Systems and methods for producing cells

Abstract

Disclosed are systems and methods for cell culture and production processes. The system includes a cell culture vessel having a first surface configured to have a plurality of cell colonies continuously adhere thereto throughout the cell culture process; an image sensor configured to capture one or more time-series images of the plurality of cell colonies during the cell culture process; a cell removal tool configured to remove one or more cells from the first surface of the cell culture vessel during the cell culture process; and a computing subsystem configured to track one or more characteristics of the plurality of cell colonies based on the one or more time-series images and control the cell removal tool to remove the cells based on the one or more characteristics.

Description

Related Applications

[0001] This application is a continuation of U.S. Provisional Application No. 63 / 371491, filed August 15, 2022, U.S. Provisional Application No. 63 / 371614, filed August 16, 2022, U.S. Provisional Application No. 63 / 371730, filed August 17, 2022, U.S. Provisional Application No. 63 / 371844, filed August 18, 2022, U.S. Provisional Application No. 63 / 373026, filed August 19, 2022, and U.S. Provisional Application No. 63 / 373026, filed August 1 This application claims benefit of priority to U.S. Provisional Application No. 63 / 373,029, filed on September 9, 2022, U.S. Provisional Application No. 63 / 374,899, filed on September 7, 2022, U.S. Provisional Application No. 63 / 472,370, filed on June 12, 2023, and U.S. Provisional Application No. 63 / 521,223, filed on June 15, 2023, each of which is incorporated by reference herein in its entirety. [Technical Field]

[0002] The present disclosure is generally directed to an automated cell culture system, and more particularly to rapid and accurate production of an output cell product that is scalable to enable large-scale biological manufacturing.

[0003] Incorporation by Reference All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. [Background technology]

[0004] The stochastic nature of cellular processes has long challenged biological manufacturing. This is particularly true for mammalian cellular processes involving phenotypic transitions, such as induced pluripotent stem cell (iPSC) reprogramming, or differentiation or transdifferentiation of stem cells into target cells. In addition, processes involving gene editing, which may be combined with the above processes, add significant process variability. Finally, patient-specific processes, such as autologous cell therapy or patient-specific drug discovery, are notoriously unpredictable. As a result, many cellular processes are highly variable, have low yields, and / or are labor-intensive, and therefore do not reach the clinic. Even when they do reach the clinic, the low yields, labor requirements, necessary purification and sorting steps, and multiple transfers between cell culture vessels make the process prohibitively expensive and unscalable for large patient populations.

[0005] One current approach to large-scale biological manufacturing involves the use of large bioreactors, such as stirred bioreactors, in which cells are cultured in suspension, often in clumps / aggregates, or on microcarriers. However, yields from such bulk processes are typically inefficient and manually managed, two-dimensional cell culture vessels. While the advantage of the bioreactor approach is the sheer volume of cells, the process has virtually no feedback control to account for lot-to-lot, patient-to-patient, or clone-to-clone variability. Filtration steps are sometimes added to purify the cell product, but these often reduce the viability or functionality of the cell product, potentially significantly impacting yield. Cell behavior deviations early in the process can devastatingly reduce yield or quality control (QC) assay performance and are largely undetectable until the end of the process.

[0006] Manual approaches to 2D cell culture vessels attempt to address this variability by adding highly trained operators or scientists to observe and "edit" the cell culture. Most often, these edits take the form of selective transfer from one culture vessel / vessel to another, which is repeated periodically as the cell culture grows to maximum density, often due to the outgrowth of undesired cells along with the target cells. While this manual process can eliminate bias throughout the cell culture process, subjective judgment (often based on single-point visualization through a dissecting microscope), manual and mechanical handling of cells and colonies, and frequent transfers between cell culture vessels make the process expensive, non-scalable, and prone to contamination unless performed in dedicated, expensive, high-quality cleanroom facilities. While automation addresses some of these issues, objective assessment of cell culture quality during the cell culture process is lacking. Therefore, a fast, accurate, automated, and scalable system for biological manufacturing is needed. Summary of the Invention

[0007] In accordance with certain aspects of the present disclosure, systems and methods are disclosed for incorporating automated cell culture systems that rapidly and accurately produce output cell products and are easily scalable to enable large-scale biological manufacturing.

[0008] In one embodiment, a system for culturing cells includes a cell culture vessel including a first surface configured to have a plurality of cell colonies continuously adhere thereto throughout a cell culture process; an image sensor configured to capture one or more time series images of the plurality of cell colonies during the cell culture process; a cell removal tool configured to remove one or more cells from the first surface of the cell culture vessel during the cell culture process; and a computing subsystem configured to track one or more characteristics of the plurality of cell colonies based on the one or more time series images and control the cell removal tool to remove cells based on the one or more characteristics.

[0009] In some embodiments, the cell culture process comprises producing a plurality of clonal induced pluripotent stem cells (iPSCs) from a plurality of somatic cells.

[0010] In some embodiments, the cell culture process further includes reprogramming the plurality of somatic cells to form a plurality of iPSC colonies, and wherein the computing subsystem is further configured to maintain a cell density of the plurality of iPSC cell colonies below a first threshold amount, select a first clonal iPSC cell colony from the plurality of iPSC cell colonies, remove a plurality of iPSC cell colonies other than the first clonal iPSC cell colony from the first surface, and maintain a cell density of the first clonal iPSC cell colony below a second threshold amount while the first clonal iPSC colony expands.

[0011] In some embodiments, the first threshold is 750,000 cells / cm 2 , 500,000 cells / cm 2 , 400,000 cells / cm 2 , 300,000 cells / cm 2 , or 250,000 cells cm 2 It is one of them.

[0012] In some embodiments, the second threshold is 750,000 cells / cm 2 , 500,000 cells / cm 2 , 400,000 cells / cm 2 , 300,000 cells / cm 2 , or 250,000 cells cm 2 It is one of them.

[0013] In some embodiments, the cell culture process has a duration of one of at least 7 days, at least 10 days, at least 20 days, at least 30 days, at least 45 days, or at least 60 days.

[0014] In some embodiments, maintaining the cell density of the plurality of iPSC cell colonies below a first threshold comprises repeatedly removing portions of the plurality of iPSC cell colonies and expanding remainders of the plurality of iPSC cell colonies.

[0015] In some embodiments, selecting the first clonal iPSC cell colony is based on one or more characteristics.

[0016] In some embodiments, the first clonal iPSC cell colony has the highest clonal quality among the plurality of iPSC cell colonies based on one or more characteristics.

[0017] In some embodiments, the cell culture process further comprises extracting a portion of the first clonal iPSC cell colony from the first cell culture container.

[0018] In some embodiments, the cell culture process further includes profiling a portion of the first clonal iPSC cell colony and providing the resulting profile to a computing subsystem.

[0019] In some embodiments, the computing subsystem is configured to provide one or more characteristics to a machine learning model and receive instructions therefrom on which cells to remove.

[0020] In some embodiments, the cell removal tool comprises a pulsed laser.

[0021] In some embodiments, the pulsed laser comprises one or more visible light lasers.

[0022] In some embodiments, the first surface comprises a laser film.

[0023] In some embodiments, the laser film is semi-transparent and has wavelength-selective absorption.

[0024] In some embodiments, the laser film is a plasmonic film.

[0025] In some embodiments, the laser film is configured to enable light-based cellular imaging.

[0026] In some embodiments, the light-based cellular imaging is within an imaging wavelength range detectable by an image sensor.

[0027] In some embodiments, the laser film is further configured to enable light-based cell ablation within an ablation wavelength range emitted by the pulsed laser, the ablation wavelength range being different from the imaging wavelength range.

[0028] In some embodiments, the laser film has properties that absorb light energy from a pulsed laser, thereby ablating one or more cells from the first surface.

[0029] In some embodiments, the laser film has a property of at least partially absorbing light energy from a pulsed laser within a first range of wavelengths and a property of at least partially transmitting light energy within a second range of wavelengths to an imaging sensor.

[0030] In some embodiments, the one or more characteristics are selected from cell proliferation rate, cell number, colony surface area, colony area growth rate, colony morphology, and fluorescent marker expression.

[0031] In some embodiments, the cell removal tool comprises a continuous wave laser.

[0032] In some embodiments, the first surface comprises a laser film and a biocoating, wherein the continuous wave laser is configured to ablate the biocoating.

[0033] In one embodiment, a method for culturing cells includes introducing a plurality of cell colonies onto a first surface of a cell culture container; capturing one or more time series images of the plurality of cell colonies with an image sensor during the cell culture process; tracking, by a computing subsystem, one or more characteristics of the plurality of cell colonies based on the one or more time series images; and controlling, by the computing subsystem, a cell removal tool based on the one or more characteristics to remove the one or more cell colonies from the first surface of the cell culture container during the cell culture process.

[0034] In one embodiment, a computer program product for culturing cells includes a computer-readable storage medium having program instructions embodied therewith, the program instructions being executable by a processor to cause the processor to perform a method including receiving one or more time series images of a plurality of cell colonies captured during a cell culture process; tracking, by a computing subsystem, one or more characteristics of the plurality of cell colonies based on the one or more time series images; and controlling, by the computing subsystem, a cell removal tool to remove one or more cell colonies from a substrate during the cell culture process based on the one or more characteristics.

[0035] In one embodiment, a system for culturing cells includes: a cell culture vessel including a first surface, the first surface configured to have one or more cell colonies adhere thereto; an image sensor configured to capture one or more time series images of a first cell colony within the one or more cell colonies; and a computing subsystem configured to iteratively manage the surface area of ​​the first cell colony according to a method including: calculating a surface area of ​​the first cell colony as the first cell colony grows; selecting a portion of the first cell colony to remove to reduce the surface area of ​​the first cell colony if the surface area exceeds a predetermined threshold; and removing the selected portion of the first cell colony from the first surface using a cell removal tool.

[0036] In some embodiments, the surface area is calculated based on one or more time-series images of the first cell colony.

[0037] In some embodiments, repeatedly managing the surface area of ​​the first cell colony comprises increasing the clonality of the first cell colony over time.

[0038] In some embodiments, the portion of the first cell colony is selected to migrate across the first surface as the remainder of the first cell colony grows.

[0039] In some embodiments, the first surface comprises an extracellular matrix, and wherein the cell removal tool is configured to remove the extracellular matrix from beneath a selected portion of the first cell colony.

[0040] In some embodiments, the absence of extracellular matrix throughout the region inhibits cells from proliferating within the region.

[0041] In some embodiments, the cell removal tool comprises a continuous wave laser system.

[0042] In some embodiments, the cell removal tool comprises a pulsed laser system.

[0043] In some embodiments, the first surface comprises a laser film.

[0044] In some embodiments, the laser film has properties that allow it to absorb light energy from a pulsed laser, thereby ablating one or more cells attached to the laser film.

[0045] In some embodiments, the laser film has a property of at least partially absorbing light energy from a pulsed laser within a first range of wavelengths and a property of at least partially transmitting light energy within a second range of wavelengths to an imaging sensor.

[0046] In some embodiments, the laser film is semi-transparent and has wavelength-selective absorption.

[0047] In some embodiments, the laser film is a plasmonic film.

[0048] In some embodiments, the laser film is configured to enable light-based cellular imaging.

[0049] In some embodiments, the light-based cellular imaging is within the imaging wavelength range emitted by the image sensor.

[0050] In some embodiments, the laser film is further configured to enable light-based cell ablation within an ablation wavelength range emitted by the electromagnetic radiation source, the ablation wavelength range being different from the imaging wavelength range.

[0051] In some embodiments, the first surface is configured such that the first cell colony continues to adhere thereto continuously during said repetitive administering.

[0052] In some embodiments, iteratively controlling the surface area of ​​the first cell colony comprises controlling the cell density of the first cell colony.

[0053] In some embodiments, the predetermined threshold is one of a 5-fold, 10-fold, 20-fold, 30-fold, 50-fold, or 100-fold increase in surface area over the initial surface area of ​​the first cell colony.

[0054] In one embodiment, a method for culturing cells includes introducing a plurality of cell colonies onto a first surface of a cell culture container; capturing one or more time series images of a first cell colony within the one or more cell colonies; calculating a surface area of ​​the first cell colony as the first cell colony grows; selecting a portion of the first cell colony for removal to reduce the surface area of ​​the first cell colony if the surface area is above a predetermined threshold; and removing the selected portion of the first cell colony from the first surface using a cell removal tool.

[0055] In one embodiment, a computer program product includes a computer-readable storage medium having program instructions embodied therewith, the program instructions being executable by a processor to cause the processor to perform a method including capturing one or more time-series images of a first cell colony; calculating a surface area of ​​the first cell colony as the first cell colony grows; selecting a portion of the first cell colony to remove to reduce the surface area of ​​the first cell colony if the surface area is above a predetermined threshold; and removing the selected portion of the first cell colony from the surface area using a cell removal tool.

[0056] In one embodiment, a system for culturing cells includes a cell culture container including a sealed cell culture chamber enclosing a fluid medium and a first surface configured for a cell culture to adhere thereto; a cell removal tool configured to selectively remove one or more cells from the first surface of the cell culture container; and a controller configured to use the cell removal tool to repetitively remove one or more cells, thereby maintaining the cell culture below a threshold density throughout the cell culture process, wherein the cell culture chamber is configured to seal during the cell culture process.

[0057] In some embodiments, the cell culture comprises one or more cell colonies.

[0058] In some embodiments, the repetitive removal of one or more cells comprises removing a portion of a first cell colony of the one or more cell colonies.

[0059] In some embodiments, the portion is selected such that the remainder of the first cell colony after removal of the portion of the first cell colony migrates across the entire first surface.

[0060] In some embodiments, the repetitive removal of one or more cells comprises dividing a first cell colony within the one or more cell colonies into multiple sub-colonies.

[0061] In some embodiments, the cell removal tool is further configured to detach a first subcolony in the plurality of subcolonies from the first surface.

[0062] In some embodiments, the cell culture vessel further comprises a fluid port configured to remove the first subcolony.

[0063] In some embodiments, the cell removal tool is further configured to migrate the first subcolony to a first region of the first surface, wherein the fluid medium flushes the cells from the first region through the fluid port.

[0064] In some embodiments, the repeated removal of one or more cells comprises increasing the size and confluence of the cell culture.

[0065] In some embodiments, the cell removal tool comprises a continuous wave laser.

[0066] In some embodiments, the cell removal tool comprises a pulsed laser.

[0067] In some embodiments, the pulsed laser comprises one or more ultraviolet visible lasers.

[0068] In some embodiments, the first surface comprises a laser film.

[0069] In some embodiments, the laser film has properties that absorb light energy from a pulsed laser, thereby ablating one or more cells from the first surface.

[0070] In some embodiments, the laser film has properties to at least partially absorb optical energy from a pulsed laser within a first range of wavelengths and to at least partially transmit optical energy within a second range of wavelengths.

[0071] In some embodiments, the first surface is configured to maintain continuous adherence of the cell culture thereto throughout the cell culture process.

[0072] In some embodiments, the cell culture process comprises reprogramming and expanding induced pluripotent stem cells.

[0073] In some embodiments, the threshold density is 750,000 cells / cm 2 , 500,000 cells / cm 2 , 400,000 cells / cm 2 , 300,000 cells / cm 2 , or 250,000 cells cm 2It is one of them.

[0074] In some embodiments, the cell culture process has a duration of one of at least 7 days, at least 10 days, at least 20 days, at least 30 days, at least 45 days, or at least 60 days.

[0075] In some embodiments,

[0076] In one embodiment, a method of culturing cells includes introducing a plurality of cell colonies onto a first surface of a cell culture vessel, the cell culture vessel including a cell culture chamber enclosing a fluid medium and a first surface; sealing the cell culture chamber throughout the cell culture process; and repeatedly removing one or more cells from the first surface using a cell removal tool, thereby maintaining the cell culture below a threshold density throughout the cell culture process.

[0077] In one embodiment, a computer program product for culturing cells includes a computer-readable storage medium having program instructions embodied therein, the program instructions being executable by a processor to cause the processor to perform a method including using a cell removal tool to repetitively remove one or more cells from a first surface of a cell culture vessel, the cell culture vessel including a cell culture chamber enclosing a fluid medium and a first surface, thereby maintaining the cell culture below a threshold density throughout the cell culture process.

[0078] In one embodiment, a method of manufacturing gene-edited cells includes seeding a plurality of gene-edited cells in a cell culture vessel; culturing, by a cell culture system, the plurality of gene-edited cells into a plurality of gene-edited cell colonies; cloning, by the cell culture system, the plurality of gene-edited cell colonies by repetitive, spatially selective removal of one or more portions from the plurality of gene-edited cell colonies as the colonies grow; tracking, by the cell culture system, one or more characteristics of the plurality of gene-edited clonal cell colonies; maintaining, by the cell culture system, a cell density of the plurality of gene-edited clonal cell colonies based on the tracked characteristics; selecting, by the cell culture system, a first gene-edited clonal cell colony from the plurality of gene-edited clonal cell colonies; removing, by the cell culture system, a plurality of gene-edited clonal cell colonies other than the first gene-edited clonal cell colony from the cell culture vessel; and expanding, by the cell culture system, the first gene-edited clonal cell colony.

[0079] In some embodiments, the method further comprises harvesting at least a portion of the first gene-edited clonal cell colony by a cell culture system.

[0080] In some embodiments, the method further comprises using the collected portion of the first gene-edited clonal cell colony in a cell therapy.

[0081] In some embodiments, the plurality of gene-edited cells comprises gene-edited induced pluripotent stem cells.

[0082] In some embodiments, the cloning comprises: a) expanding a plurality of gene-edited cell colonies using a cell culture system; b) removing a portion of each of the plurality of cell colonies using a cell culture system; and c) repeating steps a)-b), wherein with each iteration, the percentage of clonal cells within each of the plurality of gene-edited cell colonies increases.

[0083] In some embodiments, the one or more characteristics include at least one of cell proliferation rate, colony surface area, colony area growth rate, colony morphology, and fluorescent marker expression.

[0084] In some embodiments, the tracking includes capturing, by the cell culture system, a plurality of time series images of the plurality of gene-edited clonal cell colonies; and determining, by the cell culture system, the tracked characteristic from the plurality of time series images.

[0085] In some embodiments, maintaining includes: a) expanding the plurality of gene-edited clonal cell colonies using a cell culture system; b) determining, using a cell culture system, a region of each of the plurality of gene-edited clonal cell colonies to remove based on one or more characteristics to maintain a cell density of the plurality of gene-edited clonal cell colonies below a threshold; c) removing, using a cell culture system, the region of each of the plurality of gene-edited clonal cell colonies; and d) repeating steps a) through c) until a target confluence is reached.

[0086] In some embodiments, the cell culture system selects the first gene-edited clonal cell colony based on one or more characteristics.

[0087] In some embodiments, the cell culture system includes at least one of an imaging sensor, a computing subsystem, and an electromagnetic radiation source.

[0088] In some embodiments, the electromagnetic radiation source comprises a continuous wave laser.

[0089] In some embodiments, the electromagnetic radiation source comprises a pulsed laser.

[0090] In some embodiments, the cell culture vessel comprises a laser film, wherein the plurality of gene-edited cells are cultured on the laser film.

[0091] In some embodiments, the laser film has properties that allow it to absorb light energy from a pulsed laser, thereby ablating cells attached to the laser film.

[0092] In some embodiments, the pulsed laser comprises one or more visible light lasers.

[0093] In some embodiments, the laser film is semi-transparent and has wavelength-selective absorption.

[0094] In some embodiments, the laser film is a plasmonic film.

[0095] In some embodiments, the laser film is configured to enable light-based cellular imaging.

[0096] In some embodiments, the light-based cellular imaging is within the imaging wavelength range emitted by the image sensor.

[0097] In some embodiments, the laser film is further configured to enable light-based cell ablation within an ablation wavelength range emitted by the electromagnetic radiation source, the ablation wavelength range being different from the imaging wavelength range.

[0098] In some embodiments, the plurality of gene-edited cells, the plurality of gene-edited cell colonies, and the plurality of gene-edited clonal cell colonies are serially attached to a first surface of a cell culture vessel.

[0099] In some embodiments, the method has a duration of one of at least 7 days, at least 10 days, at least 20 days, at least 30 days, at least 45 days, or at least 60 days.

[0100] In one embodiment, a system for producing gene-edited cells includes an enclosed cell culture chamber enclosing a fluid medium and a first surface configured for a cell culture to adhere thereto, and a cell removal tool configured to selectively remove one or more cells from the first surface, the cell removal tool further configured to perform a method according to any of the above embodiments. [Brief explanation of the drawings]

[0101] The novel features of the present disclosure are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present disclosure will be obtained by reference to the following detailed description that sets forth illustrative implementations, in which the principles of the disclosure are utilized, and the accompanying drawings, in which: [Figure 1] FIG. 1 is a block diagram of a cell culture system according to various implementations. [Figure 2] 1 is a flowchart of a method of operating a cell culture system according to various implementations. [Figure 3] 1A-C illustrate portions of the process for iPSC reprogramming according to various implementations. [Figure 4] 8A-B illustrate cell removal during the iPSC reprogramming process according to various implementations. [Figure 5] 1A-C show cell isolation during the iPSC reprogramming process according to various implementations. [Figure 6] 1A-C are images showing cell isolation during the iPSC reprogramming process according to various implementations. [Figure 7] 1A-C show non-iPS cell removal during the iPSC reprogramming process according to various implementations. [Figure 8] 8A-B show the removal of neighboring cells around an iPSC colony during the iPSC reprogramming process according to various implementations. [Figure 9]8A-B show the removal of detached cells from iPSC colonies during the iPSC reprogramming process according to various implementations. [Figure 10] 8A-B show the removal of non-iPS cell candidates during the iPSC reprogramming process according to various implementations. [Figure 11] 1A-C show the removal of cell colonies during the iPSC reprogramming process according to various implementations. [Figure 12] AB are images showing the removal of cell colonies during the iPSC reprogramming process by various implementations. [Figure 13] 1A-C show the selection of cell colonies during the iPSC reprogramming process according to various implementations. [Figure 14] 1A-C show the spreading of cell colonies within a cell culture chamber during the iPSC reprogramming process according to various implementations. [Figure 14] D-E show density-controlled initial colonies spread throughout the growth chamber with various implementations. [Figure 15] 8A-B show the removal of cells outside of designated regions during the iPSC reprogramming process according to various implementations. [Figure 16] 1A-C show the removal of various cells during the iPSC reprogramming process according to various implementations. [Figure 17] 1A-C show fragmentation of cell colonies within a cell culture chamber during the iPSC reprogramming process according to various implementations. [Figure 18] 8A-8B are images showing fragmentation of cell colonies within a cell culture chamber during the iPSC reprogramming process using various implementations. [Figure 18C] 1 shows high density hiPSC cell cultures removed using laser microbubble lysis and washing according to various implementations. [Figure 18D]1 shows the regrowth of hiPSC cell cultures after 24 hours according to various implementations. [Figure 19] 1A-C show the collection of cells in a cell culture chamber during the iPSC reprogramming process according to various implementations. [Figure 20A] FIG. 1 is a block diagram of a computing subsystem within a cell culture system according to various implementations. [Figure 20B] 1 is a flowchart of a method for controlling a cell culture according to various implementations. [Figure 21A] 1 shows exemplary normalized bright-field z-stack images of hiPSC colonies according to various implementations. [Figure 21B] 1 shows exemplary outputs of a deep learning neural network trained to predict nuclear staining from brightfield z-stacks after thresholding according to various implementations. [Figure 21C] 1 shows a first exemplary brightfield image z-stack slice of hiPSC colony growth over approximately 65 hours according to various implementations. [Figure 21D] 21B shows the image of FIG. 21A with polygons depicting the determined colony areas according to various implementations. [Figure 21E] 10 shows a second exemplary brightfield image z-stack slice of hiPSC colony growth over approximately 65 hours according to various implementations. [Figure 21F] 21C with polygons depicting the determined colony areas according to various implementations. [Figure 21G] 10 shows a third exemplary brightfield image z-stack slice of hiPSC colony growth over approximately 65 hours according to various implementations. [Figure 21H] 58E shows the image of FIG. 58E with polygons depicting the determined colony areas according to various implementations. [Figure 22] 1A-1D are diagrams of a closed cassette system for use in a cell culture system according to various implementations. [Figure 23A] 1A-1C are diagrams of cell culture chambers within a closed cassette system according to various implementations. [Figure 23B] 1 is an image of an exemplary cell culture chamber according to various implementations. [Figure 23C] 1 shows exemplary hiPSCs grown under continuous medium flow in a liquid-filled chamber less than about 1 mm in height according to various implementations. [Figure 24] 1A-1C illustrate the removal of cells from a cell culture chamber in a closed cassette system according to various implementations. [Figure 25] 1A-1C illustrate agitation of cells in a cell culture chamber within a closed cassette system according to various implementations. [Figure 26] 1A-1C are diagrams of single-use portions of a closed cassette system for use in a cell culture system according to various implementations. [Figure 27] 1A-1D are diagrams of permanent portions of a closed cassette system for use in a cell culture system according to various implementations. [Figure 28] 1A-1C illustrate various cell culture chamber configurations within a closed cassette system for use within a cell culture system according to various implementations. [Figure 29] 1A-1C are diagrams of modular bioprocessing systems according to various implementations. [Figure 30] 1 illustrates a vessel transport function within a modular bioprocessing system according to various implementations. [Figure 31A] FIG. 1 is another diagram of a modular bioprocessing system according to various implementations. [Figure 31B] 1 shows an exemplary prototype process module (bottom, with handle) and a partially inserted cell culture cassette, according to various implementations, shown installed with a RAID storage array (16 drive bays visible) and a backup power module (top, marked Tripp Lite). [Figure 32] 1A-1D are diagrams of a modular cell culture system according to various implementations. [Figure 33]1A-1D are diagrams of cell culture cassettes compatible with modular cell culture systems according to various implementations. [Figure 34] FIG. 10 is another diagram of a cell culture cassette compatible with a modular cell culture system according to various implementations. [Figure 35] 1A-1D are diagrams of a rack-type modular cell culture system according to various implementations. [Figure 36] AE show selective cell extraction and analysis of adherent cells by various implementations. [Figure 37] 1A-C show selective cell extraction and analysis of semi-adherent cells by various implementations. [Figure 38] 1A-C illustrate a cell culture process with selective cell extraction and analysis according to various implementations. [Figure 39] 1 is a flowchart illustrating a method of cell extraction and analysis according to various implementations. [Figure 40] 1 is a graph illustrating the absorption / transmission behavior at different wavelengths of a resonant optical farm according to various implementations. [Figure 41] 1A-1C are images of a microwell plate with a resonant optical film on a cell-bearing surface according to various implementations. [Figure 42] AC are images of cells undergoing cell editing and washing in a cell culture chamber with a resonant optical film according to various implementations. [Figure 43] 1A-1C are images of resonant optical film surfaces according to various implementations. [Figure 44] 1 is a graph showing the transmission spectrum of an optical film that resonates at a specific wavelength. [Figure 45] FIG. 1 is a block diagram of a cell culture system according to various implementations. [Figure 46] 1A-D illustrate the use of SERS to measure the contents within a cell culture vessel according to various implementations. [Figure 47] AF show laser ablation of cell culture vessel film during SERS measurements with various implementations. [Figure 48] 1A to 1C show the poration of cells in a cell culture vessel during SERS measurements using various implementations. [Figure 49] FIG. 1 is a block diagram of an exemplary SERS subsystem for use in a cell culture system according to various implementations. [Figure 50] FIG. 1 is a block diagram of another exemplary SERS subsystem for use in a cell culture system according to various implementations. [Figure 51] FIG. 1 is a block diagram of another exemplary SERS subsystem for use in a cell culture system according to various implementations. [Figure 52] 1A-1D are diagrams of porous membranes for use in cell culture vessels according to various implementations. [Figure 53] 1A-1D illustrate the use of porous membranes in multiwell plates according to various implementations. [Figure 54] 1A-1D illustrate the use of porous membranes in cell culture vessels according to various implementations. [Figure 55] 1A-1D illustrate cell culture systems with shared laser resources according to various implementations. [Figure 56] 1A-1C illustrate another cell culture system with a shared laser resource according to various implementations. [Figure 57] 1A-1C illustrate a cell process module utilizing a shared laser resource according to various implementations. [Figure 58] AF show the patterning of matrix biocoatings using various implementations. [Figure 59] AF illustrate laser patterning of biocoatings to confine cell growth according to various implementations. [Figure 60] 1A to 1E are diagrams showing biocoatings in cell culture vessels that bind to specific cells in various implementations. [Figure 61] 1A-1C illustrate the movement of cell colonies using a laser scanning device according to various implementations. [Figure 62]1A-1D illustrate the transfer of cell colonies using a laser scanning device and biocoating according to various implementations. [Figure 63] 10A-10C illustrate another example of cell colony transfer using a laser scanning device and biocoating according to various implementations. [Figure 64] 10A-10C illustrate another example of cell colony transfer using a laser scanning device and an antifouling biocoating according to various implementations. [Figure 65] 10A-10C illustrate another example of cell colony transfer using a laser scanning device and an antifouling biocoating according to various implementations. [Figure 66] 10A-10C are images showing the movement of cell colonies using a laser scanning device according to various implementations. [Figure 67] 1A-1D illustrate division of cell colonies according to various implementations. [Figure 68] 10A-10D further illustrate cell colony division according to various implementations. [Figure 69] 10A-10D further illustrate cell colony division according to various implementations. [Figure 70] 1A-1D illustrate a process for forming clonal cell colonies according to various implementations. [Figure 71] 1A-1C illustrate another process for forming clonal cell colonies according to various implementations. [Figure 72] 1A-1C illustrate another process for forming clonal cell colonies according to various implementations. [Figure 73] 1A-D illustrate a process for laser control of cell colony uniformity according to various implementations. [Figure 74] 1A-E illustrate a process for harvesting portions of a cell colony according to various implementations. [Figure 75] 1A-D illustrate a process for sampling a portion of a cell colony according to various implementations. [Figure 76]1A-C illustrate a process for dissociating cell colonies according to various implementations. [Figure 77] 1A-C illustrate a process for sorting cells in a cell colony according to various implementations. [Figure 78] 1A-D show a process for purifying cells in a cell colony according to various implementations. [Figure 79] AG show prior art processes for screening and selection of gene-edited clonal cells. [Figure 80] AF show methods for in situ cloning of cell colonies by repeated sectioning according to various implementations. [Figure 81] AF show methods for the selection and expansion of multiple gene-edited cells according to various implementations. [Figure 82] FIG. 1 illustrates methods for iPSC reprogramming and gene editing according to various implementations. [Figure 83] 1 shows a diagram of a conventional aggregated cell passaging process of the prior art. [Figure 84] 1A-1D show diagrams of continuous management of cell clumps using cell removal tools according to various implementations. [Figure 85] 1 is a graph comparing the growth rate of cells using a conventional passaging process versus continuous management according to various implementations. [Figure 86] 10A-10C show graphs illustrating cell growth metrics as a function of local cell density according to various implementations. [Figure 87] 1 shows a graph illustrating simulated vector clearance during a single passaging step by various implementations. [Figure 88] 1A-1D illustrate examples of continuous sampling cell culture management according to various implementations. [Figure 89] FIG. 1 illustrates another example of continuous sampling cell culture management according to various implementations. [Figure 90] FIG. 1 illustrates another example of continuous sampling cell culture management according to various implementations. [Figure 91] FIG. 1 illustrates another example of continuous sampling cell culture management according to various implementations. [Figure 92] 1A-1D illustrate examples of spatially selective colony expansion according to various implementations. [Figure 93] FIG. 1 illustrates another example of spatially selective colony expansion according to various implementations. [Figure 94] FIG. 1 illustrates a conventional process for adherent cell culture expansion. [Figure 95] 1A-1D illustrate examples of dynamic cell culture expansion according to various implementations. [Figure 96] 1A-1C illustrate another example of dynamic cell culture expansion according to various implementations. [Figure 97] 1 is a flowchart illustrating a method for an iPSC cell culture process according to various implementations. [Figure 98] 1 is a flowchart illustrating a method for a cell culture process according to various implementations.

