Automated flow cytometry preparation and acquisition system, and method of using the same.

Abstract

This invention provides a robotic system for automated sample preparation and a method for preparing samples. [Solution] A processor comprising multiple sample processing modules, multiple robotic components integrated with the sample processing modules, and memory, wherein when a stored instruction is executed, the processor controls the sample processing modules and robotic components to prepare multiple samples for flow cytometry analysis, and an operable connection unit between the processor, the sample processing modules, and the multiple robotic components. The system includes a flow cytometer, which, when an instruction is executed by the processor, loads each prepared sample of the multiple samples into the flow cytometer, causes the flow cytometer to analyze each prepared sample of the multiple samples, and the operable connection unit operablely connects the processor, the sample processing modules, the flow cytometer, and the multiple robotic components.

Description

[Technical Field]

[0001] Cross-reference of related applications In accordance with 35 U.S. SC § 119(e), this application claims priority to the filing date of U.S. Provisional Patent Application No. 63 / 719,515, filed on 12 November 2024, the disclosures of which are incorporated herein by reference in their entirety. [Background technology]

[0002] Introduction The characterization of analytes in biological fluids is a crucial part of biological research, medical diagnosis, and the assessment of a patient's overall health and wellness. Detecting analytes in biological fluids such as human blood and blood-derived products can yield results that can play a role in determining treatment protocols for patients with various disease conditions.

[0003] Flow cytometry is a technique used to characterize and often sort biological materials, such as cells in blood samples or particles of interest in other types of biological or chemical samples. A flow cytometer typically includes a sample reservoir for receiving a fluid sample, such as a blood sample, and a sheath reservoir for containing sheath fluid. The flow cytometer transports particles (including cells) in the fluid sample as a flow of cells into the flow cell while directing the sheath fluid towards the flow cell. Light is irradiated into the flow stream to characterize its components. Variations in the material in the flow stream, such as morphology or the presence of fluorescent labels, can cause variations in the observed light, which enable characterization and separation. To characterize the components in the flow stream, light must strike and collect the flow stream. The light source in the flow cytometer can vary and may include one or more broad-spectrum lamps, light-emitting diodes, and single-wavelength lasers. The light source is aligned with the flow stream, and the optical response from the illuminated particles is collected and quantified.

[0004] The isolation of biological particles has been achieved by adding sorting or collection capabilities to flow cytometers. Particles in an isolated stream that are detected to possess one or more desired characteristics are individually isolated from the sample stream by mechanical or electrical removal. A common flow sorting technique utilizes droplet sorting, in which a fluid stream containing linearly isolated particles is divided into droplets. The droplets containing the particles of interest are charged and deflected towards the collection tube by passing through an electric field. Typically, linearly isolated particles in the stream are characterized as they pass through an observation point located directly below the nozzle tip. Once a particle is identified as meeting one or more desired criteria, the time it takes for the particle to reach the droplet departure point and detach from the stream in the droplet can be predicted. Ideally, a brief charge is applied to the fluid stream just before the droplet containing the selected particles detaches from the fluid stream, and then grounded immediately after the droplet detaches. The droplet to be sorted retains its charge when detaching from the fluid stream, while all other droplets remain uncharged.

[0005] Typically, before a sample is characterized by flow cytometry or analyzed by other means, samples such as biological samples require preparation, including, for example, staining and / or washing. Such preparation steps may be time- and labor-intensive, i.e., requiring an operator or technician to perform or supervise such aspects of sample preparation. Furthermore, when such preparation steps are performed or supervised by a human technician, they can introduce variability into the flow cytometry analysis of such prepared samples. [Overview of the project]

[0006] Therefore, the inventors recognized the need for a robotic system that enables fully automated sample preparation and fully automated flow cytometry analysis. In particular, a modular robotic system that enables automated sample preparation for flow cytometry assays is needed to provide a walkaway solution for staining, washing, and acquiring samples, which has the ability to perform multiple specific experiments simultaneously and in staggered order. Embodiments of the present disclosure address this need. Embodiments of the present disclosure address the limitations of existing technologies by providing a complete walkaway solution, i.e., a system configured to allow the preparation and analysis of flow cytometry samples without direct supervision or operation by the user. Such improvements to existing technologies can, among other things, improve the consistency and accuracy of sample preparation, as well as the efficiency and cost-effectiveness of sample preparation and flow cytometry analysis of prepared samples.

[0007] Aspects of the present disclosure include robotic systems for automated sample preparation. A system according to a particular embodiment includes a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, which, when executed by the processor, cause the processor to control the sample processing modules and robotic components to operate them to prepare a plurality of samples for flow cytometry analysis, and an operable connection between the processor, the sample processing modules, and the plurality of robotic components. A system according to a particular embodiment further includes a flow cytometer, the plurality of robotic components further integrated with the flow cytometer, the memory further containing stored instructions, which, when executed by the processor, cause the processor to control the sample processing modules, robotic components, and flow cytometer to load each of the plurality of prepared samples into the flow cytometer, and the flow cytometer to operate to analyze each of the plurality of prepared samples, and the operable connection operably connects the processor, the sample processing modules, the flow cytometer, and the plurality of robotic components.

[0008] A method for preparing samples for flow cytometry analysis using the system described herein is also provided. A method according to a particular embodiment includes introducing a plurality of samples into a first sample processing module of a plurality of sample processing modules of the system, wherein the system comprises a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, the instructions, when executed by the processor, causing the processor to control the sample processing modules and robotic components to operate in order to prepare a plurality of samples for flow cytometry analysis, and an operable connection between the processor, the sample processing modules and the plurality of robotic components, providing the system with sample preparation instructions, and activating the system to automatically prepare the samples in accordance with the sample preparation instructions. In some cases, the system further comprises a flow cytometer, and the sample preparation instructions further include instructions for loading the prepared samples into the flow cytometer using the robotic components, instructions for analyzing the samples by flow cytometry using the flow cytometer, and instructions for removing the samples from the flow cytometer using the robotic components.

[0009] Computerized methods for preparing samples for flow cytometry analysis using the system described herein are also provided. A computerized method according to a particular embodiment involves receiving a plurality of samples into a first sample processing module of a plurality of sample processing modules of the system, wherein the system comprises a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, the instructions, when executed by the processor, causing the processor to control the sample processing modules and robotic components to operate the sample processing modules and robotic components to prepare a plurality of samples for flow cytometry analysis, and controlling the robotic components to manipulate the plurality of samples using the sample processing modules in order to prepare the plurality of samples according to instructions stored in memory. In some cases, the system further comprises a flow cytometer, and the sample preparation instructions further include instructions for loading the prepared samples into the flow cytometer using the robotic components, instructions for analyzing the samples by flow cytometry using the flow cytometer, and instructions for removing the samples from the flow cytometer using the robotic components. [Brief explanation of the drawing]

[0010] This disclosure can be best understood by reading the following detailed description in conjunction with the attached drawings. The drawings include the following figures.

