Integrated cell analysis of biological cells sampled from a bioreactor

Abstract

Integrated cell analysis of biological cells sampled from a bioreactor can be provided by: a bioreactor; a sensor; a processor; and a memory containing instructions that, when executed by the memory, automatically perform operations including: extracting a sample from cells being cultured in the bioreactor; preparing the sample to generate a prepared sample; analyzing the prepared sample to identify values ​​of associated cell analysis parameters; and adjusting the settings of the bioreactor based on the difference between the value and the window in response to determining that the value is outside a window of the associated cell analysis parameters.

Description

[0001] priority This disclosure claims the benefit and priority of U.S. Provisional Patent Application No. 63 / 616,117, entitled “Integrated Cell Analysis of Biological Cells Sampled from a Bioreactor”, filed on December 29, 2023, the entire contents of which are incorporated herein by reference. Background Technology

[0002] Investment and interest in developing cell and gene therapies for treating intractable diseases are growing. For cell therapies, living biological cells, typically obtained from patients or healthy donors, are often processed and genetically modified, cultured, or produced in bioreactors to generate therapeutic materials for infusion into patients. However, the production and quality control of such cell therapies present the industry with many unique challenges. For at least these reasons, there is a growing need to monitor, measure, and characterize cells during the cell production process in bioreactors (e.g., where cells are cultured and grown).

[0003] Therefore, there is an expectation and need to develop new methods and systems that can automate and integrate the processes of cell production, cell sampling, sample monitoring, and cell analysis, so that feedback from these processes can effectively guide and improve cell production in a timely manner to enhance the quality of therapeutic cells and accelerate the production process for said therapeutic cells. Summary of the Invention

[0004] This disclosure provides a means for managing biological cells produced from a bioreactor (e.g., culturing, sampling, analyzing, and monitoring) for integrated cell analysis.

[0005] In one embodiment, a system is provided, comprising: a bioreactor; a sensor; a processor; and a memory containing instructions that, when executed by the processor, automatically perform operations including: extracting a sample from cells being cultured in the bioreactor; preparing the sample to generate a prepared sample; analyzing the prepared sample to identify values ​​of associated cell analysis parameters; and adjusting settings of the bioreactor based on the difference between the values ​​and the window in response to determining that the values ​​are outside a window of the associated cell analysis parameters.

[0006] In some such embodiments, the sample is obtained at a first time point, and the operation further includes: extracting additional samples from the cells being cultured in the bioreactor at a second time point after the first time point; preparing the additional samples to generate additional prepared samples; analyzing the additional prepared samples to identify additional values ​​of the associated cell analysis parameters; and maintaining the settings of the bioreactor in response to determining that the additional values ​​are within the window of the associated cell analysis parameters.

[0007] In some such implementations, the first duration between the first time and the second time is equivalent to the second duration between the second time and the third time, during which subsequent samples are extracted from the cells being cultured in the bioreactor to determine subsequent values ​​of the associated cell analysis parameters.

[0008] In some such implementations, the duration between the first time and the second time is one of the following: at least thirty minutes; at least one hour; at least two hours; at least six hours; at least twelve hours; at least twenty-four hours; at least thirty-six hours; at least forty-eight hours; at least seventy-two hours; at least eighty-four hours; at least ninety-six hours; at least one hundred and twenty hours; at least one hundred and forty-four hours; or at least one hundred and sixty-eight hours.

[0009] In some such embodiments, the operation further includes: extracting a second sample from the cells being cultured in the bioreactor at a first time; preparing the second sample to produce a second prepared sample; analyzing the second prepared sample to identify a second value of a second associated cell analysis parameter; maintaining the bioreactor settings until a second time in response to determining that the second value is within a second window of the second associated cell analysis parameter; extracting a third sample from the cells being cultured in the bioreactor at the second time; preparing the third sample to produce a third prepared sample; analyzing the third prepared sample to identify a third value of the second associated cell analysis parameter; identifying a trend of the second associated cell analysis parameter between the first time and the second time in response to determining that the third value is within the second window of the second associated cell analysis parameter; and adjusting a second setting of the bioreactor based on the difference between the trend and the window between the second time and the third time in response to determining that a predicted value of the trend at a third time when a fourth sample is planned to be extracted is outside the window.

[0010] In some such embodiments, preparing the sample to produce the prepared sample includes one, two, three, four, or all of the following: identifying or registering the sample; incubating the sample; staining the sample; adding a buffer or culture medium to the sample; or adding a therapeutic agent to the sample.

[0011] In some of these implementations, the associated cell analysis parameters include one, two, three, four, five, six, seven, or all of the following: pH; temperature; level or concentration of components or reagents within the bioreactor or sample; cell identity; cell number; cell purity; cell size; or run time.

[0012] In some such implementations, the operation further includes automatically discarding the prepared sample after identifying the value of the associated cell analysis parameter.

[0013] In some such embodiments, the cells grown in the bioreactor are extracted from a first biological subject prior to growth in the bioreactor and are obtained from the bioreactor for use as a modified cell culture to treat or prevent a disease in a second biological subject, wherein the modified cell culture comprises: cells genetically modified to express one or more heterologous genes; cells cultured for immunotherapy; or cells cultured for stem cell therapy.

[0014] In some of these implementations, the bioreactor remains independent and operates automatically based on instructions specifically received prior to the extraction of the sample.

[0015] In one embodiment, a method is provided, the method comprising: extracting a cell culture from a first biological subject; inserting the cell culture into a bioreactor; growing the cell culture in the bioreactor from a first time to a second time; modifying the cell culture in the bioreactor from the first time to the second time to produce a modified cell culture; obtaining the modified cell culture from the bioreactor; and supplying a therapeutically effective amount of the modified cell culture to a second biological subject suffering from or at risk of developing a disease that is treatable, preventable, or manageable by application of the modified cell culture.

[0016] In some such embodiments, growing and modifying the cell culture further includes automatically culturing the cell culture according to operations including: extracting a cell sample from the bioreactor at an intermediate time between the first time and the second time; preparing the cell sample to generate a prepared sample; analyzing the prepared sample to identify values ​​of associated cell analysis parameters; and adjusting the settings of the bioreactor based on the difference between the value and the window before the second time in response to determining that the value is outside a window of the associated cell analysis parameters.

[0017] In some such implementations, the prepared sample is discarded after the values ​​of the associated cell analysis parameters have been identified.

[0018] In some such embodiments, growing and modifying the cell culture further includes: automatically culturing the cell culture according to operations including: extracting a first cell sample from the bioreactor at a first intermediate time between the first time and the second time; preparing the first cell sample to produce a first prepared sample; analyzing the first prepared sample to identify a first value of an associated cell analysis parameter; maintaining the bioreactor settings in response to determining that the first value is within a window of the associated cell analysis parameter until a second intermediate time between the first intermediate time and the second time; extracting a second cell sample from the bioreactor at the second intermediate time; preparing the second cell sample to produce a second prepared sample; analyzing the second prepared sample to identify a second value of the associated cell analysis parameter; identifying a trend of the associated cell analysis parameter between the first intermediate time and the second intermediate time in response to determining that the third intermediate time is within the window of the associated cell analysis parameter; and adjusting the bioreactor settings based on the difference between the trend and the window between the second intermediate time and the third intermediate time in response to determining that a predicted value of the trend between the second intermediate time and the second time at which the third sample is planned to be extracted is outside the window.

[0019] In some such embodiments, a sample is extracted from the bioreactor via a needle and inserted into an analytical container, which is then moved to the analytical module, which includes a sensor that is detached from the bioreactor and determines values ​​of cell growth parameters.

[0020] In some such implementations, the bioreactor remains independent between the first and second times and operates automatically based on instructions specifically received prior to the first time.

[0021] In some such embodiments, the modified cell culture comprises: cells genetically altered to express one or more heterologous genes; cells cultured for use in immunotherapy; or cells cultured for use in stem cell therapy.

[0022] In one embodiment, a method is provided, the method comprising: extracting a sample from cells being cultured in a bioreactor; preparing the sample to produce a prepared sample; analyzing the prepared sample to identify values ​​of associated cell analysis parameters; and adjusting settings of the bioreactor based on the difference between the values ​​and the window in response to determining that the values ​​are outside a window of the associated cell analysis parameters.

[0023] In some such embodiments, the sample is extracted at a first time point, and the method further includes: extracting additional samples from the cells being cultured in the bioreactor at a second time point after the first time point; preparing the additional samples to generate additional prepared samples; analyzing the additional prepared samples to identify additional values ​​of the associated cell analysis parameters; and maintaining the settings of the bioreactor in response to determining that the additional values ​​are within the window of the associated cell analysis parameters.

[0024] In some such embodiments, the method further includes: extracting a second sample from the cells being cultured in the bioreactor at a first time; preparing the second sample to produce a second prepared sample; analyzing the second prepared sample to identify a second value of a second associated cell analysis parameter; maintaining the settings of the bioreactor until a second time in response to determining that the second value is within a second window of the second associated cell analysis parameter; extracting a third sample from the cells being cultured in the bioreactor at the second time; preparing the third sample to produce a third prepared sample; analyzing the third prepared sample to identify a third value of the second associated cell analysis parameter; identifying a trend of the second associated cell analysis parameter between the first time and the second time in response to determining that the third value is within the second window of the second associated cell analysis parameter; and adjusting a second setting of the bioreactor based on the difference between the trend and the window between the second time and the third time in response to determining that a predicted value of the trend at a third time when a fourth sample is planned to be extracted is outside the window.

[0025] In some such implementations, the method further includes automatically discarding the prepared sample after identifying the value of the associated cell analysis parameter.

[0026] In some such embodiments, the cells grown in the bioreactor are extracted from a first biological subject prior to growth in the bioreactor, and once a predetermined growth value is reached, they are removed from the bioreactor for use as a modified cell culture to treat or prevent a disease in a second biological subject, wherein the modified cell culture comprises: cells genetically modified to express one or more heterologous genes; cells cultured for immunotherapy; or cells cultured for stem cell therapy.

[0027] Additional features and advantages of the disclosed methods and apparatus are described in the following detailed description and accompanying drawings, and will become apparent from the following detailed description and accompanying drawings. The features and advantages described herein are not exhaustive, and in particular, many additional features and advantages will be apparent to those skilled in the art in light of the accompanying drawings and description. Furthermore, it should be noted that the language used in this specification has been chosen primarily for readability and guidance purposes, and is not intended to limit the scope of the subject matter of the invention. Attached Figure Description

[0028] Figure 1 The illustration depicts a system for automatically sampling biological cells from a bioreactor for integrated cell analysis and production, according to an embodiment of the present disclosure.

[0029] Figure 2 This is a flowchart of an exemplary method for automatically sampling biological cells from a bioreactor for integrated cell analysis and production, according to a non-limiting embodiment of the present disclosure.

[0030] Figure 3 This is a flowchart of an exemplary method for automatically managing the growth and culture of cell samples for research, treatment, or prevention, according to embodiments of this disclosure.

[0031] Figure 4 Exemplary method settings according to embodiments of the present disclosure are illustrated.

[0032] Figure 5 A computing device according to an embodiment of the present disclosure is illustrated.

[0033] Figures 6A to 6L Cellular analysis parameters of CAR-T cells produced in a G-REX® 24-well bioreactor device (available from Wilson Wolf Corp.) according to an embodiment of this disclosure are shown.

[0034] Figures 7A to 7F Cellular analysis parameters of T cells cultured in a G-REX 24-well apparatus in the presence of different cytokines (IL2, IL7, or IL15) according to an embodiment of the present disclosure are shown.

[0035] Figure 8 An overview of an exemplary T-cell production process with a feedback loop, according to an embodiment of the present disclosure, is illustrated. The T-cell production process begins with thawing PBMCs and allowing them to stand overnight one day prior to production (D-1). On day 0 (D0), cells are produced in bioreactor well plates at a rate of 1 × 10⁻⁶. 6 The cells were seeded at a density of 10 cells / well and the resting cells were activated. Activation was terminated on day 3 (D3) by replacing the activation medium with culture medium. A feedback loop began on day 4 (D4), which involved performing cell analysis to assess selected quality parameters. Based on these results, the culture conditions were adjusted for conditions that failed to meet quality control (QC) standards. Additional cell analysis was performed on day 6 (D6), and the final harvest occurred on day 10 (D10).

[0036] Figure 9 This is a schematic diagram illustrating a test group and a feedback loop for activating the sample group according to an embodiment of the present disclosure.

[0037] Figure 10 The kinetics of T cell growth during an exemplary production process in a control group, according to an embodiment of this disclosure, are illustrated. In the illustrated results, PBMCs that were left to rest overnight showed a growth rate of 1 × 10⁻⁶ on day zero. 6 Cells were seeded at a density in bioreactor plates and cultured from day 0 to day 3 in activation medium (e.g., RPMI 1640 containing 10% FBS, supplemented with soluble CD3 / CD28 activator and 200 U / mL IL-2). From day 3 onwards, cells were maintained in expansion medium containing 200 U / mL IL-2. Cell counting was performed using flow cytometry on days 3, 4, 6, and 10.

[0038] Figures 11A to 11C The illustration shows the results of evaluating cell quality parameters of the control group and two identical experimental groups using flow cytometry on the fourth day according to an embodiment of the present disclosure. Figure 11A The total number of cells in Sample 1 and its x-fold change relative to the control group are plotted. Figure 11B The percentage of stem cell memory T-cells (Tscm) in Sample 1 and their x-fold change relative to the control group are plotted. Figure 11C The cell count of Tscm in Sample 1 and its x-fold change relative to the control group are plotted.

[0039] Figures 12A to 12CThe illustration depicts the results of cell quality parameter assessment for a control group and two identical experimental groups using flow cytometry throughout the production process, according to an embodiment of this disclosure. Following the initial cell analysis on day four, sample 3 was transferred and maintained under modified culture conditions so that feedback could be applied to the remaining portion of the production process. Figure 12A The dynamics of cell proliferation over time in Sample 1 are illustrated, as well as the x-fold change in total cell number relative to the control group, measured on days 4, 6, and 10. Figure 12B The dynamics of the percentage change of Tscm throughout the manufacturing process are illustrated, as well as the x-fold change of the percentage of Tscm relative to the control group in Sample 1 measured on days 4, 6, and 10. Figure 12C The dynamics of Tscm cell number changes throughout the manufacturing process are illustrated, as well as the x-fold change in Tscm cell number in Sample 1 relative to the control group, as assessed on days 4, 6, and 10. Detailed Implementation

[0040] This disclosure provides methods for sampling biological cells from a bioreactor for integrated cell analysis. These biological cells allow practitioners to reduce, minimize, or eliminate variability in cell analysis processes and results from cells extracted from a cell culture bioreactor through automated or semi-automated integrated cell analysis and measurements, including cell sampling, cell handling, cell measurement, and cell analysis result reporting, for optional changes to or maintenance of the cell culture bioreactor process and / or for optional subsequent administration of cultured cells to biological subjects (e.g., patients). The systems, apparatus, and methods described herein can be used to sample biological cells from a bioreactor for integrated cell analysis and achieve significant benefits and advantages compared to conventional methods.

[0041] Cell therapy is a broad concept that describes, for example, the injection, transplantation, or implantation of live cells into a patient to treat intractable diseases. The production of cells for cell therapy may involve obtaining living biological cells from a patient or healthy donor. These cells may be processed, genetically modified, cultured, or produced in a bioreactor (e.g., for use in therapeutic materials for infusion into a patient).

[0042] One of the most important requirements for cell therapy is the consistency of product quantity and quality. For example, attributes used to determine the quantity and quality of products in cell therapy may include, but are not limited to, cell quantity (cell number), cell identity, cell purity, cell potency, cell viability, and other cell quality parameters. While maintaining consistency and reliability of cell sample quantity and quality is important for effective cell therapy, achieving this consistency and reliability is difficult for a variety of reasons. For example, the starting materials used in cell therapy (which typically include living biological cells) can vary significantly from batch to batch. Furthermore, because biological cells are alive and growing during the manufacturing process, any variation in cell growth medium, cell growth conditions, or any other growth parameters (known or unknown) can lead to significant differences in the final product.

[0043] Typically, manual processes are used to remove cell samples from bioreactors or to process the 'removed cells' for assays and analyses. These manual steps for cell sampling (e.g., extracting a volume of cells from a culture) often result in inconsistent sample volumes or poor homogeneity of cell suspensions (e.g., depending on the operator performing the sampling, the production site used, or the time of day). Manual sampling may also limit the time when it can be performed (e.g., during weekends or late at night) and may miss critical time points when samples need to be analyzed. Therefore, manual sampling is an inefficient process and susceptible to human error, leading to variations in cell yield, adversely affecting the results of analytical measurements, and ultimately negatively impacting the cell therapy delivered to patients.