[0102] These and other features of the present implementations will be better understood by reading the following detailed description in conjunction with the figures set forth herein. The accompanying drawings are not drawn to scale. For clarity, not every component may be labeled in every drawing. DETAILED DESCRIPTION OF THE INVENTION

[0103] Reference will now be made in detail to the exemplary embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts.

[0104] The systems, devices, and methods disclosed herein are described in detail by way of example and with reference to the Figures. The examples discussed herein are merely examples and are provided to aid in the explanation of the apparatus, devices, systems, and methods described herein. None of the features or components shown in the Figures or described below should be considered essential with respect to any particular implementation of any of these devices, systems, or methods, unless specifically indicated as essential.

[0105] Also, for any method described, whether or not the method is described in conjunction with a flow diagram, unless otherwise specified or required by context, it should be understood that any express or implied order of steps performed in performing the method does not imply that the steps must be performed in the order presented, but instead may be performed in a different order or in parallel.

[0106] As used herein, the term "exemplary" is used in the sense of "example" rather than "ideal." Furthermore, the terms "a" and "an" as used herein do not denote a limitation of quantity, but rather denote the presence of one or more of the referenced item.

[0107] Disclosed herein are systems and methods including an automated cell culture system that rapidly and accurately produces output cell products and is easily scalable to enable large-scale biological manufacturing. The system may include a cell imaging subsystem that acquires images of the cell culture, a cell editing subsystem that edits (e.g., removes) one or more cells during the cell culture process, a computing subsystem that controls the cell editing subsystem based on the acquired images, or any combination thereof. The computing subsystem may apply machine learning to data collected by the system (e.g., imaging data, sensor data, input, and output assay data) to determine how to effectively edit the cell culture to reach a desired output. This allows for dynamic monitoring and control of how the cell culture develops from input cells to the output cell product. The automated nature of the system eliminates the need for manual human intervention at many stages of cell culture development, thereby reducing the time and cost of producing the output cell product. Furthermore, the computing subsystem's ability to simultaneously monitor and control multiple cell culture processes allows for easy scalability.

[0108] 1 is a block diagram of a cell culture system 100 according to various implementations. The cell culture system 100 receives input cells 102 as "source" cells as the cell culture system 100 performs various cell culture processes. The input cells 102 may be sorted, expanded, or otherwise modified prior to the cell culture performed by the cell culture system 100. Input cell types include, but are not limited to, somatic cells (including, but not limited to, fibroblasts, mature blood cells and progenitor cells (e.g., CD34+ cells and erythroblasts), keratinocytes, epithelial cells (including blood- and urine-derived epithelial cells), Sertoli cells, endothelial cells, granulosa epithelial cells, neurons, pancreatic islet cells, epidermal cells, epithelial cells, hepatocytes, hair follicle cells, keratinocytes, hematopoietic cells, melanocytes, chondrocytes, lymphocytes (B and T lymphocytes), erythrocytes, macrophages, monocytes, mononuclear cells, fibroblasts, cardiomyocytes, and other muscle cells), as well as any living somatic cells in general. The term "somatic cells", as used herein, also includes adult stem cells and pluripotent stem cells (including, but not limited to, induced pluripotent stem cells and embryonic stem cells).

[0109] The input cells 102 may be analyzed with one or more input cell assays 108 that function to quantify the state of the input cells 102. The input cell assays 108 may be non-destructive (e.g., cell counting), or alternatively, a sample may be extracted for testing, including but not limited to, genomic profiling, gene expression assays (e.g., PCR, qPCR, microarray, single-cell RNA-seq), whole exome sequencing (WES), whole genome sequencing (WGS), karyotyping, short tandem repeat (STR) analysis, sterility testing (testing for bacteria and viruses), or other phenotypic analyses, including but not limited to cell surface antigen or intracellular staining immunofluorescence or flow analysis, as well as cell viability, morphology, and migration assays, or any other implementation known to those skilled in the art. Sample extraction may be performed using an automated or semi-automated process within a closed cell culture environment to allow for continuous propagation of the cell culture within a sterile environment. The results of these assays are transmitted to the computing subsystem 110, which can use the results of various software applications to monitor, predict, and control the cell culture processes performed by the cell culture system 100.

[0110] Input cells 102 are placed in a cell culture 104 where they will remain for the duration of the process performed by the cell culture system 100. The cell culture 104 may reside within a cell culture vessel 106. The cell culture vessel 106 may include one or more chambers that hold the cell culture and may take the form of a microwell plate, a flask, a stackable cell culture vessel, a sealed cassette system, a microfluidic chamber, a custom bioreactor vessel, or any other implementation known to those skilled in the art. The cell culture vessel 106 may be a closed / sealed sterile environment for the cell culture 104 and the fluid media used in the cell culture process.

[0111] The cell culture 104 may be used for several cellular processes performed and monitored by the cell culture system 100, including, but not limited to, cell reprogramming (to pluripotent or multipotent forms), cell differentiation, cell transdifferentiation, cell expansion, cell sorting, clonal isolation, cellular gene editing, cell-based protein production, cell-based virus production, combinations thereof, or any other implementation known to one of skill in the art.

[0112] The cell culture vessel 106 may be configured to allow periodic observation of the cell cultures 104 using the imaging subsystem 112. For example, the cell culture vessel 106 may include a sealed cassette system having at least one transparent or translucent surface that allows for optical or laser-based imaging and editing. The imaging subsystem 112 may be configured to provide label-free imaging suitable for long-term cell culture observation, although some implementations may include fluorescence imaging capabilities for immunofluorescence or other labeling images. Label-free modalities utilized by the imaging subsystem 112 include, but are not limited to, bright-field imaging, phase imaging, dark-field imaging, transmission imaging, reflectance imaging, quantitative phase imaging, holographic imaging, two-photon imaging, autofluorescence imaging, Fourier ptychographic imaging, defocused imaging, or any other implementation known to those skilled in the art. The imaging subsystem 112 may be shared among one or more of the cell culture vessels 106.

[0113] The cell culture system 100 further includes a cell editing subsystem 114 for editing the cell culture 104. The cell editing subsystem 114 can edit the cell culture 104 at a regional, colony-specific, and / or cell-specific level. In this context, editing can include selective destruction and / or removal of cells or cell regions, as well as non-destructive manipulation of cells (including intracellular delivery of compounds to cells or extraction of compounds from cells). The cell editing subsystem 114 can edit the cell culture 104 through a variety of directed energy mechanisms. In other words, the cell editing subsystem 114 can generate energy that is used directly to edit cells and / or convert one form of energy (e.g., light, mechanical) into another form of energy to achieve cell editing. Mechanisms by which the cell editing subsystem 114 acts on the cells in the cell culture include, but are not limited to, a robotic system that mechanically actuates a tip or tool throughout the cell culture, a magnetic actuator that interfaces with a magnetic tool that interacts with the cell culture, a system configured to selectively apply an electric field throughout a portion of the cell culture, an ultrasonic system configured to apply ultrasonic energy to a portion of the cell culture, a droplet or particle release / acceleration system designed to impact droplets or particles on a portion of the cell culture, an optical system designed to deliver optical energy to a portion of the cell culture, a combination of these, or any other implementation known to one of skill in the art. The cell editing subsystem 114 may be shared between one or more of the cell culture vessels 106.

[0114] Optical mechanisms for cell editing include, but are not limited to, optical systems that direct energy directly to cells in cell culture or the surrounding medium, optical systems that direct energy directly to particles or dyes added to the cell culture medium (including, but not limited to, particles functionalized to bind to specific cells or particles taken up by the cells), or optical systems that direct energy directly to particles or films on a surface adjacent to a portion of the cell culture, or any other implementation known to those skilled in the art. Optical mechanisms can manipulate cell cultures by several approaches, including, but not limited to, increasing the local temperature to the point where cells are destroyed by thermal damage, increasing the local temperature to cause boiling and / or bubble formation to detach a portion of the cell culture from the surface, or rapidly increasing the local temperature to affect mechanical forces on the local cell membrane, causing rapid bubble formation and subsequent collapse, or combinations thereof.

[0115] The cell culture system 100 may also include several sensors and controls 116 that can measure and act on the cell culture 104. For example, the sensors and controls 116 can perform functions such as measuring media conditions within the cell culture 104, replenishing fresh media, or adding reagents or gases to adjust media conditions for optimal cell culture growth. Sensors that detect conditions of the cell culture 104, cell culture media, and / or the surrounding cell culture vessel 106 include, but are not limited to, temperature sensors, humidity sensors, gas composition sensors including, but not limited to, O and CO concentration sensors, gas flow rate sensors, dissolved gas sensors including, but not limited to, dissolved O sensors, liquid flow rate sensors, and sensors that measure cell culture media components (e.g., nutrients, waste products, vitamins, metabolites, proteins, extracellular vesicles, cell mass, or cell debris) (including, but not limited to, light absorption sensors, light scattering sensors, mass spectroscopy sensor systems, optical or electrical pH sensors), and viscosity sensors.

[0116] Control devices that can interact with the cell culture 104 or cell culture vessel 106 include, but are not limited to, liquid handling systems that inject or extract various liquids into or from the cell culture 104 or cell culture vessel 106, environmental control systems that control the temperature or other environmental parameters of the cell culture 104 or cell culture vessel 106, power systems that provide power to the cell culture vessel 106, and mechanical or robotic systems that can move or manipulate the cell culture vessel 106 or portions thereof.

[0117] The computing subsystem 110 may be configured to control other components of the cell culture system 100 to perform a particular cell culture process on the cell culture 104 and generate an output cell product 118. The output cell product 118 may include both cells and cell-derived products, and may be collected from the cell culture 104. Output cellular products 118 that may be generated by the computing subsystem 110 include, but are not limited to, induced pluripotent stem cells, proteins (e.g., cytokines, antibodies, hormones), lipid particles (e.g., exosomes), viral particles, somatic cells (including, but not limited to, fibroblasts, mature blood cells and progenitor cells (e.g., CD34+ cells and erythroblasts), keratinocytes, epithelial cells (including blood- and urine-derived epithelial cells), Sertoli cells, endothelial cells, granulosa epithelial cells, neurons, pancreatic islet cells, epidermal cells, epithelial cells, hepatocytes, hair follicle cells, keratinocytes, hematopoietic cells, melanocytes, chondrocytes, lymphocytes (B and T lymphocytes), erythrocytes, macrophages, monocytes, mononuclear cells, fibroblasts, cardiomyocytes, and other muscle cells), any living somatic cell in general, and any combination of the above. The term "somatic cell" as used herein also includes adult stem cells.

[0118] The output cell product 118 can be measured by output cell product assays 120 (including, but not limited to, genomic profiling assays (e.g., PCR, qPCR, microarray, single-cell RNA-seq), whole exome sequencing (WES), whole genome sequencing (WGS), karyotyping, short tandem repeat (STR) analysis, sterility testing (testing for bacteria and viruses), or other phenotypic analyses including, but not limited to, cell surface antigen or intracellular staining and immunofluorescence or flow analysis), as well as cell viability, morphology, and migration assays, or potency assays such as self-renewal and teratoma formation assays, and germ layer differentiation assays) to determine key product parameters such as phenotype distribution, protein production, gene activation, and genomic structure. The output assay data can be communicated to the computing subsystem 110 to refine predictive models (based on image data, sensor data, and information from prior cell culture processes and other sources) for cell culture monitoring and control. Output cell product assays 120 include, but are not limited to, viability assays, cell counting, flow cytometry, immunostaining imaging assays, PCR assays (including but not limited to qPCR, ddPCR), RNA sequencing assays including single cell RNA assays, cell differentiation assays, embryoid body formation assays, trilineage differentiation assays, karyotyping assays, DNA sequencing, or any other implementation known to one of skill in the art.

[0119] The computing subsystem 110 is configured to collect data from a range of sources and organize it in a manner that allows prediction of the success rate / quality / functionality of the cell culture 104, often on a cell-by-cell, colony-by-colony, or region-by-region basis. For example, using local cell density and growth rate data obtained through analysis of a time series of label-free images provided by the imaging subsystem 112, along with data about the input cells (e.g., to control for patient-specific factors), the computing subsystem 110 can predict which regions of the cells are most likely to produce a superior cell product and which regions are least likely to produce a good product, based on multiple observed treatment histories and corresponding cell quality data measured by the output cell product assay 120. In situations where cell medium is limited or there is competition between cells for space within the cell culture vessel 106, the computing subsystem 110 can instruct the cell editing subsystem 114 to remove regions or individual cells predicted to be underperforming.

[0120] Another function of the computing subsystem 110 is to use cellular data derived from imaging related to environmental parameters, as well as sensor data from the sensors and controller 116, and assay data from the input cells 102 and / or output cell products 118 to preemptively adjust cell culture conditions according to cell number, growth rate, differentiation state, phenotype, or other factors, in addition to real-time cell culture medium readings. Using models trained in previous iterations, the computing subsystem 110 can adjust, using the controller 116, media conditions such as fresh media source, media type, temperature, pH, dissolved oxygen level, reagent or vitamin levels, or other overall cell culture characteristics. Similarly, the computing subsystem 110 can use cellular data obtained from imaging, optionally in conjunction with cell culture medium sensor data, to determine when the cell culture 104 is ready for harvest. Actuators utilized by the controller 116 include, but are not limited to, liquid handling robots, liquid circulation systems with valves and pumps, temperature control elements, pH controllers, gas exchange mechanisms for controlling dissolved gases, or any other implementation known to those skilled in the art.

[0121] Computing subsystem 110 can control cell editing subsystem 114 to edit cell culture 104 according to cell management algorithms (e.g., to maintain a specific cell density, to maintain a specific exclusion region within the cell culture vessel), in a timed manner (e.g., delivery of gene activation or gene editing compounds to cells at specific intervals), and / or as a result of predictions made by computing subsystem 110 (e.g., removal of cells predicted not to produce optimal levels of a desired phenotype or function). "Editing" can include both destruction (including apoptosis, lysis, physical removal) of cells and / or colonies, as well as selective delivery of compounds to cells and / or regions of cells via intracellular delivery mechanisms, or selective extraction of compounds from cells via intracellular delivery mechanisms or other types of cell manipulation.

[0122] The computing system 110 may be configured to perform a variety of image processing tasks, including but not limited to traditional image processing (including, but not limited to, filtering, normalization, contrast enhancement, z-stack processing, thresholding, histogram transformation, edge detection, correlation, convolution, frequency space operations, blob detection, morphological operations, localization, warping, object detection, object tracking, or combinations thereof), deep learning-based image processing (including, but not limited to, convolutional neural networks, fully connected neural networks, semantic and instance level segmentation, encoder-decoder networks, multi-scale algorithms, regression networks, visual attention models, visual field transformers, generative adversarial models, U-Net, ResU-Net, SegNet, X-Net, ENet, BoxENet, long short-term memory neural networks, and combinations thereof). The data may include elements implementing techniques such as, but not limited to, linear regression, nonlinear regression, hierarchical regression, generalized linear models, logistic regression, log-linear models, and non-parametric models, statistical models, pattern recognition, statistical learning (including but not limited to, linear regression, nonlinear regression, hierarchical regression, generalized linear models, logistic regression, log-linear models, and non-parametric models), machine learning (including but not limited to, decision trees, random forests, support vector machines, neural nets, deep learning, association models, sequence modeling, and genetic modeling), clustering techniques including hierarchical and non-hierarchical clustering, supervised machine learning models, unsupervised machine learning models, databases (including but not limited to, SQL databases and NoSQL databases), visualization tools for images, cell colonies, clones, and other data, combinations of these elements, or any other implementation known to one of skill in the art.

[0123] The computing subsystem 110 may also include data storage devices for storing image data, sensor data, results of data analysis, and program code executed by the computing subsystem 110. The computing subsystem 110 may also include input / output devices that allow a user to view data, monitor and control the cell culture system 100, or transfer data into or out of the cell culture system 100. For example, the computing subsystem 110 may include a display screen, a monitor, communication / interface ports, a keyboard, an audio system, etc. The computing subsystem 110 may be adjacent to other components in the cell culture system 100 (e.g., a local computer) or may be remote from other components in the cell culture system 100 (e.g., a cloud server). In some implementations, the computing subsystem 110 may have one or more components that are adjacent to other components in the cell culture system 100 and some components that are remote from other components in the cell culture system 100. The computing subsystem 110 may be configured to communicate with other components within the cell culture system 100 using wired and / or wireless connections (e.g., Ethernet cables, fiber optics, Wi-Fi, Bluetooth), and may be configured to communicate with external components using wired and / or wireless connections. The computing subsystem 110 may also have additional functionality and components not disclosed herein, as would be apparent to one skilled in the art.

[0124] Cell culture system 100 can be configured to enable an extended cell culture process to be performed within a single cell culture vessel 106 using cell editing subsystem 114. When commanded by computing subsystem 110, cell editing subsystem 114 can selectively remove cells from the cell culture so that the cell culture does not overgrow the cell culture vessel, thus eliminating the need for frequent transfers (“passaging”) that can stress the cell population, disrupt cellular processes, introduce potential sterility and contamination issues, and preclude tracking of cell-, region-, colony-, or clone-specific behavior over time. Thus, the combination of continuous monitoring via image and sensor data enabled by the single-vessel process can enable computing subsystem 110 to predict optimal regions or cells to remove to maintain a cell density low enough to remain within a single cell culture vessel 106. In this process, cell culture system 100 can also perform in-situ cell “sorting” to enrich the population according to real-time measurements.

[0125] FIG. 2 is a flowchart of an exemplary method 200 of operating a cell culture system according to various implementations. Method 200 can be performed by a cell culture system such as cell culture system 100. At block 202, input cells are seeded into a cell culture vessel that is fully imageable and capable of supporting the cell culture for the duration of the cell process. This results in a fully imageable cell culture in a single vessel. The cell culture vessel can provide a sealed, sterile environment for the cell culture process. At block 204, the cell culture process can be performed on the single-vessel, fully imageable cell culture. The cell culture process can be sustained in the single vessel for the duration of the process (as opposed to, sometimes selectively, transferring cells from vessel to vessel to maintain a characteristic density). The cell culture process can be monitored and controlled by a computing subsystem within the cell culture system.

[0126] At block 206, cells may be observed using the imaging subsystem to acquire a complete, continuous, and rich time series of cellular data. At block 208, the computing subsystem may analyze the cellular data to develop a high-fidelity predictive model of cellular outcomes. The computing subsystem may utilize the predictive model to dynamically adjust the cell culture process. For example, at block 210, the computing subsystem may control the cell editing subsystem to selectively remove cells from the cell culture to de-densify the cell culture. The selective removal may then be optimally configured to improve the predicted yield, functionality, phenotype, or other characteristics of the output cell product. Method 200 may iterate through the steps of collecting imaging data, refining the predictive model, and editing the cell culture until an output cell product is generated at block 212.

[0127] At block 214, an output cell product assay 214 can be performed on the output cell product at the end of the cell culture operation. The results of the assay can be used along with the time-series cell data to adjust the predictive model at block 208. In some cases, the output cell product can be dynamically collected from the process (e.g., a subset of cells can be selected and removed from the cell culture, or a cell product within the medium can be removed from the cell culture), and the corresponding assay results can be immediately fed back into the predictive model. In this way, method 200 enables a fully automated method for dynamically processing and editing a cell culture, from input cells to output cell product. This enables a faster, more accurate cell culture process without the time and expense of manual human intervention, thereby reducing the time and cost to generate the output cell product. This approach is also easily scalable to enable large-scale biological manufacturing.

[0128] Clonally reprogrammed iPSCs Induced pluripotent stem cells (iPSCs) have the potential to revolutionize regenerative medicine. Their ability to self-renew, differentiate into any cell type in the body, and be manufactured from small patient tissue samples makes them an ideal starting material for personalized cell and tissue therapies. The same genetic plasticity that allows these cells to be used to manufacture biologics also makes them susceptible to selection pressures, potentially putting products and processes at risk if altered.

[0129] However, there are several obstacles to constructing cost-effective, safe, and efficient hiPSC-derived cell therapies. Building a master cell bank (MCB) of hiPSCs using current protocols is extremely labor- and time-intensive (up to 4 months), and the cost of generating clinical-grade iPSC lines is estimated at US$1.2 million. A large portion of these costs includes the labor and quality control (QC) measures required to ensure the safety and efficacy of the final product. Any method aimed at reducing these costs would significantly aid in enabling cost-effective manufacturing of hiPSC-derived cell therapy products.

[0130] One factor contributing to the low number of hiPSC lines passing QC assays is the heterogeneous nature of iPSC cultures. Variability exists both within and across iPSC lines with respect to differentiation potential, tumorigenicity, epigenetic profile, and other parameters. The exact reasons behind this remain unclear and may be related to differences in source material, protocols, or operator technique. Nevertheless, this points to the need for more standardization and automation of the entire iPSC manufacturing and characterization technology, which could help minimize heterogeneity within MCBs and achieve a well-controlled process that enables consistent production of products. If the cell bank is non-clonal, any potential changes made to upstream processes (e.g., raw materials, process parameters, manufacturing plant) could exert selective pressure on the cultures, resulting in changes to the manufacturing process or final product. Clonality is a critical step in stable cell line development (CLD) in the biotherapeutic workflow and is closely monitored by government regulatory agencies. If clonality is not sufficiently demonstrated, regulatory agencies such as the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) may require additional manufacturing controls, which can increase the cost of clinical trials and delay the drug's arrival at patients.

[0131] Several methods for reprogramming iPSCs exist, including genomic integration, non-genomic integration, minicircle vectors, Sendai protocol, mRNA, self-replicating RNA, CRISPR activators, and recombinant proteins, each of which is summarized herein.

[0132] Genome integration method: One of the most commonly used methods for reprogramming is the integration of reprogramming factors into genome by lentivirus or retrovirus transduction.Although this method is highly efficient, it may cause the permanent unregulated integration of exogenous genes into genome, and may have oncogenic potential, so it is not suitable for use in therapeutic approaches.

[0133] Non-genomic integration methods: Non-genomic integration methods (footprint-free) include several methods for exogenously expressing reprogramming factors and RNA components from either episomal DNA vectors, RNA viruses, or messenger RNA (mRNA). Among integration-free methods, the episomal method is a technically simple, rapid, convenient, and reproducible approach for generating iPSCs. However, episomal vectors have lower reprogramming efficiency compared to viral vectors. Furthermore, in many studies using episomal systems, transcription factors were individually delivered by nucleofection. However, due to differences in vector uptake by nucleofection, gene expression levels vary widely between cells.

[0134] Minicircle vectors: Minicircles are DNA vectors that lack a bacterial backbone and contain transcription units commonly found in episomal plasmids. Therefore, they are relatively small compared to other commercially available vectors. Their small size and ability to evade immune responses result in high expression of foreign genes both in vitro and in vivo. Minicircles have also shown potential in preclinical gene therapy research, and proof-of-concept studies combining minicircle vectors and stem cells suggest a potential regenerative tool for clinical application.

[0135] Sendai: Sendai virus is a single-stranded RNA virus that does not integrate into the host genome or alter the genetic information of the host cell. Because the virus remains in the cytoplasm, it is diluted out of the host cell approximately 10 passages after viral infection. Sendai virus can infect a wide range of cell types, both proliferating and quiescent, with high transduction efficiency. Expression of transgenes delivered by Sendai virus is detectable as early as 6–10 hours after transduction, with maximum expression detected >24 hours after transduction. Sendai-based reprogramming vectors have been used successfully to reprogram neonatal and adult fibroblasts and blood cells.

[0136] CRISPR activation (CRISPRa): CRISPRa uses a catalytically inactivated CRISPR-Cas9 system (dCas9) fused to a transactivator domain for transcriptional activation of endogenous genes without DNA editing. Highly efficient, multiplexed CRISPRa reprogramming of fibroblasts has recently been reported with improved fidelity. Activation of the reprogramming gene's endogenous promoter using CRISPRa improves the quality of human pluripotent reprogramming.

[0137] Expression of reprogramming factors using mRNA offers an alternative method for generating transgene-free iPSCs. It has been shown that in vitro transcribed mRNA can efficiently express reprogramming factors when transfected into human fibroblasts. While reprogramming factor mRNA is commercially available, this method is labor-intensive, requires daily transfection of mRNA for seven consecutive days, and has limited success in reprogramming blood cells. However, despite significant progress in developing synthetic mRNA-based reprogramming approaches, one of the major obstacles to this method remains the elicitation of an innate immune response after multiple daily mRNA transfections, resulting in increased cellular stress and severe cytotoxicity.

[0138] Self-replicating mRNA (srRNA): An alternative to mRNA-based reprogramming is the use of srRNA. Structurally, srRNA mimics its synthetic mRNA counterpart and contains the coding sequences for the "Yamanaka" transcription factors Oct4, Klf4, Sox2, and cMyc, as well as four nonstructural proteins that enable its replication. The application of srRNA allows for the prolonged duration of protein expression without the need for multiple daily transfections, maintaining the protein expression required to reprogram cells.

[0139] Recombinant protein: Protein-based hiPS cell technology offers a novel and potentially safe method for generating patient-specific stem cells that does not require ex utero embryo destruction. This system completely eliminates genome manipulation and DNA transfection, resulting in human iPS cells suitable for drug discovery, disease modeling, and future clinical translation. However, the generation of p-hiPS cells is very slow and inefficient and requires further optimization. It has been suggested that p-hiPS cells may be generated more efficiently by using purified reprogramming proteins, particularly because the use of whole protein extracts limits the concentration of factors delivered to target cells.

[0140] Due to the plastic nature of somatic cells during reprogramming, hiPSCs can be generated from several cell sources that may be categorized into two groups: adherent and suspension, each with various challenges and advantages, which are discussed herein.

[0141] Fibroblasts and other adherent cells: Fibroblasts are the most commonly used primary somatic cell type for iPSC generation. Their various properties have supported their use in innovative iPSC generation experiments. One major advantage is their high availability, as they can be easily isolated from skin biopsies. Furthermore, their culture, propagation, and cryopreservation characteristics are simple with regard to nutrient requirements and viability in culture. However, the required skin biopsy remains an invasive approach, a major drawback to using fibroblasts as starting material. In addition, skin fibroblasts have been shown to accumulate mutations, particularly over the lifespan of an individual, that can adversely affect the outcome of the reprogramming process. Other adherent cell types used for reprogramming include keratinocytes from hair follicles and skin biopsies, epithelial cells derived from urine and blood, synovial cells, and beta islet cells. The compatibility of all potential somatic cell types with existing and emerging reprogramming methods needs to be evaluated by those skilled in the art.

[0142] Suspension cells: CD34+ blood stem cells and erythroblasts purified from peripheral blood mononuclear cells (PBMCs) are one of the most studied cell types as starting material for reprogramming. This is primarily due to their ease of collection via blood draw and the low number of mutations these cells accumulate over their lifespan that can adversely affect outcomes. All reprogramming methods, except mRNA electroporation, have been used successfully to reprogram these cell types.

[0143] Ensuring clonality is part of an overall control strategy for cell-based products. It improves process consistency and directly impacts product quality and safety. However, for cell-based biologics entering the clinical phase, no single regulatory document explicitly states that cell banks must be monoclonal, primarily reflecting the inability of current technology to ensure monoclonality. However, starting with a monoclonal population maximizes the potential for optimizing the manufacturing process by reducing variability associated with heterogeneous cell behavior within cultures.

[0144] The only current method capable of distinguishing monoclonal from polyclonal populations within established cell lines is fluorescence in situ hybridization (FISH). This relies on random monoallelic expression of genes (so-called allelic exclusion), where a subset of human genes is typically expressed at a single allele in a certain fraction of cells within a tissue, regardless of the allele's parental origin. It is hypothesized that application of FISH to assess allelic expression patterns within one or more of these genes would enable the differentiation of monoclonal from polyclonal cell populations. However, while FISH has been quite successful in determining clonality in B and T cell lines due to the specific genetic recombination events that occur in these cells, applying FISH to other cell types that do not naturally undergo genetic recombination (e.g., hiPSCs) has proven technically challenging and incompatible with reliable high-throughput analysis of samples. Therefore, due to the lack of a biological assay, current methods for assessing hiPSC clonality rely on image-based determination of the single-cell origin of the culture and / or statistical methods that reduce the probability of cells originating from multiple cells within the culture. Several clonal strategies are described herein.

[0145] Single-cell plating (limiting dilution): To generate a more uniform, homogeneous population of hiPSCs, many laboratories have opted for clonal derivation of cell lines. By plating a single hiPSC per growth area for expansion, the resulting product is a clonal population of cells, with each cell being genetically and phenotypically more similar to other cells in the same culture than to those in hiPSC cultures with non-clonal origins. Single-cell plating can involve several methods, from limiting dilution to cell sorting. The single-cell origin of the culture is particularly important for gene-edited hiPSCs, where each cell in the culture must retain the edited version of the gene. Unfortunately, the process of generating clonal cultures from single cells poses significant challenges for cells that require contact with neighboring cells for survival. As a result, hiPSC survival rates after single-cell plating are very low, and cells that undergo proliferation and expansion often fail final quality control, even though they have acquired mutations beneficial for single-cell survival.