[0011] [Figure 1A] This document illustrates the steps of an exemplary workflow for sample preparation and flow cytometry analysis performed automatically by one embodiment of the system, compared to similar steps performed manually by a laboratory technician. [Figure 1B] Examples of adding manual and automated workflows are provided. [Figure 1C]Present examples of additional manual workflows and automated workflows. [Figure 1D] Illustrative microtiter plates and illustrative reagent troughs for use by a system according to one embodiment are shown. [Figure 1E] Present another example of an automated workflow for sample preparation and flow cytometry analysis of the prepared samples. [Figure 1F] An illustrative system for automated sample preparation according to one embodiment is shown. [Figure 1G] An illustrative system for automated sample preparation according to one embodiment is shown. [Figure 1H] An illustrative system for automated sample preparation according to one embodiment is shown. [Figure 1I] An illustrative system for automated sample preparation according to one embodiment is shown. [Figure 1J] An illustrative system for automated sample preparation according to one embodiment is shown. [Figure 1K] An illustrative system for automated sample preparation according to one embodiment is shown. [Figure 1L] An illustrative system for automated sample preparation according to another embodiment is shown. [Figure 1M] An illustrative system for automated sample preparation according to another embodiment is shown. [Figure 1N] An illustrative system for automated sample preparation according to yet another embodiment is shown. [Figure 10] An illustrative system for automated sample preparation according to yet another embodiment is shown. [Figure 1P] An illustrative system for automated sample preparation according to yet another embodiment is shown. [Figure 1Q] Illustrative sample processing modules that can be integrated into the systems of the present disclosure are shown. [Figure 1R] A schematic diagram of an illustrative system according to one embodiment is shown. [Figure 2] Present a flow cytometry system according to a particular embodiment. [Figure 3-1] This shows an image-enabled particle sorting machine according to a specific embodiment. [Figure 3-2] This shows an image-enabled particle sorting machine according to a specific embodiment. [Figure 4] A functional block diagram of a particle analysis system according to a specific embodiment is shown. [Figure 5] A functional block diagram of an example of a control system according to a specific embodiment is shown. [Figure 6A] A schematic diagram of a particle sorting machine system according to a specific embodiment is shown. [Figure 6B] A schematic diagram of a particle sorting machine system according to a specific embodiment is shown. [Figure 7A] A flowchart illustrating an automated sample preparation method for flow cytometry analysis according to different embodiments is shown. [Figure 7B] A flowchart illustrating an automated sample preparation method for flow cytometry analysis according to different embodiments is shown. [Figure 7C] A flowchart illustrating an automated sample preparation method for flow cytometry analysis according to different embodiments is shown. [Figure 8] This shows an embodiment of a computer-controlled system according to a specific example. [Modes for carrying out the invention]

[0012] Aspects of the present disclosure include robotic systems for automated sample preparation. A system according to a particular embodiment includes a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, which, when executed by the processor, cause the processor to control the sample processing modules and robotic components to operate them to prepare a plurality of samples for flow cytometry analysis, and an operable connection between the processor, the sample processing modules, and the plurality of robotic components. A system according to a particular embodiment further includes a flow cytometer, the plurality of robotic components further integrated with the flow cytometer, the memory further containing stored instructions, which, when executed by the processor, cause the processor to control the sample processing modules, robotic components, and flow cytometer to load each of the plurality of prepared samples into the flow cytometer, and the flow cytometer to operate to analyze each of the plurality of prepared samples, and the operable connection operably connects the processor, the sample processing modules, the flow cytometer, and the plurality of robotic components.

[0013] A method for preparing samples for flow cytometry analysis using the system described herein is also provided. A method according to a particular embodiment includes introducing a plurality of samples into a first sample processing module of a plurality of sample processing modules of the system, wherein the system comprises a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, the instructions, when executed by the processor, causing the processor to control the sample processing modules and robotic components to operate in order to prepare a plurality of samples for flow cytometry analysis, and an operable connection between the processor, the sample processing modules and the plurality of robotic components, providing the system with sample preparation instructions, and activating the system to automatically prepare the samples in accordance with the sample preparation instructions. In some cases, the system further comprises a flow cytometer, and the sample preparation instructions further include instructions for loading the prepared samples into the flow cytometer using the robotic components, instructions for analyzing the samples by flow cytometry using the flow cytometer, and instructions for removing the samples from the flow cytometer using the robotic components.

[0014] Computerized methods for preparing samples for flow cytometry analysis using the system described herein are also provided. A computerized method according to a particular embodiment involves receiving a plurality of samples into a first sample processing module of a plurality of sample processing modules of the system, wherein the system comprises a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, the instructions, when executed by the processor, causing the processor to control the sample processing modules and robotic components to operate the sample processing modules and robotic components to prepare a plurality of samples for flow cytometry analysis, and controlling the robotic components to manipulate the plurality of samples using the sample processing modules in order to prepare the plurality of samples according to instructions stored in memory. In some cases, the system further comprises a flow cytometer, and the sample preparation instructions further include instructions for loading the prepared samples into the flow cytometer using the robotic components, instructions for analyzing the samples by flow cytometry using the flow cytometer, and instructions for removing the samples from the flow cytometer using the robotic components.

[0015] Before describing this disclosure in more detail, it should be understood that this disclosure is not limited to the specific embodiments described and can therefore naturally vary. It should also be understood that the scope of this disclosure is limited only by the appended claims, and that the terms used herein are intended solely to describe and not to limit the specific embodiments.

[0016] Where a range of values ​​is presented, it should be understood that each value between the upper and lower limits of that range, up to one-tenth of the lower limit unit unless explicitly indicated otherwise in the context, and any other stated or intermediate values ​​within that stated range are included in this disclosure. The upper and lower limits of these smaller ranges may independently be included in the smaller range, except for any specifically excluded limits within the stated range, and are also included in this disclosure. If a stated range includes one or both limits, the range excluding one or both of those limits is also included in this disclosure.

[0017] In this specification, certain ranges are presented with numbers preceded by the term “approximately.” The term “approximately” is used herein to provide literal support for the exact number preceded by the term, as well as for numbers that are close to or nearly close to the number preceded by the term. In determining whether a number is close to or approximates a specifically stated number, the close or approximate unstated number may, in the context in which it is presented, represent a substantial equivalent of the specifically stated number.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art to which this disclosure belongs. Any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of this disclosure, but representative exemplary methods and materials are described here.

[0019] All publications and patents cited herein are incorporated herein by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference, and are incorporated herein by reference to disclose and describe the methods and / or materials to which the publications are relatedly cited. Any citation of a publication is for the purpose of making that disclosure prior to the filing date, and this disclosure should not be construed as an acknowledgment that such publication has no prior rights by prior disclosure. Furthermore, the publication dates presented may differ from the actual publication dates and may need to be independently verified.

[0020] It should be noted that, as used herein and in the appended claims, the singular forms “a,” “an,” and “the” refer to multiple subjects unless the context clearly indicates otherwise. It should also be noted that claims may be written to exclude any optional element. Therefore, this statement is intended to serve as a precedent for the use of exclusive terms such as “alone” and “only” in relation to the enumeration of elements in the claims or the use of “negative” limitations.

[0021] As will be obvious to those skilled in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has separate components and features that can be readily separated from or combined with any of the features of several other embodiments without departing from the scope or spirit of this disclosure. Any method of description may be carried out in the order of the described events or in any other logically possible order.

[0022] While systems and methods are described for grammatical fluidity with functional descriptions, claims should not necessarily be interpreted as being limited by constructing a limitation of “means” or “steps” unless explicitly formulated under 35 U.S. SC § 112, and should be given the meaning of the definitions and the full scope of equivalents provided by the claims under the doctrine of equivalents, and if the claims are explicitly formulated under 35 U.S. SC § 112, it should be clearly understood that a full set of statutory equivalents should be given under 35 U.S. SC § 112.

