 102 is used, the polymer 102 is preferably one that does not stress cells or is non-toxic, or one that is biocompatible. Examples of polymers include polyethylene glycol (PEG), 2-methacryloyloxyethyl phosphorylcholine polymer (MPC polymer), and the like. Further, a degradable linker 103 may be bonded to the end of the polymer 102 opposite to the bonding portion with the culture vessel 101. The degradable linker 103 is a molecule that is decomposed by a specific external stimulus. Degradable linker 103 connects first molecule 104 to the bottom of the container, with or without polymer 102 . Examples of the degradable linker 103 include a linker that is decomposed by light of a specific wavelength, a linker that is decomposed by an enzyme, a linker that is decomposed by temperature, and the like. The degradable linker is preferably a photodegradable linker because it allows control on a single cell basis and takes a short time to degrade.

The photodegradable linker is a molecule having a structure that is decomposed by light of a specific wavelength, and conventionally known linkers can be used. Furthermore, the wavelength at which the photodegradable linker is decomposed almost coincides with the absorption wavelength of the molecule. For example, when the photodegradable linker contains a methoxynotrobenzyl group, assuming that the absorption at 346 nm is 1, it exhibits an absorption of 0.89 at 364 nm, 0.15 at 406 nm, and 0.007 at 487 nm. That is, if a 365 nm light source is used, the photodegradable linker is decomposed efficiently, and the photodegradable linker has a property that it is hardly decomposed by a 488 nm light source. In this way, the wavelength of the light irradiated to the photodegradable linker may be any wavelength that corresponds to each photodegradable linker. For example, the wavelength is around 330 to 450 nm. In addition, for example, 30 mW/cm ² , 100 sec. → It is preferable to irradiate at 3 J/cm ² .

The first molecule 104 has a site capable of binding to cells. As the site capable of binding to cells, for example, oleyl groups, cholesteryl groups, antibodies, aptamers, molecular recognition polymers, etc. can be used.

The oleyl group and cholesteryl group are hydrophobic and adhere to the surface of floating cells. The first molecule 104 may be formed by adding a spacer such as PEG to the oleyl group and including an NHS group (N-hydroxysuccinimide group) at the end thereof.

The antibody binds to a cell surface molecule antigen present on the cell. Examples of the antibodies include antibodies against cancer-specific antigens, antibodies against major histocompatibility antigens, and antibodies against sugar chains.

The aptamer is a nucleic acid molecule or peptide that specifically binds to molecules possessed by cells. Examples of the aptamer include DNA aptamers, RNA aptamers, peptide aptamers, and modified aptamers in which specificity is improved by introducing modifications into the nucleic acid backbone or base.

The molecular recognition polymer captures target cell surface molecules with high selectivity even in the presence of compounds with physicochemical properties similar to cell surface molecules. The molecular recognition polymer is also called a molecular imprint polymer and has a selectively synthesized compound recognition region.

FIG. 3 shows a schematic example of the state in which the first molecule 104 is immobilized within the culture container 101. A first molecule 104 is immobilized on the bottom surface of the culture container 101 via a polymer 102 and a degradable linker 103. In FIG. 3, the first molecule 104 is directly bonded to the degradable linker 103, but it may also be bonded to the degradable linker 103 via a polymer. By employing this configuration, when the first molecule 104 and the cells introduced into the culture container 101 approach or come into contact with each other, the first molecule 104 can capture the cells.

The first molecule 104 is preferably immobilized so that one cell is bound to each spot. By capturing one cell per spot, cells having molecules (eg, antibodies, sugar chains, etc.) that can bind to the first molecule 104 can be selected at a single cell level. Moreover, such sorting can also be performed for all spots.

Furthermore, the first molecules 104 are preferably immobilized in an array within the culture container 101. As a method of spotting the first molecules 104 in an array, a microcontact printing method, a spotting method, or a method of disassembling unnecessary portions after placing them on the entire surface using the characteristics of the photodegradable linker is used. good. Regarding the part where it is desired to prevent cells from being captured, the PEG or the MPC polymer may be coated or bonded to the part of the culture vessel 101, thereby suppressing non-specific adsorption of cells. After releasing unnecessary cells by irradiating the photodegradable polymer with light, it is preferable that PEG or MPC polymer remain so as to prevent non-specific adsorption of cells to the released spots.

Note that the first molecule 104 to be spotted may be one type, and for example, the first molecule 104 configured to specifically capture only one type of cell may be employed. Alternatively, first molecules 104 having different specificities may be immobilized for each spot, and different cells may be captured for each spot. Alternatively, the inside of the culture container 101 may be divided into sections, and the first molecules 104 having different specificities may be immobilized in each section, thereby making it possible to capture different cells in each section in the same container. can. Alternatively, the first molecule 104 that captures all types of cells may be immobilized, and in this case, cells may be sorted using a labeled second molecule, which will be described later. Multicolor analysis becomes possible by using multiple types of labeled second molecules.

The culture container 101 may be configured so that its volume can be changed. It is preferable that the variable part of the culture container 101 be formed of a flexible material, and it is preferable that the culture container 101 can be expanded and contracted vertically and/or horizontally. The volume can be changed by adjusting the amount of liquid or the amount of air introduced from the connecting part 105 provided in the culture container 101. Additionally, the flow rate of the liquid or air supplied into the culture container 101 is controlled so as to change the volume of the liquid (for example, culture medium, buffer solution, staining buffer, etc.) in the culture container 101 without changing the volume. may be implemented. Thereby, reactions and the like can be performed on the cells in the culture container 101 at an optimal concentration.

After a sample containing cells is introduced into the culture container 101, in order to efficiently trap the cells in the first molecules 104, it is preferable to reduce the volume of the culture container 101 or the volume of the medium. This is because when the volume or medium volume is small, the probability of contact between the cells and the first molecules 104 increases. Further, after culturing the cells captured by the first molecules 104, if the cell density becomes high, it is preferable to increase the volume of the culture container 101 or the volume of the medium. Increasing the volume or medium volume increases the cell culture space. Further culture medium can be added by increasing the volume.

Note that the culture container 101 preferably has gas permeability. This makes it possible to create an environment in the container suitable for cell culture (e.g., optimal CO ₂ concentration, optimal temperature, etc.) when, for example, oxygen supply and/or carbon dioxide evacuation are required in cell culture. I can do it. In particular, the surface on which cells proliferate is preferably formed of, for example, a porous membrane or an oxygen permeable membrane.

The culture container 101 may be connected to a sample containing the cells or a container containing the culture solution by a connecting portion 105. For example, as shown in FIG. 4, a cell input section 106, a second molecule supply section 107, an activating agent supply section 108, a gene supply section 109, a culture solution supply section 110, a washing solution supply section 111, a waste liquid storage section 112, and the cell collection unit 113, or a plurality of them may be connected to the culture container 101. The whole of these may be installed under conditions suitable for cell culture, or only the culture container 101 may be installed under conditions suitable for cell culture.

The cell input unit 106 holds a sample (particularly a liquid sample) containing cells, and inputs the sample into the culture container 101.

The second molecule supply unit 107 holds the second molecule therein and is configured to feed the second molecule into the culture container 101. If multiple types of second molecules are required, the number of second molecule supply units 107 may be increased according to the number. The second molecule may be a molecule capable of binding to cells. The second molecule may be labeled with a fluorescent substance or the like. The first molecule 104 and the second molecule form a structure (for example, a sandwich structure) in which a cell is sandwiched, and the formation of the structure can be recognized by the label. The second molecule, like the first molecule 104, may be selected from the group consisting of, for example, oleyl groups, antibodies, aptamers, and molecular recognition polymers. The second molecule may be a molecule that specifically binds only to desired cells among the cells captured by the first molecule 104.

The label of the second molecule may be one type of fluorescent substance or multiple types of fluorescent substances. For example, one type of cell may be recognized using one type of fluorescent substance. Alternatively, multiple types of cells may be recognized using multiple types of fluorescent substances, and a technique such as so-called multicolor analysis may be used. Cells that cannot be recognized by the second molecule apply stimulation to the degradable linker 103 at the spot where the cell is captured, and the stimulation cleaves the degradable linker 103, releasing the cell. Free cells can be washed away from the culture container 101 with a washing solution as unnecessary substances. Based on pseudo-stained images for each cell feature identified from information learned from bright field images, phase contrast images, polarized images, unstained images, and fluorescent images without using a second molecule. Cells may be identified and released by light stimulation. The identification may be performed by the information processing device 2 described later. The information processing device 2 can drive the optical control unit 210 based on the result of the identification to apply the optical stimulation. In the case of this method, a second molecule is not required, which can contribute to reducing process costs. Also, since the dyeing process can be omitted, it contributes to shortening the process.

The cleaning liquid supply unit 111 holds the cleaning liquid. A cleaning liquid is supplied when cleaning unnecessary materials etc. in the culture container 101. The washing liquid may be one commonly used for cell culture and the like. Examples of the washing solution include, but are not limited to, physiological saline, Tris buffer, HEPES buffer, purified water, and the like.

The activating agent supply unit 108 holds an activating agent for activating cells, particularly a liquid containing the activating agent. The activating agent supply unit 108 may be configured to supply an activating agent into the culture container 101. The activator may be selected depending on the cell and includes, but is not particularly limited to, cytokines, hormones, interleukins, antibodies, and the like. The activating agent can activate the cells before, during, or after culturing the cells.

The gene supply unit 109 holds genes that are desired to be introduced into cells. The gene supply unit 109 may be configured to supply the gene into the culture container 101. The gene may be an endogenous gene or a foreign gene. The gene may be incorporated into a phage vector, plasmid vector, viral vector, or the like suitable for gene introduction. For example, the gene supply unit 109 can supply a virus vector incorporating a target gene to the culture container 101. Thereby, cells can be infected with the virus vector to introduce genes. Furthermore, the gene supply unit 109 may supply a genome editing reagent containing a specific base sequence and a specific enzyme, such as the CRISPR/Cas9 system, to the culture container 101, thereby introducing the gene into the cells. Good too.