[0146] Low-density plating (repeated colony picking): To avoid the need to plate hiPSCs at single cells, many laboratories and publications rely on statistical probability modeling to plate hiPSCs at low density and derive "clonal" populations by manually picking and replating fragments from single colonies several times, either manually or using techniques such as ClonePix. This has been shown to result in highly homogeneous hiPSC cultures, but has not provided absolute proof of clonality. This is primarily because plated cells may reside within a distance of 150 μm of each other, allowing cells to migrate and form polyclonal colonies.

[0147] Clonality assay: Currently, there are no assays that address the clonality of existing hiPSC cultures. To ensure absolute clonal origin, imaging-based techniques to track single cells during expansion and MCB generation have been proposed by the FDA.

[0148] One of the quality aspects required for hiPSC-derived cell therapy products is ensuring the complete exclusion of reprogramming materials. In the case of integration methods, this requires the use of an excisable gene cassette (e.g., the Cre-lox system) engineered into a viral vector encoding the reprogramming factors. Upon activation, an exogenous enzyme (e.g., Cre recombinase) cleaves the DNA around the insertion site and removes the cassette containing the reprogramming factors. The cell's own DNA repair system then repairs any remaining breaks in the genome, and the cells are considered "safe" and ready for downstream applications, including cell therapy. Sequencing of the cell population is required to ensure complete excision of the cassette.

[0149] For non-integrative reprogramming methods, it is sufficient to demonstrate that DNA, mRNA, or viral vectors (e.g., Sendai) are no longer detectable by qPCR. The mechanism of DNA elimination in episomal and microcircle methods relies on cell growth-based dilution of the reprogramming plasmid in the cell's progeny. Additionally, elimination depends on the type of replication origin used to drive replication of these plasmids, which directly impacts the rate at which the plasmid is diluted below the detection threshold.

[0150] The time required for complete elimination of DNA-based non-integrated reprogramming materials varies significantly between methods and clones and can take 40 to 120 days, significantly slowing the manufacturing process. Any method that allows for faster and more consistent elimination of reprogramming methods would enable more cost-effective and safer cell therapy production. Using mRNA-based reprogramming has the major advantage of generating footprint-free hiPSCs much faster than other methods. Synthetic mRNA generally degrades within 48 hours after its entry into cells. However, due to its rapid degradation, up to 14 consecutive transfections are required to maintain sufficient levels of protein expression and reprogram cells. Therefore, synthetic mRNA-based reprogramming is better suited to reprogramming robust cell types such as fibroblasts and epithelial cells, instead of blood stem cells, which are sensitive to multiple transfections. To overcome the challenge of multiple transfections and generate footprint-free hiPSC lines within 40 days, a novel approach using srRNA can be used. These synthetic mRNAs contain additional genetic elements in their structure, which allow them to replicate once inside mammalian cells. Depending on the type of replication element, srRNA can persist in the cell for up to 30 days, after which it is rapidly removed by cellular type I interferon activity following withdrawal of the interferon inhibitor B18R.

[0151] All of the non-integrative methods mentioned above have been shown to successfully reprogram somatic cells into hiPSCs. However, high variability among clones derived using these methods has hindered their commercial production. One of the biggest sources of this variability is the initial reprogramming cargo load introduced into the cells. Currently, there is no method to control the load of DNA, RNA, or protein delivered to each cell in culture by transfection. This depends on several factors, such as the cell cycle stage, metabolic activity, and cell surface area of ​​the transfected cells. However, the amount of cargo entering the cells can directly affect several aspects of the reprogramming process, such as reprogramming efficiency and the rate of exogenous material clearance, and therefore production time. In fact, due in part to these factors, significant variability among clones is often observed, resulting in highly heterogeneous, non-clonal cultures of hiPSCs. The ability to track and analyze single cells during the reprogramming and expansion process and ensure clonality using image-guided algorithms may provide a powerful tool to distinguish fully reprogrammed from partially reprogrammed clones. Especially when combined with qPCR-based quantification of remaining reprogramming material within each clone during the early stages of reprogramming, our cell culture system for growing hiPSCs may provide great insight into selecting the best clones to accelerate the production of safe hiPSCs.

[0152] In summary, challenges facing rapid and relatively inexpensive large-scale reprogramming of iPSCs include low yields and inconsistency in obtaining high-quality iPSC clones. This is exacerbated by the inability to observe reprogramming behavior during the reprogramming process, inconsistent cell handling, and frequent passaging, which introduces variability into the cells. Additionally, ensuring clonality in iPSC cell cultures to reliably produce monoclonal iPSC output cell products is challenging. In addition to inconsistent behavior during reprogramming observation, low fidelity QC results and / or high QC volume / cost make consistent monoclonality even more challenging.

[0153] The systems and methods disclosed herein provide a reliable, automated process for single-clonal reprogramming of iPSCs, and particularly hiPSCs. The cell culture systems disclosed herein (e.g., cell culture system 100) can be used to generate iPSCs that are the result of a true clonal reprogramming process, in which a single iPS candidate cell or cell colony is isolated using a cell removal mechanism (e.g., cell editing subsystem 114) that acts on other cells and confirmed by imaging. The colony(s) resulting from the expansion of this single cell are then isolated from colonies growing from other cells, optionally using a cell removal mechanism that acts on clonal cross-contamination cells, with removal coordinated and confirmed by imaging and image analysis. The colony(s) of the single starting cell are then isolated to form the final clonal output cell product. The entire cell culture process may be performed in a closed system, such as a closed cassette system. Cell culture vessels do not need to be opened or exposed to the external environment for medium changes, imaging, cell editing, and other cell culture process manipulations. Thus, the cell culture systems herein are configured to grow monoclonal cell colonies (eg, iPSC colonies) within a closed system.

[0154] In some implementations, isolation of a single clone from multiple clonal colonies is achieved by a cell removal mechanism acting on other colonies, with removal coordinated and confirmed by imaging and image analysis. In some implementations, the cell removal mechanism includes at least a pulsed laser system. In some implementations, the entire process up to the output cell product is performed within a single cell culture vessel. In some implementations, cells are reprogrammed in a sealed microfluidic environment, such as a sealed cassette system.

[0155] The cell culture system disclosed herein offers several advantages over prior art techniques for monoclonal reprogramming of iPSCs. For example, the cell culture system can be used to track reprogrammed cells at the single-cell level or at the cell cluster / colony level, and a precise laser system can be used to remove any unwanted cells in the cell culture. Unwanted cells can be analyzed and predicted by an image-based algorithm during any stage of reprogramming and expansion, and, according to this prediction, can be any cells that do not pass QC or manufacturing requirements at the end of the manufacturing process. QC requirements focus on ensuring the safety and potency of the output cell product and are determined by regulatory agencies. Manufacturing requirements are specific to cell culture systems and aim to reduce product costs and manufacturing time, including, but not limited to, eliminating cells that divide too slowly, cells with a high reprogramming cargo load, and cells that migrate and are difficult to track.

[0156] The cell culture system is also agnostic to the starting material. It can be configured to reprogram fibroblasts or other adherent cells, such as keratinocytes, epithelial cells, or synoviocytes, regardless of the reprogramming method. Using the system's image-based algorithms, fibroblasts can be distinguished from newly reprogrammed cells based on a set of phenotypic characteristics specific to pluripotent stem cells, including, but not limited to, cell morphology, cell proliferation rate, chromatin condensation, nuclear-to-cytosol ratio, and cell migration patterns. The cell editing subsystem of the cell culture system can then be used to remove unwanted adherent cells.

[0157] When using the cell culture system disclosed herein to reprogram suspension cells, such as CD34+ stem cells or erythroblasts, the number of cells adhering to the cell culture surface is significantly reduced after reprogramming. Only about five days after transfection(s), cells sufficiently loaded with reprogramming agent begin to adhere and form colonies of fully or partially reprogrammed cells. As with the above-described method using adherent cells, the cell culture system is trained to distinguish the most promising single-cell-derived colonies at an early stage and maintain them in isolation by removing any unwanted cells surrounding the emerging colonies and, eventually, all other cells within the growth area.

[0158] Additionally, the cell culture system disclosed herein does not require single-cell plating, limiting dilution, or repeated colony picking to create clonal populations of cells. The process of deriving clonal hiPSC populations from single cells has previously proven highly inefficient due to increased cell death 48 hours after plating. The biological mechanisms behind this phenomenon are not well understood. To increase cloning efficiency, low-density plating is commonly used to ensure cell survival, but clonality is often compromised. Despite better survival, this method requires frequent imaging to ensure cells do not migrate and form polyclonal colonies. Once detected, these wells containing polyclonal colonies must be removed from the experiment, resulting in cost loss. In fact, it has been shown that hiPSCs tend to migrate and form colonies together when plated at a distance less than 150 μm apart. To date, no technology exists to control the distance between cells when plating at low density.

[0159] However, cell culture systems can be configured to fully reprogram hiPSCs plated at the highest density possible with a cell separation of at least 150 μm. Due to the random plating position of each cell, the cell editing subsystem can be configured to remove any cells that reside less than 150 μm from their neighbors to reduce the likelihood of polyclonal colony formation. To increase the number of monoclonal lines, low-density plating is often followed by repeated hiPSC colony picking, but this is not necessary when using cell culture systems. This directly translates to reduced production costs per clonal hiPSC line compared to methods based on single-cell plating or low-density plating followed by repeated clonal picking. An additional advantage of this approach is that the total number of cell divisions is minimized compared to forcing clonality after reprogramming. hiPSCs are particularly prone to genetic or karyotypic variations, and the burden of these variations is known to increase with the number of cell divisions (or associated "passages"). By enforcing clonality from the start of reprogramming, the entire population of hiPSCs obtained at the end of the reprogramming process can be used for quality control and the current application, rather than as input to the process starting again from a single cell.

[0160] Figures 3A-C illustrate portions of the process for iPSC reprogramming according to various implementations. Specifically, Figures 3A-C show the cell seeding and initial reprogramming stages, in which somatic cells are seeded into a cell culture vessel and reprogramming factors are delivered either prior to seeding or within the chamber itself. Figure 3A shows an exemplary cell culture chamber 302, shown here as a fluid chamber with two ports for filling / removing and media circulation. The cell culture chamber 302 is seeded (indicated by arrow 304), and then non-reprogrammed input cells 306 are allowed to settle within the cell culture chamber 302. For example, the reprogramming process may utilize CD34+ cells delivered with an episomal vector prior to seeding via electroporation. Figure 3B shows the emergence of pre-IPS cells 308 from a subset of non-reprogrammed input cells 306 after a period of time. Generally, to some extent, reprogrammed cells become attached to a surface with a support matrix. FIG. 3C shows an initial medium exchange in the cell culture chamber 302, where fresh medium 310 replaces the initial medium, and in the process, cells that have not begun to adhere (except pre-IPS cells 308) are washed away, as indicated by arrow 316.

[0161] 4A-B illustrate cell removal during the iPSC reprogramming process according to various implementations. Cell removal can be performed to restrict initial cell attachment and growth to areas undisturbed by liquid, thermal, or chemical gradient effects at the edge(s) of the cell culture vessel. FIG. 4A shows a design region 402 within a cell culture chamber designated for initial cell emergence. Design region 402 can be designed to allow space for emerging colonies to grow within design region 402 before hitting a designated boundary away from the edge of the cell culture chamber (shown by the outer dashed line). Cells outside this initial boundary, shown as cells 404, are identified and removed using a cell removal mechanism (e.g., cell editing subsystem 114 in FIG. 1). This cell removal mechanism may be optical (laser), acoustic (focused ultrasound), mechanical, or the like, and must lyse, disrupt, and / or lift the cells from the growth surface. In either case, this removal mechanism is operated by a computing system (e.g., computing subsystem 110 in FIG. 1). Preferably, the cell removal mechanism performs this operation without the need to open the cell culture vessel (i.e., is compatible with closed vessel / media systems). The cell removal mechanism can target individual cells identified via imaging or sweep the entire area outside a specified boundary. Figure 4B shows the resulting cell population after removal of cells outside the boundary and appropriate washing to remove cell debris.

[0162] Figures 5A-C illustrate cell isolation during the iPSC reprogramming process according to various implementations. A cell removal mechanism (e.g., cell editing subsystem 114) can be used to isolate single cells within a cluster of emerging iPSC candidates. Figure 5A shows a cell culture chamber containing a mixture of source somatic cells (unreprogrammed) and emerging iPSCs in small colonies 502. Each of these colonies 502 often corresponds to a single source cell. For example, when CD34+ cells are reprogrammed using episomal vectors delivered via electroporation, the reprogramming efficiency is approximately 0.05% per cell. Therefore, in a vessel containing 10,000 CD34+ cells, an average of 5 cells are expected to emerge as iPSCs. Statistically, these cells are unlikely to emerge directly adjacent to each other, but in some cases, they may be close enough together to fuse into a single colony and lose their monoclonality.

[0163] The cell culture system disclosed herein can ensure monoclonality using a combination of imaging, image processing from label-free images to determine precise cell position coordinates, a method for computing an optimal set of cell removal, and a mechanism for individually removing or terminally destroying selected cells. This results in isolated single living cells within a sufficiently large area to prevent "cross-contamination" between already emerged iPS clones or with iPS cells yet to emerge from neighboring somatic cells. This selection and removal process is illustrated in Figure 5B. Selected iPS candidate cells 504 are identified and have a virtual perimeter 506 drawn around them. Any cells within these perimeters that are not selected iPS candidates are marked for removal / destruction, and a cell removal mechanism dissolves / irreparably destroys / removes them from the culture, as indicated by the outlined cell colony 508. After removal, the selected emerged iPS cells remain as single cells within the perimeter, as shown in Figure 5C by the "clonal perimeter" 510.

[0164] Figures 6A-C are images showing cell isolation during the iPSC reprogramming process according to various implementations. Figures 6A-C show actual images captured from a cell culture chamber undergoing the process described with reference to Figures 5A-C. The cells in Figures 6A-C are iPSCs that emerged from CD34+ cells during reprogramming. In Figure 6A, several CD34+ cells 604 (approximately 10 microns in diameter) that show no signs of reprogramming are located near a cluster of cells showing signs of successful reprogramming, including "selected" cells 602, and several connected "unselected" cells 606. As mentioned above, the goal is to isolate the selected cells as the only viable cells within a localized region. Figure 6B shows a pattern of dots 608 targeted by a cell removal mechanism (e.g., cell editing subsystem 114), which in this case is a nanosecond pulsed laser (<10 ns pulse width, 532 nm) focused on a 20 nm titanium semi-absorbing film on the cell growth surface. The resulting explosive microbubbles lyse and detach the target cells, but induce little collateral damage to surrounding cells, particularly the selected iPS candidate cells 602. In Figure 6C, cell viability staining was used to determine the viability of the selected cells 602, and it is demonstrated that no other live cells remain within the imaging field.

[0165] 7A-C illustrate non-iPS cell removal during the iPSC reprogramming process according to various implementations. For example, certain cells may begin to differentiate into non-iPS cell types during cell culture and therefore need to be removed. In some cases, a partial reprogramming failure may occur, causing a source somatic cell to differentiate into a non-iPS cell 702, potentially contaminating the emerging iPSC candidate cells or colonies 706. These cells are located by the computing subsystem using image analysis and classified as non-source and non-iPS candidate cells based on their unique morphological characteristics. Non-iPS cells can be distinguished from unreprogrammed source cells 704 or emerging iPSC candidate cells or colonies 706 that should remain in the cell culture. To prevent non-iPS cells from proliferating and contaminating the iPS cell culture, these errant cells are identified and then removed using a cell removal mechanism (e.g., cell editing subsystem 114), as shown in FIG. 7B. Non-iPS cells can be identified, located, and targeted by the cell removal mechanism. The cell culture chamber then contains only the source somatic cells and iPS candidate cells, as shown in Figure 7C.

[0166] 8A-B illustrate the removal of neighboring cells around an iPSC colony during the iPSC reprogramming process according to various implementations. This can ensure the continuous clonality of the iPSC colony. FIG. 8A shows an example in which three clonal iPS-like clones with corresponding exclusion zones 802 are designed to maintain clonality by removing any cells that do not clearly belong to the original clonal colony. The size of these zones can be determined by the interval between imaging / selective cell removal, the expected areal growth rate of the colony, and the expected rate of emergence of other iPS candidates from somatic cells. Any neighboring cells 804 detected within these clonal zones that do not clearly belong to the clonal colony can be considered contaminant cells, marked for removal, and removed. After removal (which may include direct removal or subsequent removal via disruption and washing), the exclusion zone 802 once again clearly represents the original clone. Throughout the selective removal operations shown in this disclosure, reimaging after removal and washing can be used to confirm removal of the targeted cells. Any remaining cells can be re-targeted using the cell removal mechanism (e.g., cell editing subsystem 114) until removal is complete.

[0167] 9A-B illustrate the removal of cells detached from iPSC colonies during the iPSC reprogramming process according to various implementations. Cells that migrate away from iPSC candidate colonies beyond the perimeter centered on those colonies can potentially compromise the clonality of confirmed clonal colonies. This operation is similar to the process described with reference to FIGS. 8A-B, except that it applies to cells whose origin cannot be traced back to the clone occupying the exclusion zone 902. If these potentially escaping cells 904 cannot be traced back to their colony of origin as potentially clones of that colony, they are considered contaminant cells and must be removed. If iPS-like cells can be traced back to a local clone, the exclusion zone 902 may instead be expanded to include these cells. Note that the circular zones shown in FIGS. 9A-B herein are merely exemplary. In most cases, exclusion zones are distance-based metrics based on the closest cells known to belong to a particular clone to define polygonal exclusion zones. Pure clonal zones are shown in Figure 9B, with no unrelated cells present within their exclusion zones 902, after the cell removal mechanism (e.g., cell editing subsystem 114) has removed potentially escaping cells 904.

[0168] 10A-B are diagrams illustrating the removal of non-iPS cell candidates during the iPSC reprogramming process according to various implementations. Once new iPS colonies are unlikely to emerge from the somatic cells, the remaining somatic cells (e.g., CD34+ cells delivered with an episomal vector), as shown in FIG. 10A, are considered contaminating cells and are dynamically removed from the cell culture chamber, targeting non-reprogrammed cells 1004 and leaving only iPSC colonies 1002. After the remaining non-reprogrammed cells are removed, only iPS colonies 1002 remain, as shown in FIG. 10B.

[0169] 11A-C illustrate the removal of cell colonies during the iPSC reprogramming process according to various implementations. For example, cell colonies can be removed when two clonal colonies of different clonal origins collide and are at risk of cross-contamination. The cell culture system disclosed herein advantageously allows multiple clonal colonies to coexist within a cell culture vessel without the possibility of clonal cross-contamination (i.e., the generation of non-clonal colonies) through continuous imaging, tracking, and isolation of clonal colonies. As a result, the behavior of each colony is more uniform due to its clonal origin, and ultimately, there is no need for a post-reprogramming clonal process to ensure effective quality control results. Clonal behavior can be tracked over time, and if a clone is determined to be poor or if two clones are at risk of colliding within a vessel, one clone may be selected for removal.

[0170] FIG. 11A shows two clonal colonies 1104 and 1106 that have been determined to be at risk of collision within the next imaging / editing period, as indicated by boundary 1102. In this example, clone 1106 has been determined to have a high probability of producing a good iPSC clone. These determinations may be made by a computing subsystem (e.g., computing subsystem 110) in cooperation with a cell imaging subsystem (e.g., imaging subsystem 112), or may be determined by manual observation and selection, or a combination of automatic and manual observation / selection. As a result, as shown in FIG. 11B, the colliding (by prediction) but recessive clone 1104 is selected for removal. After removal, the selected clone 1106 is now no longer at risk of collision or inter-clonal contamination, as shown in FIG. 11C.

[0171] Figures 12A-B are images illustrating the removal of cell colonies during the iPSC reprogramming process according to various implementations. In the example shown in Figures 12A-B, a final decision can be made to select a single clone / colony to create a single clone sample within a cell culture vessel. In Figure 12A, a desired colony 1202 is selected manually or automatically (e.g., by a computing subsystem). Several other (unselected) colonies 1204 are present within the cell culture vessel. In this example, the image shown is a bright-field microscope image of a single well of a 96-well microplate. The brighter (colony) areas are actually a series of points plotted across the image representing the extracted (x,y) coordinates of each cell, as predicted by a deep learning algorithm that effectively converts the bright-field image into cell nuclei coordinates. The polygonal image of the desired colony 1202 represents the selection of those cells selected to remain within the vessel. The reversal of this cell selection is used to guide removal. 12B shows an image taken 24 hours after cell ablation with a pulsed laser, where the selected colony 1202 is the only remaining (and growing) colony. The selected colony 1202 has grown alone and the microplate well has been opened to expand it, removing the other colonies.

[0172] 13A-C illustrate the selection of cell colonies during the iPSC reprogramming process according to various implementations. This shows the final selection of a single clonal colony to generate the output iPS cell product. A cell removal mechanism (e.g., cell editing subsystem 114) is used to remove any other cells or colonies that do not arise from the selected clone. In FIG. 13A, the selected colony 1302 is retained, while any other colonies 1304 are marked for removal and removed by the cell removal mechanism, as shown in FIG. 13B. Finally, as shown in FIG. 13C, only the selected colony 1302 remains in the container. The absence of any other cells in the well can be confirmed by one or more subsequent imaging runs, and the cell removal mechanism (and appropriate washing) is used to remove any remaining cells until it is confirmed that only the desired clonal colony 1302 is present.

[0173] 14A-C illustrate the spreading of cell colonies within a cell culture chamber during an iPSC reprogramming process according to various implementations. Specifically, a cell removal mechanism (e.g., cell editing subsystem 114) can be used to detach one or more cell colonies derived from a common cell (i.e., a monoclonal colony) and subsequently detach and distribute the colony(ies) throughout the cell culture vessel to maximize space for clonal expansion. In the example shown in FIGS. 14A-C, the clonal colony is dissected into fragments, then gently lifted from the cell culture surface, and then distributed throughout the cell culture chamber to seed a uniform expansion of the clone. In FIG. 14A, a clonal colony 1402 is treated with a selective cell removal mechanism that acts on a subset of cells 1404, which are then removed from the cell culture vessel. After removal of the subset of cells 1404 as shown in FIG. 14B, the clonal colony 1402 is fragmented. Individual colony fragments are easily lifted from the cell growth surface using trypsinization or any similar process. Once suspended, the fragments can then be redistributed around the vessel, as shown in Figure 14C. Figures 14D-E show initial colonies of controlled density spread throughout the growth chamber. As shown in Figure 14D, a single colony is split into four fragments using laser treatment. The split fragments of the colony then continue to grow with some preference outward after washing and continuous cell culture, as shown in Figure 14E.

[0174] 15A-B illustrate the removal of cells outside a designated region during an iPSC reprogramming process according to various implementations. Cells growing outside a designated region of a cell culture chamber can be removed to prevent cell growth in boundary regions of the cell culture vessel where media conditions, chemical gradients, temperature, flow rates / shear, and convection may not be uniform or consistent. FIG. 15A shows several cells 1504 outside a designated region 1502 of a cell culture chamber. The cells 1504 can be identified and removed using a cell removal mechanism (e.g., cell editing subsystem 114) so ​​that all cells in the cell culture chamber subsequently grow within the designated region 1502.

[0175] 16A-C illustrate the removal of various cells during the iPSC reprogramming process according to various implementations. For several reasons, cells may be removed during the cell culture process: (a) proliferating outside of designated growth areas; (b) growing to excessive density within the colony; or (c) including spontaneously differentiating cells. FIG. 16A shows a cell culture chamber containing various cells, including iPSCs 1602 at a desired density but without spontaneously differentiating cells, spontaneously differentiating cells 1604, an area of ​​an iPSC colony 1606 that is too dense due to internal colony growth, and cells 1608 that have extruded beyond the established boundaries for cell growth. It is preferable to control the internal density of the iPSC colony so that all cells remain observable by label-free imaging, all cells remain removable by a cell removal mechanism (e.g., cell editing subsystem 114), and cells do not grow to a density at which they spontaneously differentiate or form 3D structures prone to differentiation. As shown in Figure 16B, spontaneously differentiating cells 1604, dense colonies 1606, and border cells 1608 are all designated as contaminating cells that are targeted for removal 1610 via imaging (e.g., imaging subsystem 112) and downstream calculations (e.g., computing subsystem 110). The cell culture system can determine the coordinates of the target cells 1610 and then remove them using a cell removal mechanism. The resulting cell culture is free of these potential obstacles to high-quality clonal iPSC cultures, as shown in Figure 16C.

[0176] 17A-C illustrate fragmentation of cell colonies within a cell culture chamber during the iPSC reprogramming process according to various implementations. Once a clonal cell colony reaches maximum density (e.g., grows to fill the entire designated growth area of ​​the cell culture chamber), a cell removal mechanism (e.g., cell editing subsystem 114) repeatedly removes a portion of the cells to allow multiple divisions of the iPS cells (conventionally known as "passaging," but as implemented herein, does not require removal of the clonal iPS cells from the cell growth surface or cell culture vessel). For example, this may enable the elimination of reprogramming vectors, including, but not limited to, episomal vectors, Sendai virus, or self-replicating mRNA. In this example, the cell removal mechanism is used to reduce cell number and expand the growth area, but the cells are removed in a biologically relevant manner, leaving the iPS cells in contact with neighboring clusters of cells.

[0177] A clonal iPSC cell culture 1702 approaching high or maximum confluency is shown in Figure 17A. Figure 17B illustrates a method for reducing cell number to allow cell division without overcrowding, thus eliminating vectors. That is, a cell removal pattern 1704 is calculated based on cell imaging, leaving an iPSC structure with adjacent contacts that maintains sufficient iPSC numbers and iPSC health. This is similar to the traditional inter-vessel passaging of aggregated iPSCs, but allows the process to be performed in a single vessel, greatly simplifying the process, reducing consumable usage, reducing stress on the remaining cells, and allowing the process to be performed inside a sealed, sterile vessel, isolated from other patient samples and potential contamination. A computing subsystem (e.g., computing subsystem 110) can determine the cell removal pattern 1704 from an image acquired from a cell imaging subsystem (e.g., imaging subsystem 112). Figure 17C shows the remaining cell colony 1706 after the cell removal mechanism has removed the cell removal pattern 1704. Cell colony 1706 can undergo further new cell divisions into the resulting gap while maintaining sufficient cell-to-cell connectivity to maintain cell health and chemical and mechanical signaling that is often lost during conventional passaging. It should be noted that several patterns are possible that meet these criteria, such as an "island-positive" pattern such as that shown here (where, on average, convex islands of cells remain and are surrounded by a network of the removed area), or an "island-negative" pattern where cells form a network around the removed convex area.

[0178] Figures 18A-B are images showing fragmentation of cell colonies within a cell culture chamber during the iPSC reprogramming process according to various implementations. Figures 18A-B are images showing the operations described with reference to Figures 17A-C on actual cells. Figure 18A shows a cell culture vessel (e.g., a single well in a 96-well plate) containing iPS cells labeled with calcein AM (a live cell stain). Near the top of the well, the iPS cells have reached a high density within region 1802. The cells were imaged using label-free brightfield imaging (not shown), and a deep learning network was used to extract the (x,y) coordinate locations of all cells. The cell locations were used to calculate local density. If the density within region 1802 was higher than desired, a pattern of cell removal was calculated that would leave an intact, continuous network of iPSCs. As can be seen from the difference between the images in Figure 18A (before selection and removal) and Figure 18B (after selective removal of cells), region 1802 has significantly reduced density, but still contains a viable network of iPSCs for further proliferation (as indicated by calcein AM cell viability staining). This process can be repeated to eliminate the reprogramming vector from the iPSCs. Another example of cell removal and subsequent regrowth is shown in Figures 18C-D. Figure 18C shows a high-density hiPSC cell culture that has been removed using laser microbubble lysis and washing. Figure 18D shows the regrowth of the hiPSC cell culture after 24 hours.

[0179] 19A-C illustrate the collection of cells within a cell culture chamber during an iPSC reprogramming process according to various implementations. In this example, a cell culture is prepared by using a cell removal mechanism (e.g., cell editing subsystem 114) to open gaps between small islands of cells, allowing subsequent removal with an agent such as trypsin to be performed gently (e.g., requiring less exposure time), and then removing the clonal iPS cells in suspension. FIG. 19A shows a clonal cell colony 1902 approaching maximum confluency, generated using the systems and methods disclosed herein. The cell population could be directly treated with trypsin for lifting and collection. However, in this example, a selective cell removal mechanism, as shown in FIG. 19B, can be used to selectively remove sparsely populated cells 1904, thereby breaking the clonal cell colony 1902 into smaller islands before lifting it into suspension. Finally, as shown in FIG. 19C, clonal cells 1906 derived from the clonal cell colony 1902 can be collected in suspension from within the cell culture vessel.

[0180] The operations described with reference to FIGS. 3A-19C can be performed by a cell culture system (e.g., cell culture system 100) as disclosed herein. In addition to providing a closed system for cell culture growth (e.g., a closed cassette system), the cell culture system can provide automated imaging, cell editing, cell collection, cell monitoring and prediction, and other cell culture functions. In some implementations, the cell culture system can operate in a fully automated manner with user control of the cell culture process via a user interface. In some implementations, the cell culture system can also operate in a semi-automated manner in which a user can manually perform one or more of the cell culture steps. For example, a user can manually observe the cell culture to identify cells and cell colonies to keep or remove, and the cell culture system can use automated cell editing functions to remove unwanted cells and cell colonies. Thus, the cell culture systems disclosed herein can be configured to generate a single clonal cell output product, such as a single clonal iPSC, using the operations described with reference to FIGS. 3A-19C within a closed system. The use of automated cell imaging and editing can help maintain cell culture clones during cell growth and expansion. Because the output cell product will be used in a variety of cell therapy and other medical applications, ensuring monoclonality is important for a variety of reasons, including patient safety, differentiation / treatment efficacy, and adherence to applicable laws, regulations, and standards regarding cell therapy utilizing the output cell product.