[0023] system overview: Aspects of this disclosure include robotic systems for automated sample preparation. “Automated sample preparation” means that the system of the present invention is configured to automatically prepare a sample, i.e., to automatically prepare a sample for flow cytometry analysis. “Automatically” means, for example, that the system is configured to perform sample preparation in a walkaway manner, where walkaway means that the system prepares the sample automatically so that a user, e.g., a system operator, does not need to interact with, manipulate, or otherwise control the sample or the system, i.e., the system reliably and safely prepares the sample for flow cytometry analysis so that a user or system operator can leave the system, i.e., does not need to pay attention to the system. In some cases, the system is configured to automatically prepare multiple samples for flow cytometry analysis. In some cases, the system is configured to automatically and sequentially prepare multiple samples for flow cytometry analysis. Sequentially preparing multiple samples means that embodiments of the system may be configured to stagger the preparation of multiple distinct sample preparation workflows. In some cases, preparing multiple samples sequentially means that two or more samples are prepared by the system at the same time, that is, a specific sample preparation module is used to prepare the first sample, while a specific other sample preparation module is used to prepare the second sample simultaneously.

[0024] Sample preparation means performing any desired operation on a sample so that the sample or aspects of the sample can be analyzed by flow cytometry. In some cases, sample preparation includes staining and / or washing the sample. Other examples of sample preparation steps are provided herein. In embodiments, sample preparation includes utilizing one of a plurality of sample processing modules included in embodiments of the system of the present invention. In embodiments, the sample processing module includes, for example, one or more liquid handlers, centrifuges, or incubators. Other examples of such sample processing modules are provided herein.

[0025] A “robot” system means that the system comprises multiple robotic components, i.e., components that can independently grasp and move objects, such as sample plates. In embodiments, robotic components include, for example, robotic arms, robotic clamps, or robotic grippers. Other examples of robotic components are provided herein. A “modular” system means that embodiments of the system may be configured to include different combinations of sample preparation modules and / or different combinations of robotic components. As described herein, standard laboratory equipment is used in the system, and therefore, a modular system may be configured with different laboratory equipment or different numbers of laboratory equipment instances. In some cases, after the system has been deployed, for example, after it has been installed in a laboratory environment, the sample processing modules and / or robotic components may be modified or changed, for example, replaced.

[0026] Embodiments of the system of this disclosure integrate robotics with a typical standalone laboratory setup to enable automated sample preparation and sample acquisition for flow cytometry assays. In the embodiments, a robotic arm interacts with integrated laboratory setup components to mimic human movement in a laboratory space, replicating the antibody dilution process, the cell staining process with fluorescence-conjugated antibodies, the sample washing process, and the resuspension process for subsequent transfer to a flow cytometer, enabling automated data acquisition. While there is flexibility regarding the possibility of preparing samples in test tube and / or deep-well plate formats, the primary output of the system embodiments is a fully stained flow cytometry sample formatted as desired, for example, in a 96-well standard depth plate format. In some cases, multiple 96-well plates can be prepared for a given flow cytometry experiment, allowing the user, i.e., the system operator, e.g., a scientist, to rapidly increase weekly test throughput. Inventions of such integrated systems enhance experimental power, promote workflow standardization, and improve reproducibility by automating error-prone manual steps that can lead to user-to-user variability (i.e., steps not used in embodiments of the system of this disclosure). A key advantage provided by embodiments of the system of this disclosure, through the implementation of specially selected robotics programmed to mimic human interaction in a laboratory environment, is the ability to enable walkaway flow cytometry sample preparation and acquisition without human supervision, and ultimately, to expand and maximize working time over any given period, e.g., one week of working time.

[0027] In some cases, embodiments of the system of the present invention are configured and operate as follows: (1) A static robotic arm and a second robotic arm on a moving trajectory are positioned to reach all the important experimental equipment components of this embodiment of the integrated system. The static robotic arm is equipped with a dedicated gripper to enable the vertical loading and unloading of sample plates into the centrifuge unit. (2) Each instrument is connected to a larger system to receive and transmit commands via a single scheduling software. (3) The scheduling software is programmed to mimic a human process for a flow cytometry assay by combining in appropriate combinations the processes on the integrated experimental equipment (e.g., including a liquid handler, barcode scanner, centrifuge, washing station, incubator, sample hotel / stacker and / or flow cytometer) performed by the two robotic arms. Given the modularity of the embodiments of the system of the present disclosure, any or all of the equipment components of the system can be selected and combined for assay execution. (4) Via the scheduling software, the liquid handler is commanded to perform any selected sequence of pre-programmed but configurable scripts for handling reagents and samples and pipetting. (5) Flexibility to schedule flow cytometry assays in advance and / or to run two or more assays simultaneously. (6) Pre-configured communications and warning messages are sent to users, such as system operators or research operators, to notify them of status updates and the completion of assay executions.

[0028] System advantages: Embodiments of the system offer several advantages over existing solutions. Such advantages include, but are not limited to, the following: (1) flexibility in sample preparation and handling in multiple laboratory instrument formats (test tubes and plates), but a clear focus on the 96-well sample plate format for increased sample throughput and improved experimental capabilities. (2) the ability to prepare and process multiple 96-well sample plates in a single assay run, as well as across multiple staggered scheduled assay runs. Other technologies focus only on test tube handling or have limited plate throughput. (3) Embodiments of the system enable end-to-end walkaway automation throughout the entire sample preparation and sample acquisition process. This is an advantage over existing systems, as none of their platforms have the comprehensive capability to fully automate both the sample preparation and sample acquisition processes to the extent that the embodiment of the system of this disclosure enables sample plate throughput and the degree of sample mixing and sample combinations. (4) Embodiments of the system of the present invention can operate unattended overnight after a standard shift, not only because of their ability to acquire sample plates on a flow cytometer instrument, but also because they can initiate methods for handling sample preparation reagents and samples on a liquid handler.

[0029] Existing technologies within the sample preparation space include: (1) BD FACSLyric integrated with the BD FACSDuet premium sample preparation system. Information on this existing technology can be found on the website, which is obtained by adding "https: / / www." before "bdbiosciences.com / en-us / products / instruments / sample-prep-systems / facslyric-with-facsduet", and this website is incorporated herein in its entirety. This technology provides a technology with automated sample transfer through physical integration with a BD FACSLyric flow cytometer, which includes a comprehensive sample preparation system that assists with onboard mixing (up to 45 reagents), washing and centrifugation, and enables subsequent automated sample acquisition. However, this technology focuses on reagent mixing (up to 23 reagents) as well as sample preparation and tube handling (up to 40 samples per worklist with continuous loading), but only has the capacity to process one sample plate (96 wells) at a time. Therefore, this existing technology does not realize the advantages of experimental power and sample flexibility that the embodiments of the system of this disclosure realize, as BD FACSLyric, integrated with the BD FACSDuet premium sample preparation system, is configured to operate in test tubes only for fixed-panel clinical flow cytometry studies.