The culture solution supply unit 110 holds a culture solution suitable for cells and supplies the culture solution to the culture container 101. A culture medium suitable for the cells can be selected; for example, Eagle's medium, D-MEM medium, E-MEM medium, RPMI-1640 medium, Dulbecco's PBS medium, etc. can be used. Note that if the culture solution is colored with phenol red or the like, the optimum pH range of the culture solution (for example, pH 6.8 to 7.2) can be controlled while the cells are being cultured in the culture container 101.

The waste liquid storage section 112 temporarily receives the waste liquid, culture liquid, etc. containing the above-mentioned unnecessary substances. The waste liquid is subjected to sterilization treatment, etc., as necessary, and then discarded.

The cell collection unit 113 collects and retains the cells cultured in the culture container 101. The recovery method is not particularly limited, but can be performed by suction, extrusion, placing the cell recovery unit 113 below the culture container 101, or the like.

The physicochemical environment supply unit 114 maintains or provides the physicochemical environment of the sample holding unit 100. The physicochemical environment during culture can be appropriately selected depending on the cells, and examples thereof include, but are not limited to, humidity, pH, osmotic pressure, oxygen partial pressure, carbon dioxide partial pressure, and the like. This provides cells with an optimal physicochemical environment and increases cell survival rate.

The connecting part 105 connects the culture container 101 and any one or more of the above-mentioned parts 106 to 114, through which the liquid flows. For example, a tube is used for the connecting portion 105. As a liquid feeding method, a peristaltic pump or the like that does not come in contact with liquid is preferable.

The cell culture section 10 may further include a cell culture section control section 200, and the cell culture section control section 200 includes, for example, an optical control section 210 and an environment control section. The cell culture section control section 200 performs physicochemical control on the cells included in the sample holding section 100 and/or the environment around the cells.

The optical control unit 210 may apply stimulation by irradiating the degradable linker 103 with light of a specific wavelength through optical control. The optical control unit 210 may include, for example, a light source and a MEMS (Micro Electro Mechanical Systems) element for causing the light emitted from the light source to reach a predetermined position (a predetermined position in the container 101). . The MEMS device may be, for example, a DMD or a scanning mirror. The optical control unit 210 may further include an optical element (for example, a lens, a filter, a mirror, a prism, etc.) for controlling the shape and/or wavelength of the light.

The environment control unit may maintain or provide a physicochemical or physiological environment around the cells contained in the sample holding unit 100 through physicochemical or physiological control.

FIG. 5 shows an example of the configuration of the optical control section 210. The optical control unit 210 shown in FIG. 5 includes a light source 211, a focusing lens 212, an excitation filter 213, a digital mirror device 214, and a projection lens 215 in order to irradiate the light of the specific wavelength. By having the above configuration, unnecessary cells can be selected and released. The light source 211 emits light of a wavelength corresponding to the degradable linker 103. A focusing lens 212 focuses the light, and an excitation filter 213 extracts and transmits only light of a specific wavelength. The digital mirror device 214 is composed of movable micromirrors, and by tilting each micromirror, it is possible to selectively irradiate each spot on which the first molecules 104 are immobilized. The projection lens 215 irradiates the light reflected by the digital mirror device 214 toward the surface of the culture container 101 where the spot where the first molecule 104 is immobilized is located. By selective light irradiation by the optical control unit 210, the degradable linker 103 in the spot where the cells to be released are captured can be selectively decomposed.

The optical control unit 210 may further include a stimulation control unit that makes it possible to stimulate the degradable linker 103 for each of the first spots. If the optical control unit 210 is a light irradiation device, it is sufficient to individually irradiate cells arranged in the culture container 101 at intervals of several tens of μm, for example, a digital micromirror device (DMD), a liquid crystal panel, MEMS shutters etc. can be used. It is possible to support multicolor analysis by disposing an excitation filter 213 between the light source 211 and the DMD 214, and adding a mechanism for rotating the filter so as to obtain an optimal filter configuration depending on the purpose. Since a DMD equipped with a full HD number of micromirrors is commercially available, the stimulation control section of a light irradiation device using this can simultaneously control (turn ON/OFF irradiation on) 1920×1080 sites. Therefore, individual control of approximately 2×10 ⁶ cells is possible at the same time. For example, when cells (ie, Φ30 um or less) are arranged at a pitch of 30 μm at 1920×1080 sites, an area of approximately 58×33 mm is required. If you want to treat ¹⁰⁷ cells, prepare 10 sides of this. When five sides are arranged in two rows, the size is 116 x 165 mm, which is one size smaller than B6 size, and is a size that can be realized for analysis of 2 x 10 ⁷ cells.

The environment control unit controls the physicochemical environment and/or physiological environment within the container 101. In order to control the physicochemical environment, the environment control section controls the physicochemical environment supply section 114, thereby controlling the humidity, pH, osmotic pressure, oxygen partial pressure, or carbon dioxide inside the container 101. Partial pressure, etc. can be controlled. This provides an optimal physicochemical environment for the cells in the culture environment and increases the survival rate of the cells. In order to control the physiological environment, the environment control section can control at least one selected from the group consisting of the activator supply section 108, the gene supply section 109, and the culture solution supply section 110. . This provides an optimal physiological environment for the cells in the culture environment and improves the efficiency of cell culture. Control of the physiological environment may include control by at least one of culture medium, stimulation factors, transcription factors, and cell density.

(2-2) Measuring section 3

The cell culture system 1000 includes a measurement unit 3 that acquires at least one selected from the group consisting of information regarding cells before treatment, information regarding cells after treatment, and information regarding cells during treatment. The measurement unit 3 includes an image acquisition unit 600 that acquires information regarding cells being processed by the cell culture unit control unit 200 by acquiring images. The image acquired by the image acquisition unit 600 may be a stained image and/or a non-stained image.

The stained image may include a fluorescent image. Further, the unstained image is at least one of a bright field image, a phase contrast image, a polarized light image, and an image that is identified from information learned from the unstained image and the fluorescent image and pseudostained for each cell feature. may include. In addition to the image acquisition section 600 or instead of the image acquisition section 600, the measurement section 3 includes a signal detection section that acquires information regarding the cells being processed by the cell culture section 10 by acquiring signals. Good too. For example, the image acquisition unit 600 may be configured as a microscope system 5000 described below (2-2-1). Furthermore, when the measuring section 3 includes the signal detecting section, the measuring section 3 may be configured as a biological sample analyzer 6100. The biological sample analysis device 6100 will be explained in “(2-2-2) Biological sample analysis device 6100”.

Note that the measurement unit 3 can analyze the proliferation state of the cells from the information regarding the size of the cell mass and the number of cells acquired by the measurement unit 3. For example, in the case of T cells, cell clusters may be created during cell proliferation. By measuring the area of the cell cluster, it is possible to predict the number of cells, and by measuring the number of clusters, it is possible to predict the total number of cells in the container. By acquiring measurement values regarding the mass in time series, the proliferation state of the cells can be confirmed.

(2-2-1) Microscope system 5000

An example of the configuration of the microscope system 5000 is shown in FIG. A microscope system 5000 shown in FIG. 6 includes a microscope device 5100, a control section 5110, and an information processing section 5120. The microscope device 5100 includes a light irradiation section 5101, an optical section 5102, and a signal acquisition section 5103. The microscope device 5100 may further include a sample mounting section 5104 on which a biological sample S1 such as a cell is placed. Note that the configuration of the microscope system 5000 is not limited to that shown in FIG. may be used as the light irradiation unit 5101. Further, the light irradiation unit 5101 may be arranged so that the sample mounting unit 5104 is sandwiched between the light irradiation unit 5101 and the optical unit 5102, and may be arranged, for example, on the side where the optical unit 5102 is present. The microscope device 5100 may be configured with one or more selected from the group consisting of bright field observation, phase contrast observation, differential interference observation, polarized light observation, fluorescence observation, and dark field observation.

The microscope system 5000 may be configured as a so-called WSI (Whole Slide Imaging) system or a digital pathology system, and may be used mainly for pathological diagnosis. The microscope system 5000 may also be configured as a fluorescence imaging system, particularly a multiplex fluorescence imaging system.

Additionally, the microscope system 5000 may be used to perform intraoperative pathological diagnosis or remote pathological diagnosis. In the intraoperative pathological diagnosis, while the surgery is being performed, the microscope device 5100 acquires data of the biological sample S1 obtained from the patient undergoing the surgery, and transmits the data to the information processing unit 5120. I can do it. In the remote pathological diagnosis, the microscope device 5100 can transmit the data of the acquired biological sample S1 to the information processing unit 5120 located in a location apart from the microscope device 5100 (for example, in another room or building). . In these diagnoses, the information processing unit 5120 receives and outputs the data. Based on the output data, the user of the information processing unit 5120 can perform a pathological diagnosis.

(Biological sample S1)
The biological sample S1 may be a sample containing biological components. The biological component may be a biological tissue, a cell, a biological liquid component (eg, blood, urine, etc.), a culture, or a living cell (eg, a cardiac muscle cell, a nerve cell, a fertilized egg, etc.). The biological sample S1 may be a solid substance, and may be a specimen fixed with a fixing reagent such as paraffin or a solid substance formed by freezing. The biological sample S1 may be a section of the solid object. A specific example of the biological sample S1 is a section of a biopsy sample.

The biological sample S1 may be subjected to treatments such as staining or labeling. The treatment may be staining to show the form of the biological component or to show the substances (for example, surface antigens, etc.) that the biological component has, such as HE (Hematoxylin-Eosin) staining and immunohistochemistry staining. etc. can be mentioned. The biological sample S1 may be subjected to the above-mentioned treatment using one or more reagents, and the reagents may be fluorescent dyes, coloring reagents, fluorescent proteins, fluorescently labeled antibodies, or the like.