[0044] Artificial processing of sampled cells for analysis may involve adding cell analysis reagents to the sample; incubating cells with reagents in some apparatus or device; washing and resuspending cells; aliquoting cell samples into different containers (e.g., test tubes or wells of microplates); and placing the cell containers into a cell analyzer for experimentation. Depending on the cell analyzer used, additional manual steps may be involved in handling samples, operating the instrument, performing data acquisition experiments, and data analysis. These manual steps in cell processing and cell assay experiments introduce additional variables or uncertainties into the cell analysis process, leading to increased variability in assay results. Similarly, manual steps can limit the time window for performing and conducting cell assay experiments. Furthermore, in manual processes, cell assay results are not used to guide or control possible cell production processes in an automated or semi-automated manner. That is, data from different cell analyzer devices or systems cannot be synchronized in a timely manner, thus failing to effectively guide the culture process of cell therapy products in bioreactors.

[0045] Therefore, this disclosure describes systems, apparatuses, and methods for automatically sampling, processing, and analyzing biological cells from bioreactors for integrated cell analysis and production, which address and overcome one or more known deficiencies of conventional methods for artificial cell sampling and analysis in cell therapy. Without being bound by theory, the systems, apparatuses, and methods described herein can achieve one or more of the following: (a) reducing variability in cell sampling from a bioreactor (e.g., for cell samples expected to be identical); (b) reducing variability in cell preparation or cell handling for cell measurement steps; (c) reducing variability in cell measurement and cell analysis; (d) reducing labor-intensive and time-consuming steps for cell sampling, cell handling and cell analysis, data analysis, and reporting; (e) allowing real-time feedback from cell analysis to guide cell culture (e.g., long-term cell culture) to achieve optimal cell culture or production in a bioreactor; (f) allowing for systematic process monitoring and control during cell culture (e.g., long-term cell culture) and analytical measurements to meet regulatory requirements, as well as combinations of the foregoing, and other benefits that will be apparent to a person of ordinary skill in the art upon reading this disclosure.

[0046] In some embodiments, the systems, apparatuses, and methods described herein are designed for use throughout the entire cell analysis process, including cell sampling, cell processing, cell measurement, and cell analysis result reporting. In some embodiments, the systems, apparatuses, and methods achieve one or more of the following benefits and advantages, including but not limited to: (a) automated or semi-automated integrated cell analysis and measurement; (b) consistent cell sampling; (c) potential standardization of cell sampling from bioreactors as a universal method; (d) consistent and reproducible cell preparation and cell processing; (e) less variability in cell measurement and cell monitoring; (f) integrated sample-to-results throughout the cell analysis process using cell samples taken from the bioreactor; (g) easier integration of multiple types of cell measurements and cell analyses; (h) better compatibility of the cell analysis process with automated closed cell culture bioreactors; (i) better measurement results; and (j) use of cell sample analysis to guide culture conditions and methods to improve and optimize cell quality and reduce culture time and increase efficiency, for example, to implement closed-loop feedback. The mechanism utilizes information from cell analysis to guide and control the cell culture process in real time (e.g., adjust culture medium composition, pH, etc.); (k) employs a closed, fully automated system, including therapeutic cell product culture bioreactors, cell sampling devices, sample preparation systems, cell analysis instruments, and related software and information systems, to meet regulatory compliance requirements, for example, to maintain and ensure data integrity and process compliance in cell therapy production and quality control (QC), and employs the automated workflows described herein, where each step is traceable, and data is stored in a centralized, secure storage device. This provides significant benefits and advantages to the automated processes described herein compared to manual sampling and measurement, which may have inherent limitations in meeting compliance requirements, such as process and data traceability, their combination, and other benefits that will become apparent to a person skilled in the art upon reading this disclosure.

[0047] Various embodiments of this disclosure include one or more of the following: (i) a bioreactor in which cells are cultured and grown, possibly having automated culture medium replacement, automated cell culture nutrient supply, etc.; (ii) a mechanism or apparatus for moving tubes, boxes, microtiter plates, or any dishes or containers from a stack of such dishes or containers to a predetermined position relative to the bioreactor; (iii) a mechanism or apparatus for moving a desired volume of cell sample from the bioreactor to a dish or container or tube, box, or microtiter plate at a predetermined schedule (optionally, a mechanism for mixing or homogenizing the cell sample in the bioreactor before moving the cell sample to the dish); (iv) a mechanism or apparatus for moving a dish or container (containing a cell sample) to a cell preparation or processing station (e.g., as previously described in (ii); (v) a device for preparing or processing cells for cell culture. The apparatus for measuring cell samples includes (vi) adding suitable cell measurement reagents to or adding cell samples to suitable cell measurement reagents, incubating cell samples with reagents for the required length of time under suitable conditions, or processing cell samples prepared for cell measurement; (vii) apparatus or device for moving dishes or containers to a cell measurement apparatus (e.g., after cell samples have been processed or prepared); (vii) a mechanism for initiating cell measurements for data acquisition according to an appropriate measurement schedule or procedure; (viii) optionally, a mechanism for initiating data analysis, creating an analysis report, or forwarding the analysis report to another computing system (e.g., for use by another software); (ix) mechanisms that may alter cell culture conditions or parameters in a bioreactor to optimize cell culture (e.g., long-term cell culture) based on the analysis results, and combinations thereof.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0049] As used in this article, the articles “one” and “a (kind)” refer to one (kind) or more (kinds) (e.g., at least one (kind)) the grammatical object of the article.

[0050] As used herein, “about” or “approximately” generally refers to the acceptable degree of error of a measured quantity given the nature or precision of the measurement. An illustrative degree of error is within 20 percent (20%) of a given value or range of values, typically within 10 percent, and more usually within 5 percent.

[0051] As used herein, “automatic,” “automated,” and their variations should generally refer to processes performed without direct human interaction or command. Automatically performed actions can be executed based on parameters or settings defined by a human user, but without user command. For example, the action of opening a sample tray can be performed or directed by a human user (e.g., by pressing a button), or it can be automatically performed by a computerized system in response to a triggering condition. Operations described as semi-automatic may refer to processes that are partially performed by a human and partially automatic. For example, a computer may request human confirmation before automatically performing an action, thus making the sequence semi-automatic. In another example, a computer may pause the execution of an automatically performed operation to give a human operator the opportunity to cancel or modify the operation, thus making the sequence semi-automatic.

[0052] As used herein, “culture” or “cell culture” refers to the process of growing cells under controlled conditions over a prolonged period of time. In some embodiments, culture occurs, and the controlled conditions are facilitated by a bioreactor. Such conditions, also referred to herein as “parameters,” may include, but are not limited to, pH, temperature, levels or concentrations of components or reagents (e.g., O2, CO2, amino acids, proteins, nutrients, drugs, hormones, or culture media), process parameters (e.g., the frequency of culture medium replacement, or the flow rate at which fresh culture medium is introduced into the bioreactor during culture medium replacement), or run time (e.g., the duration of cell growth). In some embodiments, culture involves growing cells in an aqueous nutrient solution referred to as cell culture medium. Cell culture medium may contain an energy source (e.g., carbohydrates) and can be used in various cell culture processes. “Culture” or “cell culture” may also refer to the composition of cells grown through the processes described above. This disclosure describes examples of cell cultures used to manufacture or produce cells for cell-based therapies, and therefore the terms “cell culture,” “cell production,” or “cell manufacturing” may be used interchangeably to refer to the process of culturing, growing, or producing cells in a bioreactor.

[0053] As used herein, the term "module" may refer to a subsystem. A module may include programs that, when executed, affect individual functionality or aspects of the overall automated or semi-automated process of integrated cell analysis and production, including the automated sampling of biological cells from a bioreactor. In some embodiments, the module is a computer subsystem. In some embodiments, the module may also refer to the underlying device used to implement individual functionality or aspects. For example, as described herein, a module may include, but is not limited to, a "bioreactor module," a "sample extraction module," a "sample preparation module," a "sample analysis module," or a "controller module" (also referred to herein as a "controller").

[0054] Unless the context clearly indicates otherwise, “or” is used herein to mean the inclusive meaning of “or” (see the exclusive meaning of “or”) and is interchangeable with the term “and / or”. Unless the context clearly indicates otherwise, the use of the term “and / or” in certain places herein does not imply that the use of the term “or” is not interchangeable with the term “and / or”.

[0055] As used herein, the term "sample" refers to a biological sample obtained or derived from a source of interest. For example, the term "cell sample" as used herein refers to a sample containing at least one cell. In some embodiments, a cell sample contains multiple cells. In some embodiments, the cells are placed in a culture medium. In some embodiments, the source of interest includes an organism, such as an animal or a human. The sample source may be blood or blood components; body fluids; solid tissue, such as solid tissue from fresh, frozen, or preserved organs, tissues, biopsies, excisions, smears, or aspirates; or cells from any stage of pregnancy or development of the subject. For example, cell samples may be isolated or harvested directly or indirectly from a subject, organ, or tissue. In some embodiments, the sample is a primary sample, for example, obtained directly from the source of interest by any suitable means. In some embodiments, the sample is a preparation obtained by processing the primary sample (e.g., by removing one or more components or by adding one or more reagents to said primary sample). Processing the primary sample may include biological manipulation of primary cells, such as transfecting genes into primary cells, knocking out certain genes from primary cells, or culturing and passaged primary cells in a suitable culture medium. Therefore, samples may include transfected cells, cultured cells, or cell lines from biological subjects.

[0056] As used herein, various compounds may be referred to by the associated element abbreviations established by the International Union of Pure and Applied Chemistry (IUPAC), which are familiar to those skilled in the art. Similarly, various units of measurement may be used herein, referred to by the relevant abbreviations established by the System of Units (SI), with various prefixes, which are familiar to those skilled in the art.

[0057] Certain terms are used throughout the specification and claims to refer to specific features or components. As those skilled in the art will understand, different people may use different names to refer to the same feature or component. This document is not intended to distinguish between components or features with different names but the same function.

[0058] Figure 1A system 100 for integrated cell analysis and production, according to an embodiment of the present disclosure, is illustrated, the integrated cell analysis and production including the automated sampling of biological cells from a bioreactor. For example... Figure 1 As shown, system 100 includes multiple modules (collectively referred to as "integrated cell therapy module" 102) for directly producing, sampling, or analyzing biological cell cultures, and a controller 170 for processing information received from integrated cell therapy module 102 and transmitting commands based on said information. In some embodiments, system 100 further includes an external storage medium 190. One or more components of system 100 may communicate via communication network 160.

[0059] In various embodiments, controller 170 includes various hardware (e.g., a printed circuit board with electronic circuitry) configured to process information (e.g., analog or digital signals) received from one or more integrated cell therapy modules in integrated cell therapy module 102, and to execute and transmit commands based on computer-executable instructions. In some embodiments, controller 170 is or includes a microcontroller (e.g., as an embedded system) embedded within any module of integrated cell therapy module 102, thereby controlling processes performed for automatically sampling biological cells from a bioreactor for integrated cell analysis and production.

[0060] like Figure 1 As shown, controller 170 includes one or more processors 172 and memory 174. The one or more processors 172 may be or include one or more types of digital circuitry configured to perform operations on a data stream, including the functions described herein. In some embodiments, the one or more processors 172 include a first processor (e.g., a microprocessor) and a second processor (e.g., a second microprocessor) for performing individual or parallel functionalities. Memory 174 may be or include any type of long-term, short-term, volatile, non-volatile, or other memory device and should not be limited to any particular type or number of memories, or the type of medium storing the memory. Memory 174 may store instructions that, when executed by processor 172, cause controller 170 to perform one or more methods discussed herein. As used herein, memory 174 is an example of a device including a computer-readable storage medium and should not be construed as a transmission medium or the signal itself.

[0061] In some embodiments, controller 170 includes one or more of an integrated application 184, a network interface 176, a user interface 178, and a sample database 180. The integrated application 184 may be or include software, programs, or code for allowing scheduling or initiation of different stages, steps, or actions involved in the process of automated sampling of biological cells for integrated cell analysis and production. In some embodiments, the integrated application 184 enables controller 170 to communicate with integrated cell therapy modules 102 (optionally via communication network 160) and enables one or more integrated cell therapy modules in integrated cell therapy modules 102 to perform actions based on a scheduling of actions. For example, integrated application 184 may receive an indication that a sample has been extracted (e.g., from bioreactor module 110), and then enable sample extraction module 120 to transfer the sample to sample preparation module 130 (e.g., by sending command signals to robot control 134).

[0062] Network interface 176 allows controller 170 to communicate with other systems or subsystems (e.g., any of the integrated cell therapy modules 102) via communication network 160. For example, network interface 176 may include wired interfaces (e.g., electrical interfaces, radio frequency (RF) interfaces (via coaxial cable), optical interfaces (via fiber optics)), wireless interfaces, modems, etc. In some embodiments, one or more integrated cell therapy modules in integrated cell therapy module 102 may also have corresponding network interfaces to allow communication with other systems or subsystems.

[0063] In various implementations, the user interface 178 may be or include a portal, allowing a user or operator of the controller 170 to configure one or more aspects of a process for automated sampling of biological cells for integrated cell analysis and production. For example, the user or operator may use the user interface 178 to set parameters for growing cells in a bioreactor (bioreactor parameters or bioreactor module parameters), or to set sample sizes for extraction and analysis. Once these functionalities are configured, the controller 170 can perform various operations without further human intervention.

[0064] In various embodiments, sample database 180 may be or include a repository, list, or record of cell cultures and cell culture samples managed by controller 170. Samples or cell cultures are identifiable in sample database 180 by one or more of a sample identifier, a cell culture identifier, or a bioreactor device identifier. In some aspects, sensitive identifying information about samples or cultures (e.g., patient data) may be encrypted or stored as metadata. In some aspects, sample database 180 may also record attributes, characteristics, or conditions (collectively, “parameters”) set for samples or sample cultures (e.g., parameter record 182). Parameters may include: bioreactor parameters, which are conditions set for cell culture or growth in a bioreactor; and cell analysis parameters, which are attributes or characteristics of the sampled and analyzed cells. In some embodiments, sample database 180 may be stored externally (e.g., at external storage medium 190) to save bandwidth, processing, and other computing resources of controller 170. Alternatively, controller 170 may store a brief or temporary record of information related to the sample, while external storage medium 190 may store a more complete version of the information (e.g., as shown by sample database 192 and parameter record 194 stored in external storage medium 190).

[0065] The integrated cell therapy module 102 may include, but is not limited to, a bioreactor module 110, a sample extraction module 120, a sample preparation module 130, and a sample analysis module 150. The bioreactor module 110 may be or include subsystems, programs, or logic that enable associated devices (e.g., a bioreactor) to support a bioactive environment for the cell culture process based on a set of parameters. In some embodiments, the bioreactor module 110 may also include associated devices that can be modified or maintained based on programs or logic. In some embodiments, the bioreactor module 110 includes a microprocessor 111 (e.g., an embedded microprocessor). In some implementations, execution of the program (e.g., by microprocessor 111) may cause the activation of controls within the bioreactor apparatus (e.g., parameter control 112), which causes one or more parameters for cell culture (referred to herein as bioreactor parameters) to be maintained (e.g., pH; temperature; levels or concentrations of components or reagents (e.g., O2, CO2, amino acids, proteins, nutrients, drugs, hormones, or culture media); process parameters such as the frequency of culture medium replacement or the flow rate used to introduce new culture medium into the bioreactor during culture medium replacement, or run time).

[0066] For example, bioreactor module 110 can regulate pH by allowing acid, alkali, or buffer media to flow into or out of a container holding cell culture medium. Furthermore, bioreactor module 110 can regulate temperature by adjusting (e.g., electronically) the heat supplied to the container. In another example, bioreactor module 110 can regulate the level or concentration of a component or reagent by adjusting the flow into or out of the container. Additionally, the running time can be adjusted via a timer that sets the time for termination of the cell culture process, sample extraction, or notification to the user that the cell culture process is complete. Bioreactor module 110 may further include a network interface 114 that allows controller 170 or an operator of controller 170 (e.g., via user interface 178) to be informed of and control various parameters of bioreactor module 110. Network interface 114 may share one or more sub-components or functionalities with network interface 176.