[0181] Cell culture density mapping, statistics and management In some implementations, the imaging subsystem disclosed herein is used to generate a map of cell density across at least a portion of a cell culture vessel. This density can be recorded over time as a time-series cell density map. The density map can be generated from label-free images using several methods, including, but not limited to, (1) predicting the location of individual cells or nuclei via a machine learning model such as a pre-trained convolutional neural network and then aggregating these locations into a local density map; (2) directly predicting local density from label-free images via a machine learning model such as a pre-trained convolutional neural network; and / or (3) predicting local density from label-free images via a set of conventional image processing operations, such as band-pass filtering, thresholding, and summation of multiple z-slices, followed by scaling to estimate the number of nuclei or cells within a local region. As described above, label-free images can include, but are not limited to, bright-field, dark-field, phase, quantitative phase, DIC, and other image types, each of which optionally includes multiple z-slices (focal planes).

[0182] Density maps can be generated at multiple scales, representing the span of the local region for which density is estimated. For example, the input bright-field image may have a resolution of 0.65 microns and three Z planes; the density mapping model may be trained using a ground truth density with a span of 20 microns (twice the sigma used in Gaussian filtering); the resulting map output has a resolution of 10 microns to capture this span. Additional density maps at lower resolutions may be generated, or the density map may be processed through image processing operators, such as bandpass filters, to identify specific features in the cell culture, such as colonies of specific sizes, colony margins, or individual cells.

[0183] For example, in iPSC cell culture, density maps can be used to track both confluence and local density as cells expand within a vessel. A range of healthy cell densities can be established, e.g., a maximum local density of 750,000 cells / cm2. Cell removal mechanisms, such as laser-activated explosive microbubbles, can then be used to remove (1) regions over a specific size that exhibit this density (e.g., a threshold surface area for adherent cells) or (2) regions predicted to reach that density within a set timeframe, e.g., over the next 24 hours, during a process in which the cell culture is imaged and periodically (e.g., daily or more frequently) scanned with a laser. Cell removal maps can be processed in a way that preserves biologically relevant structures, e.g., to leave intact clusters of cells in iPSC cultures to maintain good cell health.

[0184] Using this local density mapping and management technique, cell cultures, such as iPSC cultures, can be maintained at healthy local densities while maintaining or achieving various overall densities. This contrasts with conventional processes in which cell growth is uncontrolled and an empirical "confluence" (rough area covered by cells) measurement is used to determine when to transfer cells to a new vessel. Using this method, relatively high local densities can be maintained within an overall sparse vessel (e.g., when islands of cells reach a high enough density to initiate a reprogramming or differentiation process), or a maximum healthy local density can be maintained, while simultaneously bringing the entire cell culture closer to 100% confluence than conventional cell culture processes, which can result in the spontaneous formation of unwanted 3D structures, cell death or quiescence, or spontaneous cell differentiation due to the local accumulation of cells beyond healthy densities. For example, if confluence is defined as the percentage of a desired cell vessel growth area that is covered by cells (sometimes defined as, for example, 10% of the maximum desired local cell density (e.g., 75,000 cells / cm for iPSCs)), and local cell density is measured only within these covered areas, the present disclosure allows for achieving a combination of confluence and local cell density measurements and maintaining a desired outcome, such as differentiation efficiency or cell process yield, which is not generally achieved in passive cell culture. For example, for the purpose of maximally efficient cell expansion in a single vessel, cell confluences of >75%, >80%, >85%, >90%, or >95% can be achieved using the present disclosure while maintaining a local cell density measurement (which may be 400,000-500,000 cells / cm, 500,000-600,000 cells / cm, 600,000-700,000 cells / cm, 700,000-800,000 cells / cm, or 800,000-900,000 cells / cm) such that the 90th percentile local density measured over an area approximately 250 microns in diameter remains below a desired maximum. These desired maximum densities may vary depending on the cell type and cell culture conditions.Conversely, the present disclosure can be used to maintain a narrow distribution of local cell densities, for example, during a cell differentiation process, while maintaining an overall low cell confluence. For example, local densities can be maintained with a CV of <50%, <40%, <30%, <25%, <20%, <15%, or even <10% when measured within a 250 micron diameter area, while maintaining a confluence level of <50%.

[0185] Measurement of cell division, proliferation and motility The systems and methods disclosed herein can use a time series of cell density maps along with two or more measurements to generate maps of cell culture dynamics, including, but not limited to, local cell division rates, cell colony growth over adjacent regions or into areas removed by a cell removal process, or cell motility over adjacent regions.

[0186] A computing subsystem (e.g., computing subsystem 110) can generate density maps at a first time point and a subsequent second time point, and calculate an approximate local cell division rate by dividing the density at the second time point by the density at the first time point, taking the logarithm of this ratio to the base 2, inverting the result, and multiplying by the time elapsed from the first time point to the second time point. Typical division rates for low-density iPSCs can range from 16 to 18 hours, while, for example, lineage-committed (i.e., differentiating) cells have cell cycles (division rates) in the 24 to 32 hour range. High-density iPSCs (e.g., greater than 500,000 cells / cm) can also exhibit lower cell division rates. Importantly, these density-adjusted cell division rates are important markers not only of spontaneous differentiation but also of some karyotypic abnormalities that arise during iPSC reprogramming, and some DNA damage that may arise during reprogramming or be inherent to the source somatic cells.

[0187] As a result, the present disclosure enables mapping of density and cell division rate, followed by the use of matrix operations in a computing subsystem to select regions of cells where division rate and density exceed a normal or desired range. In some cases, ranges outside the "normal" range may be selected for process development. In many cases, including during the production of clinical cell doses, a known good range of density and division rate will be known, and regions of cells outside this range can be marked for removal and eliminated using a cell editing subsystem, such as a pulsed laser and laser-activated film that creates explosive microbubble formation. By controlling both cell density and division rate in this manner, it is possible to restrict the range of cell division rates in a sample to a narrower distribution than would naturally occur in an uncontrolled cell sample (e.g., an iPSC cell sample or any other cell type disclosed herein, including differentiating or differentiated cells). For example, the resulting cell division rate (which may be adjusted for cell density effects by a curve relating normal cell division rate to local cell density) may be limited to a standard deviation (i.e., coefficient of variation or CV) of less than 25%, 20%, 15%, 10%, 7.5%, 5%, 2.5%, or 1% of the average division rate. This narrowing of the distribution using a combination of an imaging subsystem that repeatedly images the cell culture (optionally using fiducial marks to ensure alignment as described above), a computing subsystem that calculates a cell density map and division rate, and a cell culture editing (i.e., cell removal) subsystem that removes regions of cells whose density and division rate fall outside a specific band can be used to improve the yield of cells obtained by providing more uniform and therefore predictable characteristics, by obtaining more pluripotent cells, or by removing populations with abnormal karyotypes or other DNA abnormalities. In some implementations, the same concept can be applied during the cell differentiation process to remove undifferentiated cells, improperly differentiated cells, or cells with certain karyotypic, DNA, or epigenetic damage.

[0188] In other applications, achieving a certain number of cell divisions during the process is important. For example, in some iPSC reprogramming processes, reprogramming vectors (including but not limited to Sendai virus and episomal vectors) must be eliminated from cell populations before quality control assays that measure pluripotency and other characteristics. Elimination of these vectors typically occurs as a byproduct of cell division, during which the vector DNA does not replicate at the same rate as the cellular DNA. For example, for some episomal vectors, the loss rate per cell division is approximately 5%. Traditional cell culture processes use "passage" (transfer from one vessel to another) as a rough timing tool to estimate when the vector will be sufficiently eliminated. However, there is no way to track the actual number of cell divisions, and even the average for the entire population is difficult to accurately calculate, since "confluence" (visually estimated cell coverage of the vessel) is only recorded before passaging. Because cells are thoroughly remixed during each passaging step, tracking the division rates of subpopulations or the total number of divisions is impossible. For example, some cell culture processes involve approximately 20 passages ("late passage" processes). Because one passage typically lasts 3-4 days, a 20-passage cell culture process may span 60-80 days. The nominal population doubling time (PDT) is approximately 18 hours, but in practice, it may be slightly longer due to density effects, so that 20 passages may result in 70-90 population doublings over the cell culture process.

[0189] The systems and methods disclosed herein also allow for the calculation of local cell division rates, and therefore the integral number of divisions over time, using density mapping and passaging-free processes enabled by laser or other density control. Removal of regions of cells dividing too slowly or too quickly, as described herein, can equalize the number of divisions and thereby equalize the expected time to vector elimination. In addition to narrowing the range of cell division rates, the present disclosure can be used to remove regions calculated to have too few cumulative cell divisions over a period of time. For example, regions where the average number of divisions differs by more than 20%, or more than 10%, or more than 5% may be removed. This also removes regions of cells that have divided significantly more than the minimum number of divisions required for vector elimination and can further remove any additional mutations that accumulate with excessive cell divisions. This method of local cell division monitoring and management can be used in multiple types of cellular processes where a certain number of cell divisions is required to obtain a stable final population.

[0190] Cell colony density mapping, statistics and management Cell colonies can be imaged, localized, and tracked over time using the imaging and computing subsystems. Methods for such localization and tracking can include the use of cell culture density mapping, as described herein. The computing subsystem can further measure characteristics of each colony, including, but not limited to, area, perimeter, cell number, circularity, fine-scale circularity, fractal dimension, cell morphology, density, density variation across the area of ​​the colony, prevalence of debris and / or dead cells, and prevalence of differentiated cells. Additionally, the evolution of these characteristics over time can, in turn, be used as features (e.g., areal growth rate, rate of density change, cell division rate, etc.).

[0191] These features may be presented to an operator during selection of a cell colony from a plurality of cell colonies located within a cell culture vessel. In other cases, the computing subsystem may rank or score the cell colonies by these features based on a database of previous operator selections and features. In other cases, the computing subsystem may rank or score the cell colonies by these features based on a database of previous assay results for the selected cell colony.

[0192] Finally, cell colony characteristics and selection can be used to protect and preferentially expand one cell colony, which may be a clonal cell colony, while removing other cell colonies from the cell culture vessel (which can be done using a laser and laser-activated film cell ablation system).

[0193] Aseptic Transfer and Expansion The cellular processes described herein can be performed aseptically within a single chamber configured to allow imaging and selective removal of cells. In other cases, portions of the process are performed in different chambers, and cells are aseptically transferred from one chamber to another using single-use fluidic connectors or sterile tubing welding operations. The output populations of these imaging / laser-based chamber processes can be greater than 5 million cells, 10 million cells, 15 million cells, 50 million cells, or 100 million cells. In other cases, cells can be aseptically transferred from one chamber to a larger bioreactor system for expansion of the cell population. For example, sterile cell culture systems or various stirred-tank bioreactors (including microcarriers) can be used to expand cell populations to greater than 100 million, 500 million, or even 1 billion cells under completely sterile conditions. During each sterile transfer, samples can also be removed (aseptically) from the system for intermediate assays to evaluate the cell population.

[0194] iPSC quality assessment The systems and methods disclosed herein enable the generation of high-quality cell products. The resulting cell products may be characterized by a relatively higher degree of quality compared to conventionally produced cell products. In particular, iPSC products are characterized by the challenges of maintaining sterility and maximizing the functionality of the resulting iPSC colonies when reprogramming and expanding cell cultures. For example, iPSCs may change over time with respect to pluripotency and self-renewal as cells accumulate genetic abnormalities as they undergo multiple division cycles. These defects not only reduce the ability of iPSCs to maintain their stem cell-like qualities but may also increase the risk of tumor formation when used in cell therapy. However, the present systems and methods provide automated or semi-automated production of high-quality iPSCs, including clonal iPSCs, in a sterile environment. For example, the cell culture density mapping, cell division, proliferation, and motility measurements, as well as cell colony density mapping and sterile transfer / expansion described herein, may improve the quality of the resulting iPSC cell products.

[0195] The quality of an iPSC cell product (e.g., a clonally expanded iPSC population) can be assessed by various assays and analytical methods, as described throughout this disclosure. In some implementations, molecular analysis is performed to verify the improved quality of the iPSC product. Non-limiting examples of such molecular analysis are described in MacArthur et al., "Generation and comprehensive characterization of induced pluripotent stem cells for translational research," Regen. Med. (2019) 14(6), 505-524, the entire contents of which are incorporated herein by reference. For example, MacArthur et al. described molecular assays for assessing pluripotency, genomic stability, and safety, including: (1) using computational pluripotency models to evaluate microarray-based global transcriptome data (e.g., PluriTest); (2) evaluating real-time qPCR data against a biomarker panel of select genes to obtain a qualitative assessment of pluripotency and trilineage differentiation (e.g., TaqMan hPSC Scorecard); (3) using whole-genome array-based assays (e.g., KaryoStat Assay or KaryoStat HD Assay) to determine total chromosome copy number gain / loss or genetic mosaicism; (4) using next-generation sequencing-based assays (e.g., Oncomine Comprehensive Assay v3, OCAv3) to identify variants associated with oncogenic hotspot mutations, including Tp53; and (5) using microsatellite short tandem repeat (STR) analysis (e.g., AmpFLSTR Identifiler Direct PCR Amplification Kit) to authenticate parental and resulting reprogrammed iPSC lines.

[0196] In some implementations, cell products (e.g., iPSCs or cells differentiated from iPSCs) generated according to the systems or methods disclosed herein are evaluated for one or more categories of cell quality or cell culture quality. Examples of such categories include safety, identity, cell health, and pluripotency. These categories may correspond to clonal quality (cell health) or clonal functionality (e.g., pluripotency).

[0197] Safety categories can include testing for contamination, such as assays for mycoplasma, bacteria or fungi, and endotoxins. The systems and methods disclosed herein can provide an overall percentage reduction in the likelihood of contamination with one or more of mycoplasma, bacteria, fungi, or endotoxins of at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, or 99% compared to conventional protocols for generating and expanding iPSCs. The systems and methods disclosed herein can provide an overall percentage reduction in the likelihood of contamination with one or more of mycoplasma, bacteria, fungi, or endotoxins of 0.5%, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, or 25% or less in a random selection of cell products. The selection of cell products used to determine the contamination rate can include at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, or 400 cell products. For example, detecting mycoplasma contamination in one of a random selection of 20 iPSC cell products generated using the systems and methods disclosed herein indicates a 5% contamination rate. Testing for mycoplasma, bacteria, fungi, and endotoxins can be assessed using various commercially available assays. In some implementations, mycoplasma, bacterial, and fungal assays provide positive / negative identification of contamination, while endotoxin testing determines whether the cell product exceeds a threshold endotoxin concentration (e.g., 0.25 EU / mL).

[0198] The safety category may include an assessment for the presence of residual vectors used in iPSC reprogramming. Through control and monitoring of cell division using the systems and methods disclosed herein, qPCR testing can be used to confirm whether any vectors used in reprogramming have been eliminated (e.g., <0.01 copies / cell) within the cell culture (e.g., clonal iPSC colonies). The safety category may also include genetic testing, such as assays for chromosomal integrity (e.g., g-banded karyotyping, KaryoStat, whole genome sequencing) and assays for oncogene integrity (e.g., RNA sequencing or whole genome sequencing). For example, chromosomal integrity can be assessed to confirm whether the karyotype of the cell product is normal (diploid and identical to the donor). The systems and methods disclosed herein enable colony measurement and selection (e.g., removal of abnormal karyotypes associated with abnormal colonies), selection of regions with normal division rates (e.g., abnormal karyotypes associated with abnormal growth rates are removed via cell culture editing), and minimization of overall variability in cell division (e.g., some karyotypic abnormalities resulting from excessive division). In some embodiments, the cell product (e.g., iPSC clonal colony) has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, wherein a random selection of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 cells within the population is determined (e.g., according to methods disclosed herein or known in the art) to have an abnormal karyotype percentage within 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, or 25%.

[0199] Oncogene integrity may be assessed to confirm that the iPSC cell product is genetically identical to the donor with respect to oncogenes or other markers of tumorigenicity (e.g., oncogene duplications, tumor suppressor gene deletions, and other de novo mutations may occur during reprogramming and / or cell culture division / expansion). The systems and methods disclosed herein enable colony measurement and selection, as well as the selection of regions with normal division rates that may be associated with oncogene integrity. Thus, this selection process can generate iPSC products with improved oncogene integrity without the need for any invasive imaging (e.g., immunostaining). In some embodiments, the cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, wherein a random selection of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 cells within the population are determined to lack oncogene integrity within 5%, 10%, 15%, 20%, or 25% of the percentage.

[0200] Identity categories can be assessed to determine donor identity using assays for short tandem repeats (STRs). The systems and methods disclosed herein allow for a sterile process with fewer or minimized transfers compared to traditional iPSC reprogramming and culture, thereby reducing the risk of cross-contamination. In some implementations, the cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, where a random selection of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 cells within the population is determined to be a 100% match to the donor.

[0201] Cell health categories can be assessed using viability and proliferation assays and analyses. The systems and methods disclosed herein can provide time-lapse colony measurement and selection to remove unwanted / undesirable cells or clones using imaging features determined to be associated with cell quality. For example, cells can be assessed and selected for optimal division rates, thereby improving viability and downstream differentiation. Cell products may be frozen for storage and / or transport prior to differentiation or some other manipulation toward cell therapy (e.g., autologous cell therapy). In these cases, maximizing cell viability upon thawing is important. In some implementations, a dye exclusion assay is used to determine cell viability. In some embodiments, the thawed cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, wherein a random selection of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 cells within the population are determined to be at least 60%, 70%, 80%, 90%, or 95% viable using a dye exclusion assay. In some embodiments, the thawed cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, which has an average viability of at least 60%, 70%, 80%, 90%, or 95% using a dye exclusion assay. Thawing may occur at least 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, 7 days, 2 weeks, 3 weeks, 4 weeks, 5 weeks, 6 weeks, 7 weeks, or 8 weeks after freezing.

[0202] Cell proliferation can be assessed using cell culture and imaging. The systems and methods disclosed herein can enable colony measurement and selection, as well as the selection of regions with normal or optimal division rates, which may reflect cell fitness. Growth or division rates can be measured using proliferation assays or by monitoring growing colonies via imaging analysis (e.g., machine learning identification of cell numbers in specific regions of a cell culture from images collected over time). In some embodiments, the cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, where a random selection of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 cells within the population is determined to be within a target or optimal average division rate by at least 50%, 60%, 70%, 80%, 90%, or 95% percentage. In some embodiments, the thawed cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, wherein a random selection of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 cells within the population is determined to have an average division rate with a coefficient of variation of 0.05, 0.1, 0.2, 0.3, 0.4, 0.5 or less. In some embodiments, the thawed cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, where a random selection of at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 cells within the population is determined to have an average division rate with a standard deviation within 0.5, 1, 1.5, 2, 2.5, 3, 3.5, or 4 hours. In some cases, the division rate is between 10 and 20 hours.In some cases, the average division rate is 10 to 12 hours, 10 to 14 hours, 10 to 16 hours, 10 to 18 hours, 10 to 20 hours, 12 to 14 hours, 12 to 16 hours, 12 to 18 hours, 12 to 20 hours, 14 to 16 hours, 14 to 18 hours, 14 to 20 hours, 16 to 18 hours, 16 to 20 hours, or 18 to 20 hours. In some cases, the average division rate is 10 hours, 12 hours, 14 hours, 16 hours, 18 hours, or 20 hours. In some cases, the average division rate is at least 10 hours, 12 hours, 14 hours, 16 hours, or 18 hours. In some cases, the average division rate is at most 12 hours, 14 hours, 16 hours, 18 hours, or 20 hours.

[0203] Pluripotency categories can be assessed using a variety of methods, including, but not limited to, assays for iPSC gene expression (e.g., via immunostaining or RNA expression analysis), trilineage differentiation, and other differentiation assays. Immunostaining, such as flow cytometry or other imaging, can be performed to assess iPSC gene expression. In some implementations, at least 70%, 80%, 90%, 95%, or 99% of a random selection of cells from the iPSC product express at least one intracellular pluripotency marker (OCT4, NANOG) and one extracellular / membrane marker (SSEA4+, TRA-1-60, TRA-1-81). In some implementations, a random selection of cells from the iPSC product express at least 2%, 4%, 6%, 8%, 10%, 15%, or 20% higher levels of at least one intracellular pluripotency marker (OCT4, NANOG) and / or one extracellular membrane (SSEA4+, TRA-1-60, TRA-1-81) marker when compared to iPSC products generated using conventional protocols.

[0204] Assessment of pluripotency of iPSC cell products via RNA expression analysis can be performed, for example, using commercially available assays (e.g., PluriTest) that provide microarray or RNAseq analysis. As an illustrative and non-limiting example, the PluriTest assay utilizes expression data to determine a Pluripotency Score and a Novelty Score. The Pluripotency Score is an indicator of how strongly model-based pluripotency characteristics are expressed within the analyzed sample, while the Novelty Score indicates the general model fit for a given sample (a lower Novelty Score indicates a better fit of the sample with the current data model). In some embodiments, the cell product (e.g., iPSC clonal colony) has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, where a statistically representative selection of this population has a Pluripotency Score of at least 25, 30, 35, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 and a Novelty Score of 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, or 1.5 or less. The Pluripotency Score and / or Novelty Score can be an average value calculated using a sample size of at least 5, 10, 15, 20, 30, 40, or 50 samples.In some embodiments, the cell product (e.g., iPSC clonal colony) has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, where a statistically representative selection of this population has a Pluripotency Score at least 1, 2, 3, 4, or 5 higher than a cell product generated using a conventional protocol and a Novelty Score at least 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, or 0.1 lower than a cell product generated using a conventional protocol.

[0205] iPSC cell products can be assessed for differentiation into target lineages using a variety of assays, including differentiation, immunostaining, and functional assays. In some implementations, the cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, which is determined to have a differentiation efficiency that is at least 10%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% more efficient than iPSC cell products generated using conventional protocols. In some embodiments, the cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, which is determined to have a coefficient of variation reduced by at least 10%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, or 75% compared to iPSC cell products generated using conventional protocols.

[0206] iPSC cell products can be assessed for trilineage differentiation using various assays, such as qPCR (e.g., TaqMan hPSC Scorecard). Trilineage differentiation can be used to assess iPSC differentiation into ectoderm, mesoderm, and endoderm. Endoderm markers can include SOX17, FOXA2, CXCR4, and GATA4. Mesoderm markers can include NCAM1 and TBXT. Ecoterm markers can include NES (nestin) and PAX6. Other markers can include, but are not limited to, those disclosed in the TaqMan hPSC Scorecard, as described in Fergus et al., "Characterizing Pluripotent Stem Cells Using the TaqMan® hPSC Scorecard™ Panel." Methods Mol Biol. 2016;1307:25-37 (incorporated herein by reference in its entirety). In some embodiments, the iPSC cell product has a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells, which is determined to have a statistically improved or higher trilineage differentiation score or index than iPSC cell products generated using conventional protocols. In some embodiments, processes for generating iPSC cell products according to the systems and methods disclosed herein, on average, lower or reduce the failure rate (e.g., failure to undergo trilineage differentiation) by at least 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% compared to conventional protocols when generating iPSC cell products, optionally having a population of at least 10,000 cells, 50,000 cells, 100,000 cells, 200,000 cells, 500,000 cells, 1 million cells, 5 million cells, or 10 million cells.

[0207] As used herein, conventional protocols for generating iPSC products refer to the same reprogramming methods used in accordance with the systems and methods disclosed herein and known in the art, but which use manual processes for cell selection and culture, including manual passaging. For example, conventional protocols do not include ongoing imaging, analysis, and cell editing based on cell or colony measurements and / or observed division rates, as described herein.

[0208] Method for controlling a cell culture system Current cell culture processes rely on time-lapse processes without observation, or, in some 2D cell culture processes, on occasional imaging and primarily human observation of the cell culture, which is primarily done manually, to monitor progress, assess quality, and / or determine "editing." Examples of ways in which cell cultures can be edited include passaging cells when they reach a certain density, removing differentiating cells, or transferring colonies with the "correct" morphology as confirmed by a human observer.

[0209] There is a strong demand in the industry for automated cell culture processes, and in response, image processing technologies have been developed that attempt to replicate the observations of cell culture experts. For example, several image processing systems have been demonstrated that evaluate iPSC colonies based on their overall morphology to facilitate colony selection decisions. These systems essentially replicate current human observations, which may be performed at a single time point or multiple time points, but do not correlate information between images. Decisions may be made based on overall images (pixel data) of cell colonies that roughly correspond to shape and density. These systems generally do not incorporate cell-level data or statistics, or they do not incorporate time-series data or statistics.

[0210] Few, if any, models exist that relate cell-level and time-series statistics to outcome data for cell culture processes (e.g., reprogramming, differentiation, gene editing expansion). As a result, the ability to predict and control cell cultures using current image analysis techniques is significantly limited, even when appropriate feedback control measures are applied to the plate (e.g., editing cell cultures using mechanisms that can remove cells or move cells or colonies). Even if large-scale time-series data could be collected, the volume of data that could be generated would make data storage and analysis challenging. Large-scale automated biological manufacturing needs to address these issues to become economically feasible.

[0211] Various implementations disclosed herein include systems and methods for efficiently collecting and analyzing data from a cell culture and using that data to automate cell editing decisions for the cell culture. These systems and methods address shortcomings of the prior art and enable dynamic, automated, and easily scalable cell monitoring and editing. FIG. 20A is a block diagram of a computing subsystem within a cell culture system 2000A according to various implementations. Cell culture system 2000A may be similar to cell culture system 100 described with reference to FIG. 1. For example, cell culture system 2000A may include cell culture 104 undergoing a cell culture process in cell culture vessel 106 to produce output cell product 118. Cell culture system 2000A may also include a computing subsystem 110, a cell imaging subsystem 112, and a cell editing subsystem 114 that collectively monitor and control the cell culture process. An output cell product assay 120 may be performed on output cell product 118.

[0212] The cell culture vessel 106 may be configured to allow label-free imaging access to the cell culture 104 held therein. In an exemplary implementation, the cell culture vessel 106 may include a 96-well microplate with imaging-compatible cover glass (glass or optical-quality polymer) used to house the cell culture 104 of somatic cells to be reprogrammed into iPSCs through the use of episomal vectors expressing Yamanaka factors.

[0213] The cellular imaging subsystem 112 can be configured to acquire label-free images of the cell culture 104 over time (e.g., every 24 hours, or in another example, at a rate greater than twice the cell growth rate). The cellular imaging subsystem 112 can use imaging modes including, but not limited to, bright-field imaging, dark-field imaging, phase-contrast imaging, differential interference contrast imaging, quantitative phase imaging, Fourier ptychography imaging, or combinations thereof. The cellular imaging subsystem 112 can acquire multiple images throughout the cell culture, which are then merged into a single, larger image. In some implementations, the cellular imaging subsystem 112 can acquire a Z-stack of images, which are then used to better determine cell location and cellular data. An example of a normalized bright-field z-stack image of a hiPSC cell culture is shown in FIG. 21A. In some implementations, the cellular imaging subsystem 112 can provide illumination in multiple modes, angles, and / or colors using programmable lighting. The cell imaging subsystem 112 can capture images using a CMOS, CCD, or other image sensor, which can be an area sensor or a line sensor.

[0214] An example implementation of the cell imaging subsystem 112 may include a broadband LED-based brightfield illuminator configured to illuminate the cell culture 2004A in the cell culture vessel 106. The brightfield illuminator may have a 10× microscope objective (NA=0.3) mounted on a Z-translation stage and a 5 megapixel 12-bit monochrome CMOS camera used to capture images of the cell culture at three Z levels near the optimal focus for the cell culture 104 (in this example, at Z=−5 microns, Z=0, and Z=+5 microns).

[0215] The images acquired by the cell imaging subsystem 112 are generally of a resolution that allows at least the resolution of individual cells or nuclei in the cell culture. For example, in the case of 2D adherent cell cultures, images may be acquired at a resolution at least several times lower than the average cell nuclear diameter or the average nuclear spacing, whichever is smaller. In an exemplary implementation, when monitoring iPSC reprogramming from blood cells, the nuclear diameter averages about 9 microns, and the average nuclear spacing may be as low as 5 microns in very dense iPSC colonies. In this example, an imaging resolution of about 2 microns or less is then desirable to identify cell nuclei. In some implementations, the imaging resolution used to identify cells or cell components (e.g., organelles) is about 10 microns or less, about 9 microns, about 8 microns, about 7 microns, about 6 microns, about 5 microns, about 4 microns, about 3 microns, about 2 microns, about 1 micron or less. In some implementations, the imaging resolution used to identify cell colonies is about 25 microns or less, about 20 microns, about 15 microns, about 14 microns, about 13 microns, about 12 microns, about 11 microns, about 10 microns, about 9 microns, about 8 microns, about 7 microns, about 6 microns, about 5 microns, about 4 microns, about 3 microns, about 2 microns, about 1 micron or less.

[0216] The cellular imaging subsystem 112 transmits the acquired image data to the computing subsystem 110 via electrical or optical methods, which may be wired or wireless. The computing subsystem 110 may include several software and / or hardware modules that perform image analysis and cell editing decisions. For example, all of the components within the computing subsystem 110, as shown in FIG. 20A , may be implemented as software applications or routines. In another example, some of the components may be implemented in software, while others may be implemented in hardware or a combination of software and hardware.

[0217] The computing subsystem 110 may include an image normalizer 2002A configured to normalize all of the received cell culture images. Normalization may include removing local image artifacts or lighting conditions. For example, if the illumination across a single image field is non-uniform, the image normalizer 2002A may remove this non-uniformity through a band-pass filter, local mean subtraction or division, or division / reduction by a pre-measured image field. In another example, each image may be low-pass filtered to create an image of local illumination, with the cutoff frequency for the low-pass selected to remove most or all cell-related features. In this example, the original image is then divided by the low-pass result to create a normalized image that removes effects from the local illumination or light capture conditions.

[0218] The image stitcher 2004A can receive the normalized images and is configured to create a contiguous image from multiple images of the cell culture 2004A. For example, a single well of a microwell plate may require approximately 50 image tiles to capture all areas of the cell culture with sufficient resolution. The image stitcher 2004A reassembles these tiles into a single contiguous image for storage and subsequent processing. The resulting contiguous image may have dimensions beyond two axes. Examples of other axes may include, but are not limited to, the Z axis (from multiple Z-slice images), illumination or capture color channels, illumination or capture angles, and combinations that create a three- or more-dimensional data volume.