The specimen may be prepared from a specimen or tissue sample collected from a human body for the purpose of pathological diagnosis or clinical examination. Further, the specimen is not limited to the human body, but may be derived from animals, plants, or other materials. The specimen includes the type of tissue used (e.g., organ, cell, etc.), the type of disease targeted, the attributes of the subject (e.g., age, sex, blood type, race, etc.), and the lifestyle habits of the subject. (For example, eating habits, exercise habits, smoking habits, etc.) The specimens may be managed by being assigned identification information (for example, various barcode information, etc.) that allows each specimen to be identified.

(Light irradiation unit 5101)
The light irradiation unit 5101 includes a light source for illuminating the biological sample S1 and an optical unit that guides the light irradiated from the light source to the sample. The light source can irradiate the biological sample with visible light, ultraviolet light, or infrared light, or a combination thereof. The light source may be one or more selected from the group consisting of a halogen lamp, a laser light source, an LED lamp, a mercury lamp, and a xenon lamp. A plurality of types and/or wavelengths of light sources may be used in fluorescence observation, and may be appropriately selected by those skilled in the art. The light irradiation unit 5101 can have a configuration of a transmission type, a reflection type, or an epi-illumination type (a coaxial epi-illumination type or a side-emission type).

(Optical section 5102)
The optical section 5102 is configured to guide light from the biological sample S1 to the signal acquisition section 5103. The optical unit 5102 may be configured to enable the microscope device 5100 to observe or image the biological sample S1. Optical section 5102 can include an objective lens. The type of objective lens may be appropriately selected by those skilled in the art depending on the observation method. Further, the optical section 5102 may include a relay lens for relaying the image magnified by the objective lens to the signal acquisition section 5103. The optical unit 5102 may further include optical components other than the objective lens and the relay lens, such as an eyepiece, a phase plate, and a condenser lens.

Furthermore, the optical section 5102 may further include a wavelength separation section configured to separate light having a predetermined wavelength from among the light from the biological sample S1. The wavelength separation section may be configured to selectively allow light of a predetermined wavelength or wavelength range to reach the signal acquisition section. The wavelength separation section may include, for example, one or more selected from the group consisting of a filter that selectively transmits light, a polarizing plate, a prism (Wollaston prism), and a diffraction grating. The optical components included in the wavelength separation unit may be placed on the optical path from the objective lens to the signal acquisition unit 5103, for example. The wavelength separation section is provided in the microscope apparatus 5100 when fluorescence observation is performed, particularly when the excitation light irradiation section is included. The wavelength separation unit may be configured to separate fluorescent light from each other or white light and fluorescent light.

(Signal acquisition unit 5103)
The signal acquisition unit 5103 may be configured to receive light from the biological sample S1 and convert the light into an electrical signal, particularly a digital electrical signal. The signal acquisition unit 5103 may be configured to be able to acquire data regarding the biological sample S1 based on the electrical signal. The signal acquisition unit 5103 may be configured to be able to acquire data of an image (image, in particular, a still image, a time-lapse image, a moving image) of the biological sample S1, and in particular, an image of the biological sample S1 magnified by the optical unit. The image data may be configured to obtain image data. The signal acquisition unit 5103 includes one or more image sensors, CMOS, CCD, etc., each having a plurality of pixels arranged one-dimensionally or two-dimensionally. The signal acquisition unit 5103 may include an image sensor for obtaining a low-resolution image and an image sensor for obtaining a high-resolution image, or an image sensor for sensing for AF etc. and an image sensor for outputting images for observation etc. It may also include an element. In addition to the plurality of pixels, the image sensor includes a signal processing unit (including one, two, or three of a CPU, a DSP, and a memory) that performs signal processing using pixel signals from each pixel; The signal processing sensor may also include an output control section that controls output of image data generated from pixel signals and processed data generated by a signal processing section. Furthermore, the image sensor may include an asynchronous event detection sensor that detects as an event that a change in brightness of a pixel that photoelectrically converts incident light exceeds a predetermined threshold. The image sensor including the plurality of pixels, the signal processing section, and the output control section may preferably be configured as a one-chip semiconductor device.

(Control unit 5110)
The control unit 5110 controls imaging by the microscope device 5100. The control unit 5110 can adjust the positional relationship between the optical unit 5102 and the sample platform 5104 by driving the movement of the optical unit 5102 and/or the sample platform 5104 for imaging control. The control unit 5110 can move the optical unit 5102 and/or the sample mounting unit 5104 in a direction toward or away from each other (for example, in the direction of the optical axis of the objective lens). Further, the control unit 5110 may move the optical unit 5102 and/or the sample mounting unit 5104 in any direction in a plane perpendicular to the optical axis direction. The control unit 5110 may control the light irradiation unit 5101 and/or the signal acquisition unit 5103 for imaging control.

(Sample placement section 5104)
The sample mounting section 5104 may be configured such that the position of the biological sample S1 on the sample mounting section 5104 can be fixed, and may be a so-called stage. The sample placement unit 5104 may be configured to be able to move the position of the biological sample S1 in the optical axis direction of the objective lens and/or in a direction perpendicular to the optical axis direction.

(Information processing unit 5120)
The information processing unit 5120 can acquire data (for example, imaging data, etc.) acquired by the microscope device 5100 from the microscope device 5100. The information processing unit 5120 can perform image processing on imaging data. The image processing may include color separation processing. The color separation process is a process of extracting data of a light component of a predetermined wavelength or wavelength range from imaging data to generate image data, or removing data of a light component of a predetermined wavelength or wavelength range from the imaging data. This may include processing, etc. Further, the image processing may include autofluorescence separation processing that separates the autofluorescence component and dye component of the tissue section, and fluorescence separation processing that separates the wavelengths of dyes that have different fluorescence wavelengths from each other. In the autofluorescence separation process, an autofluorescence signal extracted from one of the plurality of samples that are the same or have similar properties may be used to remove an autofluorescence component from image information of the other sample. .

The information processing unit 5120 may transmit data for controlling imaging to the control unit 5110, and the control unit 5110 that has received the data may control imaging by the microscope device 5100 in accordance with the data. The information processing unit 5120 may be configured as an information processing unit such as a general-purpose computer, and may include a CPU, RAM, and ROM. The information processing unit 5120 may be included within the casing of the microscope device 5100, or may be located outside the casing. Moreover, various processes or functions by the information processing unit may be realized by a server computer or cloud connected via a network.

Note that the image acquired by the signal acquisition unit 5103 may be a stained image and/or a non-stained image. The signal acquisition unit 5103 may acquire information regarding cells before processing, during processing, and after processing as feature amounts from the image. Specific examples of information regarding the cells will be described later.

The stained image is, for example, a fluorescent image obtained by the light irradiation unit 5101 irradiating excitation light onto the biological sample S1 stained with a fluorescent reagent. Thereby, for example, molecular marker analysis of the biological sample S1 having biomarkers such as CD4 and CD8 becomes simple and quantitative. The unstained image may be a bright field image, a phase contrast image, or a polarized image obtained from the unstained biological sample S1. Furthermore, the non-stained image may be an image that is identified from information learned from the non-stained image and the fluorescent image and pseudo-stained for each cell feature. The pseudo-stained images allow prediction of various labels such as nucleus, cell type (e.g. nerve), cell state (e.g. cell death, etc.) from unstained images, and chemical staining It becomes possible to eliminate the limitation on the number of simultaneous labels due to the overlap of fluorescence spectra. As for the specific method of generating the pseudo-stained image, a conventionally known method can be used, and the present technology is not particularly limited.

(2-2-2) Biological sample analyzer 6100

An example of the configuration of the biological sample analyzer 6100 is shown in FIG. The biological sample analyzer 6100 shown in FIG. The information processing unit 6103 includes an information processing unit 6103 that processes information regarding the emitted light. Specific examples of the biological sample analyzer 6100 include a flow cytometer and an imaging cytometer. The biological sample analyzer 6100 may include a sorting section 6104 that sorts out specific biological particles P in the biological sample S2. A specific example of the biological sample analyzer 6100 including the sorting section 6104 is a cell sorter.

(Biological sample S2)
The biological sample S2 may be a liquid sample containing biological particles P. The biological particles P are, for example, cells or non-cellular biological particles. The cells may be living cells, and more specific examples include blood cells such as red blood cells and white blood cells, and reproductive cells such as sperm and fertilized eggs. Further, the cells may be directly collected from a specimen such as whole blood, or may be cultured cells obtained after culturing. Examples of the non-cellular biological particles include extracellular vesicles, particularly exosomes, microvesicles, and the like. The biological particles P may be labeled with one or more labeling substances (for example, a dye (particularly a fluorescent dye), a fluorescent dye-labeled antibody, etc.). Note that the biological sample analyzer 6100 according to this embodiment may analyze particles other than the biological particles P, and beads or the like may be analyzed for calibration or the like.

(Flow path C)
The flow path C may be configured to allow the biological sample S2 to flow, in particular, to form a flow in which biological particles contained in the biological sample S2 are substantially aligned. The channel structure including the channel C may be designed to form a laminar flow, and in particular, a laminar flow is formed in which the flow of the biological sample S2 (sample flow) is surrounded by the flow of the sheath liquid. Designed to be. The design of the channel structure may be appropriately selected by those skilled in the art, and a known design may be adopted. The flow channel C may be formed in a flow channel structure such as a microchip (a chip having a flow channel on the order of micrometers) or a flow cell. The width of the channel C may be 1 mm or less, particularly 10 μm or more and 1 mm or less. The channel C and/or the channel structure including the channel C may be formed from a material such as plastic or glass.