[0067] The sample extraction module 120 may be or include a subsystem, program, or logic that causes associated devices to extract and hold cell culture samples from the bioreactor for placement in a location for delivery to another module (e.g., sample preparation module 130). In some embodiments, the sample extraction module 120 may also include associated devices that are controlled or activated based on a program or logic (e.g., via associated actuators or ports). In some embodiments, the sample extraction module 120 may include a microprocessor 121 (e.g., an embedded microprocessor). In some aspects, execution of a program (e.g., via microprocessor 121) may result in the activation and movement of one or more actuators 128 (e.g., motors, levers, pumps, etc.) to facilitate the mixing of cells and culture medium within the bioreactor (e.g., to ensure uniform volume distribution of cells with culture medium in the bioreactor), or to facilitate the extraction or removal of samples from the bioreactor module 110 and the delivery of the sample or sample aliquots to another module (e.g., sample preparation module 130). One or more actuators 128 can be positioned to perform both extraction and delivery (e.g., by positioning one actuator toward the bioreactor module 110 and another toward the sample preparation module 130).

[0068] Furthermore, extraction or delivery can be performed via a port (receive port 122) for receiving samples from bioreactor module 110 and a port (delivery port 124) for delivering samples or sample aliquots to the second module. Receive port 122 may include a pump (e.g., an injection pump) (receive pump 123), or may be connected to the pump. Receive pump 123 may be configured to extract samples (e.g., a predetermined volume of sample) from bioreactor module 110 at a predetermined schedule.

[0069] For example, the receiving pump 123 may be equipped with sensors to accurately detect when a specified volume of sample has been extracted from the bioreactor. Alternatively, the receiving pump 123 may be designed to hold only a specified volume, such that it automatically stops extraction when the specified volume is reached. In some embodiments, the receiving pump 123 may be placed in or located within the bioreactor module 110 (automatically (e.g., via a robot or mechanism of the bioreactor) or manually) to facilitate sample extraction. However, in other embodiments, the receiving pump 123 may be located outside the bioreactor module 110 (e.g., within the sample extraction module 120 as shown).

[0070] In some embodiments, delivery port 124 may include or be connected to a sample dispensing needle 125. The sample dispensing needle 125 may be configured to deliver a sample or aliquots of a sample to a second module (e.g., sample preparation module 130 or sample analysis module 150). For example, one or more actuators 128 (e.g., robotic arms, pulleys, motors, levers, etc.) may position the sample dispensing needle 125 to be filled with a predetermined amount of sample and may move the sample dispensing needle 125 toward the second module. Alternatively or additionally, actuators 128 may move the sample dispensing needle 125 outside the sample extraction module 120 to allow a user or automated system to easily move the sample dispensing needle 125 to the second module (e.g., sample preparation module 130 or sample analysis module 150).

[0071] In addition, the sample extraction module 120 may include a network interface 126 to allow communication with the controller 170 and other modules via a communication network 160. The network interface 126 may share one or more sub-components or functionalities with the network interface 176. The network interface 126 may allow the sample extraction module 120 to optionally receive signals from other modules (e.g., the controller 170) via the communication network 160. The received signals may cause the sample extraction module 120 (e.g., by forwarding electrical signals to the actuator 128) to extract samples from the bioreactor module 110 or to deliver samples or aliquots to a second module.

[0072] The sample preparation module 130 may be or include a subsystem, program, or logic that enables the associated device to: obtain a sample or sample aliquots (e.g., from the sample extraction module 120); add one or more reagents (a first reagent and a second reagent (e.g., a cell suspension buffer)) to the sample or sample aliquots; mix the reagents with the sample or sample aliquots; incubate the sample or sample aliquots with the reagents; wash the sample or sample aliquots (e.g., cell washing); and deliver the prepared sample to another module (e.g., the sample analysis module 150).

[0073] In some embodiments, the sample extraction module 120 may also include associated devices that are controlled or activated based on a program or logic (e.g., via an associated actuator or port). In some embodiments, the sample preparation module 130 includes a microprocessor 131 (e.g., an embedded microprocessor). In some embodiments, execution of a program (e.g., by the microprocessor 131) activates and moves one or more robotic controls 134 (e.g., a robotic arm, motor, lever, pump, etc.) to perform one or more of the functions described herein. For example, the sample preparation module 130 may use a motor to cause a stirrer to mix reagents with a sample or sample aliquots, or may use a robotic arm (e.g., activated via an electronic pulley and belt system) to obtain or transport a sample or sample aliquots.

[0074] The sample preparation module 130 may include a port (receiving port 136) for receiving samples or aliquots from a second module (e.g., sample extraction module 120); and a port (delivery port 138) for conveying samples or aliquots to a second module (e.g., sample analysis module 150). In some embodiments, the receiving port 136 may include, or be connected to, a test tube. The test tube may be configured to receive samples or aliquots (e.g., a predetermined volume of sample, according to a predetermined schedule) from the sample extraction module 120 or the bioreactor module 110. For example, the test tube may be held or extended outward from the sample preparation module 130 (e.g., through elements or arms of the sample preparation module 130) so that the sample dispensing needle 125 of the sample extraction module 120 may place samples or aliquots into the test tube.

[0075] Alternatively or alternatively, the receiving port may include or be connected to a microfluidic cassette (e.g., a microfluidic cassette for flow cytometry assays). The microfluidic cassette may be configured to receive samples or aliquots from a second module (e.g., sample extraction module 120). For example, a microfluidic cassette (e.g., a microfluidic cassette for flow cytometry assays) may be connected to a stack of microfluidic cassettes (e.g., a stack of microfluidic cassettes for flow cytometry assays). The stack of microfluidic cassettes may be powered via a motor or electronic pulley to move the microfluidic cassettes to an exposed location outside the sample preparation module 130, where samples or aliquots may be received from another module (such as the sample extraction module or bioreactor module). Alternatively or alternatively, the stack of microfluidic cassettes may dispatch microfluidic cassettes (e.g., microfluidic cassettes for flow cytometry assays) to dispensing locations or may facilitate barcode reading.

[0076] Alternatively or concurrently, the receiving port 136 may include or be connected to a sampling manifold. The sampling manifold may be configured to receive samples or aliquots from a second module (e.g., sample extraction module 120). For example, the sampling manifold may include multiple chambers containing different samples or aliquots from the bioreactor. For example, the sampling manifold may include a plate with multiple wells. The sampling manifold may be located on a platform of the sample preparation module 130, which may be exposed to the outside to receive samples or aliquots (e.g., via sample dispensing needle 125 in the sample extraction module). In some embodiments, robotic control 134 may move the platform holding the sampling manifold to prepare the samples or aliquots contained within the sampling manifold.

[0077] In some embodiments, the test tubes, microfluidic cartridges, or sampling manifolds may be pre-loaded with reagents for cell analysis (e.g., lyophilized antibodies for flow cytometry assays). In some embodiments, the sample preparation module 130 may include slots for a user or operator to load the required amount of reagents to mix with the sample or sample aliquots in the test tubes, microfluidic cartridges, or sampling manifolds. In other embodiments, the reagents may not be pre-loaded but may be loaded by the system or human user before or after adding cells or other samples for analysis to the receiving port 136 or sample holding device.

[0078] In some embodiments, the sample preparation module 130 may include a staining and incubation station 140. In some aspects, the staining and incubation station 140 may include a submodule storing programs or logic that enable one or more robot controls 134 to perform one or more functions related to staining or incubating a sample or sample aliquots.

[0079] For example, the staining and incubation station 140 can be configured to: dispense staining buffer (e.g., a predetermined volume of staining buffer) into test tubes, microfluidic cassettes, or sampling manifolds; mix the sample and reagents (e.g., staining buffer) in the test tubes, microfluidic cassettes, or sampling manifolds via convection or fluid motion using various means (e.g., agitating the test tubes, microfluidic cassettes, or sampling manifolds to facilitate mixing or incubation); or incubate the sample or sample aliquots (e.g., for a predetermined incubation time). In some embodiments, the sample preparation module 130 may include a compartment for storing staining buffer from which a predetermined amount of staining buffer can be dispensed into test tubes, microfluidic cassettes, or sampling manifolds, any of which can be held in place by the staining and incubation station 140. Dispensing can be performed in response to receiving a signal indicating that the sample or sample aliquots are ready for staining. In one embodiment, mixing of samples and reagents in a test tube, microfluidic cassette, or sampling manifold can be performed via an actuator below the platform, thereby inducing fluid movement, such as fluid convection. In some embodiments, agitation can be performed via an actuator below the platform, causing the platform, test tube, microfluidic cassette, or sampling manifold to perform oscillating, linear, or orbital movements, thereby mixing the samples and reagents in the test tube, microfluidic cassette, or sampling manifold. In some embodiments, incubation can be performed by controlling one or more parameters of the environment in which the sample or aliquot is stored. After incubation, the sample or aliquot may be referred to as a prepared sample.

[0080] In some embodiments, delivery port 138 may include or be connected to a test tube moving arm. The test tube moving arm may be configured to deliver prepared samples or aliquots of prepared samples (e.g., a predetermined volume of prepared sample or according to a predetermined schedule) to another module (e.g., sample analysis module 150). For example, one end of the test tube moving arm may hold a test tube (e.g., via a clamping surface or via a test tube holder), while one or more joints of the test tube moving arm may be rotated in response to an electrical signal using robot control 134 (e.g., a motor), thereby moving said end of the test tube moving arm toward the sample analysis module 150.

[0081] Alternatively or concurrently, delivery port 138 may include or be connected to a conveyor. The conveyor may be configured to transport prepared samples to another module (e.g., sample analysis module 150). For example, the conveyor may include an electronic pulley powered by a motor of robot control 134 in response to a signal (e.g., received from controller 170). Using the motor, the conveyor can move any compartment or holder containing the prepared sample (e.g., test tube or microfluidic cartridge) to sample analysis module 150. For example, the conveyor may be configured to move a microfluidic cartridge from a dispensing position to supply a cell analyzer 158 (e.g., flow cytometer) to sample analysis module 150.

[0082] Alternatively or concurrently, delivery port 138 may include or be connected to a plate processor (e.g., a robotic plate processor). The plate processor may be configured to deliver prepared samples to another module (e.g., sample analysis module 150). For example, the plate processor may include multiple holes on a plate, whereby the plate can be picked up and moved to a position on sample analysis module 150 by a robotic arm of robotic control 135. The robotic arm may include a gripping or locking element at one end for picking up the plate by gripping or locking, respectively. Furthermore, the robotic arm may include one or more joints that can be powered and rotated via motors in response to signals (e.g., received from controller 170). Using the motors, the robotic arm can move the plate processor, including multiple holes for holding prepared samples, to sample analysis module 150. In some embodiments, the plate processor may refer to a combination of a plate and a robotic arm. In some embodiments, the sampling manifold may include a plate.

[0083] In some embodiments, the test tubes, microfluidic cassettes, or sampling manifolds containing samples, aliquots, or prepared samples may be labeled with barcodes. In such embodiments, a tube moving arm, conveyor, or plate processor can move the test tubes, microfluidic cassettes, or sampling manifolds so that the barcodes can be read (e.g., via barcode reader 142). Alternatively or additionally, the tube moving arm, conveyor, or plate processor can move the test tubes, microfluidic cassettes, or sampling manifolds toward the staining and incubation station 140 of the sample preparation module 130 (e.g., for the staining and incubation processes described above).

[0084] Furthermore, the sample preparation module 130 may include a network interface 144 to allow communication with the controller 170 and other modules via a communication network 160. The network interface 144 may share one or more sub-components or functionalities with the network interface 176. The network interface 144 may allow the sample preparation module 130 to receive signals from other modules (e.g., the controller 170) that cause the robot control 134 to perform one or more of the functions described herein. For example, in response to receiving a signal from the controller 170, the sample preparation module 130 may prompt the robot control 134 to deliver the prepared sample to the sample analysis module 150. Therefore, the controller 170 may function as a single software control system that provides instructions to the robot control 134 (e.g., a robotic arm), the staining and incubation station 140, and the barcode reader 142.

[0085] The sample analysis module 150 may be or include a subsystem, program, or logic that causes an associated device to receive a sample, sample aliquot, or prepared sample from another module (e.g., sample preparation module 130 or sample extraction module 120), detect one or more parameters of the sample or prepared sample (referred to herein as cell analysis parameters), and generate a value for each of the one or more cell analysis parameters. In some embodiments, the sample analysis module 150 may also include an associated device that is controlled or activated (e.g., via its sensors, ports, or actuators) based on the program or logic. In some embodiments, the sample analysis module 150 may include a microprocessor 151 (e.g., an embedded microprocessor). In some embodiments, execution of the program (e.g., by the microprocessor 151) may result in a port (receive port 152) receiving a sample and may result in sensors measuring or detecting one or more parameters of the sample. In some embodiments, the sample analysis module 150 includes a receive port 152, a delivery port 154, one or more sensors 156, and a cell analyzer 158 (e.g., a flow cytometer). The receiving port 152 can receive a sample or prepared sample from a second module (e.g., sample extraction module 120 or sample preparation module 130), while the delivery port 154 can be used to deliver the sample or prepared sample to another module or container (e.g., waste) after the sample has been analyzed (referred to herein as the analyzed sample).

[0086] The value of each cell analysis parameter can be generated in response to the receipt of a sample or preparation sample by the sample analysis module 150 (e.g., via receiving port 152). For example, receiving port 152 may have a latch or other mechanical element that locks when the sample or preparation sample enters, thereby triggering sensor 156 to begin measuring or detecting one or more cell analysis parameters. In some embodiments, the values ​​can be transmitted as signals to controller 170 via network interface 159. For example, the strength of the signal (e.g., analog signal or electromagnetic wave) may be proportional to the value of the corresponding cell analysis parameter. Cell analysis parameters may relate to cells being cultured or cells in a sample or preparation sample. Cell analysis parameters may include, but are not limited to: cell identity or cell type; cell number; cell purity; cell size; cell potency; cell viability; whether the cell has a marker; the metabolic state of the cell; or the cell's ability to take up or produce substances. For example, in some embodiments, when the parameter involves identification (e.g., cell identity or cell type), a digital code of the cell identity or cell type can be transmitted to controller 170. For example, in some implementations, when the parameters involve information about a heterogeneous population of cells (e.g., different cell types in the cell population, the percentage of each cell type), digital communication can be used to transmit comprehensive information about the cell types in the cell population to the controller 170.

[0087] The sample analysis module 150 may use one or more sensors 156 or a cell analyzer 158 (e.g., a flow cytometer) to detect one or more cell analysis parameters and generate values ​​for said one or more cell analysis parameters. For example, sensor 156 may include a cell density sensor that can capture images of cells to measure cell density and thereby determine the number of cells in a sample or prepared sample having a predefined volume. In some embodiments, the cell analyzer 158 may be or include a flow cytometer configured to dispense buffer into test tubes, microfluidic cartridges, or manifolds containing the sample or prepared sample. For example, the flow cytometer may include a container holding the buffer and releasing a predetermined amount of the buffer into test tubes, microfluidic cartridges, or manifolds positioned to receive said predetermined amount of buffer. The release may occur in response to the flow cytometer being activated or commanded to perform a measurement. Thus, the cell analyzer 158 may allow the buffer to be mixed with the sample, then the sample to be incubated (e.g., for a predetermined time period), and then flow cytometry analysis to be performed. In some implementations, the cell analyzer 158 may be portable (e.g., a portable flow cytometer).

[0088] In addition, the sample analysis module 150 may include a network interface 159 to allow communication with the controller 170 and other modules via a communication network 160. The network interface 159 may share one or more sub-components or functionalities with the network interface 176. The network interface 159 may allow the sample analysis module 150 to transmit signals to other modules (e.g., the controller 170). For example, in response to the sample analysis module 150 generating or preparing a sample, the sample analysis module 150 may transmit signals to the controller 170 to report the values ​​of the cell analysis parameters.

[0089] The communication network 160 may include wired and wireless networks. Examples of wired networks may include personal area networks (PANs), wide area networks (WANs) or local area networks (LANs), client-server networks, and so on. Examples of wireless networks include Wi-Fi and general packet radio service (GPRS) networks, enhanced data GSM environment (EDGE) networks, 802.5 communication networks, code division multiple access (CDMA) networks, Bluetooth networks or long term evolution (LTE) networks, LTE-advanced (LTE-A) networks, or fifth-generation (5G) networks.

[0090] Figure 2 This is a flowchart of an exemplary method 200 for automatically sampling biological cells from a bioreactor for integrated cell analysis and production, according to a non-limiting embodiment of this disclosure. Specifically, Figure 2 The illustration shows how the controller 170 and the integrated cell therapy module 102 (e.g., bioreactor module 110, sample extraction module 120, sample preparation module 130, or sample analysis module 150) perform culturing, sampling, extraction, preparation, and analysis, and use feedback to automatically generate biological cells in real time or near real time, which helps reduce time and inconsistencies and leads to more effective cell therapy.