[0030] Existing technologies within the sample preparation space further include Stratedigm Flow Cytometer Automation. Information on this existing technology can be found on the website, which is obtained by adding "https: / / " before "stratedigm.com / flow-cytometer-automation", and this website is incorporated herein in its entirety. This technology enables the integration of a sample plate hotel (A710), a microplate mover robotic arm (A710 HTH), temperature-controlled incubators (A800, A810), a high-throughput plate autosampler (A600 HTAS), and a bulk reagent fluid storage module (A640 CPM-4 bulk fluid container) with the flow cytometer instrument platform. However, this existing technology does not have the experimental capabilities provided by embodiments of the present disclosure, cannot prepare multiple sample plates with a wide variety of reagents (embodiments of the system of the present disclosure can support a number significantly greater than 23, and are not limited), and cannot handle a variety of specimens (this too is not limited by embodiments of the system of the present disclosure). This existing technology does not perform reagent mixing and cell sample staining, which are carried out by the integrated liquid handler in the embodiment of the system of this disclosure.

[0031] Existing technologies within the sample preparation space further include the Cytek Orion Reagent Cocktail Preparation System. Information on this existing technology can be found on the website, which is accessed by adding "https: / / " before "cytekbio.com / pages / orion", and this website is incorporated herein in its entirety. This existing technology allows researchers to automate the preparation of antibody mixtures for flow cytometry, with the ability to create mixtures containing up to 60 individual antibodies. However, this existing technology is a standalone system that replicates a small liquid handler with limited functionality and the inability to centrifuge and wash the sample combined with the mixture. This existing technology is not integrated with a flow cytometer.

[0032] Further embodiments of the system: Embodiments of the system of this disclosure for automated flow cytometry preparation and acquisition are configured to automate flow cytometry preparation, staining, and testing by integrating and automating antibody dilution, sample staining with antibody, sample centrifugation and washing, and transfer to a flow cytometer for data acquisition. Such a system can be used to prepare multiple samples in the fields of immunology, cell biology, stem cells, and antigen discovery. Specific main use cases of this system include, but are not limited to, the following flow cytometry processes: antibody discovery screening, determination of optimal antibody concentrations, antibody stability testing over time, and quality testing of large-scale production antibodies.

[0033] In an embodiment, the system is a modular robotic system comprising the following components for performing key lab bench processes: a liquid handler, e.g., Hamilton Vantage for handling liquids; a plate washer and aspirator, e.g., Biotek Elx405 for plate washing and suction; a centrifuge, e.g., Hettich Rotanta for temperature-controlled centrifugation of plates; a flow cytometer, e.g., Bio-Rad ZES for flow cytometry acquisition; a storage device, e.g., Thermo Fisher Cytomat 10c for storing experimental resources at controlled temperature and humidity; additional storage devices, e.g., two plate hotels for storing experimental resources at room temperature; a barcode scanner, e.g., MicroScan ESP for barcode scanning and plate tracking; and two robotic arms for coordinating the movement of experimental resources between different instruments.

[0034] As described, the embodiment of the system is an automated sample preparation system. The implementation of automation can improve consistency (i.e., consistency of sample preparation) by reducing mechanical bias and error rates, enhance experimental capability, increase working time outside of standard business hours, and make predictive results available. In addition, these advantages of the embodiment of the system of this disclosure increase the throughput of flow cytometry reagent development and testing, giving scientists the ability to reallocate time from hands-on data generation to data interpretation.

[0035] Modularity of the system's embodiment: The system's embodiments are modular. Therefore, the system's embodiments are configured to operate in any order using only a subset of the integrated instruments, thereby enabling improved operational functionality and flexibility. Other embodiments of the system are configured to sequentially perform or execute a flow cytometry sample preparation process without acquisition and an automated flow cytometry acquisition process of multiple pre-prepared plates.

[0036] Technical features that form the basis of the system's embodiment: In embodiments, the system is configured to modularly automate the preparation, staining, and testing of flow cytometry by automating antibody dilution, sample staining with antibodies, sample centrifugation and washing, and transfer to a flow cytometer for data acquisition. Embodiments of the system of the present invention, as described herein, include off-the-shelf laboratory equipment or other facilities. In embodiments, equipment that enables the modular experimental processes and their technical interdependence includes, but is not limited to, the following: (1) A Hamilton Vantage liquid handler assists in flow rate regulation of biological specimens throughout the completion of the cell staining process. The Hamilton Vantage is programmed to dilute antibody reagents to specified concentrations and transfer the diluted reagents to a single-cell suspension to complete cell staining. Cell staining enables the detection of antigens localized on or inside cells by specific and selective affinity. (2) A static plate hotel, robotic arm, and plate orient enable the deployment and transfer of specimens throughout embodiments of the system. These components provide physical connections between all other equipment in the system. (3) A Hettich Rotanta enables temperature-controlled centrifugation of specimens in embodiments of the system. Centrifugation is a process of separating molecules and particles of varying densities by centrifugal force by rapidly rotating a sample in a solution. Embodiments of the system separate stained cells of interest from excess antibodies and solution residues. (4) One or more plate washers, such as Biotek Elx405, are used to aspirate the supernatant of a previously centrifuged sample, resuspend the sample with agitation, and dispense the fresh solution onto the cells. This washing technique allows for the removal of waste, thereby promoting cleaner data and supplying cells with an essential solution to support cell viability. (5) Thermo Fisher Cytomat 10c facilitates temperature and humidity controlled storage of biological samples, solutions, and reagents. Optimizing temperature and humidity storage conditions and staining conditions supports the viability of biological samples as well as the shelf life of solutions and reagents.(6) The MicroScan ESP system barcode scanner assists in tracking sample data throughout the system. (7) QInstruments BioShake allows for shaking of unsupervised plate racks or tube racks to facilitate automated chemical reactions. (8a and 8b) Bio-Rad ZE5 and BD FACSLyric® flow cytometers acquire stained cells. The two integrated cytometers allow samples to be sent to either or both instruments for parallel processing and / or acquisition. Flow cytometry techniques are used to characterize single suspended cells and particles in solution. When a sample is injected into the cytometer one particle at a time, a laser intersects with the particle, generating both scattered light signals and fluorescence signals. These signals are converted into electrical signals via photodiodes and photomultiplier tubes and analyzed by a computer. Data from the computer is compiled into a Flow Cytometry Standard file (.fcs). Cell populations can be identified by their scattering and fluorescence properties. (9) In one embodiment, proprietary software called Cellario is used to link the individual physical components and software of the system embodiment together.

[0037] Other embodiments of the system: The embodiments of the System of this Disclosure are modular systems. Therefore, the embodiments of the System can be extended to automate relevant workflows in the fields of cell biology, molecular biology, and immunology. The embodiments of the System can support research-only (RUO) and in vitro diagnostic (IVD) product development, as well as the testing of products or samples across research and development, preclinical, and clinical regulatory levels. Multiplexed bead-based assays, such as BD® Cytometric Bead Array, can be automated using embodiments of the System. Some common bench protocols, such as cell staining and preparation for fluorescence-activated cell sorting, and cell enrichment that does not require a sterile environment, can also be automated by embodiments of the System of this Disclosure. The applications of such systems can be extended by integrating new equipment into embodiments of the System. For example, adding a spectrophotometer and / or thermoshaker allows embodiments of the System to automate assays such as ELISA and Bradford protein assays. For example, adding a Hamilton On-Deck Thermal Cycler extends the capabilities of embodiments of the System to automate multi-step genomic workflows.