The biological sample analyzer 6100 according to the present embodiment is configured such that the biological sample S2 flowing in the flow path C, in particular, the biological particles P in the biological sample S2, is irradiated with the light from the light irradiation unit 6101. may be configured. The biological sample analyzer 6100 may be configured such that the interrogation point of the light on the biological sample S2 is in the channel structure in which the channel C is formed, or the interrogation point of the light may be configured to be located outside the channel structure. Examples of the former include a configuration in which the light is irradiated onto a channel C within a microchip or a flow cell. As an example of the latter, the biological particles P may be irradiated with the light after exiting from the flow path structure (particularly, the nozzle portion thereof), and for example, a jet-in-air type flow cytometer can be mentioned.

(Light irradiation unit 6101)
The light irradiation unit 6101 includes a light source unit that emits light, and a light guide optical system that guides the light to the flow path C. The light source section includes one or more light sources. The type of light source may be, for example, a laser light source or an LED. The wavelength of light emitted from each light source may be any wavelength of ultraviolet light, visible light, or infrared light. The light guide optical system includes, for example, optical components such as a beam splitter group, a mirror group, or an optical fiber. Further, the light guiding optical system may include a lens group for condensing light, and may include, for example, an objective lens. The number of light irradiation points on the biological sample S2 may be one or more. The light irradiation unit 6101 may be configured to collect light irradiated from one or a plurality of different light sources onto one irradiation point.

(Detection unit 6102)
The detection unit 6102 includes at least one photodetector that detects light generated by the light irradiation of the biological particles P by the light irradiation unit 6101. The light to be detected is, for example, fluorescence or scattered light (for example, any one or more selected from the group consisting of forward scattered light, back scattered light, and side scattered light). Each photodetector includes one or more light receiving elements, and has, for example, a light receiving element array. Each photodetector may include one or more photomultiplier tubes (PMTs) and/or photodiodes such as APDs and MPPCs as light receiving elements. The photodetector includes, for example, a PMT array in which a plurality of PMTs are arranged in one dimension. Further, the detection unit 6102 may include, for example, an image sensor such as a CCD or a CMOS. The detection unit can acquire images of biological particles (for example, bright field images, dark field images, fluorescence images, etc.) using the imaging device.

The detection unit 6102 includes a detection optical system that causes light of a predetermined detection wavelength to reach a corresponding photodetector. The detection optical system includes a spectroscopic section such as a prism or a diffraction grating, or a wavelength separation section such as a dichroic mirror or an optical filter. The detection optical system may be configured, for example, to separate light from the biological particles P, and to detect light in different wavelength ranges by a plurality of photodetectors, the number of which is greater than the number of fluorescent dyes. A flow cytometer including such a detection optical system is called a spectral flow cytometer. Further, the detection optical system may be configured, for example, to separate light corresponding to the fluorescence wavelength range of the fluorescent dye from the light from the biological particle P, and to cause the corresponding photodetector to detect the separated light. good.

Additionally, the detection unit 6102 may include a signal processing unit that converts the electrical signal obtained by the photodetector into a digital signal. The signal processing section may include an A/D converter as a device that performs the conversion. A digital signal obtained by conversion by the signal processing section can be transmitted to the information processing section. The digital signal can be handled as data related to light (hereinafter also referred to as "optical data") by the information processing section. The optical data may include, for example, fluorescence data. More specifically, the light data may be light intensity data, and the light intensity may be light intensity data of light including fluorescence (for example, may include feature quantities such as Area, Height, and Width). It's good.

(Information processing unit 6103)
The information processing unit 6103 includes, for example, a processing unit that processes various data (for example, optical data) and a storage unit that stores various data. When the processing section acquires light data corresponding to a fluorescent dye from the detection section, the processing section can perform fluorescence leakage correction (compensation processing) on the light intensity data. Further, in the case of a spectral flow cytometer, the processing unit performs fluorescence separation processing on the optical data and obtains light intensity data corresponding to the fluorescent dye.

The fluorescence separation process may be performed, for example, according to the unmixing method described in JP-A No. 2011-232259. When the detection unit 6102 includes an imaging device, the processing unit may acquire morphological information of the biological particles based on the image acquired by the imaging device. The storage unit may be configured to store the acquired optical data. The storage unit may further be configured to store spectral reference data used in the unmixing process.

When the biological sample analyzer 6100 includes a sorting section 6104 described below, the information processing section 6103 can determine whether or not to sort out the biological particles P based on the optical data and/or the morphological information. Then, the information processing unit 6103 controls the sorting unit 6104 based on the result of the determination, so that the sorting unit 6104 can sort out the biological particles P.

The information processing unit 6103 may be configured to be able to output various data (for example, optical data, images, etc.). For example, the information processing unit 6103 can output various data (eg, two-dimensional plot, spectral plot, etc.) generated based on the optical data. Further, the information processing unit 6103 may be configured to be able to accept input of various data, for example, accept gating processing on a plot by a user. The information processing unit 6103 can include an output unit and/or a user interface for executing the output or input.

The information processing unit 6103 may be configured as a general-purpose computer, and may be configured as an information processing unit 6103 that includes a CPU, RAM, and ROM, for example. The information processing unit 6103 may be included in the casing in which the light irradiation unit 6101 and the detection unit 6102 are provided, or may be located outside the casing. Further, various processes or functions by the information processing unit 6103 may be realized by a server computer or cloud connected via a network.

(Preparative separation section 6104)
The sorting unit 6104 can perform sorting of the biological particles P, for example, according to the determination result by the information processing unit 6103. The separation method may be a method in which droplets containing biological particles P are generated by vibration, an electric charge is applied to the droplets to be separated, and the traveling direction of the droplets is controlled by electrodes. The fractionation method may be a method in which the traveling direction of the biological particles P is controlled within the flow path structure and the fractionation is performed. The flow path structure is provided with a control mechanism using, for example, pressure (injection or suction) or electric charge. As a specific example of the flow path structure, for example, the flow path C has a flow path structure in which the flow path C branches into a recovery flow path and a waste fluid flow path downstream thereof, and specific biological particles are directed to the recovery flow path. Examples include chips that are collected (for example, the chip described in Japanese Patent Application Laid-open No. 2020-76736).

(3) Information processing device 2

The information processing device 2 has at least a control section 300, as shown in FIG. Further, it may include an input section 301, a storage section 302, an output section 303, a display section 304, a learning section 400, a database 500, etc., as necessary. Note that each part of the information processing device 2 may be connected via a network. In addition, there may be a plurality of these parts, and they may be provided externally, such as in a cloud, and connected via a network.

Further, the information processing device 2 may be configured as a general-purpose computer, and may be configured as an information processing section including a CPU, RAM, and ROM, for example. The information processing device 2 may be included in the housing in which the cell culture section 10 and the measurement section 3 are provided, or may be located outside the housing. Further, various processes or functions performed by the information processing device 2 may be realized by a server computer or cloud connected via a network.
Each part of the information processing device 2 will be described in detail below.

(Control unit 300)
The control unit 300 predicts a plurality of culture prediction results for each culture condition of a cell group including different cells, and performs control to visualize information regarding the cultured cell composition and cell proliferation process as the culture prediction results. . This makes it possible to see a bird's-eye view of the culture prediction results for each culture condition, and allows the user to select from multiple culture condition options and link the predictions for reaching the desired cell group with the culture conditions to increase efficiency. It can be done in a specific manner. The specific process performed by the control unit 300 will be explained in "(4) Control step S120" described later.

(Input section 301)
The input unit 301 allows a user or the like to operate the visualized culture prediction results. This allows, for example, to select the culture conditions to be performed. In this case, the control unit 300 can control the culture conditions based on the culture conditions selected by the input unit 301.

Further, the user etc. access each part of the cell culture device 1 and the information processing device 2 via the input unit 301 and operate these parts.

Note that the installation location and number of input units 301 are not particularly limited, and they may be installed on the side of the casing that includes the control unit 300, on the side of the cell culture device 1 described above, or on both sides. It may be installed.

As the input unit 301, for example, one or more buttons, a mouse, a keyboard, a touch panel, a mobile information terminal, etc. can be used. Furthermore, the input unit 301 is not an essential component of the information processing device 2, and may be installed outside the cloud or the like and connected to the control unit 300 via a network, or may use an external storage device.

(Storage unit 302)
The storage unit 302 can store all matters in the cell culture system 1000 according to the present technology. Note that as the storage unit 302, an external storage device or the like may be used to store all matters related to the cell culture system 1000 according to the present technology.

Note that the installation location and number of storage units 302 are not particularly limited, and they may be installed on the side of the casing that includes the control unit 300 described above. Furthermore, the storage unit 302 is not an essential component of the information processing device 2, and may be installed outside the cloud or the like and connected to the control unit 300 via a network, or an external storage device may be used.

(Output section 303)
The output unit 303 receives instructions from the control unit 300 and outputs, for example, all matters related to the cell culture system 1000 according to the present technology.

Note that the installation location and number of output units 303 are not particularly limited, and they may be installed on the side of the casing that includes the control unit 300, on the side of the cell culture device 1 described above, or on both sides. It may be installed.

As the output unit 303, a printer, speaker, mobile information terminal, etc. can be used. Further, the output unit 303 is not an essential component of the information processing device 2, and may be installed outside the cloud or the like and connected to the control unit 300 via a network, or an external output device may be used.

(Display section 304)
The display unit 304 receives instructions from the control unit 300 and displays, for example, all matters related to the cell culture system 1000 according to the present technology.

Note that the installation location and number of display units 304 are not particularly limited, and they may be installed on the side of the casing that includes the control unit 300, on the side of the cell culture device 1 described above, or on both sides. It may be installed.

As the display unit 304, a display, a touch panel, a projector, a mobile information terminal, etc. can be used. Furthermore, the display unit 304 is not an essential component of the information processing device 2, and may be installed outside the cloud or the like and connected to the control unit 300 via a network, or may use an external output device.