[0219] An important consideration is the overwhelming volume of data that can be generated at any one time point. In a relatively simple example where a single well of a 96-well microplate is imaged at five Z positions, with 1-micron resolution and a 16-bit output format, the data volume obtained in a single imaging pass is roughly 50 megabytes. This results in nearly 5 gigabytes of data in a single pass across the plate. The cell culture process performed herein may last 30 days or more, with images captured one or more times per day, potentially resulting in a data volume of hundreds of gigabytes. This amount of data makes analysis or direct modeling of the biological outcomes of the cell culture process extremely difficult. As a result, most current approaches have used only snapshots of image data for this purpose. However, this sampling or single-time point approach misses the majority of potentially relevant data in cell culture. The computing subsystem 110 includes several modules designed to refine this data into smaller amounts of information while still capturing all of the important characteristics of the cell culture 104.

[0220] For example, the computing subsystem 110 may include a cell localization device 2006A that performs the first step of converting a large volume of imaging data of the cell culture 104 into a more compact representation. The cell localization device 2006A may be configured to receive stitched images of the cell culture 104, first segment the images to identify cells or nuclei, and then extract their center coordinates and, optionally, nuclear envelopes from the segmented images. The cell localization device 2006A may perform these functions using traditional image processing and / or neural network-based processing. In one example, image information from five or more Z slices may first be combined into three images. These three images are then input in a tiled format to a convolutional neural network that has been pre-trained on a set of label-free images and corresponding fluorescent nuclear stained images. An example of a convolutional network architecture used in this task is U-Net. The network creates a single image corresponding to the predicted corresponding nuclear fluorescent image. This image is subsequently thresholded, and watershed morphological image processing is used to determine the centroid of each nucleus, as well as the corresponding nuclear envelope. As an example, Figure 21B shows the output of a deep learning neural network that has been trained to predict nuclear staining from bright-field z-stacks.

[0221] The cell location data generated by cell localization device 2006A may be stored in real-time cell feature database 2008A. "Real-time" in this case means location data for a single imaging time point. The data stored in real-time cell feature database 2008A may include, for each cell, the coordinates of the cell within the observed portion of cell culture 104 and the time the data was acquired. It may also include other data such as cell or nuclear envelope information, which may be either a polygon or shape feature description representing the envelope.

[0222] Additional cellular features may be extracted by one or more cellular feature predictors 2010A and added to the instant cellular feature database 2008A. The cellular feature predictor 2010A may make further predictions based on prior training at the cellular or regional level. For example, the cellular feature predictor 2010A may be trained using a series of brightfield images along with corresponding fluorescently labeled image stains of cellular pluripotency, images received from the image stitcher 2004A. The cellular feature predictor 2010A may then create an image of this predicted fluorescence, calculate a local average "virtual" fluorescence using the previously extracted XY coordinates for each cell, and add the resulting features to the cellular record in the instant cellular feature database 2008A. Other cellular features may also be calculated directly from the instant cellular feature database 2008A and added to the cellular record for convenience (e.g., calculating local cell density at various scales).

[0223] The cell localization device 2006A and the cell feature prediction device 2008A are based on the application of deep learning models (e.g., convolutional neural networks, including multi-layer perceptrons and fully connected networks, e.g., Mask Predictive models for semantic segmentation trained in supervised, unsupervised, and semi-supervised ways using various optimizers, sequentially and / or in combination (such as stochastic gradient descent with and without momentum, RMSProp, Adagrad, and Adam), with various learning rate schedules, based on trained representations derived from morphological features by R-CNN, networks using an expanding path / contracting path architecture (such as U-Net), networks with and without residual connections, networks trained with multiple objective functions (such as focal loss, cross-entropy loss, and mean squared deviation loss), as well as ensembles of models trained using the aforementioned methods in conjunction with image processing algorithms to generate training examples for supervised and semi-supervised training forms, may be utilized, as well as various processing algorithms including, but not limited to, image-based post-processing and refinement of semantic segmentation masks derived from deep learning models.

[0224] Colony locator 2012A can be configured to calculate the boundaries of colonies within cell culture 104 using the real-time cell locations stored in real-time cell feature database 2008A. A colony of cells can include any subset, cluster, or region of cell culture 104. This process can be performed using local density calculations and can also use additional features extracted by cell feature predictor 2010A (e.g., prediction of pluripotency). Colony locator 2012A establishes the boundaries of each colony, typically in the form of a polygon.

[0225] Each colony record is then stored in an instant colony feature database 2014A. Additional colony characteristics can be calculated using colony feature calculator(s) 2016A. For example, various statistics about the cells contained in the colony can be determined or estimated, including count, density, mean virtual fluorescence prediction, and other criteria. In addition, geometric characteristics of the colony can be calculated from the cell positions and / or outline polygon.

[0226] As time-series images are collected, the colony tracker 2018A correlates successive instantaneous colonies to generate a persistent record of the colony, which is stored in the tracked colony feature database 2022A. For example, the colony tracker 2018A can determine that cell colonies in approximately the same position between two time-series images are the same colony. The colonies can then be assigned a number or some other indicator, and information about the colony at each time point can be correlated and stored together. The tracked colony features of a colony may include a series of instantaneous colonies in the instant colony feature database 2014A so that a time-series of instantaneous colony features can be reconstructed. However, it may be desirable to pre-calculate and store various features for the tracked colonies, including centroid trajectories, cell count history, area history, shape factor history, etc. These features, along with cell statistical features, can be calculated using one or more tracked colony feature calculators 2022A and added to the appropriate tracked colony record in the tracked colony feature database 2022A. Figures 21C-H show representative examples of brightfield image z-stack slices of hiPSC colony growth over approximately 65 hours, and the corresponding images from which polygons were calculated that delineate the determined colony areas.

[0227] The databases in the computing subsystem 110 (e.g., the instant cell feature database 2008A, the instant colony feature database 2014A, and the tracked colony feature database 2022A) may be relational in the sense that they allow features to be traced back to their origin. In other words, tracked colonies are related to the instant colonies that formed them and to the instant cell features that make them up, which can be traced back to specific regions of pixels in the image data.

[0228] At this point, the large amount of image time series data has already been reduced to a small set of features for each tracked colony. This allows the colony outcome predictor 2024A to operate efficiently and, importantly, to be trained on a reasonably small data set. The colony outcome predictor 2024A is configured to predict a colony outcome in terms of phenotype, functionality, genotype, pluripotency, purity, growth rate, or other product characteristics using the tracked colony features in the tracked colony feature database 2022A. The colony outcome predictor 2024A can calculate a score for each colony, which represents the likelihood that the colony will produce or produce a high-quality cellular output product 2018A. The colony outcome predictor 2024A can be driven by a statistical cell outcome model 2026A optimized using the set of tracked colony features from the tracked colony feature database 2022A and the corresponding output cell product assay results 120, which in turn were generated for each output cell product 118 using the output cell product assay 120. The colony outcome predictor 2024A and statistical outcome model 2026A may use one of several machine learning methods including, but not limited to, methods from topological data analysis such as logistic and multinomial regression, ordinal logistic regression, support vector machines, classification and regression trees, random forests, boosting trees, principal component analysis, independent component analysis, k-means, hierarchical, density-based and neighborhood-based clustering, autoregressive models, Gaussian process fitting, hierarchical Bayesian models, probabilistic graphical models, persistent homology, deep learning models including multi-layer perceptron models and recurrent neural networks, reinforced models such as genetic algorithm models and virtual ant colony methods, and ensembles and cascades of these methods with heuristic and rule-based methods to predict quantitative and qualitative colony outcomes based on extracted features and output cell product assay results 2028A stored in the tracked colony database 2022A.

[0229] If a colony or region of cells needs to be removed from the cell culture 104, the colony editor 2030A can be configured to select the region or colony to be removed from the cell culture 104 to make room for cells / regions with higher prediction scores and / or ensure product clonality. The colony editor 2030A can drive the editing subsystem 114, which can remove cells, colonies, or regions of cells. The colony editor 2030A can also terminate the cell culture and dispose of it or collect the output cell product 118. In some implementations, the colony editor 2030A can also control various actuators or other controls (e.g., the controller 116) to manipulate other environmental parameters within the cell culture vessel 106. For example, the colony editor 2030A can control functions such as reagent changes or parameter changes such as temperature, pH, O, nutrient, and media supply rate. The result of this editing operation should be that the net predicted score of the cell culture 104 increases and / or space within the cell culture vessel 2006A is freed up for the remaining (predicted) higher scoring cells.

[0230] 20B is a flowchart of a method 2000B of controlling a cell culture according to various implementations. Method 2000B can be performed by a computing subsystem of a cell culture system (e.g., computing subsystem 110 of cell culture system 100). Method 2000B can also be for the cell culture system to automatically monitor and edit the cell culture during the cell culture process.

[0231] At block 2002B, the computing subsystem may receive multiple images of a cell culture in a cell culture vessel. The images may be received from a cell imaging subsystem (e.g., cell imaging subsystem 112) that collects the multiple images. The multiple images may be a collective image of the cell culture. The cell imaging subsystem may utilize one of a variety of imaging modalities to capture images, including bright-field imaging, phase imaging, dark-field imaging, transmission imaging, reflectance imaging, quantitative phase imaging, holographic imaging, two-photon imaging, autofluorescence imaging, Fourier ptychographic imaging, defocused imaging, or any other implementation known to those skilled in the art. Prior to image analysis of the multiple images, the computing subsystem may perform several pre-processing steps, such as those described with reference to blocks 2004B-2006B.

[0232] At block 2004B, the computing subsystem may normalize the multiple images. Normalization may include removing local image artifacts or other extraneous lighting effects or conditions from the images to obtain a clear image of the cell culture.

[0233] At block 2006B, the computing subsystem may stitch multiple images together to form a single image of the cell culture. The stitched image may be a 2D image of the cell culture or may include three-dimensional aspects as well. Each of the multiple images may be associated with position data that can be used to properly stitch the images together.

[0234] At block 2008B, the computing subsystem may identify the locations of multiple cells within the stitched image. The stitched image may represent the state of the cell culture at a particular time. Various image processing and / or neural network-type processes may be used to identify the locations of multiple cells. The cell locations may be expressed as coordinates of the cell's nucleus or center, and may also include nuclear envelope information. A cell feature predictor may be utilized, which uses previous imaging data as well as training set data that allows the computing subsystem to distinguish individual cells from other cells and the background image and determine coordinates representing the cell's location. The cell feature predictor may improve as more data is analyzed over time, making the predictor more accurate.

[0235] At block 2010B, the positions of the cells may be stored, for example, in a real-time cell feature database that records the position of each cell at the instant that the images (and resulting stitched images) are collected.

[0236] At block 2012B, the computing subsystem may identify one or more cell colonies or cell clusters within the stitched image. A cell colony or cluster may be any group, subset, or region of a cell culture. A colony feature calculator may be utilized to distinguish the cell colonies from each other and from the background image. The colony feature calculator may utilize cell position data, previous imaging data, and training set data to accurately identify different cell colonies within the stitched image. Cell colonies may be defined by shape and position data, as well as other data that convey information about the cell colony.

[0237] At block 2014B, information about each cell colony may be stored. For example, cell colony data may be stored in an instantaneous colony characteristic database that records the location and characteristics of each cell colony at the instant in time that multiple images (and the resulting stitched image) are collected.

[0238] In block 2016B, the computing subsystem may track one or more colonies over time. This may include repeating the steps of blocks 2002B-2014B at several points in time to collect time-series cell colony data. The computing subsystem may utilize a tracking colony feature calculator to determine cell colonies in the time-series images. All data related to the same cell colony may be correlated to create time-series data regarding cell and cell colony growth and changes over time. The tracking colony feature calculator may utilize the instantaneous colony feature data, previous imaging data, and training set data to accurately identify the same colony over time.

[0239] At block 2018B, the time series data for each tracked colony may be stored in a database. For example, the tracked cell colony data may be stored in a tracked colony characteristics database that records the location and characteristics of each cell colony over time.

[0240] In block 2020B, the computing subsystem may predict the outcome of each tracked colony in the cell culture. For example, the computing subsystem may generate an outcome score based on the time series of tracked cell colony data. The outcome score may represent the likelihood that a particular cell colony will successfully produce a desired output cell product at some point in the future. A cell outcome model may be utilized to generate the outcome score. The outcome score may be based on several data sources, including the time series tracked colony data of the current cell culture, tracked colony data from a previous cell culture process of the same type, output cell product assay data, and training set data.

[0241] At block 2022B, the computing subsystem may edit one or more of the tracked colonies based on the tracked colonies' predicted outcomes. For example, if the cell colony's outcome score indicates that it is a low-quality colony that is unlikely to produce the desired output cell product, the computing subsystem may instruct the cell editing subsystem (e.g., cell editing subsystem 114) to remove the low-quality colony. In another example, the computing subsystem may determine that two cell colonies will soon overlap and instruct the cell editing subsystem to remove the cell colony with the low outcome score to provide more space for the remaining cell colony to grow. Editing may encompass other functions that affect cell colony growth, such as transporting cargo into or out of cells, or altering environmental parameters of the cell culture vessel.

[0242] Method 2000B can repeat itself iteratively throughout the entire cell culture process until the output cell product is completely harvested or the cell culture is disposed of in its entirety. In this manner, method 2000B provides automatic and dynamic tracking, prediction, and control of the cell culture process. This eliminates the need for manual human intervention, reduces the potential for contamination from these interventions, and also accelerates the rate at which cell cultures are processed. Finally, by reducing high-density imaging data to low-density cell colony data, method 2000B reduces the need to store, transfer, and analyze large amounts of data.

[0243] The computing system shown in FIG. 20A can be used to implement the method shown in FIG. 20B to generate images such as those shown in FIGS. 21A-21H. FIG. 21A shows an exemplary normalized brightfield z-stack image of hiPSCs. FIG. 21B shows an exemplary output of a deep learning neural network trained to predict nuclear staining from a brightfield z-stack after thresholding. FIG. 21C shows a first exemplary brightfield z-stack slice of hiPSC colony growth over approximately 65 hours. FIG. 21D shows the image from FIG. 21A with a polygon depicting the determined colony area. FIG. 21E shows a second exemplary brightfield z-stack slice of hiPSC colony growth over approximately 65 hours. FIG. 21F shows the image from FIG. 21C with a polygon depicting the determined colony area. FIG. 21G shows a third exemplary brightfield z-stack slice of hiPSC colony growth over approximately 65 hours. FIG. 21H shows the image of FIG. 21E with polygons depicting the determined colony areas.

[0244] Sealed Cassette System Currently, there are no bioreactors or other systems in the art for clinical-grade production of cells that (1) allow for 100% non-contact measurement of cells in culture to monitor and control the biomanufacturing process, and (2) are sealed in a manner that allows for parallel manufacturing in non-sterile facilities, and further, in some cases, allows for editing of cell cultures (e.g., within the cell culture system) based on image-derived properties.

[0245] Such a system would enable a wide range of cell biomanufacturing processes at scale, consistency, yield, and cost currently unattainable. This capability is particularly important for moving new patient-specific therapies from the laboratory to clinical trials and ultimately to larger patient populations.

[0246] The systems and methods disclosed herein include a cell culture vessel including a sealed medium pathway and at least one culture chamber suitable for sterile cell production in a non-sterile facility. The at least one cell culture chamber has at least one growth surface for cells that is optically accessible for label-free imaging by transmitted and / or reflected illumination. The cell culture chamber may be liquid-filled and substantially free of any gas layer, and the growth surface may be inverted during at least a portion of the cell culture process to gravitationally separate debris and / or non-adherent cells from the culture surface. The cell culture vessel may provide a sterile, sealed, closed-loop liquid system to support a cell culture growing within the cell culture vessel.

[0247] In some implementations, the liquid systems disclosed herein may be referred to as liquid handlers. The liquid handlers may be coupled to one or more cell culture chambers and configured to (i) supply input fluid media to the one or more cell culture chambers, (ii) receive output fluid media from the one or more cell culture chambers, and (iii) mix circulated fluids, including the input fluid media, the output fluid media, or both, within the one or more cell culture chambers.

[0248] In some implementations, the cell culture vessel may include a mechanism for selectively removing cells from the cell culture surface without opening a medium pathway and at least partially separating the removed cells or cell fragments using an inverted configuration. In some implementations, time-series imaging of cells on the cell culture surface and image processing of the resulting images may be used to predict the outcome of a cell culture process. This prediction may be used to manage the manufacturing process by discarding cell cultures with undesirable predicted outcomes and / or initiating backup cultures, selectively removing cells in the cell culture chamber to improve the predicted outcome, and managing the medium within the closed system, e.g., adding fresh medium, to improve or maintain the predicted outcome. In some implementations, the cell culture vessel may include a mechanism for agitating liquid within the cell culture chamber without opening a medium pathway to remove debris or cells from the growth surface.

[0249] Various implementations disclosed herein can be used to scale out 2D cell culture processes in a manner compatible with Good Manufacturing Practice (GMP) requirements for cells and tissues used in patients. Furthermore, the disclosed implementations allow for long-term process execution, monitoring, and control in a sealed system to enable processing of tens or hundreds of patient samples in parallel at a single facility without the risk of cross-contamination. The disclosed implementations can be used for reprogramming somatic cells into induced pluripotent stem cells (iPSCs), for differentiation of stem cells into cells and / or tissues for screening or transplantation, for cell expansion, for genetic modification of cells, and other applications requiring a multi-day process in which cells are maintained with nutrients, factors, delivered vectors, etc.

[0250] FIG. 22 is a diagram of a closed cassette system 2200 for use in a cell culture system according to various implementations. The closed cassette system 2200 may be an implementation of the cell culture vessel 106 shown in FIG. 1 . The closed cassette system 2200 may include a cell culture chamber 2202 that supports the growth of an adherent cell culture 2204. In some implementations, the closed cassette system 2200 may include two or more cell culture chambers 2202. A closed liquid loop 2206 supplies fluid medium to the cell culture chamber 2202, allowing for medium and reagent exchange. The closed liquid loop 2206 may be a sterile, sealed liquid system (also referred to as a fluid system), constructed using planar microfluidic channels and / or sterile tubing that may be sterile welded and pre-sterilized using, for example, gamma and / or UV irradiation. The closed liquid loop 2206 enables the growth and maintenance of cell cultures 2204 over long periods of time for purposes of cellular reprogramming, differentiation, gene editing, and / or expansion.

[0251] The closed fluid loop 2206 may contain multiple reservoirs, typically sterile bags, which may contract or expand over the course of the cell culture process. The reservoirs may include a fresh media reservoir 2208, which supplies cell culture nutrients, vitamins, and other factors, as well as a waste reservoir 2210, into which spent media is pumped during full or partial media exchanges. Additional reagents or buffers (e.g., for pH control) are shown as reservoir 2216. A debris collection reservoir 2212 and a cell collection reservoir 2214 may also be present. Debris and / or cells are removed from the cell culture chamber 2202, transferred to the debris collection reservoir 2212, and removed from the media loop through the use of a filtration function 2228. The debris is typically discarded, while the cells captured in the cell collection reservoir 2214 are the output cell product of the cell culture process (e.g., output cell product 118 in FIG. 1 ).

[0252] Pump 2218 circulates fluid through closed fluid loop 2206. Pump 2212 shown in FIG. 22 is a peristaltic pump, but generally, closed cassette system 2200 may use other configurations that are compatible with the closed system. In the case of a peristaltic pump, the pump may operate on tubing or channels within a planar microfluidic system. Pump 2218 can operate in either a forward or reverse direction. Reverse pumping can be used to empty the cell filtration unit and pump filtered solids (debris and / or cells) into debris collection reservoir 2212 or cell collection reservoir 2214. Closed fluid loop 2206 can also be pumped in a reverse direction to ensure uniform distribution of media within cell culture chamber 2202. Pump 2218, in conjunction with actuated valve 2224 (only a portion of which is shown in FIG. 22), controls all of the fluid protocols on closed cassette system 2200.

[0253] The closed cassette system 2200 may also include a mixing and exchange section 2220, shown schematically in FIG. 22. The mixing and exchange section 2220 may perform two functions. First, it functions to promote mixing in the circulating liquid to ensure uniformity once it reaches the cell culture chamber 2202. For example, if a small amount of fresh medium is added, the mixing and exchange section 2220 functions to mix the fresh medium with the existing medium. The mixing and exchange section 2220 may have a liquid feedback mechanism to provide a greater mixing factor.

[0254] A second function of mixing and exchanging section 2220 can be gas exchange. For example, dissolved oxygen levels in fluid media can be an important factor in certain bioprocesses. If equipped with a gas exchange surface / mechanism, mixing and exchanging section 2220 can be used to control dissolved oxygen and other gas concentrations in the circulating media. If pH is controlled indirectly (not by the addition of liquid), mixing and exchanging section 2220 can be used to control dissolved CO2. If a cavitation mechanism (e.g., laser, ultrasound, or other) is used to edit cell culture 2204 within cell culture chamber 2202, mixing and exchanging section 2220 can be used to control the overall dissolved gas concentration in order to maintain a stable threshold and predictable energy transfer for cavitation, optionally using an inert gas that does not otherwise affect the cell culture.

[0255] Temperature may be controlled separately for the mixing and exchanging section 2220 or within different portions of the mixing and exchanging section 2220 to control gas solubility for the purpose of facilitating gas exchange. Additionally, external gas pressure may be controlled in one or more portions to facilitate gas exchange. For example, in a first portion of the mixing and exchanging section 2220, the medium temperature may be elevated and the external gas pressure is below atmospheric pressure to maximize gas generation (e.g., to remove CO2, a product of live cell culture). In a second portion of the mixing and exchanging section 2220, the temperature is lowered and the external gas pressure is above atmospheric pressure to maximize the transfer of O2 or other gases to dissolved forms in the liquid medium to support the cell culture. One or more gas bubble trapping and removal stages (not shown) may be incorporated within the closed liquid loop 2206 to trap and remove any gas that comes out of solution via a gas-permeable membrane and reduced external gas pressure so that the gas does not interfere with the cell culture or liquid loop function.

[0256] The sealed cassette system 2200 may also include a sensing section 2222, shown schematically in FIG. 22. The sensing section 2222 may be used to monitor medium conditions in a non-invasive manner. In the example shown in FIG. 22, the sensing section 2222 includes two colorimetric patches (upper and lower circles) inside the sealed liquid loop 2206. The optical properties of the patches may change with pH and dissolved oxygen, respectively, and may be read using an external light source and detector. Other medium properties and components may be monitored using similar patches.

[0257] The center of sensing section 2222 displays a circular outline representing a distinct optical path for transmission, reflection, or scattering measurements performed without an intercalant. For example, ultraviolet (UV), visible, near-infrared (NIR), mid-wave infrared (MWIR), or long-wave infrared (LWIR) spectroscopic transmission measurements may be performed to assess media contents, including, but not limited to, nutrients, waste products, vitamins, and bioprocess by-products. Alternatively, Raman spectroscopic measurements may be performed on the media and its contents. Additionally, scattering measurements at one or more wavelengths and scattering angles may be performed to assess media contents. Measurements performed in sensing section 2222 may be used in closed-loop control of closed cassette system 2200. For example, data from sensing section 2222 may be used to make decisions about adding fresh media, adding liquid to control pH, or changing gas exchange rates or compositions. Additionally, these measurements, along with imaging-based measurements, can be used to track cell culture bioprocesses and predict outcomes using statistical models (or to train these statistical models based on endpoint outcomes).

[0258] The closed cassette system 2200 may also include a plurality of ports 2226 located at various points along the closed fluid loop 2206. These may be single-use ports (e.g., for filling or inoculating the cell culture chamber 2202 or the entire closed cassette system 2200, or for collecting the output cell product) that are sterile welded after use. Such ports may also be fitted with single-use sterile connectors.

[0259] In a typical use of the closed cassette system 2200, incremental exchange of medium occurs over time based on a fixed time schedule, or more preferably, based on some combination of time and observed cell culture characteristics (such as total cell number). Medium exchange may be monitored by a computing subsystem (e.g., computing subsystem 110) of a cell culture system utilizing the closed cassette system 2200. Such incremental exchange may be performed by closing a valve in a flow loop located between a waste outlet (e.g., an outlet leading to the waste reservoir 2210) and a fresh medium inlet (e.g., an inlet from the fresh medium reservoir 2208), opening the waste inlet, opening the fresh medium inlet, and then operating the pump 2218 in the forward direction for a given duration. In this manner, any amount from a small amount to the entire amount of medium in the closed cassette system 2200 may be exchanged, depending on the pumping duration and rate. The closed cassette system 2200 may include other components not shown in FIG. 22, such as additional pumps, valves, reservoirs, and sensors.

[0260] FIG. 23A is a diagram of a cell culture chamber 2300 in a closed cassette system according to various implementations. The cell culture chamber 2300 can be similar to the cell culture chamber 2202 of FIG. 22. FIG. 23A shows both a top view and a cross-sectional view of the cell culture chamber 2300. The cell culture chamber 2300 includes at least one inlet channel 2302 used to deliver culture medium to the cell culture chamber 2300. This culture medium can be from the closed liquid loop of the closed cassette system. The culture medium may include fresh culture medium and / or reagents that are incrementally added to and mixed with the fluid flow in the closed liquid loop. The fluid flow, which is typically slow and laminar, gradually expands into the cell culture chamber 2300 through an expansion section 2304. Additional features may be added to uniformize the overall flow profile. The goal is to create a uniform, very slow flow in the target cell growth region 2308. In many cases, the goal is to minimize continuous and / or directional shear stress on cells in culture, preferably <5 dynes / cm. 2 , and preferably <1 dyne / cm 2 In some implementations, the shear stress exerted on the cells in culture is maintained at about 10 dynes / cm. 2 , 9 dynes / cm 2 , 8 dynes / cm 2 , 7 dynes / cm 2 , 6 dynes / cm 2 , 5 dynes / cm 2 , 4 dynes / cm 2 , 3 dynes / cm 2 , 2 dynes / cm 2 , or 1 dyne / cm 2 The medium is removed from the cell culture chamber 2300 via the outlet channel 2310. It should be noted that in some cell culture processes, the direction of flow may be reversed (i.e., medium enters through the outlet channel 2310 and exits through the inlet channel 2302).

[0261] Cells 2306 are cultured within cell culture chamber 2300 and, optionally, confined to a target cell growth region 2308 via a surface treatment and / or editing system. Within this region, cells are observed via a label-free imaging system (e.g., cell imaging subsystem 112). Imaging may operate with one or more known modalities, including, but not limited to, transmission imaging, reflectance imaging, bright field, dark field, phase, differential interference contrast (DIC), quantitative phase imaging (QPI), Fourier ptychographic imaging in transmission or reflection, holographic imaging, or a combination thereof. All cells 2306 may be imaged over time to monitor the progress of the cell culture and make predictions regarding quality and yield. To this end, positioning marks 2312 visible to the cell imaging subsystem may be provided to provide a stable spatial reference over time and to accurately monitor cell behavior at the colony level or at the cellular level.

[0262] Cells 2306 may be an adherent cell culture attached to the top surface of cell culture chamber 2300, as shown in the cross-sectional view of FIG. 23A. Cells 2306 may be attached to a laser film on the top surface, which allows for light-based imaging and cell editing operations without breaking the seal of cell culture chamber 2300. Cells 2306 may initially be cultured on the bottom surface of cell culture chamber 2300 until they attach to the surface, and then cell culture chamber 2300 may be inverted so that cells 2306 are present on the new top surface, as shown in the cross-sectional view. Inversion, enabled by a growth chamber fully filled with medium, may be utilized to separate non-adherent cells, cell debris, and other debris or particles that are denser than the cell culture medium from the adherent cell culture. For example, during reprogramming of suspension somatic cells into iPSCs (which are adherent), inversion of cell culture chamber 2300 gently separates unsuccessfully reprogrammed somatic cells from the reprogrammed iPSCs using gravity. The somatic cells that fall to the bottom surface can then be washed out of the cell culture chamber 2300. Conversely, when the stem cells differentiate into suspension cells, the normally differentiated cells can be gently separated by inverting the cell culture chamber 2300.

[0263] In another example, the cell culture chamber 2300 can be used to grow adherent cells that have been genetically reprogrammed or have episomal vectors delivered to them for non-integrated expression (where the programming includes antibiotic resistance). Antibiotics can then be used to kill the undelivered cells. Debris from these cells can then fall off the upper growth surface of the cell culture chamber rather than potentially contaminating the remaining successfully delivered (and therefore antibiotic-resistant) cells. In another example, an editing mechanism (e.g., a laser) can be used to lyse or damage specific cells on the growth surface by mechanical force, heat, ultrasound, electric field, or photodamage in a manner compatible with the sealed cassette, and the damaged / destroyed cell debris is gravitationally separated from unaffected live cells so as not to settle on live cells. In another example, a matrix or coating is used underneath the cells, which can be selectively modified / removed to release the adherent cells. This modification is performed in a manner compatible with the sealed container. The separation mechanisms described herein can be used to remove unwanted cells, to remove desired (product) cells, or to remove selected cells for analysis.

[0264] As an illustrative and non-limiting example, a prototype adherent cell growth chamber as shown in Figure 23A may be constructed with 50 cm2 cells on a single surface. 2 It supports a cell culture area of ​​over 1000 m² and has a liquid fill height of approximately 0.5 mm, for very high-efficiency cell culture, with a total volume of approximately 3 ml. This prototype chamber can be modified (particularly to eliminate angled corners) for maximum uniform liquid flow. The chamber in this particular example contains two 110 x 74 mm, 0.17 mm thick borosilicate glass cover slips, one with two liquid ports extending therethrough, separated by a 0.5 mm thick silicone gasket with adhesive surfaces cut to define the chamber. Tubing connectors are attached to the liquid ports. Figure 23B is an image of an exemplary cell culture chamber. This chamber is 50 cm² on a single surface. 2The chamber supports a cell culture area of ​​over 1000 m² and has a liquid-filled height of approximately 0.5 mm for highly efficient cell culture, with a total volume of approximately 3 ml. The chamber is unmodified for optimal uniform liquid flow, particularly the elimination of angled corners. The chamber consists of two 110 x 74 mm, 0.17 mm thick borosilicate glass cover slips, one with two liquid ports extending through it, separated by a 0.5 mm thick silicone gasket with adhesive surfaces cut to define the chamber. Tubing connectors are attached to the liquid ports. Figure 23C shows exemplary hiPSC growth under continuous medium flow in a liquid-filled chamber less than approximately 1 mm high.