[0038] Example workflow: Figure 1A shows the steps of an exemplary workflow for sample preparation and flow cytometry analysis performed automatically by one embodiment of the system, compared to similar steps performed manually by a laboratory technician. Flowchart 101 shows the workflow steps performed by one embodiment of the system, where each workflow step is performed automatically by a robotic component manipulating one or more samples to one or more sample processing modules. Flowchart 102 shows the workflow steps performed by a laboratory technician. Both the automated workflow shown in Flowchart 101 and the manual workflow shown in Flowchart 102 are designed to prepare samples and analyze them by flow cytometry in the same way, except that in the automated workflow shown in Flowchart 101, the configuration steps are performed automatically by using one embodiment of the system.

[0039] Figures 1B and 1C illustrate additional manual and automated workflows. Flowchart 103 shows a manual preparation and acquisition workflow for flow cytometry analysis of a sample. Flowchart 103 distinguishes between workflow steps that require user interaction and passive steps (i.e., workflow steps that do not require direct user interaction, such as the antibody incubation step). Most of the steps in the manual workflow shown in Flowchart 103 require user interaction.

[0040] Flowchart 104 illustrates an automated preparation and acquisition workflow for flow cytometry analysis of a sample using one embodiment of the system of the present disclosure. Flowchart 104 distinguishes between workflow steps that require user interaction and automated steps (referred to as “workcell” steps). Automated steps or workcell steps do not require direct user interaction, allowing the user to automatically perform the preparation and acquisition workflow in walkaway mode. The majority of the steps in the automated workflow shown in Flowchart 104 are automated steps. An embodiment of the system used in connection with the automated workflow shown in Flowchart 104 comprises a sample processing module, which is a Hamilton Vantage liquid handler 104A, used in connection with two of the steps in the automated workflow shown in Flowchart 104. The embodiment of the system used further comprises a sample processing module, which is an ELx405 plate washer and a Rotanta centrifuge 104B, used in connection with two of the steps in the automated workflow shown in Flowchart 104. The workflows shown in flowcharts 103 and 104 are designed to achieve the same sample preparation and flow cytometry analysis of samples, with the exception that, with respect to flowchart 104, one embodiment of the system is used to automate most of the workflow steps.

[0041] The system embodiment used in relation to the automated workflow shown in Flowchart 104 is an integrated system that automates the preparation, staining, and acquisition of flow cytometry samples using multiple instruments, namely sample handling modules and robotic components. Such a system comprises: (1) Cellario: Scheduling software for the system embodiment; the user interacts with this software before execution begins; (2) Hamilton Vantage 104A: An automated liquid handler that performs pipetting steps during automated execution; this module is integrated into the system; (3) Hamilton Run Control: Software used to define liquid handling parameters; the user interacts with this software before execution begins; (4) BioRad ZES: A flow cytometer integrated into the system; (5) Everest: Software used to define the setup; the user interacts with this software before execution begins (i.e., before the automated steps of the workflow begin); (6) BioTek Elx405 104B: A plate washer integrated into the system; the user typically does not interact with this module; (7) Hettich Rotanta: A centrifuge integrated into the system; the user typically does not interact with this equipment; (8) Cytomat: An incubator integrated into the system; the user may place plates inside the incubator before execution begins (i.e., before starting the automated workflow shown in Flowchart 104); and (9) Acell Arms: Two robotic arms integrated into the system and configured to move plates around; the user typically does not interact with this equipment. In the automated workflow shown in Flowchart 104, plate washing refers to the process of removing excess antibodies from cells and may include moving plates to a plate washer and centrifugating multiple times. Figure 1D shows an exemplary microtiter plate 105 and an exemplary reagent trough 106, both for use by the system.The microtiter plate 105 may be used by the system to manipulate such plate 105 in connection with the system's robotic components performing a workflow, such as moving such plate 105 between sample processing modules as described herein. The reagent trough 106 may be used by the system to allow one or more sample processing modules to utilize reagents present in the reagent trough 106. The reagent trough may similarly be manipulated by the system's robotic components to manipulate such reagent trough 106 in connection with the system's robotic components performing a workflow, such as moving such reagent trough 106 between sample processing modules as described herein.

[0042] Figure 1E presents another example of an automated workflow for sample preparation and flow cytometry analysis of prepared samples. Flowchart 107 represents an automated workflow that can be performed automatically by a system according to one embodiment of the present disclosure. That is, the workflow in Flowchart 107 can be performed in a walkaway manner, i.e., without direct operator supervision or intervention. In Flowchart 107, the letter "P" refers to a plate, the letter "TR" refers to a tube rack, and the letter "AB" refers to an antibody.

[0043] Exemplary system: Figures 1F to 1K show an exemplary system for automated sample preparation according to one embodiment. System 110 comprises several sample processing modules 111A, 111B, and 111C, which include an incubator, storage unit, and cooling device, a plate washer, a plate washer, a Biotek elx405, a compressor, a vacuum pump, a static nest, bottles, a plate rotator, a HighRes Biosolutions Plateorient, a barcode scanner, a HighRes Biosolutions barcode scanner, a plate storage unit, a Hettich Rotanta, a handover nest, an automated liquid handling platform, a light curtain, a pipette, a sample receiving area, a reagent receiving area, and a waste receiving area. System 110 further includes several robotic components 112A, 112B that constitute a Hamilton Precise ACell 512 robot on a 1.5m rail. The robotic components 112A, 112B are integrated with sample processing modules 111A, 111B, 111C so that the robotic components can manipulate samples, such as microwell plates, between the sample processing modules. System 110 further includes a flow cytometer 113, which is a Biorad ZE5 Cytometer. Embodiments of System 110 are mounted on one or more fixed tables and / or carts, such as a table 115. System 110 further includes user interfaces 114A, 114B, which include a display that may be a touchscreen display and a keyboard that may include an integrated mouse or trackpad.As described herein, System 110 is configured for a user to interact with System 110 to configure a sample preparation and / or analysis workflow by interfaceing with one of the user interfaces 114A, 114B, and once System 110 is started, i.e., commanded to start sample preparation, no further user interaction is required, i.e., System 110 is configured to prepare samples for flow cytometry in a walkaway manner. System 110 further includes a processor and memory which may be integrated into the user interface, as well as operable connections between the user interface and the sample processing module and robotic components.

[0044] System 110 is configured to accept a three-phase AC hardwired power connection, a compressed air connection for receiving compressed air at 100-110 PSI, a CO2 connection for receiving compressed CO2 at 10-15 PSI, and an Ethernet connection. System 110 is configured to be fixed to the floor. System 110 includes multiple emergency stop buttons distributed throughout the system for user access. System 110 includes a system status light tower to easily indicate the system status.

[0045] Figures 1L to 1M show an exemplary system for automated sample preparation according to another embodiment. System 120 includes sample processing modules 121A, 121B, and 121C, robotic components 122A and 122B which are robotic arms, a flow cytometer 123, a user interface 124, and a table 125. The sample processing modules include a Thermo Scientific® Cytomat® 5 C Series automated incubator, a Hudson Rapidwash plate washer, a HighRes Biosolutions 4-position plate hotel, a Biotek EL406 on a slide, a Biorad ZE6 cytometer, a HighRes Biosolutions Plateorient, a barcode scanner, a static nest, an 8-position plate hotel and a handover nest, a Hettich Rotanta, and a Hamilton Vantage 2M model with a light curtain. The robotic components include a Hamilton Precise 57 robot and a Hamilton Precise 512 on a 1.5M rail.