(Learning Department 400)
The learning unit 400 uses information regarding the cells processed under the processing conditions predicted by the control unit 300 and information regarding the treatment using the cells as input information for learning, and determines the relationship between the cells and the information regarding the treatment. A first learning device to learn, information regarding the unprocessed cells, the processing conditions predicted by the control unit 300, and the unprocessed cells processed according to the processing conditions as input information for learning. , a second learning device that learns the relationship between the information regarding the cells before treatment and the treatment conditions. Thereby, information regarding the treatment conditions (in particular, culture conditions) for achieving the desired cell group and the information regarding the cell group after treatment for achieving the desired therapeutic effect of the cells is obtained from information regarding the cells before treatment in the cell group. can be predicted, increasing the efficiency of the cell culture process.

(Database 500)
The database 500 acquires and retains processing conditions for cells acquired by the cell culture unit 10, information regarding cells acquired by the measurement unit 3, and information regarding cell treatment acquired from an external database. The database 500 may be configured to transmit the above information to the control section 300 and the learning section 400. Thereby, the control unit 300 and the learning unit 400 can refer to the information held in the database 500, and the prediction efficiency and learning efficiency of the control unit 300 and the learning unit 400 are improved.

2. Second embodiment (information processing method)

(1) Overall composition

FIG. 8 shows an example of the flow of the information processing method according to the present technology. As shown in FIG. 8, the information processing method according to the present technology includes a sample preparation step S100, an information acquisition step S110 regarding cells before treatment, a control step S120, a treatment step S130, and an information acquisition step S140 regarding cells after treatment. It can be included.
Each of these steps will be explained in detail below.

(2) Sample preparation step S100

In the sample preparation step S100, the cell culture unit 10 prepares a cell group containing target cells (target cells). The type of target cells is not particularly limited, and at least one selected from the group consisting of human-derived cells, immune cells, animal-derived cells, plant-derived cells, microbial-derived cells, cancer cells, normal cells, stem cells, epithelial cells, and organoids. One or more types may be used. For example, in the case of animal cells, examples of the cells include cells in blood and cells collected from living tissue. Further, the target cells may be either adherent cells or non-adherent cells. Furthermore, the cell group may be peripheral blood mononuclear cells (PBMC) collected from a patient or donor. By culturing and propagating the collected PBMC and/or introducing genes, a cell group containing cells that attack specific cancer cells is produced, and the cell group can be used for therapeutic purposes as a cell preparation, for example. used. The PBMC is composed of various immune cell groups, including T cells, B cells, macrophages, and the like. The T cells may further be comprised of T cell subsets, including naive T cells, central memory T cells, effector T cells, and the like.

The sample preparation step S100 may include a sample input step. In the sample input step, a group of cells including target cells input from the cell input unit 106 of the cell culture unit 10 is captured in the culture container 101 by the first molecules 104 that can bind to cells. In this step, non-target cells may be collected from the waste liquid storage section 112 or the cell collection section 113 without being captured in the culture container 101.

Additionally, the sample preparation step S100 may include a second molecule supply step. In the second molecule supply step, the cells captured in the culture vessel 101 can be combined with the second molecule supplied from the second molecule supply unit. The supplied second molecule may be, for example, a fluorescent reagent, which allows the measurement unit 3 to identify the target cell. Note that cells that are not bound to the second molecule and that are not determined as target cells by the measurement unit 3 may be collected from the waste liquid storage unit 112 or the cell recovery unit 113. In addition, this technology uses information learned from bright field images, phase contrast images, polarized images, unstained images, and fluorescent images to perform pseudo-staining for each cell feature without using a second molecule. The cells may be identified based on the image obtained, and the cells may be released by light stimulation. The identification may be performed by the information processing device 2. The information processing device 2 drives the optical control unit 210 based on the result of the identification. An optical control unit 210 may perform the optical stimulation.

Further, the sample preparation step S100 may include an environment control step. In the environment control step, the environment of the culture container 101 containing the cells before treatment is controlled by the environment control section. For example, the culture container 101 receives physicochemical environment control by the environment control section, and receives physicochemical environment control such as humidity, pH, osmotic pressure, oxygen partial pressure, carbon dioxide partial pressure, etc. from the physicochemical environment supply section 114. environment may be provided. Alternatively, for example, the culture container 101 is subjected to physiological environment control by the environment control section, and receives stimulation factors, A physiological environment such as culture media, hormones, cytokines, interleukins, etc. may be provided. This provides an optimal environment for the target cells in the culture environment, thereby increasing cell survival rate and/or culture efficiency. This provides an optimal physiological environment for the target cells in the culture environment and improves the efficiency of cell culture. Note that the environmental control step may be performed not only in the sample preparation step S100 but also in steps before and after the step as appropriate.

(3) Information acquisition step S110 regarding cells before treatment

In the information acquisition step S110 regarding cells before treatment, the information processing device 2 acquires information regarding the target cells before treatment prepared in the sample preparation step S100. The information acquisition step S110 regarding cells before treatment may include a step of measuring cells before treatment. In the pre-processing information acquisition step S110, the measurement unit 3 (particularly the image acquisition unit and/or the signal detection unit) acquires image information and/or signal information. From the acquired image information and/or signal information, it is possible to extract information regarding the target cells before treatment. The image information and/or signal information may be information derived from the second molecule, for example, a fluorescent reagent, provided in the sample preparation step S100.

The information on the cells before processing extracted by the measurement unit 3 includes, for example, cell morphology, cell composition (in particular, cell number, cell ratio), and cell growth process (in particular, cell proliferation rate, cell survival rate). , cell type, genetic information, and information regarding molecules. As used herein, "cell morphology" refers to the shape of a cell or the appearance of a cell. Information regarding the molecule includes, but is not particularly limited to, gene expression control factors such as transcription factors and transcription control factors, molecular marker information, cell surface antigen information, sequence information, molecular weight, type, and the like. Information regarding the cells is acquired by the measurement unit 3 and then transmitted to the control unit 300. Further, information regarding the cells may be transmitted to the database 500 of the information processing device 2, and the database 500 may be updated.

The information acquisition step S110 regarding cells before treatment may include a step of accepting treatment conditions (in particular, culture conditions). In the processing condition receiving step, the information processing device 2 may include a step of receiving information regarding the predetermined processing conditions or the target cells after the predetermined treatment. Information regarding the predetermined processing conditions and the target cells after the predetermined processing may be received by the input unit 301 set in the information processing device 2 . Thereby, in the control step S120, which will be described later, it becomes possible to predict the information regarding the cells after the user's desired treatment and the treatment conditions for obtaining the desired treatment conditions. Furthermore, information regarding the predetermined treatment conditions and target cells after the predetermined treatment may be obtained by obtaining threshold values from the database 500 and/or an external database. Thereby, the threshold value can be utilized in the control step S120, which will be described later.

In the processing condition receiving step, the information processing device 2 may further include a step of receiving information regarding approval of the commercialized cell as a threshold value from the database 500 and/or an external database. As a result, in the control step S120, which will be described later, by referring to information regarding the approval of existing commercialized cells, the processing conditions for the cells and information regarding the cells necessary to meet the approval criteria are presented to the user. can do. Information regarding the approval of the cells can be appropriately selected from information regarding the cells, processing conditions for the cells, and information regarding the treatment. Note that information regarding the approval of the cell can be received through a user interface appropriately set in the information processing device 2. The control unit 300 may set information regarding the predetermined cell and/or the predetermined processing condition based on information regarding approval of the cell.

The processing conditions are particularly culture conditions, and the culture conditions include, for example, stimulating factors, number of culture days, types of culture reagents, number of culture reagents, number of culture steps, complexity of culture steps, and culture cost. It can be one or more selected from the group. Further, the specified predetermined processing conditions may be cell sorting or cell culture control processed by the cell culture unit control unit 200, as described later.

Information regarding the target cells after treatment may be information regarding treatment of the cells in addition to the information regarding the cells before treatment described above. The information regarding the treatment can be, for example, any one or more selected from the group consisting of the therapeutic effect of the cells on the patient, the response rate, the recurrence rate, the side effects, and the patient's treatment history. As a result, in the learning process described later, information regarding the treated cells is learned in order to arrive at information regarding the treatment, and it becomes possible to execute the cell configuration and cell proliferation process in accordance with the individual patient.

Information regarding the predetermined processing conditions or target cells after the predetermined processing received by the information processing device 2 may be transmitted to the control unit 300 and/or the database 500 as appropriate.

(4) Control process S120

In the control step S120, the control unit 300 predicts a plurality of culture prediction results for each culture condition of a cell group containing different cells. The culture prediction result is selected from among the information regarding the target cells before treatment acquired in the pre-processing information acquisition step S110 and the information regarding the target cells after the predetermined treatment conditions and predetermined treatment acquired in the treatment condition receiving step. Based on at least one, a processing condition that allows the cell group to be derived from information regarding a predetermined cell, or information regarding the cell after processing of the cell group derived by the predetermined processing condition is predicted as a prediction condition. . In this specification, the prediction condition refers to "a processing condition that allows the cell group to be derived from the information regarding the predetermined cells" generated by the prediction process by the control unit 300, or a prediction condition by the prediction process by the control unit 300. It may be the generated "information regarding the cells after the treatment of the cell group derived from the predetermined treatment conditions." That is, the prediction condition may mean information regarding a predicted prediction condition or a predicted cell.

Processing conditions that allow the cell group to be derived from information regarding predetermined cells are processing conditions that can be derived by the cell culture unit control unit 200 in order to arrive at information regarding the predetermined cells specified in the processing condition receiving step. In particular, it may be a culture condition.