[0091] like Figure 2The illustrated method 200 can be executed by a microprocessor (e.g., one or more microprocessors 111, 121, 131, or 151) of one or more integrated cell therapy modules in an integrated cell therapy module and by one or more processors 172 of controller 170 based on information received from integrated cell therapy module 102. Furthermore, the processor or microprocessor can execute method 200 based on machine-readable or computer-executable instructions stored in memory (e.g., memory 174). Although the boxes are shown as being executed by one of the integrated cell therapy modules, this disclosure contemplates that the executors can be interchanged, or one or more steps can be performed in parallel, or one or more steps can be performed in a different order than shown in the figures, and method 200 is a continuous process that can have several operations described in the various boxes executed multiple times during operation. As used herein, the term "automatic" refers to a process executed without human intervention. Thus, method 200 can be initiated or executed with respect to various parameters or input products initially set or provided by a human and can end with a human user receiving an output product, but is automatically executed by the identified system to generate the output product from the input product.

[0092] Method 200 may begin at block 210, wherein bioreactor module 110 causes cells to be cultured in a bioreactor. For example, bioreactor module 110 may enable parameter control 112 to activate or control one or more bioreactor parameters (e.g., pH; temperature; level or concentration of components or reagents; or run time) so that cells contained within the container of bioreactor module 110 can grow. Activation or control of one or more bioreactor parameters may be in response to signals received from controller 170 or input by a user.

[0093] In some embodiments, the cells may be obtained from or derived from a subject. The subject may be a human or a non-human animal (e.g., a mouse). In some embodiments, the subject has or is at risk of developing a disease (e.g., cancer). In some embodiments, the cells may be genetically modified to express one or more heterologous genes. Furthermore, in some embodiments, the cells are cultured for use in a therapy (e.g., cell therapy) to treat or prevent a disease. Non-limiting examples of such therapies may include, but are not limited to, autologous cell therapy, allogeneic cell therapy, xenogeneic cell therapy, stem cell therapy, immunotherapy, or combinations thereof. For example, the cells may be cultured for use in immunotherapy, such as chimeric antigen receptor (CAR) therapy, tumor-infiltrating lymphocyte (TIL) therapy, etc. In some embodiments (e.g., where the cells are cultured for use in immunotherapy), the cells may include immune cells (e.g., immune effector cells), T cells, or natural killer (NK) cells. In some embodiments, the cells can be cultured for use in stem cell therapies, such as embryonic stem cell therapy, neural stem cell therapy, mesenchymal stem cell therapy, or hematopoietic stem cell transplantation. Furthermore, the therapy can be differentiated or may include mature cell transplantation.

[0094] At frame 215, sample extraction module 120 extracts a cell sample from bioreactor module 110. For example, microprocessor 121 of sample extraction module 120 may extend actuator 128 of sample extraction module 120 to receiver pump 123, thereby generating or facilitating the uptake of a sample of cells being cultured in bioreactor module 110. In some embodiments, sample extraction module 120 may additionally facilitate the transfer of a cell sample or aliquots of a cell sample to another module (e.g., sample preparation module 130 or sample analysis module 150). For example, a sample dispensing needle 125 may be used to obtain a predetermined amount of extracted cell sample and transfer said amount to one or more of a test tube, microfluidic cartridge, sample manifold, or microtiter plate in sample preparation module 130.

[0095] At box 220, sample preparation module 130 prepares the extracted cell sample to generate a prepared sample. For example, preparing the extracted cell sample may include identifying or registering the cell sample (e.g., by reading a barcode on a test tube, microfluidic cartridge, or sampling manifold or microtiter plate via barcode reader 142), moving the extracted cell sample to staining and incubation station 140 of sample preparation module 130, and staining and incubating the cell sample. This movement may be caused by robotic control 134 of sample preparation module 130, which may be activated, triggered, or commanded based on signals received from controller 170, user input, or detection of an extracted cell sample being received at receiving port 136.

[0096] In some implementations, the sample preparation module 130 may further facilitate the transfer of prepared samples to the sample analysis module 150. For example, after cell sample preparation (e.g., based on a timer detecting the end of incubation (e.g., based on a predetermined duration having occurred)), one or more of a tube moving arm, conveyor, or plate processor may move the prepared sample to the sample analysis module 150, or to the outside of the sample preparation module 130, to facilitate the transfer to the sample analysis module 150.

[0097] At box 225, sample analysis module 150 analyzes parameters (e.g., cell analysis parameters) related to the cultured cells or cells in the sample. In some embodiments, the value of each cell analysis parameter is generated after the sample or prepared sample is received by the sample analysis module (e.g., receive port 252).

[0098] For example, after the microprocessor 151 receives an indication that a sample or prepared sample has been received via the receiving port 152, one or more sensors 156 or cell analyzers 158 can be activated to detect cell analysis parameters of the sample or prepared sample. Cell analysis parameters may relate to cells being cultured or cells in the sample or prepared sample. Cell analysis parameters may include, but are not limited to: cell identity or cell type; cell number; cell purity; cell size; cell potency; cell viability; whether the cells have markers; the metabolic state of the cells; or the ability of the cells to take up or produce substances. For example, in some embodiments, when the parameter relates to identification (e.g., cell identity or cell type), a digital code of the cell identity or cell type is transmitted to the controller. For example, in some embodiments, when the parameter relates to information about a heterogeneous population of cells (e.g., different cell types in the cell population, the percentage of each cell type), digital communication can be used to transmit comprehensive information about the cell types in the cell population to the controller. Therefore, the sample analysis module 150 can use one or more sensors 156 or cell analyzers 158 (e.g., flow cytometers) to detect one or more cell analysis parameters and generate values ​​for said one or more cell analysis parameters.

[0099] In some implementations, a buffer is dispensed into the sample or prepared into the sample to facilitate detection. The cell analyzer 158 may allow the buffer to be mixed with the sample, then the sample to be incubated (e.g., for a predetermined time period), and then flow cytometry analysis is performed. Flow cytometry analysis can result in values ​​for various cell analysis parameters, such as cell identity or cell type, cell number, cell purity, cell size, cell viability, etc.

[0100] At block 230, sample analysis module 150 transmits signals of analyzed parameters to controller 170. In some embodiments, the signal includes values ​​of cell analysis parameters, or may include composite values ​​or sets of values ​​of a set of cell analysis parameters. In some embodiments, the signal may include a digital signal containing cell analysis parameters, which may be transmitted to controller 170 via communication network 160. In some embodiments, the signal may include an analog signal (e.g., electromagnetic wave) wirelessly transmitted to controller 170. For example, the strength of the signal (e.g., the amplitude of the analog signal or electromagnetic wave) may be proportional to the value of the corresponding cell analysis parameter. The signal may be transmitted via communication network 160.

[0101] In various embodiments, at block 260, sample analysis module 150 disposes of the prepared sample in response to a signal transmitting the parameters to be analyzed. Depending on the steps used to prepare the extracted cell sample, the contamination procedure specified for bioreactor module 110, the ease of returning the extracted cell sample from the plate or other analytical reservoir, and combinations thereof, the analyzed sample may be discarded (e.g., discarded into a waste disposal reservoir) or returned to the bioreactor module.

[0102] At block 235, once a signal is received from sample analysis module 150, controller 170 processes the signal to determine a response to cell culture. For example, the response may relate to the end goal of cell culture occurring in bioreactor module 110. In some embodiments, the end goal may be selected at controller 170, which may result in a desired or ideal set of bioreactor parameter values. However, the values ​​received from cell analysis parameters may require adjustment of one or more preset bioreactor parameter values. Therefore, the determined response may be modulated into a signal (e.g., a second signal) and transmitted back to one or more integrated cell therapy modules (e.g., bioreactor module 110).

[0103] In various implementations, controller 170 determines to change a parameter in response to the value of an associated cell analysis parameter falling outside a window of acceptable values, and identifies one or more actions taken by bioreactor module 110 to bring the value back into the window. Alternatively, controller 170 may determine to change the parameter in response to an identified trend in which the value of the parameter is expected to place the value outside the window (or its range) before the next predetermined sampling. For example, a parameter that is within the window at times t1 and t2 and is expected to be outside the window at time t3 may cause controller 170 to generate a signal at time t2 (or before time t3) to change the parameter before the value reaches outside the window at time t3.

[0104] The controller 170 and the integrated cell therapy module 102 can use various scheduling and monitoring or triggering schemes to determine whether any signal has been received or whether a signal is ready for transmission.

[0105] At box 240, controller 170 transmits a second signal of control signals to integrated cell therapy module (e.g., bioreactor module 110) via communication network 160.

[0106] At box 245, bioreactor module 110 receives a second signal and determines whether the second signal indicates a change in various parameters of the cell culture. The second signal may be processed to determine whether the response involves changing or not changing (and thus maintaining) any one or more bioreactor parameters. Bioreactor parameters may include, but are not limited to, pH; temperature; levels or concentrations of components or reagents (e.g., O2, CO2, amino acids, proteins, nutrients, drugs, hormones, or culture media); or the run time of the cell culture process. When bioreactor module 110 is signaled to modify parameters, bioreactor module 110 may draw culture media or other consumable materials from various tanks, hoppers, or dispensers to promote or inhibit cell growth; activate or deactivate temperature control equipment (e.g., heating elements, cooling pipes, fans); and so on.

[0107] If the response is to maintain the bioreactor parameters, or if it is found that no change is necessary, method 200 proceeds to block 250, whereby bioreactor module 110 maintains the bioreactor parameters accordingly. In various embodiments, when the bioreactor parameters include ongoing supply, flow rate, or mechanical settings (e.g., fans or agitators), maintaining the bioreactor parameters includes maintaining the operation of equipment affecting the supply, flow rate, or mechanical settings at the current settings (e.g., continuing to supply reagents at the current flow rate, continuing to agitate samples at the current revolutions per minute).

[0108] If the response is to change the bioreactor parameters, method 200 proceeds to block 255, whereby bioreactor module 110 accordingly changes the bioreactor parameters (e.g., via parameter control 112). In various embodiments, the degree of change is based on the difference between the measured value and the window of cell growth analysis parameters, such that a larger difference leads to a more drastic change than a smaller difference, bringing the parameters back into the window. Changes may include the addition of acids, bases, buffer media, therapeutic agents, water, O2, CO2, and various growth media, which can be introduced into bioreactor module 110 from various tanks maintained by the system. Alternatively or additionally, bioreactor module 110 may activate or deactivate various fans, cooling elements, heating elements, agitators, etc., to change the temperature, atmosphere, or exposed surface of the cells being cultured, thereby changing the bioreactor parameters, or terminate the modification of the values ​​once values ​​previously outside the window have been brought back into the window.

[0109] Following box 250 or box 255, bioreactor module 110 continues to culture cells at box 265 and may repeat one or more steps of method 200. Accordingly, method 200 may be performed in several iterations, in which one of box 250 or box 255 is performed to adjust the cell culture without human intervention, but wherein the system automatically adjusts or maintains parameters for a certain period of time according to the desired growth parameters. In various embodiments, the duration of performing method 200 may last for one day, two days, three days, four days, five days, six days, seven days, etc., wherein various samples are extracted and examined at various sampling rates, which may include sampling for analysis at predetermined intervals (e.g., at least once every 30 minutes, one hour, two hours, three hours, six hours, twelve hours, twenty-four hours, thirty-six hours, forty-eight hours, seventy-two hours, eighty-four hours, ninety-six hours, one hundred and twenty hours, one hundred and forty-four hours, or one hundred and sixty-eight hours) or in response to triggering conditions (e.g., values ​​of different cell analysis parameters or environmental conditions). Therefore, during cell culture, the time intervals between consecutive sampling may be equal or different, and the analysis rates for different cell analysis parameters may also be the same or different.

[0110] Figure 3 This is a flowchart of an exemplary method 300 for automatically managing the growth and culture of cell samples for research, treatment, or prevention, according to embodiments of the present disclosure.

[0111] Method 300 begins at block 310, wherein an operator extracts a cell sample from a biological subject. In various embodiments, the cell sample may be extracted from the biological subject as a tissue, blood, or body fluid sample, which may be intended to be returned to the same biological subject from which the cell sample was extracted or to a different biological subject after growth and culture. In various embodiments, the operator may filter or select a subset of cells extracted from the biological subject to constitute the cell sample (e.g., to exclude unwanted cells or culture medium).

[0112] At frame 320, an operator inserts a cell sample into the bioreactor (e.g., bioreactor module 110). In various embodiments, the operator may place the cells into various containers or holding dishes for insertion into the bioreactor; or the cell sample may be provided to a port or actuator-platform assembly that receives the cell sample from the operator and automatically transfers it to the culture chamber of the bioreactor. In various embodiments, the cell sample may be placed into various sample holding dishes that can be held in the sample holding dish for the duration of growth / culture, including but not limited to: test tubes, wells of microtiter plates, microfluidic boxes, fluid manifolds, etc.

[0113] At box 330, the bioreactor automatically grows and culturees cells from a cell sample. This process is automated and requires no further input from the operator after receiving the cell sample until the cultured cell sample is returned to the operator. Accordingly, the system can operate based on instructions received before a first time and grow / culture the cell sample until a second time, provided no further instructions are received from the operator between the first and second time points. Various conveyors, robotic arms, pumps, syringes, etc., can be used to automatically move some or all of the cell sample between the various modules of the system, which are programmed to adjust growth conditions by changing one or more parameters (e.g., adding growth medium / buffer / therapeutic agent, changing temperature / humidity / atmospheric conditions, agitating the cell sample, etc.). These instructions can include time-scheduled or trigger-based operations to perform various actions at specified times or in response to sensors identifying specific parameters in the cell sample or growth environment.

[0114] Automated operation of bioreactors allows the system to be shut down—thereby reducing the likelihood of introducing human error, improving environmental control for cell growth / culture, reducing escape of controlled atmosphere, reducing the risk of external contamination, reducing cleaning requirements during or after operation, extending operation time beyond the period when human operators can monitor the system, and other benefits.

[0115] At box 335, it can be referenced regarding Figure 2 The discussed method 200 is understood to be a bioreactor that automatically controls the culture of cell samples during the duration of growth and culture operations within frame 330. The system monitors cell growth in the bioreactor to set or maintain growth conditions for the desired output from the cell samples. In various embodiments, the system maintains various cell parameters within predefined ranges of values ​​during cell growth / culture, and these parameters can be adjusted by changing environmental conditions within the bioreactor, adding various reagents to the cell samples, agitating the cell samples, etc., to maintain or bring the parameters back within the specified range. In various embodiments, the range may remain static for the duration of culture or may be changed during culture according to a predefined cell growth / culture pattern.

[0116] Between the first and second time points, frame 335 can be continuously executed for the duration of cell growth and modification, acquiring various readings of cell growth parameters at the midpoint between the first and second time points to determine how to adjust or maintain cell growth within the desired window. The bioreactor can remain independent during this period and operate automatically based on instructions specifically received prior to the first time point. Therefore, operators can follow these instructions to operate the system without requiring any further action from the operator until the cultured / modified cells are ready to be harvested.

[0117] At box 340, the operator retrieves cultured / modified cells from the bioreactor. Depending on the intended use of the cultured / modified cells, method 300 may end at box 340, and the operator may discard the cultured / modified cells, perform further experiments or assays on the sample outside the bioreactor, or return some or all of the sample to the bioreactor for continued automated culture or modification or alternative automated culture or modification.

[0118] In various embodiments, the growth and culture of cell samples may be part of immunophenotyping assays, cell activation and proliferation assays, immune cell-induced cell lysis assays, cell metabolism assays, cytokine measurements, etc. In some embodiments, the growth and culture of cell samples are used as precursors for the treatment or prevention of a disease in a biological subject, wherein the treatment or prevention uses a cell culture grown and / or modified from the cell sample as a therapeutically effective dose. These grown / modified cells may include: cells genetically altered to express one or more heterologous genes; cells cultured for immunotherapy; and cells cultured for stem cell therapy. When the sample is to be used for therapeutic treatment, method 300 may proceed to block 350.