[0046] Figures 1N to 1P show exemplary systems for automated sample preparation according to yet another embodiment. System 150 includes multiple sample processing modules 151A, 151B, and 151C, which are: an incubator, storage unit, and cooler, a well washer, compressor, and vacuum pump, a Biotek ELX405 on slides, a static nest, bottles, a HighRes Biosolutions Plateorient, a barcode scanner, a HighRes Biosolutions barcode scanner, a plate storage unit, a HighRes Biosolutions 8-position plate hotel and / or a HighRes Biosolutions low-density 6-position plate hotel, a centrifuge, a Hettich Rotanta, a handover nest, an automated liquid handling platform, a Hamilton Vantage 2M, a pipette, a sample receiving area, a reagent receiving area, a waste receiving area, a BioTek MultiFlo FX Multimode Dispenser, and a QInstruments Bioshake The system includes a thermo shaker (i.e., a heating and cooling shaker) which is Q1. One or more of the sample processing modules 151A, 151B, and 151C may be accessed remotely by a personal computer. The system 150 further includes several robotic components 152A and 152B, which include a HighRes ACell 512 robot on a 1.5m rail and / or a HighRes Biosolutions ACell 57 robot with non-replaceable Rotanta fingers. The robotic components 152A and 152B are integrated with the sample processing modules 151A, 151B, and 151C so that the robotic components can manipulate samples, such as microwell plates, between the sample processing modules.System 150 further includes a flow cytometer 153A which is a BD FACSLyric and a flow cytometer 153B which is a Biorad ZE5 Cytometer. Embodiments of System 150 are mounted on one or more fixed tables and / or carts, such as a table 155. System 150 further includes user interfaces 154A, 154B which include a display which may be a touchscreen display and a keyboard which may include an integrated mouse or trackpad. As described herein, System 150 is configured for a user to interact with System 150 to configure a sample preparation and / or analysis workflow by interface with one of the user interfaces 154A, 154B, and once System 150 is started, i.e., commanded to start sample preparation, no further user interaction is required, i.e., System 150 is configured to prepare a sample for flow cytometry in a walkaway manner. System 150 further includes a processor and memory which may be integrated into the user interface, as well as operable connections between the user interface and the sample processing module and robotic components.

[0047] System 150 is configured to accept a three-phase AC hardwired power connection, a compressed air connection for receiving compressed air at 100-110 PSI, a CO2 connection for receiving compressed CO2 at 10-15 PSI, and an Ethernet connection. System 150 is configured to be fixed to the floor. System 150 includes multiple emergency stop buttons distributed throughout the system for user access. System 150 includes a system status light tower to easily indicate the system status.

[0048] Figure 1Q shows exemplary sample processing modules that can be integrated into systems of the present disclosure, such as automated system 110 and automated system 120. Sample processing module 131 is a Hamilton Vantage liquid handler. Sample processing module 132 is a BioRad ZE5 flow cytometer. Sample processing module 133 is a BioTek ELx405 plate washer. Sample processing module 134 is a Cytomat 10 425 incubator. Sample processing module 135 is a Hettich Rotanta centrifuge. Sample processing module 136 is a Hudson Rapidwash. Sample processing module 137 is a Microscan MS-3 laser fixed-mount barcode scanner.

[0049] System schematic diagram: Figure 1R shows a schematic diagram of an exemplary system according to one embodiment. The system 140 comprises a plurality of sample processing modules 141 and a plurality of robotic components 142. The robotic components 142 are integrated with the sample processing modules 141, as indicated by arrows 145, which means that the robotic components 142 are configured to operate, act upon, or otherwise control the sample processing modules 141, for example, by moving samples in microwell plates in and out of various sample processing modules 141. The system 140 further comprises a processor 143 with memory. The memory contains stored instructions, which, when executed by the processor 143, cause the processor to control the sample processing modules 141 and robotic components 142 to operate the sample processing modules 141 and robotic components 142 to prepare a plurality of samples for flow cytometry analysis. The system 140 further comprises operable connections between the processor 143, the sample processing modules 141, and the plurality of robotic components 142. Such a functional connection includes any convenient connection that can transmit commands, such as control commands, from the processor 143 to the robot component 142 and the sample processing module 141.

[0050] Any convenient sample processing module 141 may be included in the system as described herein. The number of sample processing modules may vary depending on the embodiment and may include 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more sample processing modules. The system 140 may be configured such that different sample processing modules can be added to or removed from the system. That is, the system may be reconfigured to include additional sample processing modules or to remove specific sample processing modules as needed, even after it has been deployed, for example, in a laboratory environment. In other words, the system may be configured so that multiple types of laboratory equipment configured for the same or similar function can be used, for example, the system of this disclosure may be configured to operate with, for example, any convenient centrifuge or, for example, an automatic pipette. The system may, in some cases, be dynamically reconfigurable. Generally, the sample processing modules are standard off-the-shelf laboratory equipment as described herein. Thus, a dynamically reconfigurable system allows for the utilization of different laboratory equipment, such as, for example, on-site laboratory equipment.

[0051] In some embodiments, multiple sample processing modules, such as sample processing module 141, are configured to prepare samples for flow cytometry analysis. In some embodiments, the multiple sample processing modules constitute a standalone laboratory setup. In certain embodiments, the multiple modules include one or more of the following: an antibody dilution module, a cell staining module, a sample washing module, a sample resuspension module, a sample transfer module, and a sample analysis module. In such cases, the cell staining module may be configured for cell staining with a fluorescence-coupled antibody. As described herein, in embodiments, multiple modules include an incubator such as Cytomat 10, a storage unit, a cooler, a plate washer such as Hudson Rapidwash, a well washer such as Biotek elx405, a compressor, a vacuum pump, a static nest, a bottle, a flow cytometer such as BD FACSLyric® and / or Biorad ZE5 Cytometer, a plate rotator such as HighRes Biosolutions Plateorient, a barcode scanner such as HighRes Biosolutions Barcode Scanner, a plate storage unit such as HighRes Biosolutions Platehotel and / or HighRes Biosolutions Static Nest, a centrifuge such as Hettich Rotanta, a handover nest such as HighRes Biosolutions Handover Nests, an automated liquid handling platform such as Hamilton Vantage 2M, a pipette, a reagent dispenser such as BioTek MultiFlo FX Multimode Dispenser, and QInstruments Bioshake It includes one or more of the following: a thermoshaker (i.e., a heating / cooling shaker), a sample receiving area, a reagent receiving area, and a waste receiving area. In some cases, multiple sample processing modules are configured to perform cell staining on samples. In other cases, multiple sample processing modules are configured to incubate samples.In yet another embodiment, the sample processing modules are configured to manipulate samples in a multiwell plate. In a particular case, the sample processing modules include pipettes. In an embodiment, the sample processing modules are configured to pipette fluids into and out of a multiwell plate. In another embodiment, the sample processing modules include centrifuges. In some embodiments, the sample processing modules are configured to rotate the sample to separate its components. In yet another embodiment, the sample processing modules are configured to wash the sample.