The information regarding the processed cells of the cell group derived based on the predetermined processing conditions is the post-processing information that can be obtained by the cell culture unit control unit 200 executing a predetermined process specified by the user. This is information about cells. The predetermined process specified by the user is not particularly limited as long as it is a process condition in process step S130, which will be described later. Information regarding the cells after treatment is not particularly limited as long as it is as described above. Information regarding the cells after the treatment includes, for example, cell morphology, cell composition (in particular, cell number, cell ratio), cell proliferation process (in particular, cell proliferation rate, cell survival rate), cell type, and genetics. The information may be at least one selected from the group consisting of information and information regarding molecules.

FIG. 9 shows an example of the flow of the control step S120 of the present technology. As shown in FIG. 9, the control step S120 may include a prediction result generation step S121 and a visualization step S122. In the prediction result generation step S121, the control unit 300 selects the cell based on the information regarding the target cell before treatment acquired in the pre-treatment cell measurement step and the predetermined treatment conditions acquired in the treatment condition reception step. Predict information about the cells after processing the group and generate prediction results. Alternatively, the control unit 300 performs a predetermined measurement based on the information regarding the target cells before treatment acquired in the pre-treatment cell measurement step and the information regarding the target cells after a predetermined treatment acquired in the treatment condition receiving step. A processing condition that allows the cell group to be derived is predicted based on the information regarding the cells, and a result is generated.

The control unit 300 may acquire information regarding the target cells before processing from the measurement unit 3 and/or the database 500. Furthermore, the control unit 300 acquires information regarding the cells after the user's desired treatment and desired treatment conditions from at least one of the group consisting of the database 500, an external database, and the user interface of the information processing device 2. You may.

In the prediction result generation step S121, the control unit 300 may further generate a prediction result using either one of the first learning device and the second learning device generated by the learning unit 400 in the learning step described later. . Note that in this specification, the control step S120 means a step of executing a process of generating information regarding the derivable treatment conditions or the treated cells based on information regarding the target cells, that is, Includes inference processing in the field of learning.

The control step S120 may include a visualization step S122. In the visualization step S122, the control unit 300 particularly selects a plurality of culture prediction results from among the plurality of prediction results for each culture condition of a cell group containing different cells created in the prediction result generation step S121. Control is performed to visualize information regarding the cultured cell composition and cell growth process as a prediction result. In addition, control may be performed to visualize the prediction conditions generated in the prediction result generation step S121 described above. The culture prediction result may be presented to the user via the display section 304 set in the information processing device 2, for example. This allows the user to visually recognize the culture prediction results.

The presented culture prediction results may be transmitted to the database 500, and the database 500 may be updated. Further, the output culture prediction result may be transmitted to the cell culture unit control unit 200 of the cell culture unit 10, and the cell culture unit control unit 200 controls the cell culture unit 10 based on the output conditions. It becomes possible to treat target cells.

FIGS. 11 to 16 are diagrams illustrating the state of visualization in the visualization step S122. The visualization is performed, for example, by illustrating the culture prediction results in a table, graph, tree, etc., or three-dimensionally, but it is particularly preferable to present the results in a tree shape. It is preferable to illustrate this.

FIG. 11 is a diagram showing an example of culture prediction results. In this embodiment, in a systematic diagram in which different cell types are hierarchically classified, the cell configuration and cell growth process are illustrated using line segments and end points of the line segments. Specifically, in FIG. 11, the cell proliferation process (in particular, the cell proliferation rate) is illustrated using line segments, and the longer the line segment, the higher the cell proliferation rate. On the other hand, in FIG. 11, the cell composition (in particular, the number of cells) is illustrated using the end points of the line segment, and the name of each cell type is presented at the end of the line segment, and the end points of different sizes are shown. is shown, and the larger the size of this endpoint, the higher the proportion of each cell type whose name was presented.

Further, FIG. 12 is a diagram showing an example of culture prediction results, which is different from FIG. 11. Specifically, in FIG. 12, the thickness of the line segment is used to illustrate the cell proliferation process (in particular, cell survival rate), and the thicker the line segment, the higher the cell survival rate. It is shown that. On the other hand, in FIG. 12, the cell composition (in particular, the number of cells) is illustrated using the end points of the line segment, and the name of each cell type is presented at the end of the line segment, and the end points with different colors are shown. The darker the color of this end point, the greater the number of cells. Note that the colors presented in Figure 12 are only an example; the lighter the color of the endpoints, the higher the proportion of each cell type whose name is presented, or any other color may be used as appropriate, not just black and white. Cell composition can be shown.

In this embodiment, the starting points of the culture conditions may be displayed separately as shown in FIG. 11, or may be displayed as one as shown in FIG. 12. Displaying the cells as one as shown in FIG. 12 is useful when the target cells are determined in advance and a systematic diagram can be created based on the target cells. In addition, the direction in which the line segment extends from the starting point of the culture conditions ("lymphocyte" in FIGS. 11 and 12) is not particularly limited, and is not limited to the top, bottom, left, and right, but 360 degrees, all directions, as shown in FIG. 13 (described later). can be extended to. In addition, each starting point, each line segment, and each end point include cell type (cell type), cell number, cell ratio, number of culture days, culture medium type, culture medium replenishment date, culture medium exchange date, culture temperature, culture Information such as humidity may also be presented. Based on this information, the user can appropriately select culture conditions that will yield desired culture results.

In the present embodiment, the cell composition is particularly the cell number or cell ratio, and the cell proliferation process is particularly the cell proliferation rate or cell survival rate.

FIG. 13 is a diagram showing an example of culture prediction results, which is different from FIGS. 11 and 12. Specifically, in FIG. 13, the length of the line segment is used to illustrate the cell proliferation process (in particular, the cell proliferation rate), and the longer the line segment is, the higher the cell proliferation rate is. It is shown that. On the other hand, in Figure 13, the cell composition (in particular, the number of cells) is illustrated using the end points of the line segment, and at the end of the line segment, the name of the BR>E cell type is presented, and the shape is Different endpoints are shown, and the closer the shape is to a circle, the greater the number of cells.

In this embodiment, the line segment is a group consisting of the length of the line segment, the type of the line segment (for example, a solid line, a broken line, a dashed line, a double line, etc.), the thickness of the line segment, and the color of the line segment. Using any one or more of these methods, the cell composition and the cell growth process (in particular, the cell growth process) can be visualized and presented to the user. Furthermore, the end point of the line segment is determined by using one or more selected from the group consisting of the size of the end point, the shape of the end point, the type of the end point (e.g., pie chart, graph, etc.), and the color of the end point, Cell composition and cell proliferation process (particularly cell composition) can be visualized and presented to the user. Note that the name of the cell type, etc. may be presented inside the type of the end point.

FIG. 14 is a diagram showing an example of culture prediction results, which is different from FIGS. 11 to 13. Unlike FIG. 12 described above, FIG. 14 shows a case where there are a plurality of target cells and the proportion thereof is shown by end points. If there are two types of target cells, the ratio can be shown by the size of the endpoints, and if there are three or more types, the ratio can be further shown by using a pie chart as the type of endpoints. Specifically, in FIG. 14, the length of the line segment is used to illustrate the cell proliferation process (in particular, the cell proliferation rate), and the longer the line segment is, the higher the cell proliferation rate is. It is shown that. On the other hand, in FIG. 14, the end points of the line segment are used to illustrate the cell composition (in particular, the cell proportion), and the name and proportion of each cell type are presented at the end of the line segment, and the size The endpoints with different values are shown, and the larger the endpoint, the higher the cell percentage.

In this embodiment, as described above in "(3) Information acquisition step S110 regarding cells before processing," the control unit 300 sets a threshold value by the user or the database 500, and uses the set threshold value to perform the culture. Conditions can be determined. The threshold value can be set, for example, as to whether or not the above-described cell configuration and cell growth process satisfy desired conditions. For example, in FIG. 14, "CD4CD62L/CD8CD62L≧1" is set. If it is determined that the desired condition is not satisfied, the tree may be visualized by graying out the tree or erasing the tree itself, for example, as shown in FIG. Moreover, along with the visualization, culture conditions that do not satisfy the threshold value may not be automatically selected. This makes it possible to narrow down effective options from a plurality of options, improving usability.

Furthermore, in this embodiment, the threshold value can be used to present culture conditions suitable for the mode set by the user. The mode may be, for example, a survival priority mode that prioritizes cell survival rate, a proliferation priority mode that prioritizes cell proliferation rate, a ratio priority mode that prioritizes cell proportion, or a purity priority mode that prioritizes cell purity. It can be done. For example, FIG. 15 is a diagram showing an example of culture prediction results, which is different from FIGS. 11 to 14, and it is predicted that four strains J1 to J4 will eventually appear. Here, if a survival priority mode or a proliferation priority mode is set using the threshold value, for example, a culture condition in which the line segment is the longest or is equal to or greater than a certain threshold value may be selected. On the other hand, when the ratio priority mode or the purity priority mode is set, culture conditions may be selected such that the size of the end point of the line segment is the maximum or minimum, or above or below a certain threshold value. FIG. 15 shows a case where a proliferation priority mode that prioritizes the cell proliferation rate is set, and culture conditions may be set so that line segment J4 has the longest line segment. In addition, in each priority mode, for example, while setting the ratio priority mode, the user can further give conditions to take into consideration as appropriate, such as considering the cell proliferation process.

Furthermore, in this embodiment, culture conditions suitable for the mode may be presented to the user as "positive selection" and culture conditions unsuitable for the mode may be presented as "negative selection". This presentation includes not only simply notation but also visualization techniques such as graying out the tree or erasing the tree itself as shown in FIG. 15. Note that in this embodiment, for example, an input unit 301 may be provided that allows selection of whether or not to proceed to the subsequent processing step S130.