[0119] At box 350, an operator supplies cultured / modified cells to a biological subject for the treatment or prevention of a disease that is treatable, preventable, or manageable (or therefore experimentally supplied) through the application of the cell culture. In various embodiments, the operator may mix the cells with various buffers, delivery media, contrast agents, additional therapeutic agents, etc., before delivering the cells to the biological subject. The biological subject may be the same biological subject from whom the cell sample was initially extracted (according to box 310), or may be different subjects. This disclosure is intended to enable those skilled in the art to determine a dose constituting a therapeutically effective dose, which may be influenced by the biological subject's age, weight, sex, genetics, metabolism, comorbidities, tolerance, additional therapeutic agents in the system, and combinations thereof. Method 300 can then conclude.

[0120] Figure 4An exemplary method setup for automatically sampling biological cells from a bioreactor for integrated cell analysis and production is illustrated, where test tubes are used as cell sample containers. Test tubes 420 are moved through various integrated cell therapy modules 202 and used for flow cytometry assays (e.g., immunophenotyping assays). While flow cytometry is used as an illustrative example of an assay, other cell-based assays can also be performed (e.g., cell activation and proliferation assays, immune cell-induced cell lysis assays, cell metabolism assays, cytokine measurements). Similarly, while test tube-based methods can be used, microfluidic cartridges or manifolds can also be used in offline integrated cell therapy systems, online integrated flow cytometers, online microfluidic chip-based flow cytometers, and combinations thereof. For some assays, sample cells from the test tube can be transferred to the wells of a microtiter plate. For such assays, additional sample handling and / or processing may be required for appropriate cell-based assays.

[0121] like Figure 4 As shown, pump 410 can be used to extract cell samples from bioreactor module 110. In some embodiments, bioreactor module 110 premixes the sample before pumping out a specified volume of sample. The cell sample may fill sample dispensing needle 125, which is used to place the cell sample into test tube 420. In some embodiments, sample pump 410 or sample dispensing needle 125 is designed to accurately and efficiently dispense a specified volume of sample from bioreactor module 110. In some embodiments, sample dispensing needle 125 allows movement in the Cartesian coordinate system (x, y, and z) and can be used to puncture test tube 420. In some embodiments, test tube 420 is pre-loaded with reagents (e.g., lyophilized antibody mixture) to facilitate flow cytometry assays.

[0122] At a specified time, the robotic arm 430 (e.g., controlled via the robotic arm control 134 of the sample preparation module 130) can move the test tube 420 from a predefined (e.g., dedicated) test tube location (where antibody information is defined), causing the barcode reader 440 to read the barcode from the test tube 420 and transfer the test tube 420 to a sample dispensing location (e.g., a dedicated location that matches the sample dispensing probe location of the bioreactor module 110).

[0123] Additionally, the robotic arm 430 moves the test tube 420 to the sample preparation module 450 (e.g., the staining and culture station of the bioreactor module 110). At the sample preparation module 450, a specific volume of staining buffer is dispensed into the test tube 420, thereby allowing the sample to incubate. In some embodiments, gentle agitation may be used to promote incubation.

[0124] After a specified incubation time, the robotic arm 430 moves the test tube 420 into the flow cytometer 460 to allow for flow cytometry measurements. The type of flow cytometer used in this example is specifically selected to have a smaller footprint or a more compact form compared to other cell analyzers. In some embodiments, flow cytometry software performs automated analysis of the acquired flow cytometry measurement data. Optionally, the analysis results can be automatically transmitted as feedback to bioreactor software (e.g., integrated application 184 of controller 170), which can provide real-time control, modification, or adjustment of cell culture conditions (e.g., bioreactor parameters). In some embodiments, the robotic arm 430 for test tube movement, the sample staining station, and the barcode reader are integrated into a single software control system (e.g., controller 170).

[0125] Integrated software (e.g., integrated application 184) is used to control workflows, edit work plans, and receive and forward feedback from analyzed flow cytometry data (e.g., CD3% and count, CART cell % and count, etc.) to bioreactor module 110. Bioreactor module 110 can modify various bioreactor parameters (e.g., cell culture controls) to adjust culture conditions based on results measured from flow cytometer 460.

[0126] The advantages of this exemplary system and process include, but are not limited to: the existence of a closed system for integrating cell therapy and a simplified workflow; data traceability obtained by optionally barcode reading of the barcode on the test tube 420; single sampling via a single test tube 420; and a cleaner architecture resulting from the elimination of the need to rinse or clean fluid paths.

[0127] Although Figure 4 One method setup is illustrated, but this disclosure envisions that the methodologies described herein can be implemented with various hardware to analyze a variety of cell properties.

[0128] Figure 5 A computing device 500 according to an embodiment of the present disclosure is illustrated, which can be used as a local control device for a controller 170 or module. The computing device 500 may include at least one processor 510, a memory 520, and a communication interface 530.

[0129] Processor 510 can be any processing unit capable of performing the operations and programs described in this disclosure. In various embodiments, processor 510 can represent a single processor, multiple processors, a processor with multiple cores, and combinations thereof.

[0130] Memory 520 can be a device that is either volatile or non-volatile memory, and may include RAM, flash memory, cache, disk drives, and other computer-readable storage devices. Although shown as a single entity, memory 520 can be divided into different memory storage elements, such as RAM and one or more hard disk drives. As used herein, memory 520 is an example of a device that includes computer-readable storage media and should not be construed as a transmission medium or the signal itself.

[0131] As shown in the figure, memory 520 includes various instructions executable by processor 510 to provide operating system 522 to manage various features of computing device 500, and one or more programs 524 to provide various functionalities to users of computing device 500, including one or more of the features and functionalities described in this disclosure. Those skilled in the art will recognize that different approaches can be taken in selecting or designing programs 524 for performing the operations described herein, including selecting a programming language, the operating system 522 used by computing device 500, and the architecture of processor 510 and memory 520. Accordingly, those skilled in the art will be able to select or design suitable programs 524 based on the details provided in this disclosure.

[0132] Communication interface 530 facilitates communication between computing device 500 and other devices, which may also be as described above. Figure 5 The computing device 500 is described above. In various embodiments, the communication interface 530 includes an antenna for wireless communication and various wired communication ports. The computing device 500 may also include the communication interface 530, one or more input devices (e.g., keyboard, mouse, pen, touch input device, etc.) and one or more output devices (e.g., display, speaker, printer, etc.), or communicate via these devices.

[0133] Despite Figure 5 Although not explicitly shown, it should be understood that computing device 500 can be connected to one or more public or private networks via communication interface 530 through a suitable network connection. It should also be understood that software instructions can be loaded into memory 520 from a suitable storage medium or via wired or wireless means.

[0134] Accordingly, computing device 500 is an example of a system including processor 510 and memory 520, the memory containing instructions that, when executed by processor 510, perform various embodiments of the present disclosure. Similarly, memory 520 is an apparatus containing instructions that, when executed by processor 510, perform various embodiments of the present disclosure.

[0135] Figures 6A to 6LCellular analysis parameters of CAR-T cells produced in a G-REX® 24-well bioreactor device (available from Wilson Wolf Corp.) according to embodiments of this disclosure are shown. The data indicate that CAR-T cell characteristics, such as cell number, cell potency, cell type composition, cellular ATP production rate, and / or cellular reserve respiration capacity, change as CAR-T cells are cultured and manufactured in the bioreactor, illustrating the need for integrated cellular analysis of cells sampled from the bioreactor to guide cell culture time and achieve high cell quality.

[0136] Figure 6A The diagram shows the fold change in cell number on days 6, 8, and 10 relative to day 0 when cells were introduced into the G-REX 24-well apparatus. Cells were introduced at a density of 0.33 × 10⁻⁶. 6 cells / ml (i.e., 1.36 × 10⁻⁶ cells / ml) 6 cells / cm 2 Cells were cultured at a volume density of 5% human serum and 200 U / ml IL2 in XVIVO 15 medium (after overnight incubation in IL2-free medium). UT refers to untransduced CAR samples, and CAR-T refers to EMCAM CAR-transduced samples, where CAR transduction occurred on day 1. Cells expanded well in the Grex 24-well bioreactor apparatus, reaching 19.2-fold increase in untransduced T cells (UT) and 17.1-fold increase in EpCAM CAR-transduced T cells (CAR-T) by day 10.

[0137] Figure 6B The changes in the percentage of CD3+ and CAR+ cells during cell culture in a G-REX 24-well bioreactor device are shown. During the cell culture process, the percentage of EpCAM CAR-positive and CD3-positive cells changed, reaching 15% on day 6 and gradually decreasing to 9.5% on day 10.

[0138] Figure 6C The changes in the percentage of CD3+ cells in the total cell population during cell culture are shown, as well as the changes in the percentages of CD4+ and CD8+ cells within the CD3+ population. The CD4 / CD8 ratio changes over time. As cell production progresses, the percentage of CD8+ cells increases, while correspondingly, the percentage of CD4+ cells decreases.

[0139] Figure 6DThe percentage changes of different T cell subtypes within the total cell population are shown. Tn: naive T cells, Tcm: central memory T cells, Tscm: stem cell-like central memory T cells, Tem: effector memory T cells, Temra: terminally differentiated effector memory T cells. As cell culture progressed, more fully differentiated effector cells (Temra) and effector memory T cells (Tem) appeared. Meanwhile, the percentage of central memory cells (Tcm) decreased over time.

[0140] Figure 6E This diagram shows the time course of T47D cell lysis percentage killed by CAR-T cells harvested on day 6 of cell culture in a G-REX 24-well apparatus. The E:T ratio (i.e., effector cell to target cell ratio) here is calculated based on total effector cells, which include CAR T cells and untransduced cells. UT refers to the untransduced control sample, and CAR refers to the EpCAM CAR-transduced cell sample.

[0141] Figure 6F The time course of the percentage of T47D cells killed by CAR-T cells harvested on day 8 of cell culture in a G-REX 24-well apparatus is shown. The E:T ratio here is calculated based on total effector cells, which include both CAR T cells and untransduced cells.

[0142] Figure 6G The time course of the percentage of T47D cells killed by CAR-T cells harvested on day 10 of cell culture in a G-REX 24-well apparatus is shown. The E:T ratio here is calculated based on total effector cells, which include both CAR T cells and untransduced cells.

[0143] Figure 6H The cell potency parameter KT50—the time required to reach 50% cell lysis based on a time-major curve of cell lysis % for EpCAMCAR T cells harvested on days 6, 8, and 10—is shown. The E:T ratio here is calculated based on total effector cells, which include CAR T cells and untransduced cells. The cytotoxic potency of EpCAM CAR T cells gradually decreases from day 6 to day 10, as evidenced by the increased KT50 value in samples with an E:T ratio of 4:1.

[0144] Figure 6IThe slope of the cell potency parameter—the slope of the time-varying percentage of cell lysis for EpCAMCar T cells harvested on days 6, 8, and 10—is shown. The E:T ratio here is calculated based on total effector cells, which include CAR T cells and untransduced cells. The cytotoxic potency of EpCAM CART cells gradually decreased from day 6 to day 10, as evidenced by the decreasing slope in the sample with an E:T ratio of 4:1.

[0145] Figure 6J The AUC of cell lysis % is shown as the area under the curve (0 h to 48 h) of the cell lysis % time progression curve for EpCAM CAR T cells harvested on days 6, 8, and 10. Here, the E:T ratio is calculated based on total effector cells, which include CAR T cells and untransduced cells. The cytotoxic efficacy of EpCAM CAR T cells gradually decreases from day 6 to day 10, as evidenced by the decrease in the 48-hour AUC of the cell lysis % curve for the sample with an E:T ratio of 4:1.

[0146] Figure 6K The ATP production rate of CAR T cells at days 6, 8, and 10 when cultured in a G-REX 24-well apparatus is shown. The ATP production rate of CAR T cells was measured using an XF assay and gradually decreased over time. Furthermore, CAR T cells produced in the G-REX apparatus exhibited greater mitochondrial bioenergy than glycolytic cells.

[0147] Figure 6L The standby respiratory capacity of CAR T cells is shown on days 6, 8, and 10 when CAR T cells are cultured in G-Rex 24-well apparatus. The standby respiratory capacity of CAR T cells was measured in an XF assay and gradually decreased over time.

[0148] Figures 7A to 7F Cellular analysis parameters of T cells cultured in a G-REX 24-well apparatus in the presence of different cytokines (IL2, IL7, or IL15) according to embodiments of the present disclosure are shown. The data indicate that T cells possess different characteristics, such as cell potency, cellular ATP production rate, and cellular reserve respiration capacity, which depend on the presence of cytokines in the cell culture medium. This suggests that the selection or alteration of cell culture medium conditions can allow for the control or improvement of cell quality based on the measured cellular analysis parameters.

[0149] Figure 7AThis diagram illustrates the time progression of the percentage of cell lysis of T-47D cells killed by T cells via a BITE-mediated binding mechanism, harvested on day 7 of cell culture in a G-REX 24-well apparatus, in the presence of different cytokines IL-2, IL-7, or IL-15. The seeding density of T47D target cells was 8,000 cells / well, and effector cells were added at a 6:1 effector-to-target cell ratio 24–40 hours post-seeding for potency assays. CD3xEpCAMBiTE concentration: 500 ng / ml. T cells expanded in the presence of IL-15 showed a higher percentage of cell lysis (higher killing potency) against the target T47D (EpCAM-positive cancer cell line) compared to T cells expanded in the presence of IL-2 and IL-7.

[0150] Figure 7B This diagram illustrates the time progression of the percentage of cell lysis of T-47D cells killed by T cells via a BITE-mediated binding mechanism, harvested on day 10 of cell culture in a G-REX 24-well apparatus, in the presence of different cytokines IL-2, IL-7, or IL-15. The seeding density of T47D target cells was 8,000 cells / well, and effector cells were added at a 6:1 effector-to-target cell ratio 24–40 hours post-seeding for efficacy assays. CD3xEpCAMBiTE concentration: 500 ng / ml. T cells expanded in the presence of IL-15 showed a higher percentage of cell lysis (higher killing efficacy) against the target T47D (EpCAM-positive cancer cell line) compared to T cells expanded in the presence of IL-2 and IL-7.

[0151] Figure 7C The ATP production rate of T cells on day 7 is shown when cultured in a G-REX 24-well apparatus in the presence of IL-2, IL-7, or IL-15. T cells expanded in the presence of IL-15 exhibited a higher ATP production rate compared to T cells expanded in the presence of IL-2 and IL-7.

[0152] Figure 7D The study shows the reserve respiratory capacity of T cells on day 7 when cultured in a G-REX 24-well apparatus in the presence of IL-2, IL-7, or IL-15. T cells expanded in the presence of IL-15 exhibited a higher reserve respiratory capacity compared to T cells expanded in the presence of IL-2 and IL-7.

[0153] Figure 7EThe ATP production rate of T cells on day 10 is shown when cultured in a G-REX 24-well apparatus in the presence of IL-2, IL-7, or IL-15. T cells expanded in the presence of IL-15 showed a higher ATP production rate compared to T cells expanded in the presence of IL-2 and IL-7.

[0154] Figure 7F The reserve respiratory capacity of T cells on day 10 when cultured in a G-REX 24-well apparatus in the presence of IL-2, IL-7, or IL-15 is shown. T cells expanded in the presence of IL-7 exhibited a higher reserve respiratory capacity compared to T cells expanded in the presence of IL-2 and IL-15.

[0155] According to the method described in this paper, its parameters were prepared, cultured, and analyzed. Figures 6A to 6L and Figures 7A to 7F The cells shown are illustrated. It should be understood that the experimental procedures described herein involve the use of live cells.

[0156] In the preparation of starting materials, the first step is performed the day before cell production or expansion by thawing CD3-enriched (i.e., CD4+ and CD8+ positively selected) PBMC samples (i.e., peripheral blood mononuclear cells). This can be achieved by removing the cell vials from a -150°C freezer and thawing them in a water bath (e.g., for 2 minutes) until only small ice particles remain.

[0157] In the second step, an operator or robot uses aseptic techniques and a pipette to gently transfer the cell suspension from the frozen vial into a 50 mL centrifuge tube. The operator or robot can then add thawed culture medium to the cell suspension at a 1:20 dilution.

[0158] In the third step, the operator or robot adds 5 mL of warm thawed culture medium to the amplification medium at a rate of approximately one drop every 10 seconds, without using growth factors (such as IL2), and occasionally vortexes. The operator or robot then mixes the volume of each cell suspension with the remaining warm thawed culture medium dropwise at a final dilution of 1:20.

[0159] In the fourth step, the cells were centrifuged at 250G (250 times the force of gravity) for ten minutes at room temperature (RT).

[0160] In the fifth step, the operator or robot incubates the cells at 2-5 × 10⁻⁵ mg / L in an incubator at 37°C and 5% CO₂. 6 Cells / ml were resuspended in thawed medium and incubated overnight.