[0265] FIG. 24 illustrates the removal of cells from a cell culture chamber 2400 within a sealed cassette system according to various implementations. The cell culture chamber 2400 may be similar to the cell culture chamber 2202 of FIG. 22. Cell colonies 2402 or individual cells 2404 may be selectively lysed via directional pulses. For example, in an iPSC reprogramming process, each colony may be kept separate to ensure clonality. A cellular imaging subsystem (e.g., cellular imaging subsystem 112) can collect images of the cell culture chamber 2400, and a computing subsystem (e.g., computing subsystem 110) can utilize various machine learning processes to determine whether one or more of the cell colonies 2402 may be at risk of fusing. The computing subsystem can then control a cellular editing subsystem (e.g., cellular editing subsystem 112) to remove at least one of the cell colonies 2402. Additionally, individual cells or groups of cells may be determined by a human observer or a computer algorithm to spontaneously differentiate, in which case they may be removed via the cellular editing subsystem as illustrated herein.

[0266] FIG. 25 illustrates agitation of cells in a cell culture chamber 2500 within a closed cassette system according to various implementations. The cell culture chamber 2500 can be similar to the cell culture chamber 2202 of FIG. 22. FIG. 25 shows both a top view and a cross-sectional view of the cell culture chamber 2500. The systems and methods disclosed herein can allow for agitation or mixing of the liquid within the cell culture chamber 2500 without opening the closed cassette system. In this case, the agitation mechanism can be used to detach cell debris from the culture growth surface, which then settles on the opposite side (e.g., bottom surface) of the cell culture chamber 2500. The turbulent mixing effect of the mechanism is indicated in the top view and cross-sectional view by arrows 2502.

[0267] The stirring mechanism can include several physical modes, including, but not limited to: magnetic mixing, in which one or more magnets reside inside the cell culture chamber 2500 and an external magnetic actuator is used to move and / or rotate these magnets to achieve localized mixing and stirring; mechanical actuators that act on the upper and / or lower surfaces of the cell culture chamber, optionally in conjunction with liquid flow or stasis; laser-based techniques, in which a pulsed laser is used to induce cavitation inside the cell culture chamber 2500, resulting in localized mechanical forces and mixing (this laser may be focused, for example, on the surface opposite the cell culture); or ultrasonic waves transmitted into the cell culture chamber 2500, which can be uniformly distributed or focused on a specific area from which debris should be removed. As a result of the stirring, detached cells and / or cell debris 2504 settle to the lower surface. From there, the cell debris 2504 can be removed by one or more mechanisms, including those described above, as well as liquid flow and gravity techniques (e.g., tilting).

[0268] FIG. 26 is a diagram of a single-use portion 2600 of a closed cassette system for use in a cell culture system according to various implementations. The single-use portion 2600 can be configured to support a single cell culture process before being discarded. The single-use portion 2600 can include a chamber, fluidics, and supply and waste bags and associated tubing similar to those shown in FIG. 22. All of the components of the single-use portion 2600 can be sterilized, filled under sterile conditions, and then used in the cell culture process. After use, the output cell product-containing bag is removed using a sterile weld, and the remainder of the single-use portion 2600 can be appropriately disposed of.

[0269] The single-use portion 2600 may include a body 2602 that houses a fluidic system 2608 and a cell culture chamber 2606. The body 2602 may be transparent or translucent to allow visual or automated imaging of the fluidic components and channels, for example, to verify the absence of contamination, blockages, air bubbles, etc. A bag 2604 is attached to the single-use portion 2600. The bag 2604 may contain media reagents as well as waste and cell products. The fluidic system 2608 in the single-use portion 2600 may include channels for circulating liquids, valve sections, pump sections, gas concentration control fluidics, non-invasive sensing patches, etc.

[0270] FIG. 27 is a diagram of a permanent portion 2700 of a sealed cassette system for use within a cell culture system according to various implementations. The permanent portion 2700 may include a reusable housing 2702 that encloses a single-use portion of the sealed cassette system (e.g., single-use portion 2600). The combination of the permanent portion and the single-use portion may form a complete sealed cassette system (e.g., sealed cassette system 2200). The permanent portion 2700 may also include at least one transparent window 2704 that allows for complete imaging of the cell culture chamber located in the single-use portion. In some implementations, the window 2704 may be located on both sides of the cell culture chamber to allow for transmission imaging. In other implementations, the window 2704 may be located on only one side of the cell culture chamber (i.e., the light source and sensor are on the same side of the chamber) when reflection imaging is sufficient.

[0271] Compartment 2706 houses the supply, waste, and product bags of the single-use portion and can provide one or more temperature-controlled chambers for long-term storage (e.g., cell products can be kept at 37°C, while some reagents are kept at 4°C until use). In some implementations, permanent portion 2700 can also include actuators for operating valves and pumps in the single-use portion of the closed cassette system. For example, a spring-loaded solenoid can apply pressure to tubing on the disposable fluidic element to hold a valve closed in an inactive state; when current is applied, the solenoid opens the valve by releasing the pressure. Similarly, pumps can be driven by electromechanical systems in the permanent portion, for example, by driving a series of cylindrical rollers in a semicircle along the path of tubing on the single-use portion to initiate peristaltic pumping.

[0272] Mechanical rails 2710 may be integrated into permanent portion 2700 to provide alignment of one or more portions of the apparatus. For example, the sealed cassette system may reside within an apparatus that also includes an imaging system, a power supply system, a central computing system, a heating and cooling system, a cassette transfer system, and other components that support parallel cell culture processes in multiple sealed cassette systems. In one implementation, such an apparatus may include a server rack, and mechanical rails 2710 allow the sealed cassette system to slide in and out of the server rack. Permanent portion 2700 may also include pluggable connectors 2708 that interface with connectors on the apparatus (e.g., server rack). Pluggable connectors 2708 include, but are not limited to, electrical connectors that provide power to on-board electronics and actuators, data connectors that centrally collect sensor and status information, liquid connectors for circulating liquids for temperature control, and gas connectors that supply gas to maintain gas concentrations in the cell culture medium.

[0273] FIG. 28 illustrates various cell culture chamber configurations within a closed cassette system for use within a cell culture system according to various implementations. These configurations may include a single large chamber configuration 2802, a multiple small chamber configuration 2804, a small and large chamber configuration 2806, and other configurations not shown in FIG. 28 but known to those skilled in the art. The single large chamber configuration 2802 may be used, for example, for cell expansion. The multiple small chamber configuration 2804 may be used when multiple clonal populations are desired, for example, to have product diversity. The small and large chamber configuration 2806 may be used to first prime cells using relatively few reagents in the small chambers (which may include delivery of compounds to the cells), followed by reprogramming or differentiation and expansion in the large chambers. In all of these configurations, appropriate valving and / or filtration can be used to prevent inadvertent movement of cells from one chamber to another. However, in the last example, the fluidics may be configured to explicitly allow movement from one chamber to another via valving, filtration, and pumping.

[0274] Modular Bioprocessing System Bioprocessing is the process of using living cells or their components to obtain a desired output. Current bioprocessing equipment is available in two main types. The first type is large bioreactors, originally derived from the chemical industry and reused in cell-based processes such as protein or virus production. These bioreactors typically use large steel tanks, but more recently have been fitted with single-use bags or scaled down to glass-based stirred bioreactors. These systems are usually surrounded by custom-made sealed tubing and other modifications to make the bioreactor suitable for handling biological materials. The second type of bioprocessing equipment is miniature systems, typically derived from manual R&D laboratory equipment, including benchtop equipment and utilizing microwell plates or small flasks. In some cases, miniature systems have already been scaled up to larger vessels, and customized systems have already been developed to transport, fill, and handle stacks of plastic vessels containing cell cultures.

[0275] For large bioreactor systems, the amount of data collected during a bioprocess is often minimal. Efforts to achieve more measurement and control in tank bioreactor-type systems have largely stalled. However, proposed measurements, if implemented, are minimal and represent the state of the bioreaction, typically measuring nutrients, waste products, cell mass / density, pH, O2, temperature, and several other factors that allow for better control of the process. Several additional sampling-based measurements allow for more detailed, but less frequent, measurements of the cell mixture. However, while the physical volume of these systems is large, the data volume is very small.

[0276] Current autologous cell and gene therapy processes, such as CAR-T therapy, employ a similar approach, simply miniaturized. It is becoming increasingly clear that the lack of higher-bandwidth measurement, monitoring, and feedback control presents challenges for these treatments, and patient-to-patient variability can lead to reduced consistency and yield. On-time delivery of treatment is critical, and these shortcomings can result in significant delays. Some bioprocessing equipment suppliers have attempted to build automated modular units to address these issues; however, while these offer the ability to perform cell processes in non-sterile facilities, they maintain practices such as separating biological equipment from data infrastructure and are built for human operators only.

[0277] On the other hand, miniaturized system models derived from R&D laboratory equipment offer the potential to collect more data under actual cell culture conditions using imaging, as many formats have been specifically developed to enable microscopy and other optical measurements. However, imaging measurements of cell cultures are mostly performed as "spot checks" rather than quantitatively assessing cell or process parameters. High-content imaging remains primarily in the R&D domain or is used in quality control assays at the end of cell culture processes. For example, immunofluorescence-labeled imaging may be used on small samples to reflect the overall product.

[0278] Bioprocessing systems should ideally collect detailed, granular information about process progress, cell and cell colony status, and potential problems with purity or yield long before final quality control assays. This detailed, granular data, along with appropriate control algorithms, can be used to control and optimize both process parameters (e.g., nutrient flow, product harvest, vitamin or gas concentrations, temperature, pH, etc.) and dynamically guide cell culture by using cell removal selection or editing based on imaging results. Additionally, other optical techniques, such as spectroscopy, can be used in such forms to extract data related to biochemical components within the cell culture medium or cell mass.

[0279] This expanded use of online imaging and spectroscopic techniques will exponentially increase the amount of data generated per biological sample during the process. 2 Take the equivalent of a 5-layer Z-stack (e.g., a 1000-well plateau) for example. Using brightfield imaging with a 5-layer Z-stack, a cycle time roughly matching cell division (18 hours), 1-micron resolution, and typical 16 bits per pixel, the daily raw data stream from imaging alone is 150 gigabytes. This imaging data must be collected, processed, interpreted, and made into actionable information relevant to bioprocess prediction and control. Scaling up to facilities where hundreds of patient samples are processed in parallel reveals the scale and scope of the data infrastructure along with the bioprocessing infrastructure. That is, many terabytes per day flow through the biomanufacturing environment. Small data storage devices are no longer viable. An infrastructure is needed where biology and data coexist and work together.

[0280] Another issue in bioprocessing is the ability to efficiently automate processes. The current approach involves setting up equipment on a bench (similar to how it would be installed in a manual R&D lab), placing one or more robots among the equipment, and then training the robots to find precise locations with great accuracy to place or retrieve consumables to and from various pieces of equipment. Any movement of the equipment (swapping out for repairs) also requires retraining. Nearly all equipment has a slightly different mechanical interface and is typically designed for primarily manual R&D lab operation, with the mechanical interface to the robotic system retrofitted. As a result, building an automated system with just a few pieces of equipment is a major undertaking, requiring specialized contractors to be hired, customized benches to be assembled, and the area of ​​the central robotic arm to be carefully calculated. Scalability of the setup after construction is limited. As a result, the upfront investment in time, cost, and land footprint to increase capacity can be significant.

[0281] Some companies have attempted to remedy the scalability problem with large transport systems for microplates and extensive customized automation hardware. Other companies have built more linear robotic systems that move along shelves built specifically for each piece of equipment, with each shelf having the appropriate width, height, etc. However, these systems rely on specific positioning of the equipment to properly interface with the robotic system, which must be very flexible with many degrees of freedom and therefore very expensive.

[0282] Additionally, due to constraints on the format of these systems and the types of robotic systems and automation, the systems ultimately need to have a large planar footprint. The result resembles a warehouse where bulk products of various shapes and sizes are simply placed on shelves of various sizes. Faced with these similar problems, operators of large warehouses have attempted to standardize shelving and storage, then attempted to automate the storage and retrieval process, and adapted vertical formats for space and transportation logistical efficiencies. Similarly, scaling up biology, particularly bioprocessing and biomanufacturing, requires more modular, standardized, scalable, and data-integrated systems that minimize footprint and transportation complexity.

[0283] The systems and methods disclosed herein use industry-standard data and communication infrastructures and devices that serve as the foundation and backbone for advanced modular bioprocessing systems. The bioprocessing modules used in these systems can be fully imageable, sealed cassettes for monitoring and control purposes, including the ability to dynamically edit cell cultures by removing cells or cell colonies during the course of a process. While present implementations can use such cassette-based systems, existing microwell plates, flasks, and large (sealed) vessel formats can also be used.

[0284] Bioprocessing modules can be sized to fit into standard server rack units, with heights measured in standard units of U (1U, 2U, 4U, etc.) and widths equal to the computing, storage, and communications equipment. The modular bioprocessing system also includes common modules, such as data storage, computing, power, communications, environmental control, laser, liquid handling, and imaging modules, that may be shared among multiple bioprocessing modules on the same rack. This not only enables a highly modular, incrementally scalable format for bioprocessing facilities, but also allows for very tight integration between bioinstrumentation and data processing to accommodate the large amounts of data and communications required for fully monitored, closed-loop bioprocessing. Other advantages of such systems include rapid setup and delivery, easier automation, incremental expansion, use of existing modular units for power and environmental control, and direct integration with data infrastructure and modules.

[0285] The modular bioprocessing system may have standardized dimensions, such as a 19-inch wide enclosure, various depths including, but not limited to, 24 inches, 36 inches, and 48 inches, and various heights up to the industry standard 42U (here, 1U = 1.75 inches). All instruments and devices in various implementations are mounted in these racks and may have heights in 1U increments, so positions can be calculated purely from rack position indices. The front panel of the equipment module may have a loading area for loading / unloading microplates, flasks, cell culture vessels, or cell culture cassettes for which the system is designed. The modular bioprocessing system may also include a vertical transport mechanism for moving cell culture vessels (e.g., microwell plates) in and out of the bioprocessing module, and an on / off horizontal transport mechanism designed to move cell culture vessels between the modular bioprocessing system and other locations. These mechanisms may be automated to create a fully automated bioprocessing facility but also allow for easy human interaction with the system.

[0286] The systems and methods disclosed herein include a modular bioprocessing system including a rack, one or more bioprocessing modules configured to fit within the rack, the one or more bioprocessing modules configured to accommodate one or more cell culture vessels, and a plurality of common modules configured to fit within the rack, the common modules being shared by the one or more bioprocessing modules. This system has many advantages over current bioprocessing designs, including, but not limited to, easy setup, modification, and expansion of capabilities, as well as easy integration with data, communication, and power systems.

[0287] FIG. 29 illustrates a modular bioprocessing system 2900 according to various implementations. The modular bioprocessing system may be an implementation of a cell culture system (e.g., cell culture system 100) or may be part of a larger cell culture system that includes one or more modular bioprocessing systems. The modular bioprocessing system 2900 may include a rack 2902 that holds all of the modular components in the modular bioprocessing system 2900, including both data processing and communication modules, as well as bioprocessing modules. The rack 2902 may have a standardized server rack size. For example, the height of a server rack may be measured in U units (1U=1.75 inches). For example, a rack that is 42U in size has a usable height of 73.5 inches. The rack 7402 may also have standard depth and width dimensions. This allows for placement of modular components of several standard shapes into the rack 2902 without the need for customized sized components.

[0288] The modular bioprocessing system 2900 may also include one or more vessel interfaces 2904 that accept and hold cell culture vessels. These cell culture vessels may include, but are not limited to, standard microwell plates (e.g., 6-well, 12-well, 24-well, 48-well, 96-well, 384-well plates), cell culture flasks, microfluidic chambers, or cassettes customized for cell culture. An implementation using standard microwell plates is shown in Figure 29. In this case, the vessel interface 2904 includes a plate holder extending from the front of each bioprocessing module for loading / unloading the microwell plates. The microwell plates are then returned to the respective bioprocessing module for processing or storage.

[0289] The modular bioprocessing system 2900 may also include one or more bioprocessing modules 2906. Each bioprocessing module 2906 may be a sealed container (i.e., internal components are not exposed to external components that could contaminate the container) that contains a cell culture vessel that holds the biological sample to be processed (e.g., differentiated cells to be processed into iPSCs (or vice versa)), as well as components that support growth, editing, washing, imaging, sensing, and other functions for processing the biological sample. The bioprocessing modules 2906 may include, but are not limited to, fully imageable sealed cassettes, microwell plates, flasks, and other sealed container formats for monitoring and control purposes. Each bioprocessing module 2906 can maintain independent environmental conditions corresponding to different cellular processes or cellular process stages or states. For example, the temperature may be set differently in each module, the pH may be controlled, or the dissolved oxygen level may be set differently in each module to maintain a low-oxygen environment for some cell culture processes or process stages.

[0290] The modular bioprocessing system 2900 may also include, but is not limited to, one or more liquid handler modules 2908 configured to exchange media within the bioprocessing module 2906. Appropriate tubing and containers for media and waste may be connected to the rear (utility) side of the liquid handler module 2908 or to the bioprocessing module 2906. A single liquid handler module 2908 can support one or more bioprocessing modules 2906. For example, bioprocessing modules 2906 containing the same biological sample undergoing the same process may share a liquid handler module 2908. In other implementations, there may be a one-to-one correspondence between bioprocessing modules 2906 and liquid handler modules 2908. The liquid handler module 2908 may include a relatively simple medium exchange module that removes waste media from cell culture vessels and replenishes them with fresh media. Such medium exchange functionality may further include centrifugation in the case of suspension cell cultures. Other modular liquid handling implementations may include the ability to add multiple reagents in various combinations to wells in a microplate for purposes of drug screening or high-throughput cellular process development. Other modular liquid handling implementations may include the ability to simultaneously load multiple cell culture vessels and affect transfer between these vessels, for example, distributing cell samples to multiple wells for subsequent quantitative polymerase chain reaction (qPCR) analysis, which may also be implemented in this application via modular units.

[0291] The modular bioprocessing system 2900 may also include one or more imaging modules 2910 configured to capture time-series images of biological samples cultured within the bioprocessing module 2906. Different imaging modules 2910 may have different capabilities. For example, two label-free (such as bright-field, phase, quantitative phase, transmission, or reflective dark-field) modules may be used to capture label-free time-series images of a cell culture over several days, and a single fluorescent imaging module may be used to capture high-content multi-channel fluorescently labeled cell culture images at an endpoint. In some implementations, one imaging module 2910 may be configured to capture multiple types of images. The imaging module 2910 may be configured to automatically capture images based on a schedule, which is set by a control module within the modular bioprocessing system 2900 or by an external controller controlling multiple modular bioprocessing systems.

[0292] One advantage of the modular bioprocessing system 2900 is that modules can share resources, similar to how resources can be shared in a data server rack configuration. For example, the modular bioprocessing system 2900 can include a power supply module 2912 that provides power (e.g., 24V DC) with redundancy to all modules in the system. Similarly, the modular bioprocessing system 2900 can also include an environmental control module 2914 configured to provide heating and cooling capabilities to all modules in the system via fluid. For example, the environmental control module 2914 can maintain cell cultures at 37°C, reagents at 4°C, and cool data / computing modules to appropriate operating temperatures even under heavy loads. Because the setup of the rack 2902 and other modules is standardized, the modular bioprocessing system 2900 can use standardized fluid connectors and distribution manifolds used to cool CPU / GPU server racks. Similarly, the imaging module 2910 can be shared among multiple bioprocessing modules 2906.

[0293] Modular bioprocessing system 2900 may also include one or more data storage modules 2916 and computing modules 2918. Data storage module(s) 2916 may be configured to store images collected by one or more imaging modules 2910, sensor data collected by various sensors in modular bioprocessing system 2900, and data and applications used by computing module 2918. Computing module(s) 2918 may be configured to perform various data processing and analytical functions related to the bioprocessing of cell cultures in bioprocessing module 2906. For example, computing module(s) 2918 may perform image pre-processing, localization, normalization, and stitching functions for imaging module 2910, reducing or eliminating the need for a dedicated processor or computing module for each imaging module 2910, and possibly significantly extracting or compressing imaging data before transferring the imaging data to a centralized location (either a facility, another location including cloud resources, or a hybrid architecture of both). The computing module(s) 2918 may also perform other data processing, input / output, and communication functions for the modular bioprocessing system 2900.

[0294] The modular bioprocessing systems 2900 may be communicatively connected to a central controller, such as a central server, that controls one or more modular bioprocessing systems 2900. For example, there may be multiple modular bioprocessing systems 2900 installed in a room, which may be wired and / or wirelessly connected to a central server that controls the operation of each modular bioprocessing system 2900. The central server may also collect data from each modular bioprocessing system 2900 and may also provide a user interface for a person to view data (e.g., imaging data) collected from any modular bioprocessing system 2900, monitor the status of any bioprocessing module, and control any of the modules within any modular bioprocessing system 2900. The central server may implement many functions, including scheduling the automated processing of cell cultures, alerting users of emergency conditions in any modular bioprocessing system 2900, and presenting real-time operational data for any modular bioprocessing system 2900.

[0295] The modular bioprocessing system 2900 shown in Figure 29 is a full-height rack. However, due to the modular nature of the system, it is clear that smaller systems are feasible. For example, a minimal system for continuous cell culture measurements may include one bioprocessing module 2906, one liquid handler module 2908, one imaging module 2910, and a shared system. The system may fit into a very compact rack suitable for dense environments such as university laboratories. The modular bioprocessing system 2900 may also include other components not shown in Figure 29 and may include variations known to those skilled in the art.

[0296] FIG. 30 illustrates the vessel transport function within a modular bioprocessing system 3000 according to various implementations. The modularity and vertical format of the various implementations allows for significantly simplified cell culture vessel transport mechanisms. Furthermore, transport is compatible with parallel operation with a human operator, unlike robotic transport systems in which a potentially dangerous robotic arm is centrally located in a cluster of bioinstrumentation. The standardized modular format disclosed herein dramatically simplifies the requirements for such automated transport systems by enabling the use of single-axis, low-precision actuators (track systems) to define individual vertical rack positions and fixed horizontal positions for vessel pickup / transfer, along with low-cost sensors to verify vessel pickup and transfer in individual modules or in an overhead transport system.

[0297] Modular bioprocessing system 3000 may be similar to modular bioprocessing system 2900 shown in FIG. 29 . Modular bioprocessing system 3000 may include one or more bioprocessing modules 3002 that accept cell culture vessels. While the example shown in FIG. 30 uses microwell plates 3008 as the cell culture vessels, any suitable cell culture vessels are compatible with the described implementations, such as sealed cassettes. A set of rails 3004 may be attached to the front of the rack, allowing for controlled vertical movement of a vertical transporter 3006 attached to the rails 3004. Bioprocessing module 3002 can retrieve microwell plates 3008 onto a vessel interface (e.g., vessel interface 2904) that extends from the front of the module. Vertical transporter 3006 approaches the vessel interface from the bottom to retrieve microwell plates 3008 from bioprocessing module 3002 presenting them. The vertical transporter 3006 can then transport the micro-well plate 3008 to another position along the vertical axis of the rack and / or allow a person to collect the micro-well plate 3008. Alternatively, the vertical transporter 3006 can approach an extended receptacle interface from above as it delivers the micro-well plate 3008 to the bioprocessing module 3002, with the micro-well plate 3008 resting on the extended receptacle as it passes through. The receptacle interface then returns the micro-well plate 3008 into the associated bioprocessing module.

[0298] In single-rack installations or multi-rack installations where the racks are independent, this vertical transport is sufficient to fully automate a bioprocessing system, again with a very compact footprint compared to existing bioautomation configurations. For multi-rack systems where automated microplate exchange between racks or between individual racks and a loading / unloading or other central location is desired, a horizontal track-type transporter 3010 is provided. The horizontal transporter can transport cell culture vessels on the horizontal axis of the rack. The horizontal transporter 3010 provides a mechanical interface similar or identical to the vessel interface to hold microplate wells 3008 during transport. The vertical transporter 3006 can load microwell plates 3008 onto the horizontal transporter 3010 by approaching it from the top, or pick up plates from the horizontal transporter 3010 by approaching it from the bottom. Because neither the vertical nor horizontal transport system prevents a human operator from accessing the front (or rear) of the module, plates can be manually retrieved or added by a human operator in conjunction with the automated transport. Additionally, the automated transport operates with a minimal footprint and can use low mechanical forces to enhance safety.

[0299] FIG. 31A is another diagram of a modular bioprocessing system 3100 according to various implementations. In this implementation, cell culture vessels are implemented as cassettes 3102 that can be used for various cell culture processes, including, but not limited to, cell reprogramming, cell differentiation, cell gene editing, and / or cell-based biomanufacturing. The cassettes 3102 are sealed to enable sterile processing of multiple samples within the same environment for a high degree of control and consistency, and, optionally, for Good Manufacturing Practice (GMP) compliance for therapeutic (patient-specific) products. An example application of this implementation is the generation of patient-specific human induced pluripotent stem cells (hiPSCs) and their differentiation into replacement cells for subsequent cell therapy. In such applications, complete isolation of patient samples from one another is required, which is achieved using a cassette-based system in which the required media and reagents, as well as a waste reservoir, are contained within a sealed liquid system on the cassette 3102. In this example, cassette 3102 may include a fully imageable cell culture chamber configured to allow selective laser ablation of cells from the cell culture, with subsequent removal of the resulting debris by an on-board liquid handling subsystem. Using this combination of elements, a high degree of control, and therefore predictability and yield, can be achieved in sealed cell culture.

[0300] The cassettes 3102 can be inserted into a bioprocessing module 3106 mounted in a rack 3104, which can have standard server rack dimensions. The cassette host 3106 can provide several functions, such as (a) incubating cells within the cassettes inserted into the host, (b) operating on-cassette liquid handling systems for medium replenishment, reagent addition, and waste removal, (c) monitoring and adjusting, as needed, media conditions within the cassette, e.g., dissolved oxygen and pH, (d) providing gas exchange with circulated media within the cassette to regulate oxygen and other dissolved gas levels, (e) imaging the cells within the cassette, (f) selectively destroying and ablating cells within the growth chamber using a laser system, and (g) editing cells within the growth chamber (e.g., inserting or removing cargo into or from cells) using a laser system. In this way, a single bioprocessing module 3106 can monitor and control long-term cell culture processes without the need to remove or transport the cassettes 3102, reducing potential sources of variability within the process. The bioprocessing modules 3106 within a rack operate independently, but may share some resources as described below.

[0301] A shared computing, storage, and communication module 3108 may be used to process images acquired by each bioprocessing module 3106 for normalization, positioning, stitching, and other functions. The resulting images / data may be further processed using machine learning systems located either locally or remotely (e.g., elsewhere on-site or in the cloud). Algorithmic selections or predictions may then be calculated internally or transmitted to this computing infrastructure to drive selective laser ablation of cells within each bioprocessing module 3106 and associated cassettes 3102. For example, a shared pulsed laser module 3110 may supply laser energy to multiple bioprocessing modules 3106 via standard fiber optic connectors installed at the rear of the rack 3104. Energy may be split among the bioprocessing modules 3106 via a tree of static fiber optic splitters or switched from unit to unit via an optical switch or some other method. In some implementations, there may be more than one laser module in the modular bioprocessing system 3100. In some implementations, a single laser module may be used for modules in multiple racks within the modular bioprocessing system 3100.

[0302] The shared environmental control module 3112 can be used to provide cell culture temperature control (typically 37°C), reagent cooling (often 4°C), laser cooling, and cooling for the data storage and computing modules, especially when the local central processing unit (CPU) or graphics processing unit (GPU) performs large workloads for image processing or machine learning operations. The shared power supply 3114, in some implementations, can be used to provide redundant built-in power supplies to provide reliable DC current to the bioprocessing module 3106, the laser module 3110, and possibly the data storage and computing modules, thereby eliminating the need for individual power supplies.

[0303] Various implementations allow for compact system configurations, as shown in half-height setup 3116, with a very small footprint and very short setup time, as well as the incremental addition of bioprocessing modules 3106 to add capacity as desired. This modular configuration also allows for a high degree of redundancy and reliability, as spare modules can be added or brought online very quickly to compensate for any failures. In the example shown in FIG. 31A, a small modular system, even a half-height rack, can replace several high-grade clean rooms (often located in expensive urban spaces) for GMP cell culture and can eliminate the need for extensive personnel preparation for daily cell culture observation and manual change / transfer processes.

[0304] The modular bioprocessing system 3100 shown in Figure 31A may include a transport system similar to that described with reference to Figure 30, providing simple, human operator compatible vertical and horizontal transport for large multi-rack facilities. The modular bioprocessing system 3100 may also include other components not shown in Figure 31A and may include variations known to those skilled in the art.

[0305] Figure 31B shows an exemplary prototype process module (bottom, with handle) and a partially inserted cell culture cassette, shown installed with a RAID storage array (16 drive bays visible) and a backup power module (top, marked Tripp Lite).

[0306] Hot-swap duplicate cell culture system Many cell culture processes, including gene editing, reprogramming (e.g., reprogramming cells into iPSCs), expansion, differentiation, and biomanufacturing, can require lengthy and complex processes. The cell culture systems that carry out these processes are complex and may have many different subsystems, such as environmental sensors and controls, media / waste and reagent movement subsystems (pumps, valves, sensors), imaging subsystems, and cell editing and / or manipulation subsystems (including directed energy systems for intracellular delivery or selective cell destruction or removal, cell culture washing systems, etc.). This complexity makes these systems prone to failure due to the failure of a single component, subsystem, or software. In current systems, this typically results in the loss of the cell culture, which is very expensive and can have a significant impact on patients awaiting cellular products.

[0307] Implementations disclosed herein, for example in Figures 29-31, illustrate the use of distributed, modular systems in which cell cultures are processed simultaneously in multiple modules, each performing various functions. These implementations reduce the risk of mass failure due to shared equipment (e.g., robotic arms, imaging systems, liquid handling systems, and cell editing systems). These implementations also prevent failures, for example, when a transport robot used to move cell cultures within the system breaks down or becomes misaligned, or when a central shared imaging subsystem fails due to software issues. However, even modular systems can fail, but it is highly desirable that this failure only affects a single cell culture in process and that the failure of a cell culture module does not result in the failure, destruction, or degeneration of the cell cultures handled by the module.

[0308] In some cases, cell culture processes may require diverse processes that cannot be practically accomplished within a single cell culture system. In current systems, if not transferring cellular material, achieving such a switch requires, at a minimum, tubing and other reconfiguration, resulting in more complex processes, more manual steps, and a greater chance of damage or contamination to the cell culture.