In addition, in this embodiment, in presenting culture conditions suitable for the mode set by the user, consideration is given to stimulation factors, number of culture days, types of culture reagents, number of culture reagents, number of culture steps, complexity of culture steps, and culture cost. Any one or more parameters selected from the group consisting of: It is possible to set a threshold value for the parameter using the same method as described above, and those that meet the threshold are treated as "positive selection" as described above, and those that do not meet the threshold, It may be presented to the user as a "negative selection." This presentation includes not only simply writing the words, but also visualization methods such as graying out the tree or erasing the tree itself.

FIG. 16 is a diagram showing an example of culture prediction results, which is different from FIGS. 11 to 15. In the visualization step S122, the control unit 300 may perform the illustration in chronological order, as shown in FIG. 16. Although FIG. 16 shows the cell composition and the cell proliferation process from day 0 to day 2 of culture in chronological order, this embodiment is not limited to this, and may be used for several minutes, several hours, or several days. , it is possible to visualize the cell composition and cell growth process in a time-series manner over a period of several weeks or the like.

(5) Processing step S130

In the processing step S130, the control unit 300 performs processing regarding the sample containing the cells based on the information regarding the cells acquired in the information acquisition step S110 regarding the cells before treatment and the prediction conditions output in the control step. Processing regarding a sample containing cells may be performed, for example, by performing cell sorting or culture control on unprocessed cells captured in the cell culture device 1.

In cell sorting, for example, the degradable linker 103 is stimulated by optical control by the optical control unit 210, and cells bound to the sample holding unit 100 via the degradable linker 103 are released. Cells that can be treated and non-target cells are determined based on the information on the cells acquired in the information acquisition step S110 regarding the cells before treatment, for example, the fluorescence signal derived from the second molecule imparted to the cells, and the non-target cells are determined. Only cells can be released by the stimulation. Based on pseudo-stained images for each cell feature identified from information learned from bright field images, phase contrast images, polarized images, unstained images, and fluorescent images without using a second molecule. Cells may be identified and released by light stimulation. The identification may be performed by the information processing device 2. The information processing device 2 can drive the optical control section 210 based on the result of the identification. The optical control unit 210 may perform optical stimulation.

In culture control, for example, a sample containing cells bound to the sample holding unit 100 is cultured under environmental control by the environmental control unit. For example, the culture container 101 is subjected to feedback control by the environment control section based on the information about the cells acquired in the information acquisition step S110 about the cells before treatment, and the physicochemical environment supply section 114 provides humidity, pH, osmosis, etc. Physicochemical environments such as pressure, oxygen partial pressure, carbon dioxide partial pressure, etc. may be provided. Alternatively, for example, the culture container 101 is subjected to feedback control by the environment control unit based on the information about the cells acquired in the information acquisition step S110 about the cells before treatment, and the activator supply unit 108 and the gene supply unit 109 , and the culture solution supply unit 110, a physiological environment such as a stimulation factor, a transcription factor, a transcription control factor, a culture solution, a hormone, a cytokine, an interleukin, etc. may be supplied. This provides an optimal environment for the target cells in the culture environment, thereby increasing cell survival rate and/or culture efficiency.

An example of feedback control in the information acquisition step S110 regarding cells before processing is shown below. For example, when processing in the cell culture system 1000 is performed using PBMC as an initial cell group before culture processing, the cell group after culture processing may be The proliferation of CD4- and CD8-positive cells contained in the cells may be different. Furthermore, the proportions of naïve T cells, central memory T cells, and effector cells included in the cell group, that is, the proportions of T cell subsets, may also differ. When anti-CD3 antibody is added to the cell group from the activator supply unit 108 in the cell culture system 1000, CD8-positive cells proliferate significantly, whereas when anti-CD3/CD28 antibody is added to the cell group, CD8-positive cells proliferate significantly. , the proportion of CD4 and CD8 positive cells can be maintained and proliferated. Furthermore, depending on the culture medium, cytokines, and/or cytokine type and concentration, the proportion of T cell subsets after a certain number of days of culture may vary.

For example, in the feedback control in the information acquisition step S110 regarding cells before treatment, the environment control section controls the activating agent supply section 108 to supply only anti-CD3 antibodies into the culture vessel 101 in the initial culture step. Can be controlled. This increases the proportion of CD8 positive cells within the cell group. Then, in response to the measurement unit 3 determining that the percentage of CD8 positive cells has reached the target value, the environmental control unit causes the activator supply unit 108 to stop supplying the anti-CD3 antibody. Additionally, the activating agent supply section 108 may be controlled.

In this way, the environmental control unit controls the activating agent supply unit 108 to supply the activating agent into the culture container 101 so as to increase or decrease the proportion of one or more predetermined cells in the cell group. I can do it. The environment control unit also controls the activating agent supply unit 108 to supply the activating agent into the culture container 101 so as to increase or decrease the survival rate of one or more predetermined cells in the cell group. sell. Furthermore, the environmental control unit is configured such that the activating agent supply unit 108 supplies the activating agent into the culture vessel 101 so as to increase or decrease the gene introduction efficiency of one or more predetermined cells in the cell group. Can be controlled.

Furthermore, the environment control unit may control the activating agent supply unit 108 to additionally supply anti-CD28 antibody into the culture container 101. This allows the cell group to proliferate while maintaining the proportion of CD4- and CD8-positive cells in the cell group. Furthermore, in response to the measurement unit 3 determining that the proportion of T cell subsets in the cell group has reached the target, the environment control unit controls the culture solution supplied by the activating agent supply unit 108 and The activator supply 108 may be controlled to change the type and/or concentration of the cytokine.

In this way, the environmental control unit can control the activating agent supply unit 108 to supply the activating agent into the culture vessel 101 so as to maintain the proportion of one or more predetermined cells in the cell group. .

The processing conditions processed by the cell sorting and/or culture control may be transmitted to the database 500, and the database 500 may be updated. This improves the accuracy of generating prediction conditions in the prediction result generation step S121. In addition to the actual processing conditions, the content processed by the cell sorting and/or culture control may also include dates and periods, such as the number of culture days, the date of culture solution replenishment, or the date of culture solution exchange. .

The treatment step S130 may include a treatment execution step S131 (in particular, a culturing step). As described above, in the culturing process, the cell culture section control section 200 cultivates the sample containing the cells bound to the sample holding section 100 under the environmental control by the environment control section. In the process execution step S131, the user can select the culture conditions to be executed, for example, via the input unit 301. In this case, the control unit 300 can control the culture conditions based on the culture conditions selected by the input unit 301.

The processing step S130 may include an in-process cell information acquisition step S132 (particularly a measurement step). In processing cell information acquisition step S132, the cell culture section control section 200 controls the measurement section 3 to start measurement, and obtains information regarding the processing cells. The measuring method by the measuring section 3 is, for example, as described above, and is not particularly limited. By acquiring information about cells over time, cells can be constantly observed and abnormalities in cells can be immediately detected. The information regarding the processing is the same as the information regarding the cells before the treatment described above, and is not particularly limited. Information regarding the cells being processed may be sent to a database 500, and the database 500 may be updated.

An example of acquiring information regarding the cells being processed in the processing cell information acquisition step S132 will be shown below. For example, when PBMCs are collected, the PBMCs can be measured by the measurement unit 3 having the image acquisition unit 600 and/or the signal detection unit 700. The lymphocyte fraction is identified based on the forward scattered light, side scattered light, or back scattered light acquired by the measurement unit 3, and from information regarding the fluorescence of the target cells stained with fluorescence and/or metal-labeled antibodies. The number and percentage of living cells can be identified from information about cell types such as T cells, B cells, and macrophages, T cell subsets such as naive T cells, central memory T cells, and effector T cells, and nuclear staining of target cells. sell. The PBMC may also be obtained from images that are identified from information learned from unstained images and fluorescent images and pseudo-stained for each cell feature. As a result, cell information can be acquired during the treatment process, so that it is possible to select the cells in the treatment process S130 and omit the moving process of extracting them from the culture container 101 and the measurement process after the cells have been extracted. This makes it possible to move cells from the culture container 101 while maintaining a sterile state, and furthermore, by omitting the measurement process in the measurement unit 3, each process in the cell culture system 1000 can be simplified. It becomes possible.

The processing step S130 may include a comparison step S133. In the comparison step S133, the cell culture unit control unit 200 compares the information regarding the cells being processed acquired in the in-process cell information acquisition step S132 and the treatment conditions acquired in the treatment condition acceptance step, and makes a treatment decision. Execute. For example, if the information regarding the cells being processed satisfies the processing conditions, the cell culture section control section 200 can proceed to the subsequent culture step, but if the processing conditions are not satisfied, the cell culture section control section 200 It is possible to select as appropriate whether unnecessary cells are removed, a manufacturing stop process is performed in which the control unit 300 is controlled to stop cell production, or the control unit 300 is controlled to re-collect the cells. . Thereby, by observing information regarding the cells being processed from the measurement unit 3 over time, it becomes possible to switch the process content midway through the process and perform optimization processing.

(6) Information acquisition step S140 regarding treated cells

In the information acquisition step S140 regarding the treated cells, the measurement unit 3 acquires information regarding the treated cells. When the information regarding the cells after processing reaches a predetermined value, the cell collection unit 113 collects the cell group. The collected cells may be evaluated for information regarding treatment by the information processing device 2, or may be evaluated by an evaluation device outside the system. Information regarding the treatment of the evaluated treated cells may be sent to the database 500 after the evaluation, and the database 500 may be updated.

Information regarding the target cells after treatment may be information regarding treatment of the cells in addition to the information regarding the cells before treatment described above. The information regarding the treatment may be any one or more selected from the group consisting of the therapeutic effect of the cells on the patient, the response rate, the recurrence rate, the side effects, and the patient's treatment history. As a result, in the learning process described later, information regarding the treated cells is learned in order to arrive at information regarding the treatment, and it becomes possible to execute treatment conditions (in particular, culture conditions) according to the individual patient.