[0052] As described herein, any convenient robotic component 142 may be included in the system 140. The number of robotic components may vary depending on the embodiment and may include 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, or more robotic components. The system 140 may be configured so that different robotic components can be added to or removed from the system. That is, the system may be reconfigured to include additional robotic components or to remove specific robotic components as needed, even after it has been deployed, for example, in a laboratory environment. In other words, the system may be configured so that multiple types of robotic components configured for the same or similar function can be used, for example, the system of this disclosure may be configured to operate using any convenient robotic arm or robotic gripper mounted on different axes. The system may, in some cases, be dynamically reconfigurable. Generally, the robotic components are standard off-the-shelf laboratory equipment, as described herein. Thus, a dynamically reconfigurable system allows for the utilization of different laboratory equipment, such as, for example, a handheld laboratory setup.

[0053] In some embodiments, the robot component is configured to move one or more multiwell plates. In some embodiments, the robot component is configured to move multiwell plates in and out of a module. In other embodiments, the robot component includes fingers configured to grip multiwell plates. In yet another embodiment, the robot component is configured to operate a module. In some cases, the robot component includes rails and actuators for translating the robot component. In other cases, the robot component includes a robotic arm. The robot component of interest is a commercially available, off-the-shelf robotic arm, gripper, etc. In some cases, the robot component includes a Hamilton Precise ACell 512 robot on a 1.5m rail and / or a HighRes Biosolutions ACell 57 robot with non-replaceable Rotanta fingers. The robot component may be integrated with a sample processing module by mounting it so that the robot component can access the sample processing module, for example, so that the robot component can load or unload samples, such as multiwell plates, and move such samples or multiwell plates between different sample processing modules.

[0054] As described herein, in embodiments, the robotic components and sample handling modules may be configured to act on samples present in any convenient medium. In some cases, the modules and robotic components are configured to operate on one or more of the following: test tubes, multiwell plates, deepwell plates, and standard well plates. In other cases, the modules and robotic components are configured to operate on 96-well standard depth plates.

[0055] The processor 143, which includes memory, may be any convenient general-purpose processor or controller, such as any convenient commercially available processor or controller, as described herein. As described, the memory includes stored instructions, which, when executed by the processor, cause the processor to control the sample preparation module and robotic components to operate the sample preparation module and robotic components to prepare multiple samples for flow cytometry analysis. In other cases, the memory further includes stored instructions, which, when executed by the processor, cause the processor to control the sample preparation module and robotic components to load each prepared sample of the multiple samples into the flow cytometer and to operate the flow cytometer to analyze each prepared sample of the multiple samples. Generally, the processor and memory implement software that enables system automation, for example, so that the system can automatically prepare samples in a walkaway manner.

[0056] In some embodiments, the system is configured to automatically prepare multiple samples for flow cytometry analysis. In other embodiments, the system is configured to automatically and continuously prepare multiple samples for flow cytometry analysis. In some embodiments, the system is configured to prepare multiple samples for flow cytometry analysis in a walkaway manner. Walkaway means that the system is fully automated to prepare samples, so that when the system is instructed to prepare multiple samples, the system operator does not need to interact with the system; that is, the operator can leave the area while the system automatically prepares the samples. In certain embodiments, the system is configured to prepare multiple samples for flow cytometry analysis without requiring user interaction. In some cases, the system is configured to prepare multiple samples for flow cytometry analysis without requiring user manipulation of the samples. In other cases, the system is configured to prepare multiple samples for flow cytometry analysis without requiring user control of the sample processing module. In yet another case, the system is configured to receive user instructions requesting the preparation of multiple samples for flow cytometry analysis. User instructions may be received, for example, through a user interface. In such cases, the system may be configured to receive user instructions before preparing the sample. In specific cases, the system is configured to automatically prepare multiple samples for flow cytometry analysis. Embodiments of the system are robotic systems for automated sample preparation and flow cytometry analysis. In embodiments, the instructions include one or more of the following: scheduling software, software for defining liquid handling parameters, and software for defining system setup.

[0057] Embodiments of the system of the present disclosure may further include several additional embodiments for facilitating automated sample preparation and, in some cases, flow cytometry analysis. For example, some embodiments of the system of the present invention include one or more substrates on which sample processing modules and / or robotic components are mounted. Some embodiments further include one or more tables. Some embodiments further include a user interface. Any convenient user interface may be used, such as any commercially available off-the-shelf display and input mechanism. In some cases, the user interface includes one or more of a display, keyboard, mouse, trackpad, user tag-out device, system status light, and emergency stop button. Some embodiments further include an electrical interface for supplying power to the system. Some embodiments further include a data interface for sending and / or receiving control signals or data signals from the system. Some embodiments further include a compressed air interface for supplying pressurized air to the system. Some embodiments further include a network interface. Some embodiments further include one or more protective shields. Any convenient protective shields, such as commercially available off-the-shelf protective shields configured to protect the operator from harmful light or electromagnetic energy, for example. Some embodiments further include one or more light curtains.

[0058] As described herein, embodiments of this disclosure also include flow cytometers. Embodiments of the system of this disclosure may be configured to perform both sample preparation for flow cytometry analysis and flow cytometry analysis. Any convenient flow cytometer may be used in the system of the present invention. The flow cytometer of interest includes a light source configured to irradiate particles in the flow stream at an interrogation point in the flow cell.

[0059] The flow cell of interest includes a cuvette configured to transport particles in a flow stream. As used herein, “flow cell” is described in its conventional sense, referring to a component that includes a channel for a liquid flow stream for transporting particles in a sheath fluid. The cuvette of interest has a passage (i.e., a channel) through which it passes. The flow stream through which the channel is formed may contain a liquid sample injected from a sample tube. In certain cases, the flow cell includes a light-accessible channel. The cuvette may be made of, for example, quartz, glass, transparent plastic, etc. In some embodiments, the cuvette is formed from silica, such as fused silica. In some cases, the flow cell is configured so that light is irradiated from a light source at one or more interrogation points. As used herein, “interrogation point” refers to a region within the flow cell where particles are irradiated by light from a light source, for example, for analysis. The size of the interrogation points may vary as desired. For example, if 0 μm represents the optical axis of light emitted by the light source, the interrogation point may be in the range of -15 μm to 30 μm, e.g., -25 μm to 40 μm. Depending on specific considerations (e.g., the number and arrangement of lasers), multiple irradiation points may exist within the flow cell.

[0060] In some embodiments, the flow cell includes a sample injection port configured to supply a sample to the flow cell, or is configured to be used in conjunction with a sample injection port. In embodiments, the sample injection system is configured to provide a suitable flow of the sample into the internal chamber (i.e., flow path) of the flow cell. Depending on the desired characteristics of the flowstream, the flow rate of the sample delivered to the flow cell chamber by the sample injection port is 1 μL / min or more, e.g., 2 μL / min or more, e.g., 3 μL / min or more, e.g., 5 μL / min or more, e.g., 10 μL / min or more, e.g., 15 μL / min or more, e.g., 25 μL / min or more, e.g., 50 μL / min or more, and may include 100 μL / min or more. In some cases, the flow rate of the sample delivered to the flow cell chamber by the sample injection port is 1 μL / second or more, e.g., 2 μL / second or more, e.g., 3 μL / second or more, e.g., 5 μL / second or more, e.g., 10 μL / second or more, e.g., 15 μL / second or more, e.g., 25 μL / second or more, e.g., 50 μL / second or more, and may include 100 μL / second or more.