[0309] The systems and methods disclosed herein include cell culture systems in which components can be easily switched and replaced, allowing the cell culture system to be easily adapted to different cell culture processes and for simple repairs. The cell culture system may include a cell culture container (e.g., a sealed cassette system) including at least one cell culture chamber and auxiliary components. All fluid paths, including the cell culture chamber(s), may be sealed during at least a portion of the cell culture process to ensure sterility and prevent cross-contamination. The cell culture container may also include on-board media, reagent, buffer, product, and / or waste reservoirs and tubing components. The cell culture chamber(s) may be configured to enable imaging of the cell culture and to enable directed energy editing (e.g., intracellular delivery or lysis) of the cell culture.

[0310] The cell culture vessel (which may be a closed cell culture cassette in some implementations, as described with reference to Figures 22-28) can be quickly connected and disconnected to external components through connection plugs, so that the cell culture vessel can be plugged into or removed from a modular bioprocessing system that manages the cell culture vessel and cell culture conditions. These connections include electronic connections (e.g., for power, sensor readings, valve or pump actuation), communication connections (e.g., for inter-processor communication), and liquid or gas connections (e.g., for temperature control of the cell culture and / or media, reagents, buffers, waste, product containers on the cell culture vessel, or dissolved gas control). Liquid pathways within the cell culture vessel can be self-contained and inaccessible to maintain a closed loop and keep the cell culture vessel sterile.

[0311] The cell culture system may also include a process module(s) that receives one or more cell culture vessels and provides cell culture support functions. The process module may be configured to allow the cell culture vessel to be hot-plugged into the process module using connectors to provide monitoring and support for the cell culture vessel. The process module and cell culture vessel may be designed so that in the event of a process module failure or malfunction, the cell culture vessel can be removed from the process module via a simple mechanism, e.g., mechanical unlocking and subsequent extraction.

[0312] In some implementations, the process modules disclosed herein may also be referred to as cell culture process modules, cell culture process systems / subsystems, cell culture process mechanisms, or docking stations. Cell culture process modules include physical devices configured to provide cell culture support functions, such as media monitoring and replenishment, and gas monitoring, mixing, and replenishment. Cell culture process modules may be configured to receive one or more cell culture vessels (e.g., cell culture cassettes). Cell culture process modules configured to receive one or more cell culture vessels may also be referred to as docking stations. For example, a cassette may be received by the cell culture process module by "docking" with a receiving space of the cell culture process module that accepts the cassette. The cell culture process module can operate in cooperation with the cell culture cassette to handle one or more cell culture support functions. For example, the cell culture cassette may include a fresh medium reservoir, and the cell culture process module can fluidly connect the cell culture chamber and the medium reservoir of the cell culture cassette and then transfer fresh medium to the cell culture chamber.

[0313] The cell culture system may also include computing and communication systems that monitor and track the status of each cell culture vessel as it undergoes a cell culture process recipe. The system may essentially maintain a “digital twin” of the cell culture vessel (e.g., a dynamic digital profile of the cell culture) that may be stored on the cell culture vessel and / or a remote server. This allows the cell culture vessel to be removed from one process module and inserted into another process module without any data entry, and the receiving process module to quickly resume the cell culture process under the appropriate conditions (such as temperature, medium change, reagent or buffer addition, dissolved gas control, flow rate / liquid shear control, washing, or agitation). For example, the cell culture vessel may contain non-volatile memory, such as a flash memory, that contains a record of the cell culture process recipe, as well as a history of which steps have been performed and the conditions of the cell culture vessel. Thus, when the cell culture vessel is removed from one process module and inserted into another process module, the process module can read this memory and continue the current or next step of the cell culture protocol under the appropriate conditions. In some implementations, the cell culture vessel includes a barcode or electronic tag (which may include on-board non-volatile memory) that presents the vessel ID to the process module, which retrieves the process recipe and history from the server when the vessel is inserted so that the process can be immediately resumed.

[0314] FIG. 32 is a diagram of a modular cell culture system 3200 according to various implementations. The modular cell culture system 3200 can support several cell culture vessels formatted as sealed cell culture cassettes 3202 (e.g., sealed cassette system 2700). The cassette 3202 may have a housing including a handle 3204. The housing encloses one or more compartments 3206 for holding cell culture medium, reagents, waste, cell products, etc., as well as a fluid handling system for circulating medium, waste, debris, cell products, etc., in and out of one or more cell culture chambers 3208. The cell culture chambers 3208 may be suitable for culturing suspension and / or adherent cells. The cell culture chambers 3208 may be further configured for imaging of the cell cultures (e.g., label-free imaging through a transparent surface of the cell culture chambers 3208) and directed energy editing of the cell cultures (e.g., using the cell editing subsystem 114).

[0315] The modular cell culture system 3200 may include a series of cell culture process modules 3210, each configured to receive a cassette 3202. Each process module 3210 may be configured to manage cell culture functions for the cassette 3202 docked to that particular process controller 3210. These functions include, but are not limited to, temperature control (e.g., for cell culture, as well as for media, reagents, products, and waste (each of which may be controlled individually or in groups)), cell media and / or reagent addition and circulation, cell culture washing or harvesting, control of dissolved gas concentrations, control of pH, imaging of cell cultures, and directed energy editing (e.g., laser editing) of cell cultures.

[0316] The process modules 3210 interface with the cassettes 3202 via plug sockets 3212 for electrical, communication, gas, temperature control, and other connections. These plug sockets 3212 may be configured so that the cassettes 3202 can be quickly loaded or unloaded from the process modules 3210 without manually connecting or disconnecting wires or tubes, or in some cases even executing software programs and related functions within the containing cell culture module, thereby enabling a "hot swap" to be performed to move the cassette 3202 from one process module 3210 to another. An on-board computer 3214 within the process module 3210 may be in electrical communication with the on-board computer or memory of the cassette 3202 or may read the cassette's barcode to verify its identifier and retrieve its current operating state.

[0317] Process module 3210 communicates via communications network 3216 with cassette data monitoring system 3218, which maintains cassette status database 3220. Cassette status database 3220 stores a "digital twin" for each cassette 3202 in modular cell culture system 3200, reflecting the current cassette status and intended cell culture process. Thus, if a cassette 3202 is removed from one process module 3210 and inserted into another, the receiving process module 3210 can immediately resume the desired cell culture program for cassette 3202. This allows for rapid removal of cassette 3202 in the event of a malfunction in process module 3210 or supporting infrastructure, or for removal within a facility depending on the stage of the cell process. Process module 3210 can also communicate with module monitoring system 3222, which maintains process module "digital twin" database 3224, to monitor critical module functions and detect any deviations. Additionally, the module monitoring system 3222 can be used when a process module 3210 is moved from one process cluster or facility to another, or from one set of support systems to another.

[0318] The modular cell culture system 3200 may include support subsystems 3226 shared by multiple process modules 3210. Support subsystems 3226 include, but are not limited to, environmental control systems (e.g., for warming the cell culture and / or cooling media, reagents, products, and computing or optical subsystems), laser systems for directed energy editing of cell cultures, cell culture imaging, autofocus or positioning functions, and / or spectral sensing of media or cell cultures, power systems (e.g., internally redundant 24 VDC power supplies), and computing systems (which may also have internal redundancy) for computing or storage related to imaging, spectral sensing, cell culture editing, etc. The support subsystems 3226 may be connected to the process module 3210 via pluggable or quick connectors 3228 that facilitate easy connection or disconnection of the process module 3210 from a local cluster, e.g., a cluster of process modules 3210 on a server rack along with the support subsystems 3226. The support subsystems 3226 typically include an embedded computer or sensing / computing module 3230 that monitors and / or controls these subsystems.

[0319] One or more support subsystem monitoring services 3232 can monitor the support subsystems 3226 to track performance in a support subsystem database 3234, where again a "digital twin" is established for each support subsystem 3234 for redundancy and rapid restart capabilities. If a support subsystem 3226 exhibits a problem, it can be quickly replaced and cellular processing can continue, or the affected cassette 3202 can be moved to a process module 3210 on another set of functional support subsystems 3226 and / or one or more process modules 3210 can be moved to a new set of functional support subsystems 3226.

[0320] The modular cell culture system may also include a cell culture monitoring system 3236 configured to track cell culture conditions within each cassette 3202 (and in turn the cell culture chambers within each cassette) and managing a cell culture database 3238 that stores a "digital twin" of each cell culture (which may include time-series images, a cell or colony characteristic database, sensor data streams, etc.). Finally, an overall monitoring and control system 3240 may be configured to monitor the overall modular cell culture system 3200 by communicating with the monitoring systems 3218, 3222, 3232, and 3236, and to coordinate responses to faults or conditions requiring attention, such as the movement of cassette 3202 from one process area to another. Modular cell culture system 3200 may also include other components not shown in FIG. 32.

[0321] The process modules 3210 may have different configurations corresponding to different cell culture processes or stages of these processes. Thus, the ability to pull cassettes 3202 from one process module 3210 and place them into another while maintaining continuity of cassette state, environmental parameters, and cell culture data and processes allows for highly efficient, fault-free, multi-stage cell culture processes. Additionally, the modular cell culture system 3200 is highly flexible because it can accommodate different cell culture processes performed in parallel, thereby increasing throughput while minimizing delays due to equipment failure or other issues.

[0322] FIG. 33 is a diagram of a cell culture cassette 3300 compatible with a modular cell culture system according to various implementations. The cell culture cassette 3300 is an exemplary implementation of a cell culture vessel (e.g., cell culture vessel 106) within the cell culture system. The cassette 3300 may be primarily designed for 2D adherent cell culture. The cassette 3300 may include a 2D liquid cell culture chamber 3302 with transparent top and bottom surfaces that can be used for imaging and directed energy editing of the cell culture. Mechanical guide rails 3304 function to align the cassette 3300 with the process module upon insertion. Upon insertion, connectors 3306 plug into complementary connectors on the process module. These connectors transmit electrical signals, including, but not limited to, any necessary power, communication, signals from sensors mounted on the cassette, and control signals to actuators mounted on the cassette. The connectors 3306 may also include non-mechanical elements, such as gas or liquid ports. For example, cooling or warming liquid may flow in the loop through connector 3306, or gas to maintain the proper dissolved gas concentration may flow in the loop through connector 3306. In these cases, quick connect fittings may be used to seal the connections when cassette 3300 is removed and open them when cassette 3300 is inserted.

[0323] Connector 3306 may be removed mechanically through a locking mechanism accessible from the front of cassette 3300 or process module (possibly on or near handle 3308) or electromechanically by the process module. Because cassette 3300 may be removable from a process module regardless of software, electrical, or other failures of the process module, cassette 3300 may be quickly pulled out using handle 3308 and placed in another process module. In this example shown in FIG. 33 , cassette 3300 may include two separate storage compartments for holding liquids related to cell culture, including, but not limited to, cell media, reagents, buffers, cell products, and waste, which may be stored in sealed bags or other containers. For example, one compartment 3310 may store media and reagents at 4°C, while another compartment 3312 may store cell products at 37°C. The temperature control port 3314, which is sealed when the cassette 3300 is not in a process module, may be forced open by insertion of the cassette 3300 into the process module, allowing the process module to push temperature-controlled air perpendicular to the plane of the cassette 3300 through the compartments 3310, 3312. Thus, each compartment 3310, 3312 may be precisely temperature-controlled in a closed-loop manner while in the process module, but the port 3314 automatically closes when the cassette 3300 is removed from the process module, thereby passively maintaining the temperature within the compartments 3310, 3312 while the cassette 3300 is moved to, or waiting to be moved to, another process module.

[0324] In some implementations, cassette 3300 may be designed to allow an optical system (e.g., cell imaging subsystem 112) to access the cell culture chamber 3302 for the purposes of imaging the cell culture and / or editing the cell culture through a cell editing mechanism, such as using directed energy (e.g., cell editing subsystem 114). Directed energy editing may take the form of a magnetic tool inside the cell culture chamber 3302 directed by laser light, ultrasound, an external magnetic actuator, or other methods. The cell imaging and cell editing subsystems may interact with cassette 3300 without physical engagement, such that in the event of a failure of either subsystem, the cassette may be manually removed from the process module without damaging the cassette 3300 or the process module. The cell imaging and cell editing subsystems may also be configured to return to an “off” mode in the event of a software, electrical, or mechanical failure of the process module, for example, by shutting off laser illumination, shutting off imaging illumination, and retracting the magnetic actuator via an “active-on” solenoid or compressed air mechanism.

[0325] If a fault is detected in the process module, an "eject" sequence can be activated that unlocks the cassette 3300 and partially ejects the cassette from the process module. Partial ejection can include removing all ports and connectors 3306, closing all valves onboard the cassette 3300, stopping pumping onboard the cassette 3300, and sealing all temperature control ports 3314 (liquid or gas). This can be accomplished, for example, by a solenoid and spring-loaded actuator that is electromagnetically retracted when the process module is powered and operating properly and the cassette 3300 is inserted, but if a fault is detected or power is lost in the process module, the spring force ejects the cassette 3300 to a retracted position. In this position, the cell culture is effectively in a "safe" mode, with no liquid flow and temperature passively maintained until it can be returned to a running process module.

[0326] FIG. 34 is a diagram of a cell culture cassette 3400 compatible with a modular cell culture system according to various implementations. The cell culture cassette 3400 is an exemplary implementation of a cell culture vessel (e.g., cell culture vessel 106) within the cell culture system. The cassette 3400 may be primarily designed for suspension cell cultures maintained within a miniature stirred-tank bioreactor, with sterile tubing connected to cell media, buffers, reagents, and waste and cell product bags all stored onboard. Guide rails 3402 enable insertion of the cassette 3400 into a corresponding process module and secure mechanical alignment of plug connector ports, including an electrical / communication connector 3404 and a gas / liquid quick connector 3406. In some implementations, when inserted, a magnetic actuator on the process module aligns with a driven magnetic component 3408 connected to the agitator of the cell culture vessel. However, generally, any number of non-contact methods of agitating the interior of the cell culture vessel may be implemented within the cassette 3400. For example, other implementations may include magnetic couplings that actuate valves on cassette 3400, actuate peristaltic pumps on cassette 3400, or move actuators within the sealed cell culture vessel for purposes of washing the cell culture, circulating media, or removing cells or debris from surfaces.

[0327] A latch 3410 may be used to lock the cassette 3400 in place within the process module and may be mechanically coupled to several components to properly open and close them, including but not limited to the gas / liquid port 3406. The latch 3410 may be assisted by a handle 3412 to open before retrieving the cassette 3400. A display on the cassette 3400 may show the current status of the cassette 3400 and the cell process and may include touchscreen functionality.

[0328] In the implementation shown in FIG. 34 , two compartments 3414 are configured to hold media, reagents, buffers, cell source, and waste, cell product, etc. However, generally, any number of compartments 3414 may be present. The compartments 3414 may be temperature-controlled via air ports 3416 on the side of the cassette 3400. For example, air port 3416 may be used for the inlet (top) and outlet (bottom) of temperature-controlled air from a process module to maintain the left compartment at a temperature of 4° C. The air port 3416 may be configured to close when the cassette 3400 is not fully docked with the process module to maintain the internal temperature of compartment 3414 as much as possible. Similarly, the air port 3416 corresponding to the bioreactor may be used in either a top-down or side-to-side configuration to move air through the bioreactor enclosure and maintain its temperature, typically at 37° C.

[0329] Figure 35 is a diagram of a rack-based modular cell culture system 3500 according to various implementations. The modular cell culture system 3500 can include any number of cell culture process modules 3502 (eight shown in Figure 35) and several support modules mounted in a server-style rack 3504. The process modules 3502 can be configured to receive cell culture cassettes 3506 (shown in Figure 35 in an inserted / retracted position), which can be similar to cassette 3300 of Figure 33 for 2D adherent cell culture.

[0330] The modular cell culture system 3500 may include a shared environmental control module 3508. In an exemplary implementation, the shared environmental control module 3508 can circulate a refrigerant and two temperatures, e.g., 0°C and 40°C, along a liquid manifold housed within an environmental control column 3510. The environmental control column 3510 provides thermal "rails" to the process module 3502 to maintain the temperature of the cell culture and various media, reagent, waste, or cell product compartments. It also provides cooling to components that generate significant heat (e.g., the computing module, if present, or the shared laser module) (as opposed to air-cooling each) while maintaining a compact footprint. The environmental control module 3510 can exchange heat between return flows and may include a high flow rate of air circulated through it for heat exchange purposes via duct 3512.

[0331] The modular cell culture system 3500 may also include a computing and communications module 3514 (e.g., computing subsystem 110) that provides local computing, storage, and network communications. In an exemplary implementation, multimode fiber and optical transceivers may be used to provide communications between the computing and communications module 3514 and the individual process modules 3502, ensuring high bandwidth during cell culture imaging. The computing and communications module 3514 may also provide local processing and storage of images, as well as, possibly, computing for cell culture editing functions. The computing and communications module 3514 may also be connected to an external network via optical fiber or other communications link passing through duct 3516. The external network may store a "digital twin" of the process module 3502, cassette 3506, and support modules 3508, 3514, 3518 within the modular cell culture system 3500. These digital twins can help monitor and track cell culture, cassette, and process module status and performance against standards, and provide hot swap capabilities in the event of a failure in a process module or any support system.

[0332] The modular cell culture system 3500 may also include a cell editing subsystem, such as a shared pulsed laser system 3518. Pulsed laser light from the pulsed laser system 3518 may be transmitted to each process module 3502 via optical fibers. For example, the pulsed laser system 3518 may include a nanosecond pulsed laser emitting at 532 nm or 1064 nm. The laser light may be split into eight equal output beams (which may be achieved using free-space optics or fiber optic couplers) and coupled into polarization-maintaining single-mode fibers. These fibers are routed to corresponding process modules 3502. Each process module 3502 may be configured to synchronize pulse timing (e.g., 500 kHz) and then apply modulation (e.g., with an acousto-optic modulator) and beam steering for the purpose of directed-energy cell culture editing. In other implementations, the laser source may be shared within the cell culture module for other purposes, such as illumination for fluorescence, autofluorescence, two-photon imaging, Raman spectroscopy, or other sensing modalities. The modular cell culture system 3500 may also include a shared DC voltage power rail that provides power to the entire rack 3504 and supported devices, supplied by power ducts 3520. In an alternative implementation, the DC power supply may be attached to the rack 3504 as a rack-mounted device (possibly with connections for cooling).

[0333] Selective substance extraction and analysis During a cell culture process, it may be beneficial to selectively collect and sample cells in a cell culture to determine their characteristics. The characteristics can be used for different purposes. For example, a computing subsystem (e.g., computing subsystem 100) can associate the characteristics of a sampled cell with the cell region or colony from which the cell originated. It may also be important to image live cells at multiple time points to enable measurement of trends at the subcellular, cellular, cell neighborhood, or colony level. Another application of selective cell sampling and characterization is to monitor cell culture conditions, for example, during cell-based processes or in bioproduction systems, by selectively obtaining representative samples of cellular material. This may enable the cell culture system to determine whether to continue, alter, or stop the cell culture process based on the attributes of the collected cells. This information may also be used in machine learning models to further improve the cell culture process.

[0334] Cellular properties that can be observed or measured from label-free images include, but are not limited to, morphology, the presence / total number / size of intracellular components, density, refractive index, absorption or absorption spectrum, polarization-dependent absorption or refractive index, degree of attachment to the substrate or surrounding cells, proliferation rate, velocity, projection of cell extensions such as neurites, interactions with other cells, and spectroscopic properties including, but not limited to, Raman spectra, infrared spectra, autofluorescence, etc. Properties measured or observed can also include parameters measurable by fluorescent labels such as surface markers or other components known in the art. Properties measured or observed can also include phenotypic, genomic, epigenetic, transcriptomic, and proteomic properties of those cells.

[0335] Selective cell extraction and analysis must be performed in situ on live cells or recent live cell cultures in cell culture vessels suitable for long-term cellular processes, and observation must be performed via imaging. The cell extraction process must be minimally invasive so that remaining cells remain in culture and can continue cellular processes. In addition, the process must be compatible with closed or semi-closed cell culture systems, such as flasks or microfluidic cell culture chambers, or other 2D cell culture vessels that do not allow manual access to the cell culture area. Selective cell extraction and analysis must also be compatible with existing analytical techniques, including, but not limited to, qPCR, RNA sequencing, DNA sequencing, karyotyping, DNA methylation sequencing, chromatin accessibility measurements such as ATACseq / MNase-seq / DNase-seq, and proteomics measurements, including, but not limited to, microarrays, liquid chromatography, and mass spectrometry.

[0336] In the art, there are several current approaches for sampling cells during the cell culture process. One example is laser microdissection. This is a well-established technique in which samples are "dissected" from cells or tissue sheets and collected for analysis. This technique is often used on preserved intact tissues or when cells are fixed in foil for extraction. The disadvantage of this technique is that it is generally only suitable for continuous tissues, not where individual cells are present, and requires mechanical extraction of the detached cell sheet, which can be performed in several ways, all of which generally make it incompatible with long-term cell culture systems, especially those that are semi-closed (such as tissue culture flasks) or fully closed (such as microfluidic cell culture vessels).

[0337] Another approach is foil-based, in which tissue is attached to a foil that absorbs laser radiation and can be cut, allowing sections to be cut and then mechanically collected. Another approach is membrane collection, in which, after cutting of the desired tissue section, a "stamp" containing a rough membrane is lowered onto the tissue surface to contact the desired section, and the section is collected. Another method is release / gravity, in which tissue sections are suspended in air (on foil) and the laser-cut sections fall into a collection chamber. Another method is called fluorescence in-situ hybridization (FISH), which includes both DNA-FISH and RNA-FISH. This technique allows for the labeling and in situ imaging of several defined DNA or RNA sequences. However, cells must be fixed before hybridization and labeling, the number of sequences that can be examined is generally limited, and high-resolution fluorescence microscopy is required to image the fluorophores. Yet another approach is micropipette-based extraction of cells or subcellular components. These techniques can also target individual cells or small groups of cells and can work on living cell cultures.

[0338] Spatial transcriptome techniques for cell sampling also exist. These techniques rely on specialized surfaces pre-coded with DNA sequences to enable tracking of the spatial origin of RNA molecules. To date, these techniques have primarily been developed for tissue sections preserved in thin slices for use in pathology or ex-vivo studies. The drawbacks of this approach are that they are not applicable to in situ measurements of living cell cultures and that they are currently limited to RNA sequencing.

[0339] In short, existing methods address situations where preserved tissue samples are used, or can operate on recent live cells but involve expensive equipment and consumables, and there is no viable option for using standard analytical methods in combination with dynamic live-cell imaging. In particular, current approaches are not suitable for performing such measurements inside sealed or semi-sealed cell cultures, and possibly during the course of cellular processes (without damaging remaining live cells). Therefore, what is needed in the art is a method for extracting and sampling cells during the cell culture process in a sealed, automated cell culture system without disturbing the cell growth process.

[0340] The systems and methods disclosed herein include a system for selective cell extraction and sampling compatible with a cell culture system (e.g., cell culture system 100). The system may include a cell culture chamber suitable for long-term cell culture and imaging, a coating on the cell culture chamber for laser absorption (but transparent to imaging light), an imaging subsystem configured to image cells resident on the coating surface, a computing subsystem for selecting one or more cells for analysis, and a cell editing subsystem that uses laser pulses that impinge on the coating to create explosive microbubbles and cavitation. Cells are detached from the coating surface as a result of the microbubbles and recovered via liquid extraction, and / or cells are lysed by the microbubbles and their components are collected via liquid extraction. Cells and / or cell components can then be analyzed via various analytical techniques. In some implementations, cells to be analyzed can be selected by their image characteristics, including time-series image characteristics and / or analysis thereof. In some implementations, a series of laser and liquid removal processes can be used to sample multiple subpopulations.

[0341] Additional methods of targeted cell extraction or cell lysis are contemplated in the present disclosure. For example, cells can be extracted using a magnetic tool operable within a live cell culture vessel, including a sealed fluid chamber or cassette. The magnetic tool can be controlled by an external component that actuates components within the chamber, which is guided by a computing subsystem based on imaging data. In a variation, focused ultrasound operable within a live cell culture vessel, including a sealed fluid chamber or cassette, can be used to extract cells. An external transducer that transmits focused sound waves through the vessel wall can be used to focus the cells of interest and loosen them from the cell culture surface. The transducer can be controlled by a computing subsystem based on imaging data.

[0342] Cell lysis may be performed in situ, and the resulting debris, along with the surrounding liquid, may be removed from the vessel. If cell lysis is performed in situ, the cell culture fluid medium may be replaced with an "extraction and measurement" medium prior to lysis. This extraction medium may be free of potential contaminants, components that interfere with downstream measurements, or sample degradation components such as RNAses. In some implementations, if cell lysis is performed in situ, the cells may be fixed prior to the process, and reverse transcription of RNA to cDNA may be performed in situ. This "freezes" the cell culture state, preserving mRNA information and allowing selective multicomponent collection of material over longer periods of time, if desired.

[0343] Cells can be selectively collected intact by this selective method and lysed prior to analysis, allowing for single-cell measurements. Once cells or cell debris have been selectively separated from the cell culture, collection may be accomplished in a variety of ways, including, but not limited to, pipetting (including automated pipetting systems) into open cell culture vessels such as microwell plates, and fluid exchange and evacuation within a closed fluid chamber, where fluid exiting the chamber is washed away along with the extracted cells.

[0344] There can be several approaches to selecting cells for extraction. For example, one approach is random sampling of cells from a cell culture. This can include random region selection of cells or cell components in a high-density cell culture (e.g., selecting random 2D patches to act on with a transducer and then collecting the material), or random region selection from cell-containing areas based on images of the cell culture. Using such images, regions of different local densities can be randomly sampled to obtain a representative sample. In another approach, sampling can be guided by manual annotation of the cell culture image, where a human observes the cell culture image, selects regions of interest, and the cell editing subsystem acts on these regions before sample extraction.

[0345] In another approach, sampling can be guided by image properties as measured by a computing subsystem (e.g., computing subsystem 100). Relevant image properties include: (1) the output of an image processing subsystem that measures local density, morphology, order, orientation, etc.; (2) the output of a machine learning model whose input is an image of a cell culture and whose output is a spatial map that classifies the cell culture at the cell, neighborhood, region, colony, or other level (the machine learning model can be, for example, a supervised model trained with labeling data or an unsupervised model that classifies spatial regions into a series of clusters based solely on image data); (3) the output of a computing subsystem that locates each cell in the cell culture and calculates local properties such as cell morphology, density, colony membership, etc.; and (4) the output of a computing subsystem that locates each colony and calculates colony properties, including time series properties.

[0346] 36A-E illustrate selective cell extraction and analysis of adherent cells according to various implementations. In FIG. 36A, cells 3602 undergo a cell culture process within a cell culture vessel 3604. The cells 3602 may be attached to a surface of the cell culture vessel 3604, which may be configured to allow imaging (e.g., a transparent surface). The cells are imaged using an imaging subsystem 3606 (e.g., the cell imaging subsystem 112), which transmits data to a computing subsystem 3608 (e.g., the computing subsystem 110). In one example, the computing subsystem 3608 can classify regions of cells by texture, morphological characteristics, and time-series characteristics (e.g., changes in characteristics over time, optical flow measurements) using an unsupervised clustering model to classify cell regions. Similarly, the computing subsystem 3608 can identify individual colonies and categorize cells by colony affiliation.

[0347] In Figure 36B, computing subsystem 3608 can select a first group of cells for lysis using any of the methods described herein (e.g., an unsupervised clustering model). Computing subsystem 3608 can control cell editing subsystem 3612 (e.g., cell editing subsystem 114) to lyse the selected cells using a non-contact lysis method. For example, cell editing subsystem 3612 can be a directed pulsed laser system that interacts with a coating on the interior surface of cell culture vessel 3604 to form explosive microbubbles, lysing the target cells. Prior to this lysis process, the cell culture medium within cell culture vessel 3604 can be replaced with a dedicated temporary lysis and material collection buffer that is RNAse-free and / or may contain compounds that accelerate cell dissociation during lysis.

[0348] In Figure 36C, liquid is removed from cell culture vessel 3604. The liquid contains components of cells that have been targeted and lysed by cell editing subsystem 3612. In the example shown in Figure 36C, an automated pipetting system 3614 is used to remove liquid from cell culture vessel 3604. Automated pipetting system 3614 may optionally position pipettes to withdraw liquid from specific areas where cells have been lysed and only a portion of the total liquid in cell culture vessel 3604 has been removed, maximizing the concentration of cellular components in the collected liquid. Automated pipetting system 3614 is only one possible method of liquid extraction. Generally, multiple liquid extraction methods may also be used to remove liquid containing lysed cellular components. The lysis and extraction process shown in Figures 36B-C may be repeated multiple times for each different cell population being identified.

[0349] In Figure 36D, extracted cell samples can be processed for analysis according to one or more existing analytical techniques. For example, two cell samples 3602a and 3602b may have already been extracted. In one example, each sample 3602a, 3602b is analyzed by qPCR, and the levels of expression of a set of target genes, along with housekeeping genes that normalize for cell abundance, are measured and compared with each other and with reference readings. Data analysis is illustrated in Figure 36D by chart 3616. This approach may enable analysis of multiple cell phenotypes associated with image or image time series characteristics. This information may be used by the cell culture system in future predictive models and process optimization operations. For example, the cell culture system may selectively lyse cells and remove them from the cell culture vessel for analysis. The cell culture system may use the obtained information to monitor the progress and success of similar cell cultures, both through imaging alone and through the use of machine learning models (here trained using qPCR data and other information), and may also use this information to optimize cell culture processes that impart specific output cell target attributes.

[0350] Various intracellular components obtained via the extraction techniques disclosed herein can be used as biomarkers suitable for downstream analysis. Examples of intracellular components include cell surface proteins (especially surface biomarkers), cytoplasmic proteins, cytoplasmic RNA, nuclear proteins, mitochondrial DNA / RNA, and extracellular vesicles (EVs) and their associated materials (endosomes, exosomes, and their associated contents). RNA may include total RNA, ongoing RNA transcripts, enhancer RNA, general non-coding RNA (including, but not limited to, lncRNA, lincRNA, snoRNA, miRNA, and the like), mRNA, or any combination thereof.

[0351] Various capture techniques can be used to obtain the target intracellular component(s). Bead capture can be used to capture intracellular components after laser cell lysis. In some cases, the primary capture method uses magnetic beads targeted to a given intracellular component. Examples include DNA / RNA capture using SPRI paramagnetic beads (e.g., AmpureXP) and antibody-conjugated protein capture superparamagnetic beads (e.g., Protein A / G Dynabeads pre-complexed with an antibody targeting the protein of interest). Alternative bead / slurry methods, such as coated agarose-based bead capture for isolation of targeted molecules, can also be used if appropriate. Capture can also be achieved by collection of the total lysed material in an appropriate buffer for further downstream analysis, followed by gradient ultracentrifugation to isolate the component of interest (e.g., in the case of EVs).