(7) Learning process

The information processing method according to the present technology may further include a learning step. In the learning step, the learning unit 400 learns the relationship between information regarding cells and information regarding treatment of the cells, and generates a first learning device. Alternatively, the learning unit 400 learns the relationship between information regarding cells and processing conditions and generates a second learning device. This makes it possible to predict the treatment conditions (in particular, culture conditions) to achieve a desired cell group and the desired therapeutic effect of the cells from information about the cells in the cell group before treatment, and to improve the cell treatment process. Efficiency can be increased. Further, the control unit 300 may execute the above-described prediction process using the generated first learning device and/or second learning device.

The first learning device uses information regarding cells processed according to the prediction conditions predicted by the control unit 300 and information regarding the treatment of the cells as input information for learning, and determines the relevance of the information regarding the cells and the treatment. Learn. The information regarding the cells after treatment and the treatment of the cells after treatment are as described above. The control unit 300 may perform inference using a learning device generated by the learning device. This also makes it possible to predict optimal treatment conditions (especially culture conditions) depending on the patient.

For example, when the cell group treated in the cell culture system 1000 is PBMC, the PBMC is used for therapeutic purposes. By learning the relationship between information about the cell group after culture, such as the cell composition of the PBMC and the cell proliferation process, and information about the treatment, such as donor information, treatment success rate, incidence of side effects, and cell quality. , it is also possible to optimize the timing of collecting PBMC. This makes it possible to predict the treatment conditions to achieve a desired cell group and the desired cell treatment effect from information about the cells in the cell group before treatment, increasing the efficiency of the cell treatment process. .

The second learning device uses the information regarding the unprocessed cells, the processing conditions predicted by the control unit 300, and the unprocessed cells processed according to the processing conditions as input information for learning, and uses the information regarding the unprocessed cells as learning input information. The relationship between information about cells before treatment and the treatment conditions is learned. The processing conditions are not particularly limited as long as they are conditions that can be processed in the processing step. This makes it possible to predict the treatment conditions (in particular, culture conditions) to achieve a desired cell group and the desired therapeutic effect of the cells from information about the cells in the cell group before treatment, and to improve the cell treatment process. Efficiency can be increased. The control unit 300 may perform inference using a learning device generated by the learning device. This makes it possible to predict treatment conditions (especially culture conditions) and therapeutic effects.

The first learning device may be a learning device generated by performing machine learning on a data set including information regarding cells and information regarding treatment of the cells. The machine learning may be, for example, deep learning. The machine learning may be performed, for example, according to the information processing device or the information processing method described in International Publication No. 2021/049365 pamphlet. In the machine learning, information regarding the cells may be treated as an explanatory variable, and information regarding treatment of the cells may be treated as a target variable.

Further, the second learning device includes information regarding the cells before the treatment, the treatment conditions, and information regarding the cells before the treatment that have been treated according to the treatment conditions (i.e., information regarding the cells after the treatment); The learning device may be generated by performing machine learning on a data set including the following. The machine learning may be, for example, deep learning. The machine learning may be performed, for example, according to the information processing device or the information processing method described in International Publication No. 2021/049365 pamphlet.

In the machine learning, information regarding the cells before the treatment and the treatment conditions may be treated as explanatory variables, and information regarding the cells after the treatment may be treated as the objective variable. Such handling of explanatory variables and objective variables may be applied, for example, in an embodiment in which the control unit 300 predicts information regarding cells after processing the cell group.

Alternatively, in the machine learning, information regarding the cells before the treatment and information regarding the cells after the treatment may be treated as explanatory variables, and the treatment conditions may be treated as the objective variable. Such handling of explanatory variables and objective variables is, for example, an embodiment in which the control unit 300 predicts processing conditions (in particular, culture conditions) to enable the control unit 300 to derive information regarding the predetermined cells from the cell group. may be applied in

Note that in the present technology, the following configuration can also be adopted.
[1]
It has a control unit that predicts multiple culture prediction results for each culture condition of a cell group containing different cells,
The control unit is an information processing device that performs control to visualize the cultured cell composition and cell proliferation process as the culture prediction result.
[2]
The information processing device according to [1], wherein the visualization is performed by illustrating the culture prediction results.
[3]
The information processing device according to [2], wherein the illustration is performed using line segments and/or end points of the line segments.
[4]
The information processing device according to any one of [1] to [3], wherein the cell configuration is a cell number or a cell ratio.
[5]
The information processing device according to any one of [1] to [4], wherein the cell proliferation process is a cell proliferation rate or a cell survival rate.
[6]
The line segment is used to visualize the cell proliferation process using any one or more selected from the group consisting of line segment length, line segment type, line segment thickness, and line segment color. , the information processing device according to [3].
[7]
In [3], the end points of the line segment are visualized by using any one or more selected from the group consisting of the size of the end point, the shape of the end point, the type of the end point, and the color of the end point. The information processing device described.
[8]
The information processing device according to any one of [1] to [7], wherein the control unit determines the culture conditions using a set threshold value.
[9]
The information processing device according to [8], which visualizes cell culture conditions that do not satisfy the threshold value.
[10]
The information processing device according to [8], which uses the threshold value to present culture conditions suitable for a mode set by the user.
[11]
The mode is any one of a survival priority mode that prioritizes cell survival rate, a proliferation priority mode that prioritizes cell proliferation rate, a ratio priority mode that prioritizes cell proportion, or a purity priority mode that prioritizes cell purity. 10].
[12]
The information processing according to [10] or [11], wherein the control unit considers any one or more parameters selected from the group consisting of culture cost, number of culture days, and complexity of the culture process in the presentation. Device.
[13]
The information processing device according to [2], wherein the control unit performs the illustration in chronological order.
[14]
The information processing device according to any one of [1] to [13], further comprising an input unit for operating the visualized culture prediction results.
[15]
The information processing device according to [14], wherein the input unit selects culture conditions to be executed.
[16]
The information processing device according to [15], wherein the control unit controls culture conditions based on the culture conditions selected by the input unit.
[17]
It has a control process that predicts multiple culture prediction results for each culture condition of a cell group containing different cells,
In the control step, the information processing method is controlled to visualize the cultured cell composition and cell proliferation process as the culture prediction result.
[18]
A cell culture device having a cell culture section for culturing cell groups containing different cells, and a measurement section for measuring the cell composition and cell growth process of the cell group;
The control unit includes a control unit that predicts a plurality of culture prediction results for each culture condition of a cell group containing different cells, and the control unit controls so as to visualize the cultured cell composition and cell growth process as the culture prediction result. an information processing device;
A cell culture system with
[19]
A process including a step of predicting a plurality of culture prediction results for each culture condition of a cell group containing different cells, and controlling the cultured cell composition and cell growth process to be visualized as the culture prediction results is performed on a computer. A program to be executed.

1: Cell culture device 2: Information processing device 3: Measurement section 10: Cell culture section 100: Sample holding section 200: Cell culture section control section 300: Control section 301: Input section 302: Storage section 303: Output section 304: Display unit 400: Learning unit 500: Database 600: Image acquisition unit 1000: Cell culture system 5000: Microscope system 6100: Biological sample analyzer

Claims (19)

It has a control unit that predicts multiple culture prediction results for each culture condition of a cell group containing different cells,
The control unit is an information processing device that performs control to visualize the cultured cell composition and cell proliferation process as the culture prediction result. The information processing device according to claim 1, wherein the visualization is performed by illustrating the culture prediction results. The information processing device according to claim 2, wherein the illustration is performed using a line segment and/or an end point of the line segment. The information processing device according to claim 1, wherein the cell composition is a cell number or a cell ratio. The information processing device according to claim 1, wherein the cell proliferation process is a cell proliferation rate or a cell survival rate. The line segment is used to visualize the cell proliferation process using any one or more selected from the group consisting of line segment length, line segment type, line segment thickness, and line segment color. , the information processing device according to claim 3. 4. The cell configuration is visualized using one or more of the endpoints of the line segments selected from the group consisting of the size of the endpoint, the shape of the endpoint, the type of the endpoint, and the color of the endpoint. The information processing device described. The information processing device according to claim 1, wherein the control unit determines the culture conditions using a set threshold value. The information processing device according to claim 8, which visualizes culture conditions that do not satisfy the threshold value. The information processing device according to claim 8, which uses the threshold value to present culture conditions suitable for a mode set by the user. The mode is any one of a survival priority mode that prioritizes cell survival rate, a proliferation priority mode that prioritizes cell proliferation rate, a ratio priority mode that prioritizes cell proportion, or a purity priority mode that prioritizes cell purity. Item 10. Information processing device according to item 10. In the presentation, the control unit selects one or more parameters selected from the group consisting of stimulation factor, number of culture days, type of culture reagent, number of culture reagents, number of culture steps, complexity of culture step, and culture cost. The information processing device according to claim 10, which takes into account. The information processing device according to claim 2, wherein the control unit performs the illustration in chronological order. The information processing device according to claim 1, further comprising an input unit for operating the visualized culture prediction result. The information processing device according to claim 14, wherein the input unit selects culture conditions to be executed. The information processing device according to claim 15, wherein the control unit controls culture conditions based on the culture conditions selected by the input unit. It has a control process that predicts multiple culture prediction results for each culture condition of a cell group containing different cells,
In the control step, the information processing method is controlled to visualize the cultured cell composition and cell proliferation process as the culture prediction result. A cell culture device having a cell culture section for culturing cell groups containing different cells, and a measurement section for measuring the cell composition and cell growth process of the cell group;
The control unit includes a control unit that predicts a plurality of culture prediction results for each culture condition of a cell group containing different cells, and the control unit controls so as to visualize the cultured cell composition and cell growth process as the culture prediction result. an information processing device;
A cell culture system with A process including a step of predicting a plurality of culture prediction results for each culture condition of a cell group containing different cells, and controlling the cultured cell composition and cell growth process to be visualized as the culture prediction results is performed on a computer. A program to be executed.