[0161] In CAR-T cell production (or T cell expansion), the first step is performed on day zero: the immune cells prepared in the above preparation steps are centrifuged at 400G (400 times the force of gravity) for eight minutes, and then centrifuged at 0.5-1×10⁻⁶. 6 Cells / ml were resuspended in activation medium (i.e., amplification medium supplemented with activation solutions (such as CD3 and CD28)).

[0162] In the second operation, on the first day of CAR-T cell production (e.g., targeting...) Figures 6A to 6L (Data from the data): Immune cells activated by lentivirus transduction carrying a CAR construct for one day. In the second operation, on the first day of T cell expansion (e.g., targeting...) Figures 7A to 7F (Data in the text): Replace the activation medium with the amplification medium (100% medium replacement).

[0163] In the third operation, on the second day, a 100% medium replacement is performed by replacing the inoculation medium with preheated amplification medium.

[0164] In the fourth step, depending on the cell culture dish used in the amplification, the culture medium is changed every 2-3 days.

[0165] In order to collect cell samples during the process, on a designated date during amplification / production, samples of generated CART cells or amplified T cells are taken from the G-REX 24-well device for in-process analysis.

[0166] In order to perform cell counting, in the first operation, the cells are thoroughly mixed by blowing the cell suspension up and down three times in the G-REX 24-well device.

[0167] In the second step, the required amount of cell suspension is collected from the G-REX 24-well device using a pipette or serum pipette.

[0168] In the third step, 10 µL of cell sample was mixed with 90 µL of cell staining buffer containing 1 µL of 7AAD (cell viability dye) and incubated for five minutes. Cell counts were then performed using a flow cytometer system (e.g., NOVOCYTE® QUANTEON® from Agilent Technologies, Inc.), and the total number of cells and the total number of viable cells were recorded.

[0169] To aliquot cells for subsequent analysis, in the first step, the required volume of cultured CART cells or expanded T cells for each assay is aliquoted, and the volume of the cell suspension is calculated using the following equation based on the concentration of the cell suspension (total cells or viable cells), the seeding density for each assay (cells / well), and the number of replicates (N): Cell volume (ml) = seeding density × N / cell suspension concentration (cell number / ml).

[0170] For XCELLIGENCE functional efficacy assays, live cell concentrations are used. For XF bioenergetics assays, total cell concentrations are used. For immunophenotyping using flow cytometry, live cell concentrations are used.

[0171] In the second step, the cell suspension was centrifuged at 250G for five minutes.

[0172] In the third step, the cells are resuspended in the appropriate buffer solution used in each subsequent assay.

[0173] For XCELLIGENCE functional efficacy determination, as shown in the figure, functional efficacy / killing power is determined using an Agilent XCELLIGENCE RTCA MP or ESIGHT instrument, but other laboratory instruments may be used in various implementation methods.

[0174] In the functional power assay, target cells are prepared one day prior to the assay. In the first step of target cell preparation, 50 µL of preheated power assay medium (e.g., RPMI 1640 containing 10% FBS) is added to the wells of an E-plate, followed by plate background measurement on an RTCA system. In the second step, adherent target cancer cells expressing CAR antigens against antigens recognized by bispecific T-cell engagers (BiTEs) are isolated from cell culture dishes. In this example, EpCAM antigen expressing T-47D is used. In the third step, 50 µL of cell suspension is added at an optimal seeding density to each well of an E-plate containing 50 µL of assay medium, for example, a seeding density of 8,000 cells / well for T-47D cells. In the fourth step, the cell plate is placed in a laminar flow hood at room temperature for 30 minutes to allow for uniform cell distribution in the wells. In the fifth step, the cell plate is attached to the RTCA station, and data recording begins at 15-minute intervals throughout the experiment. In the sixth operation, data acquisition is paused when immune cells are added to the target cell plate.

[0175] When preparing effector cells on the day of the assay, in the first step, immune cells are collected and counted as previously described.

[0176] In the second operation, data were collected in a 100 μL volume according to different effector cell to target cell (E:T) ratios (e.g., 8:1, 4:1, 2:1, and 1:1, where the E:T ratio was based on total cells, including both CAR-T cells and untransduced cells). The data are shown in... Figures 6A to 6L(Includes) the number of immune cells to be added. Several E:T ratios are recommended, including high, medium, and low E:T ratios. The E:T ratio here is calculated based on 100% CAR-T cells. For BiTE cytotoxicity assays (data in...), please refer to... Figures 7A to 7F As shown in the figure, a certain concentration of BiTE (e.g., 500 ng / ml CD3XEpCAM BiTE) is added to the immune cells before the effector cells are added to the target cell plate.

[0177] In the third step, based on the plate layout diagram, set up a control with only effector cells, a control with target cells plus simulated effector cells or a control with target cells plus untransduced T cells, a control with only target cells, and a complete lysis control (target cells treated with a final concentration of 0.25% Triton X-100). Each condition should have at least five parallel assays. Users can modify the plate layout according to their experimental design. However, including the correct controls and sufficient parallel assays for each sample and control on the same plate is crucial for the correct interpretation of data and obtaining reliable power data.

[0178] In the fourth step, after adding effector cells, the E-plate is returned to the RTCA station, and real-time recordings are immediately resumed at 15-minute intervals for up to two days. The duration of power assays may vary depending on the purpose of the power test. For cell product QC, 6–24 hours is recommended. For process development, 48–72 hours is recommended.

[0179] Immediately after seeding target cells in E plates (e.g., within 30 seconds), real-time impedance measurements are initiated. However, changes in impedance are reported as the cell index (CI). The CI is further normalized to the time point exactly prior to the addition of CAR T cells, and is termed the normalized cell index (NCI).

[0180] In various implementations, the key parameters used include, but are not limited to: 1) Percentage of cell lysis (Cell lysis %): used to determine the level of immune cell-mediated killing. Percentage of cell lysis is obtained using the normalized cell index (NCI) from the sample and the average normalized cell index (NCIt) from the target-only control, according to the following equation: Cell lysis % = [1 - NCI / NCIt] * 100; 2) Area Under the Curve (AUC): used to convert real-time kinetic data into an endpoint reading. The AUC of cell lysis % is the area under the curve over a time course from the normalized time point corresponding to the time when the effector was added to the target cells to the selected time point on the curve. The larger the AUC of cell lysis %, the more effective the effector; 3) KT: used to determine the rate of immune cell-mediated cell killing. KT is measured as the killing time and is calculated from the normalized time point corresponding to the time when the effector and other relevant conditions were added to the sample. RTCA Pro software offers options for KT values ​​of 20%, 40%, 50%, 60%, and 80% cell lysis; and 4) Slope: used to describe the steepness, inclination, gradient, or rate of change of the curve within a given time window. For each selected well, the software calculates the slope of the cell index (or normalized cell index) curve within the selected time range. Data points within this time range are fitted to a straight line.

[0181] In XF assays, samples collected from the amplification system (at least 1-2 × 10⁻⁶ samples per sample) 6Centrifuge (10 min × 1000 g) in the first operation and resuspend the cells in an appropriate volume of assay medium (e.g., XF RPMI assay medium, pH 7.4, containing 10 mM glucose, 1 mM pyruvate, and 2 mM glutamine) to achieve the recommended cell density for the analyzed cell type (e.g., 2 million total cells / mL for pre-activated T cells). Add a sample of the cell suspension (typically 50 µL) to an equal volume of buffer containing the active dye 7-AAD (2X), and count the total and viable cells in the sample using a NOVOCYTE flow cytometer. If the cell density is higher or lower than 60% of the recommended density, adjust the cell suspension volume to achieve the desired cell density range, and count the cells again to confirm the final cell density. Seed a sample of cell suspension (typically 50 µL) into pre-coated PDL-coated XF96 multiwell plates and preheat overnight at 37°C (typically 3 or more parallel assay wells per cell sample). Centrifuge the multiwell plates (e.g., at 100 G for one minute), add assay medium to complete the recommended volume for the specific plate type (e.g., 200 µL), and incubate at 37°C in a non-CO2 incubator for 45 minutes.

[0182] In the second step of the XF assay, the appropriate XF SEAHORSE analyzer is programmed using command instructions to perform (e.g., three measurements, by sequentially injecting the solution from a port in a box positioned above the cell sample in the well, and performing three measurements after each injection).

[0183] In the third step of the XF assay, the following working solutions of metabolic regulators are prepared: Oligomycin A stock solution is prepared to a working concentration of 13.5 µM in the assay medium. BAM15 stock solution is prepared at an optimized concentration (typically 25 µM for human T cells), and rotenone plus antimycin A mixed stock solution is prepared to a working concentration of 5.5 µM for each.

[0184] In the fourth step of the XF assay, a sufficient volume of working solution for each modulator is added to the assay cartridge to dilute the working solution into the assay medium upon injection, reaching the final desired concentration. For example, in human T cells, the final desired concentration is a mixture of 1.5 µM oligomycin A, 2.5 µM BAM15, and 0.5 µM rotenone plus antimycin A. These concentrations are determined by titration to obtain optimal efficacy.

[0185] In the fifth step of the XF assay, the hydration assay kit containing the specified reagent is loaded into the instrument.

[0186] Figure 8 , Figure 9 , Figure 10 , Figures 11A to 11C and Figures 12A to 12C This disclosure provides experimental validation of the concepts presented herein and demonstrates the remarkable efficacy of the techniques and methods discussed herein. This disclosure envisions that, within the spirit and scope of the concepts discussed herein, modified experimental settings can be used to substantially replicate the general results discussed in the examples herein, demonstrating that low-quality cell samples can be used to manufacture high-quality therapeutic cells.

[0187] Chimeric antigen receptor (CAR) T-cell immunotherapy has shown tremendous potential in treating cancer and other diseases; however, many challenges remain, including costly manufacturing processes, short-term cell persistence, lengthy manufacturing processes, and poor cell expansion. These problems exist in both allogeneic (also known as heterologous) and autologous therapies (where the base cells are provided from different or the same biological subject, and the manufactured cells are provided to said biological subject), but are particularly pronounced in autologous therapies. While autologous therapies reduce the risk of immune rejection of the manufactured cells, the quality of the starting cells used for the production of therapeutic cells varies depending on the individual patient's health condition. Therefore, clinicians may assess a patient's health before extracting cells as the basis for autologous therapies, thus delaying treatment until the patient's health reaches a certain threshold, and if the patient does not exhibit the threshold health criteria, treatment via allogeneic therapy may be postponed. Therefore, current CAR-T product manufacturing processes involve ex vivo expansion of T cells to obtain a sufficient number of viable T cells to be infused into the patient from whom the base cells used for manufacturing are extracted. This approach is also applied to allogeneic cell therapy, rather than being limited to autologous homologous cell therapy. While this disclosure provides examples primarily concerning autologous homologous methods, it also envisions that even if the starting cells used in the manufacture of a given allogeneic cell therapy are derived from healthy donors and meet the standards for product production, variability still exists between donors, and this disclosure can be advantageously used for allogeneic treatment.

[0188] Therefore, using the same cell culture conditions to expand autologous adoptive cell therapy may not be the most efficient method for producing immune cells with high efficacy and good durability. Furthermore, aside from cell number, medical institutions (such as the U.S. Food and Drug Administration (FDA)) have not yet defined what constitutes "high efficacy" or "good durability" in any standard, thus leaving the determination of whether an experimental procedure will produce improved results for patients to individual experiments and definitions. Nevertheless, retrospective studies have associated better disease remission rates with enrichment of less differentiated T cell subsets in leukopenia products.

[0189] T cell differentiation is a gradual process characterized by changes in phenotype and function. According to the theory of linear hierarchical systems, upon exposure to antigens, naive T cells proliferate and differentiate into a subset of memory T cells, eventually differentiating into terminally differentiated effector T cells. During this differentiation process, T cells mature and gradually acquire effector functions, while simultaneously losing their self-renewal and persistence capabilities.

[0190] Advances in multiparameter flow cytometry over the past few decades have enabled the analysis of T cell phenotypic heterogeneity with increasing precision. Furthermore, the combined expression of markers such as CD3, CD4, CD8, CD45RA, CD45RO, CCR7, and CD95 has allowed for the identification of stem cell memory T cells (Tscm), central memory T cells (Tern), effector memory T cells (Tern), and terminal effector T cells (Teff). The Tscm subset represents the earliest and longest-lasting developmental stage of memory T cells, exhibiting stem cell-like properties and displaying a genetic profile intermediate between naive T cells and central memory T cells. Therefore, the self-renewal capacity, proliferative potential, telomere length, and long-term survival of Tscm have attracted considerable interest in the field of cancer therapy. In fact, in mouse adoptive T-cell therapy studies, Tscm cells have demonstrated high self-renewal, high proliferation, and superior antitumor responses compared to other memory cell subsets. Furthermore, evidence suggests that adjusting certain process parameters, such as cytokines, pH, dissolved oxygen levels, amino acid concentrations, temperature, and the type of bioreactor used, can successfully influence the expansion and differentiation status of T cells in vitro, focusing on generating a greater number of less differentiated T cells. Given the relatively low frequency of Tscm in peripheral blood, expansion techniques to increase the frequency of Tscm subsets prior to adoptive transfer are encouraged. Therefore, any method capable of guiding the generation of a greater quantity of Tscm subsets can be combined with any genetically engineered T-cell therapy for cancer treatment. Consequently, there is a need to develop advanced process analysis tools and methods that can automate and integrate cell production, cell sampling, sample monitoring, and cell analysis processes, enabling feedback from these processes to effectively guide and improve the number and frequency of Tscm cells, thereby enhancing the quality of produced T cells and accelerating the production process.

[0191] This disclosure provides settings and results from a proof-of-concept study to demonstrate the effectiveness of incorporating feedback loops into cell product manufacturing. T cells were stimulated and expanded under standard conditions and under conditions simulating clinical samples that did not meet certain quality attributes. Early in the production phase, T cells from each group were examined using various analytical tools. Cell analysis results (such as cell proliferation and differentiation status) from Samples 2 and 3 were then compared to the quality attributes (QA) of the control / sample 1. If cells in the experimental samples did not meet or exceed the control's QA, the cell culture conditions were adjusted accordingly, and cells were expanded under revised culture conditions. Thus, the cell manufacturing process was continuously improved by intermittently performing cell analysis (if necessary) throughout the manufacturing process. Accordingly, it was found that using feedback control resulted in more T cell products meeting established standards at the end of manufacturing, regardless of the initial cell state at the start of production.

[0192] Due to individual patient health variations, such as different expression levels of specific genes and proteins, patients with the same type of cancer may have cells with different characteristics, leading to varying quality properties during the manufacture of autologous therapies. The feedback loop approach described in this disclosure can help standardize cell therapies derived from different patients or donors (autologous or allogeneic), ensuring consistent quality properties at the end of production. Furthermore, the feedback loop approach described in this disclosure can also benefit current / conventional solutions when a patient is deemed too ill to provide cells worthy of attempting autologous therapy. When some patients are too ill to currently have access to cells for effective autologous therapy, physicians / caregivers may choose to provide allogeneic therapy (using cells from healthy individuals whose health meets the sample extraction threshold) or wait to observe whether the patient's health improves, such as waiting a few days after chemotherapy / antibiotic treatment, etc., so that the patient's health improves and, in some cases, the patient can provide some cells for autologous therapy production. This disclosure avoids the disadvantages and risks associated with such conventional solutions (e.g., allogeneic and waiting methods) and offers other benefits. Therefore, instead of routinely waiting for patients to exhibit a health condition associated with a threshold for sample extraction of cells (which are considered "sufficiently healthy" or "in sufficient quantity / percentage" for manufacturing an effective therapy for autologous homologous therapy), or determining the use of a different biological subject as a source when patients cannot or do not exhibit a health condition associated with threshold sample extraction, this disclosure demonstrates that it is possible to perform excellent autologous homologous therapy with therapeutically effective quantities and potency of manufacturing cells even when patients cannot or have not yet exhibited a health condition associated with conventional threshold sample extraction. Although autologous homologous therapies are generally discussed, this disclosure contemplates applying the teachings herein to allogeneic (e.g., heterologous) therapies.