[0352] The captured subcellular component(s) can be analyzed according to a variety of available analytical methods. For RNA, suitable methods include all applicable forms of NGS, including, but not limited to, total RNA-seq, mRNA-seq, scRNA-seq, enhancer RNA-seq, and exome capture sequencing approaches. More targeted qPCR-based evaluation and / or arrays can be used to evaluate isolated RNA on a smaller scale as well. For DNA, suitable methods include all applicable forms of NGS, including, but not limited to, ATAC-seq, ChIP-seq, scATAC-seq, whole-exome analysis, whole-genome sequencing, or targeted DNA region or sub-sequence sequencing. More targeted qPCR-based evaluation and / or arrays can be used to evaluate isolated DNA on a smaller scale as well.

[0353] In the case of proteins, analysis can be performed using a very wide and diverse array of downstream applications, depending on the amount and purity that can be isolated. Mass spectrometry-based or antibody probe-based methods can be used, for example, to assess the identity and / or quantity of selected protein biomarkers. Alternatively, any of a large number of other protein analytical methods (e.g., Western blot, ELISA, immunostaining, etc.) may be applied as needed.

[0354] Following selective extraction of cellular material, the cell culture process can continue within cell culture vessel 3604, as shown in FIG. 36E. In this manner, disclosed implementations enable collection of cellular material (often a very small fraction of the total growth) from a live cell culture, thus allowing the remaining cells to progress uninterrupted to the endpoint of the cell culture process. In some implementations, selective collection and analysis can be performed at multiple points during the cell culture process. The methods disclosed herein can be used for cellular processes, including, but not limited to, stem cell reprogramming (e.g., iPSC), stem cell differentiation, transdifferentiation, cell maturation, cellular gene editing, clonal growth and selection, and the like. The methods disclosed herein can be used to train image-based models to predict cellular process outcomes, or can be used directly to select optimal regions, colonies, clones, or cell cultures for further processing.

[0355] 37A-C illustrate selective cell extraction and analysis of semi-adherent cells according to various implementations. Semi-adherent cells can be grown in a cell culture vessel having a sealed liquid chamber, and cells can be selected for extraction based on imaging or imaging time-series characteristics. In FIG. 37A, the sealed liquid chamber can include a volume of liquid medium 3702 defined by an upper surface 3704 and a lower surface 3706. The upper and lower surfaces can be transparent so that cells within the sealed liquid chamber can be imaged using transmitted light imaging (e.g., bright-field imaging, Zernike phase imaging, dark-field imaging, differential interference contrast imaging, quantitative phase imaging, etc.).

[0356] In the example shown in Figure 37A, cells 3708 have already been introduced into the sealed liquid chamber when it is inverted (i.e., upper surface 3704 is below lower surface 3706), and due to their semi-adherent nature, they are weakly attached to upper surface 3704 when the chamber is inverted to the orientation shown in Figure 37A. When the sealed liquid chamber is inverted to the orientation shown in Figure 37A, any cells or debris that are not attached to upper surface 3704 fall towards lower surface 3706 and can be washed out of the sealed liquid chamber by pumping liquid therethrough.

[0357] An imaging subsystem 3710 (e.g., cellular imaging subsystem 112) can image cells 3708 adhering to the upper surface 3704 at one or more time points. A computing subsystem (e.g., computing subsystem 110) can calculate properties of individual cells based on size, morphology, intracellular content, polarization dependence, refractive index, phase, cell division, or other properties captured by the images. In some implementations, fluorescent labels can similarly be applied to indicate the presence of specific surface markers. In some implementations, trends over time of one or more of the measured properties are used. As a result of these observations, cells are grouped by classification. Cells can be grouped automatically by the computing subsystem or manually by a human operator who can view the distribution of these properties (e.g., one or more scatter plots) and select one or more clusters of cells of interest.

[0358] A non-invasive selective cell collection system (e.g., cell editing subsystem 114) can be used to remove selected cells 3712 having a particular classification from upper surface 3704, as shown in FIG. 37B. For example, the cell collection system can be a pulsed laser system that generates microbubbles when they impact an absorbent film on upper surface 3704. The microbubbles detach selected cells 3712 from upper surface 3704, causing them to fall off upper surface 3704 and into liquid medium 3702 contained within the cell chamber.

[0359] The selected cells 3712 are then collected from the sealed liquid chamber by exchanging the liquid medium 3702 in the chamber, as shown in Figure 37C. The medium exchange may be performed as part of a standard medium exchange. The selected cells 3712 are then collected for analysis. Because the selected cells 3712 are intact when extracted, both bulk analysis techniques as well as single-cell techniques such as single-cell RNAseq can be used on the collected cells.

[0360] 38A-C illustrate a cell culture process involving selective cell extraction and analysis according to various implementations. FIG. 38A shows a perfused cell culture chamber 3802 within which a cell culture 3804 is grown. For example, the cell culture 3804 may be an adherent cell culture in a continuous perfusion 2D reactor and may be approaching a specified maximum cell culture density. The cell culture 3804 may be periodically imaged to assess the culture density and, optionally, to identify the location of cells / colonies to be treated. The number of cells may be periodically reduced via non-invasive cell editing methods (e.g., using laser, ultrasound, or magnetic tool techniques described herein) to prevent cell overgrowth. This may be useful in certain cell culture processes, for example, during the elimination of episomal or viral vectors from cells, where each cell division reduces the vector load within the cell population.

[0361] In Figure 38B, a subset of cells 3806 in the cell culture can be targeted for lysis. The selected subset of cells 3806 is shown as a dark band as shown in Figure 38B. The cells can be selected in a pre-set pattern, as shown in Figure 38B, or can be based on the organization of the cells in the cell culture 3804. For example, cells can be selected from areas of the cell culture 3804 that are most dense, or areas close to the border of the cell culture chamber 3802 (where conditions are more variable), or some combination of these or other factors.

[0362] A selected subset of cells 3806 can be lysed, as shown in FIG. 38C, and the lysed cells can be suspended in a fluid medium within the cell culture chamber 3802. The fluid medium can be replaced or flushed away, and at least a portion of the spent fluid medium containing the lysed cellular debris can be collected by a sampling bag 3808 or some other collection mechanism. In the case of collection via the sampling bag 3808, a pinch valve 3810 in the primary fluid path can be closed to direct the fluid medium to the sampling bag 3808. The sampling bag 3808 can then be detached using a sterile tube weld, allowing for sterile detachment of the sample bag 3808 from the cell culture system. The contents of the sampling bag 3808 can then be sent for analysis. In an alternative implementation, an analytical system can be directly connected to the cell culture system to enable online measurement of the resulting cellular material without detaching the sample bag or container. Such an online system can perform further cleavage / homogenization of the cellular debris, filtration, preparation steps, and subsequent analysis of the cellular contents.

[0363] Using the example of iPSC reprogramming in which the reprogramming vector is eliminated over time, measurements enabled by the system include, for example, qPCR measurements of the contents of sampling bag 3808 measuring RNA expression levels of one or more housekeeping genes (e.g., GAPDH) to normalize cell number, (2) one or more components of the reprogramming vector, e.g., OCT4 if an episomal reprogramming vector is included, to monitor vector elimination, and (3) one or more non-vector gene expression, e.g., SSEA4 if not included in the vector, to measure cellular pluripotency markers. Vector-specific measurements can assess the progress of vector elimination from cells (conditions necessary for the process to be completed). Expression of endogenous genes can be used to verify that the cell culture remains highly pluripotent and has not differentiated. Optionally, potentially differentiating regions can be selectively harvested from regions deemed pluripotent in separate replicates, which can be confirmed by analysis of cell lysates.

[0364] 39 is a flowchart illustrating a method 3900 of cell extraction and analysis according to various implementations. Method 3900 can be performed by a cell culture system (e.g., cell culture system 100 of FIG. 1). In some implementations, method 3900 can be performed by a combination of an automated cell culture system and manual human labor.

[0365] At block 3902, a cell culture may be grown in a cell culture vessel (e.g., cell culture vessel 106). The cell culture may be adherent or semi-adherent cells attached to a cell growth surface of a cell culture chamber in the cell culture vessel. The cell growth surface may be transparent to allow imaging of the cell culture. The cell culture vessel may be a closed system, such as a closed cassette.

[0366] At block 3904, the cell culture system may acquire one or more images of the cell culture. For example, the cell culture system may include a cellular imaging subsystem (e.g., cellular imaging subsystem 112) configured to capture one or more images of the cell culture. In some implementations, the images may be a time series of images of the cell culture.

[0367] At block 3906, the cell culture system may identify one or more cells to extract from the cell culture. For example, a computing subsystem (e.g., computing subsystem 110) may identify and select one or more cells to extract based on the collected images. The computing subsystem may use one or more characteristics derived from the cell images to determine the cells to extract. The characteristics may include direct measurements or observations from the images as well as the output of various machine learning models or other algorithms that process the images. For example, the computing subsystem may classify cell regions by texture, morphological characteristics, and time-series characteristics (e.g., changes in characteristics over time, optical flow measurements) using an unsupervised clustering model. Similarly, the computing subsystem may identify individual colonies and group cells by colony membership. The computing subsystem may then select one or more cells from each cell region or colony so that cells with different characteristics can be extracted and sampled. In some implementations, cell identification may be performed manually by a human rather than by the cell culture system.

[0368] At block 3908, the cell culture system may selectively extract the identified cells. For example, a cell editing subsystem (e.g., cell editing subsystem 114) may be used to lyse or remove the identified cells from the cell growth surface of the cell culture chamber. The cell editing subsystem may use, for example, laser, ultrasound, or magnetic tools, among other approaches, to remove the identified cells without destroying them. Prior to extraction, the fluid medium in the cell culture chamber may be replaced with a specialized fluid that accelerates cell dissociation upon lysis. The removed cells may then be extracted from the cell culture chamber using fluid medium exchange / washout, an automated pipetting system, or other means.

[0369] At block 3910, the cell culture system may analyze the extracted cells. For example, qPCR assays and other tests / assays / measurements may be performed to determine various properties and characteristics of the extracted cells. The cell culture system may periodically repeat the steps shown in blocks 3904-3910 to extract and sample cells at different points during the cell culture process.

[0370] At block 3912, the cell culture system may adjust the cell culture process based on the analysis of the extracted cells. For example, the cell culture system may determine that sampled cells from a particular cell colony are outside of preferred cell growth parameters and therefore need to be destroyed. In another example, the cell culture system may determine that sampled cells from a particular cell colony may require additional nutrients and may initiate a fluid medium exchange to freshen the medium in the cell culture chamber. Generally, the cell culture system may alter certain environmental or growth parameters, destroy certain cells, or take other actions based on the results of the analysis. The cell culture system may also incorporate the data into machine learning models to improve the cell culture process in the future. In this manner, method 3900 provides a method of selective extraction and analysis that benefits the operation of the cell culture system and provides dynamic cell growth feedback.

[0371] Wavelength-selective films for cell culture imaging and control The industrialization of cell-based processes, such as bioprocessing and cell therapy, has rapidly increased the need for tools to manipulate cells in cell culture. High variability in cell culture processes drives the need for tools that can respond to real-time cell culture conditions, not only at the vessel level but also at the local level. Information about cell culture conditions can be useful for making various cell culture process decisions, such as adding media, reagents, buffers, or other compounds to the entire cell culture, or for terminating the cell culture, either positively for harvest or negatively for disposal.

[0372] One preferred method for monitoring cell cultures at a local level, whether it be a region, colony, local cluster of cells, or single cell level, is by imaging. Imaging can be performed by fluorescent label imaging or using label-free imaging such as bright field, phase contrast, dark field, or other transmission / scattering-based techniques. These techniques, particularly label-free techniques, require cell culture vessels and / or inserts into these vessels. These are designed to enable high-fidelity imaging, i.e., transmit light efficiently and without causing diffraction or other spatial artifacts, and do not interfere with the imaging of the contained cell culture.

[0373] At the same time, various tools for active cell culture manipulation have been developed, mostly intended to replace open-loop cell culture control (where only vessel-level changes are applied to the contained cells as a whole) or manual processes such as scraping cells with a pipette or manually transferring cell colonies from one vessel to another. These tools include tools for selective cell removal and tools for the selective intracellular delivery of compounds to cells in cell culture. A wide range of such tools used to manipulate cells is described in Stewart, Martin P. et al., "Intracellular Delivery by Membrane Disruption: Mechanisms, Strategies, and Concepts," Chem. Rev. 118, 16, 7409-7531 (2018), the entire contents of which are incorporated herein by reference.

[0374] One known method for selective cell manipulation is the use of optical energy. For example, optical cell trapping can be used to move cells individually, and optoporation can be used to focus light on individual cell membranes to perforate them for compound ...

Claims

1. 1. A system for culturing cells, comprising: a cell culture vessel including a first surface configured to have a plurality of cell colonies continuously attached thereto throughout a cell culture process; an image sensor configured to capture one or more time-series images of the plurality of cell colonies during the cell culture process; a cell removal tool configured to remove one or more cells from the first surface of the cell culture vessel during the cell culture process; a computing subsystem, tracking one or more characteristics of the plurality of cell colonies based on the one or more time series images; the computing subsystem configured to control the cell removal tool to remove cells based on the one or more characteristics; The system comprising:

2. 10. The system of claim 1, wherein the cell culture process comprises producing a plurality of clonal induced pluripotent stem cells (iPSCs) from a plurality of somatic cells.

3. The cell culture process comprises: reprogramming said plurality of somatic cells to form a plurality of iPSC colonies; The computing subsystem includes: maintaining a cell density of the plurality of iPSC cell colonies below a first threshold; selecting a first clonal iPSC cell colony from the plurality of iPSC cell colonies; removing the plurality of iPSC cell colonies other than the first clonal iPSC cell colony from the first surface; and further configured to maintain a cell density of the first clonal iPSC cell colony below a second threshold amount during expansion of the first clonal iPSC colony. The system of claim 2 .

4. The first threshold is 750,000 cells / cm ２ , 500,000 cells / cm ２ , 400,000 cells / cm ２ , 300,000 cells / cm ２ , or 250,000 cells cm ２ The system of claim 3, wherein the system is one of:

5. The second threshold is 750,000 cells / cm ２ , 500,000 cells / cm ２ , 400,000 cells / cm ２ , 300,000 cells / cm ２ , or 250,000 cells cm ２ The system of claim 3, wherein the system is one of:

6. 10. The system of claim 1, wherein the cell culture process has a duration of one of at least 7 days, at least 10 days, at least 20 days, at least 30 days, at least 45 days, or at least 60 days.

7. 4. The system of claim 3, wherein maintaining the cell density of the plurality of iPSC cell colonies below the first threshold comprises repeatedly removing portions of the plurality of iPSC cell colonies and expanding remainders of the plurality of iPSC cell colonies.

8. The system of claim 3 , wherein selecting the first clonal iPSC cell colony is based on the one or more characteristics.

9. 9. The system of claim 8, wherein the first clonal iPSC cell colony has the highest clonal quality among the plurality of iPSC cell colonies based on the one or more characteristics.

10. 4. The system of claim 3, wherein the cell culture process further comprises extracting a portion of the first clonal iPSC cell colony from the first cell culture vessel.

11. The cell culture process comprises: profiling a portion of the first clonal iPSC cell colony; and The system of claim 10 further comprising: providing the resulting profile to the computing subsystem.

12. 10. The system of claim 1, wherein the computing subsystem is configured to provide the one or more characteristics to a machine learning model and receive instructions therefrom on which cells to remove.

13. The system of claim 1 , wherein the cell removal tool comprises a pulsed laser.

14. The system of claim 13 , wherein the pulsed laser comprises one or more visible light lasers.

15. The system of claim 13 , wherein the first surface comprises a laser film.

16. 16. The system of claim 15, wherein the laser film is semi-transparent and has wavelength-selective absorption.

17. The system of claim 15 , wherein the laser film is a plasmonic film.

18. 16. The system of claim 15, wherein the laser film is configured to enable light-based cellular imaging.

19. 20. The system of claim 18, wherein the light-based cellular imaging is within an imaging wavelength range detectable by the image sensor.

20. 20. The system of claim 19, wherein the laser film is further configured to enable light-based cell ablation within an ablation wavelength range emitted by the pulsed laser, the ablation wavelength range being different from the imaging wavelength range.

21. 16. The system of claim 15, wherein the laser film has properties that absorb light energy from the pulsed laser, thereby removing the one or more cells from the first surface.

22. 16. The system of claim 15, wherein the laser film has a property of at least partially absorbing optical energy from the pulsed laser within a first range of wavelengths and a property of at least partially transmitting optical energy to the imaging sensor within a second range of wavelengths.

23. 10. The system of claim 1, wherein the one or more characteristics are selected from cell proliferation rate, cell number, colony surface area, colony area growth rate, colony morphology, and fluorescent marker expression.

24. The system of claim 1 , wherein the cell removal tool comprises a continuous wave laser.

25. 25. The system of claim 24, wherein the first surface comprises a laser film and a biocoating, and the continuous wave laser is configured to ablate the biocoating.

26. 1. A method for culturing cells, comprising: introducing a plurality of cell colonies onto a first surface of a cell culture vessel, the first surface configured to have the plurality of cell colonies continuously adhere thereto throughout the cell culture process; capturing one or more time-series images of the plurality of cell colonies with an image sensor during a cell culture process; tracking, by a computing subsystem, one or more characteristics of the plurality of cell colonies based on the one or more time series images; controlling, by the computing subsystem, a cell removal tool to remove one or more cell colonies from the first surface of the cell culture vessel during the cell culture process based on the one or more characteristics; The method comprising:

27. 1. A computer program product for culturing cells, the computer program product including a computer-readable storage medium having program instructions embodied therein, the program instructions being executable by a processor, the computer program product causing the processor to: receiving one or more time series images of a plurality of cell colonies captured during a cell culture process, the plurality of cell colonies continuously adhering to a first surface throughout the cell culture process; tracking, by a computing subsystem, one or more characteristics of the plurality of cell colonies based on the one or more time series images; controlling, by the computing subsystem, a cell removal tool to remove one or more cell colonies from a substrate during the cell culture process based on the one or more characteristics. The computer program product.

28. 1. A system for culturing cells, comprising: a cell culture vessel including a first surface, the first surface configured to have one or more cell colonies attached thereto; an image sensor configured to capture one or more time series images of a first cell colony within the one or more cell colonies; a computing subsystem, calculating the surface area of ​​the first cell colony as the first cell colony grows; selecting a portion of the first cell colony for removal to reduce the surface area of ​​the first cell colony if its surface area exceeds a predetermined threshold; removing the selected portion of the first cell colony from the first surface using a cell removal tool; the computing subsystem configured to iteratively manage the surface area of ​​the first cell colony according to a method comprising: The system comprising:

29. 30. The system of claim 28, wherein the surface area is calculated based on the one or more time-series images of the first cell colony.

30. 30. The system of claim 28, wherein iteratively managing the surface area of ​​the first cell colony comprises increasing the clonality of the first cell colony over time.

31. 30. The system of claim 28, wherein the portion of the first cell colony is selected to migrate across the first surface as the remainder of the first cell colony grows.

32. 32. The system of claim 31 , wherein the first surface comprises an extracellular matrix, and a cell removal tool is configured to remove the extracellular matrix from beneath the selected portion of the first cell colony.

33. 33. The system of claim 32, wherein the absence of extracellular matrix throughout the region inhibits cells from proliferating within the region.

34. 30. The system of claim 28, wherein the cell removal tool comprises a continuous wave laser system.

35. 30. The system of claim 28, wherein the cell removal tool comprises a pulsed laser system.

36. 36. The system of claim 35, wherein the first surface comprises a laser film.

37. 37. The system of claim 36, wherein the laser film has the property of absorbing light energy from the pulsed laser, thereby removing one or more cells attached to the laser film.

38. 37. The system of claim 36, wherein the laser film has a property of at least partially absorbing optical energy from the pulsed laser within a first range of wavelengths and a property of at least partially transmitting optical energy to the imaging sensor within a second range of wavelengths.

39. 37. The system of claim 36, wherein the laser film is semi-transparent and has wavelength-selective absorption.

40. 37. The system of claim 36, wherein the laser film is a plasmonic film.

41. 37. The system of claim 36, wherein the laser film is configured to enable light-based cellular imaging.

42. 42. The system of claim 41, wherein the light-based cellular imaging is within an imaging wavelength range emitted by the image sensor.

43. 42. The system of claim 41, wherein the laser film is further configured to enable light-based cell ablation within an ablation wavelength range emitted by an electromagnetic radiation source, the ablation wavelength range being different from the imaging wavelength range.

44. 30. The system of claim 28, wherein the first surface is configured such that the first cell colony continues to adhere thereto continuously during the repeated administering.

45. 30. The system of claim 28, wherein iteratively managing the surface area of ​​the first cell colony comprises managing a cell density of the first cell colony.

46. 30. The system of claim 28, wherein the predetermined threshold is one of a 5-fold, 10-fold, 20-fold, 30-fold, 50-fold, or 100-fold increase in surface area of ​​the initial surface area of ​​the first cell colony.

47. 1. A method for culturing cells, comprising: introducing a plurality of cell colonies onto a first surface of a cell culture vessel, the first surface configured to have the plurality of cell colonies continuously adhere thereto throughout the cell culture process; capturing one or more time series images of a first cell colony within the one or more cell colonies; calculating a surface area of ​​the first cell colony as the first cell colony grows; selecting a portion of the first cell colony for removal to reduce the surface area of ​​the first cell colony if its surface area exceeds a predetermined threshold; removing the selected portion of the first cell colony from the first surface using a cell removal tool; The method comprising:

48. 1. A computer program product for culturing cells, the computer program product including a computer-readable storage medium having program instructions embodied therein, the program instructions being executable by a processor, the computer program product causing the processor to: capturing one or more time series images of a first cell colony captured during a cell culture process, the first cell colony continuously adhering to a first surface throughout the cell culture process; calculating a surface area of ​​the first cell colony as the first cell colony grows; selecting a portion of the first cell colony for removal to reduce the surface area of ​​the first cell colony if its surface area exceeds a predetermined threshold; and removing the selected portion of the first cell colony from the surface area using a cell removal tool. The computer program product.

49. 1. A system for culturing cells, comprising: a cell culture vessel including an enclosed cell culture chamber enclosing a fluid medium and a first surface configured for a cell culture to adhere thereto; a cell removal tool configured to selectively remove one or more cells from the first surface of the cell culture vessel; a controller configured to use the cell removal tool to repeatedly remove one or more cells, thereby maintaining the cell culture below a threshold density throughout the cell culture process; The system, wherein the cell culture chamber is configured to seal during the cell culture process.

50. 50. The system of claim 49, wherein the cell culture comprises one or more cell colonies.

51. 51. The system of claim 50, wherein the repeated removal of one or more cells comprises removing a portion of a first cell colony of the one or more cell colonies.

52. 52. The system of claim 51, wherein the portion is selected such that the remainder of the first cell colony after removal of the portion of the first cell colony migrates across the first surface.

53. 52. The system of claim 51, wherein the repetitive removal of one or more cells comprises dividing a first cell colony within the one or more cell colonies into a plurality of sub-colonies.

54. 54. The system of claim 53, wherein the cell removal tool is further configured to detach a first subcolony within the plurality of subcolonies from the first surface.

55. 55. The system of claim 54, wherein the cell culture vessel further comprises a fluid port configured to remove the first subcolony.

56. 56. The system of claim 55, wherein the cell removal tool is further configured to migrate the first subcolony to a first region of the first surface, and the fluid medium flushes cells from the first region through the fluid port.

57. 50. The system of claim 49, wherein the repeated removal of the one or more cells comprises increasing the size and confluence of the cell culture.

58. 50. The system of claim 49, wherein the cell removal tool comprises a continuous wave laser.

59. 50. The system of claim 49, wherein the cell removal tool comprises a pulsed laser.

60. 60. The system of claim 59, wherein the pulsed laser comprises one or more ultraviolet-visible lasers.

61. 60. The system of claim 59, wherein the first surface comprises a laser film.

62. 62. The system of claim 61, wherein the laser film has properties that absorb light energy from the pulsed laser, thereby removing the one or more cells from the first surface.

63. 62. The system of claim 61, wherein the laser film has a property of at least partially absorbing optical energy from the pulsed laser within a first range of wavelengths and a property of at least partially transmitting optical energy within a second range of wavelengths.

64. 50. The system of claim 49, wherein the first surface is configured to maintain the cell culture continuously attached thereto throughout the cell culture process.

65. 50. The system of claim 49, wherein the cell culture process comprises reprogramming and expanding induced pluripotent stem cells.

66. The threshold density is 750,000 cells / cm ２ , 500,000 cells / cm ２ , 400,000 cells / cm ２ , 300,000 cells / cm ２ , or 250,000 cells cm ２ 50. The system of claim 49, wherein:

67. 50. The system of claim 49, wherein the cell culture process has a duration of one of at least 7 days, at least 10 days, at least 20 days, at least 30 days, at least 45 days, or at least 60 days.

68. 1. A method for culturing cells, comprising: introducing a plurality of cell colonies onto a first surface of a cell culture vessel, the cell culture vessel including a cell culture chamber enclosing a fluid medium and the first surface; sealing the cell culture chamber throughout the cell culture process; using a cell removal tool to repeatedly remove one or more cells from the first surface, thereby maintaining the cell culture below a threshold density throughout the cell culture process; The method comprising:

69. 1. A computer program product for culturing cells, the computer program product including a computer-readable storage medium having program instructions embodied therein, the program instructions being executable by a processor, the computer program product causing the processor to: performing a method comprising: using a cell removal tool to repeatedly remove one or more cells from a first surface of a cell culture vessel, the cell culture vessel comprising a cell culture chamber enclosing a fluid medium and the first surface, thereby maintaining a cell culture below a threshold density throughout the cell culture process; The computer program product.

70. 1. A method for producing a gene-edited cell, comprising: seeding a plurality of gene-edited cells into a cell culture vessel; culturing the plurality of gene-edited cells into a plurality of gene-edited cell colonies using a cell culture system; cloning the plurality of gene-edited cell colonies by the cell culture system by repetitive, spatially selective removal of one or more portions from the plurality of gene-edited cell colonies as the colonies grow; tracking one or more characteristics of the plurality of gene-edited clonal cell colonies through the cell culture system; and maintaining a cell density of the plurality of gene-edited clonal cell colonies by the cell culture system based on the tracked characteristics; and selecting a first gene-edited clonal cell colony from the plurality of gene-edited clonal cell colonies by the cell culture system; removing the plurality of gene-edited clonal cell colonies other than the first gene-edited clonal cell colony from the cell culture vessel using the cell culture system; and expanding the first gene-edited clonal cell colony through the cell culture system.

71. 71. The method of Claim 70, further comprising harvesting at least a portion of the first gene-edited clonal cell colony by the cell culture system.

72. 72. The method of Claim 71, further comprising using the collected portion of the first gene-edited clonal cell colony in a cell therapy.

73. 71. The method of Claim 70, wherein the plurality of gene-edited cells comprises gene-edited induced pluripotent stem cells.

74. The cloning may include: a) expanding the plurality of gene-edited cell colonies through the cell culture system; b) removing a portion of each of the plurality of cell colonies by the cell culture system; and c) repeating steps a)-b), wherein with each iteration, the percentage of clonal cells within each of the plurality of gene-edited cell colonies increases.

71. The method of claim 70.

75. 71. The method of claim 70, wherein the one or more characteristics comprise at least one of cell proliferation rate, colony surface area, colony area growth rate, colony morphology, and fluorescent marker expression.

76. The tracking may include: capturing, by the cell culture system, a plurality of time series images of the plurality of gene-edited clonal cell colonies; determining a tracked characteristic from the plurality of time series images by the cell culture system; 71. The method of claim 70, comprising:

77. The maintaining a) expanding the plurality of gene-edited clonal cell colonies through the cell culture system; and b) determining, by the cell culture system, regions of each of the plurality of gene-edited clonal cell colonies to remove based on the one or more characteristics to maintain the cell density of the plurality of gene-edited clonal cell colonies below a threshold; c) removing the region of each of the plurality of gene-edited clonal cell colonies by the cell culture system; and d) repeating steps a) to c) until a target confluence is reached; 71. The method of claim 70, comprising:

78. 71. The method of Claim 70, wherein the cell culture system selects the first gene-edited clonal cell colony based on the one or more characteristics.

79. 71. The method of claim 70, wherein the cell culture system comprises at least one of an imaging sensor, a computing subsystem, and an electromagnetic radiation source.

80. 80. The method of claim 79, wherein the electromagnetic radiation source comprises a continuous wave laser.

81. 81. The method of claim 80, wherein the electromagnetic radiation source comprises a pulsed laser.

82. 82. The method of claim 81, wherein the cell culture vessel comprises a laser film and the plurality of gene-edited cells are cultured on the laser film.

83. 83. The method of claim 82, wherein the laser film has the property of absorbing light energy from the pulsed laser, thereby removing cells attached to the laser film.

84. 84. The method of claim 83, wherein the pulsed laser comprises one or more visible light lasers.

85. 85. The method of claim 84, wherein the laser film is semi-transparent and has wavelength selective absorption.

86. 86. The method of claim 85, wherein the laser film is a plasmonic film.

87. 83. The system of claim 82, wherein the laser film is configured to enable light-based cellular imaging.

88. 88. The system of claim 87, wherein the light-based cellular imaging is within an imaging wavelength range emitted by the image sensor.

89. 90. The system of claim 88, wherein the laser film is further configured to enable light-based cell ablation within an ablation wavelength range emitted by an electromagnetic radiation source, the ablation wavelength range being different from the imaging wavelength range.

90. 71. The method of Claim 70, wherein the plurality of gene-edited cells, the plurality of gene-edited cell colonies, and the plurality of gene-edited clonal cell colonies are serially attached to a first surface of the cell culture vessel.

91. 71. The method of claim 70, wherein the method has a duration of one of at least 7 days, at least 10 days, at least 20 days, at least 30 days, at least 45 days, or at least 60 days.

92. 1. A system for producing gene-edited cells, comprising: a first surface configured to accommodate a sealed cell culture chamber enclosing a fluid medium and a cell culture attached thereto; a cell removal tool configured to selectively remove one or more cells from the first surface, the cell removal tool being further configured to perform a method according to any one of claims 70 to 91; The system comprising:

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