[0193] Figure 8 An overview of an exemplary T-cell production process 800 with a feedback loop according to an embodiment of the present disclosure is illustrated. Enriched CD4+ and CDS+ cells from peripheral blood mononuclear cells (PBMCs) from healthy donors are provided. Cells were thawed in a 37°C water bath for approximately two minutes and then centrifuged at 250×g for ten minutes. The cells were resuspended in 5 mL of resting medium supplemented with 5% human serum, and then counted using flow cytometry. After counting, the cells were transferred to flasks, allowed to stand, and incubated at 37°C in a 5% CO2 incubator at 5–10 × 10⁻⁶. 6Incubate overnight at 100 cells / mL. On the second day, centrifuge the statically incubated PBMCs at 400×g for eight minutes. Resuspend the cell sample in 2 mL of glucose-free basal medium and count viable cells using flow cytometry. On day zero, incubate the cells at 1×10⁻⁶ cells / mL. 6 Cells were seeded at a density of 10 cells / well into 2 mL of activation medium in the wells of the bioreactor, the activation medium comprising amplification medium and 50 µL of human CD3 / CD28 T cell activator. On day 1, an additional 6 mL of amplification medium was added to the wells of the plate. During the production process, a 75% medium refresh was performed on days 3 and 6, respectively.

[0194] To simulate variations in cell performance and state due to donor variability (which could potentially prevent samples from reaching certain thresholds for quality parameters such as total cell count, total Tscm count, and percentage of Tscm), overnight static PBMCs from the same donor were initially stimulated and amplified in basal RPMI-1 and supplemented with different concentrations of IL-2 (e.g., IL-1). Figure 9 (As shown). Cells cultured in medium containing 200 U / mL IL2 for Sample 1 were used as a standard control, while those expanded in medium containing 50 U / mL IL2 were designated as Sample 2 and Sample 3 to represent potential patient variability in the starting cell material (for low-quality initial sampling). In Sample 2 and Sample 3, Sample 2 was continuously expanded under the same culture conditions to represent a test without cell growth feedback. In contrast, cell growth feedback was applied to Sample 3. The first cell analysis was performed on day 4, representing cells that had recovered from activation-induced cell death, as indicated by... Figure 10 The cell expansion curve shown indicates this.

[0195] In short, after gently removing 6 mL of the old culture medium from the top of the culture, the cells were resuspended in the remaining medium. A small volume of the cell suspension was taken for cell counting, and a portion of the cells was prepared for flow cytometry assessment of T cell differentiation status on day four. The analytical results of samples 2 and 3 were compared with those of the control group (sample 1). If the cells in sample 3 did not meet the standards set by the control for total cell count, Tscm percentage, or Tscm cell count, the manufacturing conditions were immediately adjusted in the feedback loop.

[0196] Cells were carefully and uniformly resuspended by pipetting the culture medium up and down. After resuspending, 50 µL of cell suspension was transferred to each well plate, and 50 µL of a solution containing cell staining buffer was added. The mixture was incubated at room temperature in the dark for five minutes. Without washing, samples were loaded and absolute counts for each sample were obtained in duplicate using precise volumetric measurements. Sample loading settings were as follows: automixing at 1000 rpm for 10 seconds, mixing and rinsing once per well, stopping at 100 μL, and a sample flow rate of 66 μL / min. After sample collection, appropriate gating was applied in the measurement software, and the absolute count of 7AAD-negative cells was reported as the total viable cell count. Figures 11A to 11C The study presented the kinetic cell growth of the positive control group throughout the amplification process.

[0197] Flow cytometry was also used to assess the purity and differentiation status of T cells throughout the cell culture process. First, a scientifically sound multi-parameter 8-color / 10-parameter flow cytometry panel was designed and validated. The exemplary panel presented in this paper includes antibodies for identifying CD3, CD4, CD8, viability, CCR7, CD95, CD45RA, and CD45RO. Evidence has shown that differential expression of CD45RA, CD45RO, CD95, and CCR7 markers can identify naive T cells (Tn, CD45RA+CCR7+CD95-), stem cell memory T cells (Tscm, CD45RA+CCR7+CD95+), central memory T cells (Tcm, CD45RO+CD45RA-CCR7-), effector memory T cells (Tem, CD45RO+CD45RA-CCR7-), and terminal effector T cells (Teff, CD45RA+CD45RO+CCR7-). The panel design included antibody titration for each antibody to determine the optimal antibody concentration. Flow cytometry was performed on fresh cells on days 0, 4, 6, and 10. Cells were collected at concentrations between 0.3 × 10⁻⁶. 6 Up to 1×l0 6Cells were washed at 350 g / 5 min and resuspended in 100 μL of cell staining buffer. Fc receptors on the cells were blocked for eight minutes at room temperature (RT) using blocking buffer. Cells were then stained directly with a mixture of all surface antibodies of interest in the presence of a bright staining buffer that blocks fluorescent dye interactions without washing. The labeled cells were incubated at room temperature in the dark for twenty minutes, followed by a single wash at 350 g / 5 min. Following FDA guidelines for CAR-Cell Manufacturing, active dyes should always be added to the flow cytometry panel to remove dead cells. Therefore, after washing, cells were resuspended in 500 μL of cell staining buffer in the presence of the active dye 7AAD (1 / 100e). The samples were then incubated at room temperature for five minutes without washing. Samples were split, loaded into samplers, and collected for technical parallel assays. 0.83 × 10⁸ cells per sample were analyzed. 11 The average number of cells was determined. During data analysis, single-stain compensation controls, fluorescence minus one (FMO) controls, and unstained controls were performed to determine fluorescence propagation and gating boundaries. Furthermore, evidence-supported gating strategies were designed and applied to phenotypically characterize T cell subsets (e.g., %CD3+ T, %CD4+ T helper cells, and %CD8+ cytotoxic T cells) and T cell differentiation subsets (%Tn, %Tscm, %Tcm, %Tem, %Teff). Finally, routine instrument quality control and maintenance were performed according to the manufacturer's recommendations to ensure the accuracy of the results.

[0198] Use precise volume counting to obtain absolute cell counts. Figure 10The kinetics of cell growth in Sample 1 under reference control conditions are shown. Based on these data, day four appears to be a suitable starting point for feedback, as cell count indicates that cells are beginning to recover from activation-induced cell death, a known phenomenon following T cell activation. Based on these data, the first cell analysis was performed on day four. This cell analysis included cell counting and T cell differentiation phenotype typing. Indeed, FDA guidance documents have recognized that, in addition to CAR expression, other factors, such as cell viability and total cell count, should be considered when determining the cell dose administered to patients receiving cell therapy. Therefore, the final cell count of a T-cell product can significantly influence the therapeutic dose of immunotherapy. Other studies have shown that Tscm subsets are good candidates for adoptive cell therapy due to their longevity and self-renewal capacity. Indeed, clinical studies have demonstrated that infusion of Tscm CAR T cells leads to favorable outcomes. Therefore, we selected total cell count, percentage and number of Tscm subsets as cell quality parameters to be assessed during T-cell expansion. Data from Sample 1 were used as a baseline. Clinical starting material samples have shown significant variability from donors. Therefore, we chose a threshold where the parameters deviated from these standard values ​​by 20% to initiate cell culture readjustment. Figures 11A to 11C The changes in total cell count, Tscm percentage, and fold increase observed on day 4 are presented. The cell count in samples 2 and 3 was 0.82 × 10⁻⁶. 6 The number of cells was 28% less than that in Sample 1. Similarly, the percentage of Tscm in Samples 2 and 3 was 35%, compared to 49% in Sample 1. Further analysis revealed that the fold change in Tscm in Samples 2 and 3 relative to the control was approximately 71% of that in Sample 1. Likewise, when considering the number of Tscm cells, the data revealed that the number of Tscm cells in Samples 2 and 3 was approximately 54% of the number of Tscm cells in Sample 1.

[0199] In summary, these cell analysis results indicate that the selected quality attributes in Samples 2 and 3 fell below the baseline threshold on day 4, thus requiring adjustments to culture conditions to increase the yield of high-quality T-cell products at the end of the process. In the exemplary validation, the concentrations of interleukin-2 (IL-2) and interleukin-15 (IL-15) cytokines in Sample 3 were adjusted during the feedback period.

[0200] IL-2 is a commonly used supplement in in vitro T cell culture and is considered a promoter of T cell expansion. Alternatively, IL-15 has been reported to promote CAR-T cell proliferation and maintain their stem cell memory phenotype, thereby enhancing the antitumor activity of these cells. Furthermore, both IL-2 and IL-15 are known cytokines involved in different stages of in vivo T cell differentiation, and they are supplements to T cell culture media, playing a role in the in vitro activation, proliferation, and survival of T cells. To improve the quality of the final product in Sample 3 via feedback, and to increase the IL-2 concentration to match the IL-2 concentration in the samples, 10 ng / mL of IL-15 was added to the culture medium. Samples 1, 2, and 3 were expanded for the remainder of the ten-day culture period, starting from day four.

[0201] Two more cell analyses were performed on days six and ten to assess changes in cell quality attributes. Figures 12A to 12C As shown, on day four, both Sample 2 and Sample 3 exhibited approximately 28% fewer cells than Sample 1. However, adjusting the culture conditions in Sample 3 (using feedback) resulted in a faster growth rate compared to Sample 2 (maintained under the same culture conditions). In fact, Sample 2 reached only 37% of Sample 1's cell count by day six, while the adjusted Sample 3 reached 58% of Sample 1's cell count by day six. Furthermore, cell analysis on day ten revealed that Sample 3 reached 80% of Sample 1's total cell count (not a perfect match to the control), while Sample 2 showed very little proliferation after day six, with its total cell count on day ten similar to that on day six, and simultaneously indicating only 20% of Sample 1's total cell count. Figure 12A ).

[0202] Interestingly, the percentage of the Tscm subpopulation fluctuated throughout the manufacturing process. Figure 12B Starting at 19% on day 0, the percentage of Tscm peaked on day 4, reaching 49% in Sample 1 and 35% in Samples 2 and 3. By day 6, the %Tscm in all groups had subsequently decreased to 20%, indicating that the culture condition adjustments initiated on day 4 in Sample 3 had not yet significantly affected T cell differentiation. Surprisingly, data analysis of T cell differentiation at the end of production (day 10) showed a significant change. In fact, the results on day 10 showed that the %Tscm in Sample 3 was significantly higher than that in Sample 1 or Sample 2, with the %Tscm in Sample 3 being 63% higher than that in Sample 1. Figure 12C Sample 3 showed the lowest Tscm cell count compared to Sample 1, while Sample 2 maintained the lowest Tscm cell count across all sample groups. Therefore, the data also revealed that Sample 3 had a significantly higher Tscm cell count compared to Sample 1, while Sample 2 exhibited the lowest Tscm cell count. Figure 12C ).

[0203] Interestingly, changes in the total cell number and the percentage of Tscm can at least partially explain, for example... Figure 12C The changes in Tscm counts were observed. Overall, the findings revealed that the Tscm cell count and percentage in Sample 2 gradually decreased and remained low after day 4, while the Tscm cell counts in the adjusted sample 3 and control sample 1 gradually increased over time. Surprisingly, despite the culture medium adjustment on day 4, on day 6, the Tscm cell count in Sample 3 showed a significantly lower number of Tscm cells compared to Sample 1. Figure 12C This suggests that the duration of feedback treatment on day six may not have been long enough to observe a significant recovery in Tscm cell counts (starting from day four), as other studies have shown that not only cytokine concentration but also the duration of cytokine treatment affects T cell differentiation and cell proliferation. However, a significant increase in Tscm cell counts was observed at the end of production in sample 3 (day ten), even 30% higher than the Tscm cell count in sample 1; indicating the effectiveness of the feedback-improved culture conditions described herein and their delayed effect on cell quality.

[0204] These findings highlight the surprising improvements offered by the integrated cell analysis methods described in this paper in monitoring T-cell quality attributes during the manufacturing of T-cell products. Indeed, developing methods that provide rapid and reliable T-cell characterization, cell counting, and T-cell differentiation status can provide clinicians with the ability to guide adjustments to cell culture conditions to further enrich the clinical dosage and frequency of lower-differentiated T-cell populations in the final product. Therefore, real-time monitoring and optimization of cell numbers and T-cell differentiation in ex vivo cultures holds great potential for developing sufficiently effective CAR T-cell products, particularly in autologous therapy settings where delivering such effective concentrations has been a long-standing need. The feedback mechanisms described in this paper can streamline manufacturing workflows, enabling the widespread adoption of these therapies and potentially addressing the scaling and commercialization challenges of autologous and allogeneic T-cell therapies.

[0205] This disclosure may also be understood with reference to the clauses numbered below.

[0206] Clause 1: A system comprising: a bioreactor; a sensor; a processor; and a memory containing instructions that, when executed by the processor, automatically perform operations including: extracting a sample from cells being cultured in the bioreactor; preparing the sample to produce a prepared sample; analyzing the prepared sample to identify values ​​of associated cell analysis parameters; and adjusting settings of the bioreactor based on the difference between the values ​​and the window in response to determining that the values ​​are outside a window of the associated cell analysis parameters.

[0207] Clause 2: A system according to any one or more of Clauses 1 and 3 to 10, wherein the sample is obtained at a first time, and the operation further comprises: extracting an additional sample from the cells being cultured in the bioreactor at a second time after the first time; preparing the additional sample to produce an additional prepared sample; analyzing the additional prepared sample to identify an additional value of the associated cell analysis parameter; and maintaining the settings of the bioreactor in response to determining the additional value within the window of the associated cell analysis parameter.

[0208] Clause 3: A system according to Clause 2 and (optionally) any one or more of Clauses 4 to 10, wherein the first duration between the first time and the second time is equivalent to the second duration between the second time and the third time, wherein subsequent samples are extracted from the cells being cultured in the bioreactor at the third time to determine subsequent values ​​of the associated cell analysis parameters.

[0209] Clause 4: A system pursuant to Clause 2 and (optionally) to Clauses 3 and any one or more of Clauses 5 to 10, wherein the duration between the first time and the second time is one of the following: at least thirty minutes; at least one hour; at least two hours; at least six hours; at least twelve hours; at least twenty-four hours; at least thirty-six hours; at least forty-eight hours; at least seventy-two hours; at least eighty-four hours; at least ninety-six hours; at least one hundred and twenty hours; at least one hundred and forty-four hours; or at least one hundred and sixty-eight hours.

[0210] Clause 5: A system according to any one or more of Clauses 1 to 4 and 6 to 10, wherein the operation further comprises: extracting a second sample from the cells being cultured in the bioreactor at a first time; preparing the second sample to produce a second prepared sample; analyzing the second prepared sample to identify a second value of a second associated cell analysis parameter; maintaining the settings of the bioreactor until a second time in response to determining that the second value is within a second window of the second associated cell analysis parameter; extracting a third sample from the cells being cultured in the bioreactor at the second time; preparing the third sample to produce a third prepared sample; analyzing the third prepared sample to identify a third value of the second associated cell analysis parameter; identifying a trend of the second associated cell analysis parameter between the first time and the second time in response to determining that the third value is within the second window of the second associated cell analysis parameter; and adjusting a second setting of the bioreactor based on the difference between the trend and the window between the second time and the third time in response to determining that a predicted value of the trend at a third time when a fourth sample is planned to be extracted is outside the window.

[0211] Clause 6: A system according to any one or more of Clauses 1 to 5 and 7 to 10, wherein preparing the sample to produce the prepared sample includes one, two, three, four or all of the following: identifying or registering the sample; incubating the sample; staining the sample; adding a buffer or culture medium to the sample; or adding a therapeutic agent to the sample.

[0212] Clause 7: A system according to any one or more of Clauses 1 to 6 and 8 to 10, wherein the associated cell analysis parameters include one, two, three, four, five, six, seven or all of the following: pH; temperature; level or concentration of a component or reagent within the bioreactor or sample; cell identity; cell number; cell purity; cell size; or run time.

[0213] Clause 8: A system according to any one or more of Clauses 1 to 7 and 9 to 10, wherein the operation further comprises: automatically discarding the prepared sample after identifying the value of the associated cell analysis parameter.

[0214] Clause 9: A system according to any one or more of Clauses 1 to 8 and 10, wherein the cells grown in the bioreactor are extracted from a first biological subject prior to the growth of the cells in the bioreactor, and are obtained from the bioreactor for use as a modified cell culture to treat or prevent a disease in a second biological subject, wherein the modified cell culture comprises: cells genetically modified to express one or more heterologous genes; cells cultured for immunotherapy; or cells cultured for stem cell therapy.

[0215] Clause 10: A system according to any one or more of Clauses 1 to 9, wherein the bioreactor remains independent and operates automatically based on instructions specifically received prior to the extraction of the sample.

[0216] Clause 11: A method comprising: extracting a cell culture from a first biological subject; inserting the cell culture into a bioreactor; growing the cell culture in the bioreactor from a first time to a second time; modifying the cell culture in the bioreactor from the first time to the second time to produce a modified cell culture; obtaining the modified cell culture from the bioreactor; and supplying a therapeutically effective amount of the modified cell culture to a second biological subject suffering from or at risk of developing a disease that is treatable, preventable, or manageable by application of the modified cell culture.

[0217] Clause 12: The method according to any one or more of Clauses 11 and 13 to 17, wherein growing and modifying the cell culture further comprises automatically culturing the cell culture according to operations including: extracting a cell sample from the bioreactor at an intermediate time between the first time and the second time; preparing the cell sample to produce a prepared sample; analyzing the prepared sample to identify values ​​of associated cell analysis parameters; and adjusting the settings of the bioreactor prior to the second time based on the difference between the value and the window in response to determining that the value is outside a window of the associated cell analysis parameters.

[0218] Clause 13: The method according to any one or more of Clauses 12 and (optionally) Clauses 14 to 17, wherein the prepared sample is discarded after the value of the associated cell analysis parameter has been identified.

[0219] Clause 14: The method according to any one or more of Clauses 11 to 13 and 15 to 17, wherein growing and modifying the cell culture further comprises automatically culturing the cell culture according to operations including: extracting a first cell sample from the bioreactor at a first intermediate time between the first time and the second time; preparing the first cell sample to produce a first prepared sample; analyzing the first prepared sample to identify a first value of an associated cell analysis parameter; maintaining the settings of the bioreactor in response to determining the first value within a window of the associated cell analysis parameter until a second intermediate time between the first intermediate time and the second time; in the second intermediate time... The process involves: extracting a second cell sample from the bioreactor at a specified time interval; preparing the second cell sample to generate a second prepared sample; analyzing the second prepared sample to identify a second value of the associated cell analysis parameter; identifying a trend of the associated cell analysis parameter between a first intermediate time interval and a second intermediate time interval in response to determining that the third value is within the window of the associated cell analysis parameter; and adjusting the settings of the bioreactor based on the difference between the trend and the window between the second intermediate time interval and the third intermediate time interval in response to determining that a predicted value of the trend of the third intermediate time interval between the second intermediate time interval and the second time interval at which the third sample is planned to be extracted is outside the window.

[0220] Clause 15: The method according to any one or more of Clauses 11 to 14 and 16 to 17, wherein a prepared sample is extracted from the bioreactor via a needle and inserted into an analytical container, the analytical container is moved to the analytical module, the analytical module including a sensor, the sensor being isolated from the bioreactor and determining values ​​of cell growth parameters in the sensor.

[0221] Clause 16: The method according to any one or more of Clauses 11 to 15 and 17, wherein between the first time and the second time, the bioreactor remains independent and operates automatically based on instructions specifically received prior to the first time.

[0222] Clause 17: The method according to any one or more of Clauses 11 to 16, wherein the modified cell culture comprises: cells genetically altered to express one or more heterologous genes; cells cultured for use in immunotherapy; or cells cultured for use in stem cell therapy.

[0223] Clause 18: A method comprising: extracting a sample from cells being cultured in a bioreactor; preparing the sample to produce a prepared sample; analyzing the prepared sample to identify values ​​of associated cell analysis parameters; and adjusting settings of the bioreactor based on the difference between the values ​​and the window in response to determining that the values ​​are outside a window of the associated cell analysis parameters.

[0224] Clause 19: The method according to any one or more of Clauses 18 and 19 to 22, wherein the sample is extracted at a first time, and the method further comprises: extracting an additional sample from the cells being cultured in the bioreactor at a second time after the first time; preparing the additional sample to produce an additional prepared sample; analyzing the additional prepared sample to identify an additional value of the associated cell analysis parameter; and maintaining the settings of the bioreactor in response to determining the additional value within the window of the associated cell analysis parameter.

[0225] Clause 20: The method according to any one or more of Clauses 18 to 19 and 21 to 22, the method further comprising: extracting a second sample from the cells being cultured in the bioreactor at a first time; preparing the second sample to produce a second prepared sample; analyzing the second prepared sample to identify a second value of a second associated cell analysis parameter; maintaining the settings of the bioreactor until a second time in response to determining that the second value is within a second window of the second associated cell analysis parameter; extracting a third sample from the cells being cultured in the bioreactor at the second time; preparing the third sample to produce a third prepared sample; analyzing the third prepared sample to identify a third value of the second associated cell analysis parameter; identifying a trend of the second associated cell analysis parameter between the first time and the second time in response to determining that the third value is within the second window of the second associated cell analysis parameter; and adjusting a second setting of the bioreactor based on the difference between the trend and the window between the second time and the third time in response to determining that a predicted value of the trend at a third time when a fourth sample is planned to be extracted is outside the window.

[0226] Clause 21: The method according to any one or more of Clauses 18 to 20 and 22, the method further comprising automatically discarding the prepared sample after identifying the value of the associated cell analysis parameter.

[0227] Clause 22: The method according to any one or more of Clauses 18 to 21, wherein the cells grown in the bioreactor are extracted from a first biological subject prior to growth in the bioreactor, and are obtained from the bioreactor once a predetermined growth value is reached for use as a modified cell culture to treat or prevent a disease in a second biological subject, wherein the modified cell culture comprises: cells genetically modified to express one or more heterologous genes; cells cultured for immunotherapy; or cells cultured for stem cell therapy.

[0228] Certain terms are used throughout the specification and claims to refer to specific features or components. As those skilled in the art will understand, different people may use different names to refer to the same feature or component. This document is not intended to distinguish between components or features with different names but the same function.

[0229] As used herein, “about,” “approximately,” and “substantially” should be understood to refer to numbers within the range of the numbers mentioned, such as -10% to +10% of the numbers mentioned, preferably -5% to +5% of the numbers mentioned, more preferably -1% to +1% of the numbers mentioned, and most preferably -0.1% to +0.1% of the numbers mentioned.

[0230] Furthermore, all numerical ranges herein should be understood to include all integers, complete numbers, or fractions within that range. Moreover, these numerical ranges should be interpreted as supporting claims for any numerical value or subset thereof within that range. For example, disclosures from 1 to 10 should be interpreted as supporting ranges from 1 to 8, from 3 to 7, from 1 to 9, from 3.6 to 4.6, from 3.5 to 9.9, and so on.

[0231] As used in this disclosure, the phrase “at least one of” a list of items refers to any set of those items, including sets with a single member and every possible combination thereof. For example, when referring to “at least one of A, B, or C” or “at least one of A, B, and C”, the phrase is intended to cover the set A, B, C, AB, BC, and ABC, wherein the set may include one or more instances of a given member (e.g., AA, AAA, AAB, AABBCCC, etc.) and any order thereof. For the avoidance of doubt, the phrase “at least one of A, B, and C” should not be construed as meaning “at least one of A, at least one of B, and at least one of C”.

[0232] As used in this disclosure, the term "determine" encompasses a variety of actions, which may include calculation, operation, processing, deduction, investigation, search (e.g., via a table, database or other data structure), judgment, receiving (e.g., receiving information), accessing (e.g., accessing data in memory), retrieval, parsing, selection, picking, creation, etc.

[0233] Without further elaboration, it is believed that those skilled in the art can utilize the claimed invention to the fullest extent possible using the foregoing description. The examples and aspects disclosed herein should be interpreted as illustrative only and do not limit the scope of this disclosure in any way. It will be apparent to those skilled in the art that changes can be made to the details of the foregoing examples without departing from the fundamental principles discussed. In other words, various modifications and improvements to the specific examples disclosed above are within the scope of the appended claims. For example, any suitable combination of features from the various examples described is contemplated.

[0234] In the claims, references to elements in the singular form are not intended to mean "one and only one," unless specifically stated otherwise, but rather "one or more" or "at least one." Unless expressly stated otherwise, the term "some" refers to one or more. No element of any claim shall be construed under 35 USC § 112(f) unless explicitly stated using the phrases "means for..." or "steps for...". All structural and functional equivalents of the elements of the various embodiments described herein that are known or will be known later by one of ordinary skill in the art are expressly incorporated herein by reference and are intended to be covered by the claims. Furthermore, nothing disclosed in this disclosure is intended to be made public, whether or not such disclosure is expressly stated in the claims.

Claims

1. A system comprising: Bioreactor; sensor; processor; The memory contains instructions that, when executed by the processor, automatically perform operations including the following: Samples were extracted from cells being cultured in the bioreactor. Prepare the sample to generate a prepared sample; The prepared samples were analyzed to identify the values ​​of associated cell analysis parameters; as well as In response to determining that the value is outside the window of the associated cell analysis parameters, the settings of the bioreactor are adjusted based on the difference between the value and the window.

2. The system of claim 1, wherein the sample is acquired at a first time, and the operation further comprises: After the first time point, additional samples are extracted from the cells being cultured in the bioreactor at a second time point; Prepare the additional sample to generate additional prepared samples; Analyze the additional prepared samples to identify additional values ​​of the associated cell analysis parameters; as well as In response to determining the additional value within the window of the associated cell analysis parameters, the settings of the bioreactor are maintained.

3. The system of claim 2, wherein the first duration between the first time and the second time is equivalent to the second duration between the second time and the third time, wherein subsequent samples are extracted from the cells being cultured in the bioreactor at the third time to determine subsequent values ​​of the associated cell analysis parameters.

4. The system of claim 2, wherein the duration between the first time and the second time is one of the following: At least thirty minutes; At least one hour; At least two hours; At least six hours; At least twelve hours; At least 24 hours; At least thirty-six hours; At least forty-eight hours; At least seventy-two hours; At least eighty-four hours; At least ninety-six hours; At least 120 hours; At least one hundred and forty-four hours; or At least 168 hours.

5. The system according to claim 1, wherein the operation further comprises: A second sample was extracted from the cells being cultured in the bioreactor at the first moment; Prepare the second sample to generate a second prepared sample; Analyze the second prepared sample to identify a second value of the second associated cell analysis parameter; In response to determining that the second value is within a second window of the second associated cell analysis parameter, the settings of the bioreactor are maintained until the second time. A third sample is extracted from the cells being cultured in the bioreactor at the second time. Prepare the third sample to generate a third prepared sample; Analyze the third prepared sample to identify a third value of the second associated cell analysis parameter; In response to determining that the third value is within the second window of the second associated cell analysis parameter, the trend of the second associated cell analysis parameter between the first time and the second time is identified; as well as In response to the predicted value of the trend at the third time when the fourth sample is to be extracted being outside the window, the second settings of the bioreactor are adjusted based on the difference between the trend and the window between the second and the third time.

6. The system of claim 1, wherein preparing the sample to produce the prepared sample comprises one, two, three, four, or all of the following: Identify or register the sample; Incubate the sample; The sample was stained; Add buffer or culture medium to the sample; or Add the therapeutic agent to the sample.

7. The system of claim 1, wherein the associated cell analysis parameters include one, two, three, four, five, six, seven, or all of the following: pH; temperature; The level or concentration of the components or reagents within the bioreactor or the sample; Cell identity; Cell number; Cell purity; Cell size; or Runtime.

8. The system of claim 1, wherein the operation further comprises: After identifying the values ​​of the associated cell analysis parameters, the prepared sample is automatically discarded.

9. The system of claim 1, wherein the cells grown in the bioreactor are extracted from a first biological subject prior to growth in the bioreactor, and are obtained from the bioreactor for use as a modified cell culture to treat or prevent a disease in a second biological subject, wherein the modified cell culture comprises: Cells that have undergone genetic alteration to express one or more heterologous genes; Cells cultured for use in immunotherapy; or Cells cultured for use in stem cell therapy.

10. The system of claim 1, wherein the bioreactor remains independent and operates automatically based on instructions specifically received prior to the extraction of the sample.

11. A method, the method comprising: Cell cultures were extracted from the first biological subject; The cell culture was inserted into the bioreactor; The cell culture is grown from a first time point to a second time point in the bioreactor; In the bioreactor, the cell culture is modified from the first time to the second time to produce a modified cell culture; The modified cell culture was obtained from the bioreactor; as well as A therapeutically effective amount of the modified cell culture is supplied to a second biological subject who has a disease that is treatable, preventable, or manageable by application of the modified cell culture, or who is at risk of developing the disease.

12. The method of claim 11, wherein growing and modifying the cell culture further comprises automatically culturing the cell culture according to operations including: Cell samples were extracted from the bioreactor at the intermediate time between the first time and the second time. Prepare the cell sample to generate a prepared sample; The prepared samples were analyzed to identify the values ​​of associated cell analysis parameters; as well as In response to determining that the value is outside the window of the associated cell analysis parameters, the settings of the bioreactor are adjusted based on the difference between the value and the window before the second time.

13. The method of claim 12, wherein the prepared sample is discarded after the value of the associated cell analysis parameter is identified.

14. The method of claim 11, wherein growing and modifying the cell culture further comprises automatically culturing the cell culture according to operations including: A first cell sample is extracted from the bioreactor at a first intermediate time between the first time and the second time. Prepare the first cell sample to generate a first prepared sample; Analyze the first prepared sample to identify a first value of the associated cell analysis parameters; In response to determining the first value within the window of the associated cell analysis parameters, the settings of the bioreactor are maintained until a second intermediate time between the first intermediate time and the second time; A second cell sample is extracted from the bioreactor at the second intermediate time point; Prepare the second cell sample to generate a second prepared sample; The second prepared sample is analyzed to identify a second value of the associated cell analysis parameter; In response to determining the third value within the window of the associated cell analysis parameter, the trend of the associated cell analysis parameter between the first intermediate time and the second intermediate time is identified; as well as In response to the predicted value of the trend of the third intermediate time between the second intermediate time and the second time when the third sample is planned to be extracted being outside the window, the settings of the bioreactor are adjusted based on the difference between the trend and the window between the second intermediate time and the third intermediate time.

15. The method of claim 11, wherein a sample is extracted from the bioreactor via a needle and inserted into an analytical container, the analytical container is moved to the analytical module, the analytical module including a sensor detached from the bioreactor and in which values ​​of cell growth parameters are determined.

16. The method of claim 11, wherein between the first time and the second time, the bioreactor remains independent and operates automatically based on instructions specifically received prior to the first time.

17. The method of claim 11, wherein the modified cell culture comprises: Cells that have undergone genetic alteration to express one or more heterologous genes; Cells cultured for use in immunotherapy; or Cells cultured for use in stem cell therapy.

18. A method, the method comprising: Samples were extracted from cells being cultured in a bioreactor. Prepare the sample to generate a prepared sample; The prepared samples were analyzed to identify the values ​​of associated cell analysis parameters; as well as In response to determining that the value is outside the window of the associated cell analysis parameters, the settings of the bioreactor are adjusted based on the difference between the value and the window.

19. The method of claim 18, wherein the sample is extracted in a first instant, and the method further comprises: After the first time point, additional samples are extracted from the cells being cultured in the bioreactor at a second time point; Prepare the additional sample to generate additional prepared samples; Analyze the additional prepared samples to identify additional values ​​of the associated cell analysis parameters; as well as In response to determining the additional value within the window of the associated cell analysis parameters, the settings of the bioreactor are maintained.

20. The method of claim 18, further comprising: A second sample was extracted from the cells being cultured in the bioreactor at the first moment; Prepare the second sample to generate a second prepared sample; Analyze the second prepared sample to identify a second value of the second associated cell analysis parameter; In response to determining that the second value is within a second window of the second associated cell analysis parameter, the settings of the bioreactor are maintained until the second time. A third sample is extracted from the cells being cultured in the bioreactor at the second time. Prepare the third sample to generate a third prepared sample; Analyze the third prepared sample to identify a third value of the second associated cell analysis parameter; In response to determining that the third value is within the second window of the second associated cell analysis parameter, the trend of the second associated cell analysis parameter between the first time and the second time is identified; as well as In response to the predicted value of the trend at the third time when the fourth sample is to be extracted being outside the window, the second settings of the bioreactor are adjusted based on the difference between the trend and the window between the second and the third time.

21. The method of claim 18, further comprising automatically discarding the prepared sample after identifying the value of the associated cell analysis parameter.

22. The method of claim 18, wherein the cells grown in the bioreactor are extracted from a first biological subject prior to growth in the bioreactor, and are obtained from the bioreactor once a predetermined growth value is reached for use as a modified cell culture to treat or prevent a disease in a second biological subject, wherein the modified cell culture comprises: Cells that have undergone genetic alteration to express one or more heterologous genes; Cells cultured for use in immunotherapy; or Cells cultured for use in stem cell therapy.

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