[0061] The sample injection port may be an orifice positioned in the wall of the internal chamber, or a conduit positioned at the proximal end of the internal chamber. If the sample injection port is an orifice positioned in the wall of the internal chamber, the sample injection port orifice may be any suitable shape, including, but not limited to, linear cross-sectional shapes such as squares, rectangles, trapezoids, triangles, hexagons, etc., curved cross-sectional shapes such as circles, ellipses, etc., and irregular shapes such as parabolic bottoms coupled to flat tops. In certain embodiments, the sample injection port has a circular orifice. The size of the sample injection port orifice may vary depending on the shape, and in certain cases, it may have an opening in the range of 0.1 mm to 5.0 mm, e.g., 0.2 mm to 3.0 mm, e.g., 0.5 mm to 2.5 mm, e.g., 0.75 mm to 2.25 mm, e.g., 1 mm to 2 mm, e.g., 1.25 mm to 1.75 mm, e.g., 1.5 mm.

[0062] In certain cases, the sample injection port is a conduit positioned at the proximal end of the internal chamber of the flow cell. For example, the sample injection port may be a conduit positioned so that the orifice of the sample injection port is aligned with the flow cell orifice. If the sample injection port is a conduit positioned in line with the flow cell orifice, the cross-sectional shape of the sample injection tube may be any suitable shape, including, but not limited to, straight cross-sectional shapes such as squares, rectangles, trapezoids, triangles, and hexagons, curved cross-sectional shapes such as circles and ellipses, and irregular shapes such as parabolic bottoms joined to flat tops. The orifice of the conduit may vary depending on the shape, and in certain cases, it may have an opening in the range of 0.1 mm to 5.0 mm, e.g., 0.2 mm to 3.0 mm, e.g., 0.5 mm to 2.5 mm, e.g., 0.75 mm to 2.25 mm, e.g., 1 mm to 2 mm, e.g., 1.25 mm to 1.75 mm, e.g., 1.5 mm. The shape of the tip of the sample injection port may be the same as or different from the cross-sectional shape of the sample injection tube. For example, the orifice of the sample injection port may include a slanted tip having a 5° inclination angle in the range of 1° to 10°, for example 2° to 9°, for example 3° to 8°, for example 4° to 7°.

[0063] In some embodiments, the flow cell also includes a sheath fluid injection port configured to supply sheath fluid to the flow cell. In embodiments, the sheath fluid injection system is configured to provide a flow of sheath fluid into the internal chamber of the flow cell, for example, together with the sample, to create a layered flow stream of sheath fluid surrounding the sample flow stream. Depending on the desired characteristics of the flow stream, the flow rate of sheath fluid delivered to the flow cell chamber may be 25 μL / sec or more, e.g., 50 μL / sec or more, e.g., 75 μL / sec or more, e.g., 100 μL / sec or more, e.g., 250 μL / sec or more, e.g., 500 μL / sec or more, e.g., 750 μL / sec or more, e.g., 1000 μL / sec or more, and may include, for example, 2500 μL / sec or more.

[0064] In some embodiments, the sheath fluid injection port is an orifice positioned in the wall of the internal chamber. The sheath fluid injection port orifice may have any suitable cross-sectional shape of interest, including, but not limited to, linear cross-sectional shapes such as squares, rectangles, trapezoids, triangles, and hexagons, curved cross-sectional shapes such as circles and ellipses, and irregular shapes such as a parabolic bottom joined to a flat top. The size of the sheath fluid injection port orifice may vary depending on the shape, and in certain cases, it may have an opening in the range of 0.1 mm to 5.0 mm, e.g., 0.2 mm to 3.0 mm, e.g., 0.5 mm to 2.5 mm, e.g., 0.75 mm to 2.25 mm, e.g., 1 mm to 2 mm, e.g., 1.25 mm to 1.75 mm, e.g., 1.5 mm.

[0065] The flow cytometers of this disclosure include light sources configured to irradiate particles in the flow stream at an interrogation point in the flow cell. The number of light sources in the flow cytometer can vary. In some embodiments, the flow cytometer includes a single light source. Alternatively, the flow cytometer may include multiple light sources in some cases. In some such cases, the number of light sources ranges from 2 to 10, for example, 2 to 5, or for example, 2 to 4. Any convenient light source may be used as a light source described herein. In some embodiments, the light source is a laser. In embodiments, the laser may be any convenient laser, such as a continuous-wave laser. For example, the laser may be a diode laser, such as an ultraviolet diode laser, a visible diode laser, or a near-infrared diode laser. In other embodiments, the laser may be a helium-neon (HeNe) laser. In some cases, the laser is a gas laser such as a helium-neon laser, argon laser, krypton laser, xenon laser, nitrogen laser, CO2 laser, CO laser, argon-fluorine (ArF) excimer laser, krypton-fluorine (KrF) excimer laser, xenon-chlorine (XeCl) excimer laser, or xenon-fluorine (XeF) excimer laser, or a combination thereof. In other cases, this flow cytometer includes dye lasers such as stilbene lasers, coumarin lasers, or rhodamine lasers. In yet other cases, the laser of interest includes metal vapor lasers such as helium-cadmium (HeCd) lasers, helium-mercury (HeHg) lasers, helium-selenium (HeSe) lasers, helium-silver (HeAg) lasers, strontium lasers, neon-copper (NeCu) lasers, copper lasers, or gold lasers, and combinations thereof.In other examples, this flow cytometer includes solid-state lasers such as ruby ​​lasers, Nd:YAG lasers, NdCrYAG lasers, Er:YAG lasers, Nd:YLF lasers, Nd:YVO4 lasers, Nd:YCa4O(BO3)3 lasers, Nd:YCOB lasers, titanium sapphire lasers, thulium YAG lasers, ytterbium YAG lasers, ytterbium 2O3 lasers, or cerium-doped lasers, and combinations thereof.

[0066] A laser light source according to a particular embodiment may also include one or more optical tuning components. In a particular embodiment, the optical tuning component may include any device located between the light source and the flow cell that can change the spatial width of the irradiation, or any other characteristics of the irradiation from the light source, such as the direction of irradiation, wavelength, beam width, beam intensity, and focus. The optical tuning protocol may include, but is not limited to, lenses, mirrors, filters, optical fibers, wavelength separators, pinholes, slits, collimation protocols, and combinations thereof, any convenient device for tuning one or more characteristics of the light source. In a particular embodiment, the flow cytometer of interest includes one or more focusing lenses. The focusing lenses may, in one example, be reduction lenses. In yet another embodiment, the flow cytometer of interest includes optical fibers.

[0067] The light source may be positioned at any suitable distance from the flow cell, for example, the light source and the flow cell are separated by 0.005 mm or more, e.g., 0.01 mm or more, e.g., 0.05 mm or more, e.g., 0.1 mm or more, e.g., 0.5 mm or more, e.g., 1 mm or more, e.g., 5 mm or more, e.g., 10 mm or more, e.g., 25 mm or more, and include, for example, a distance of 100 mm or more. Furthermore, the light source may be positioned at any suitable angle with respect to the flow cell, for example, within an angle range including angles of 10 to 90 degrees, e.g., 15 to 85 degrees, e.g., 20 to 80 degrees, e.g., 25 to 75 degrees, e.g., 30 to 60 degrees, e.g., 90 degrees.

[0068] In some embodiments, the light source of interest includes a plurality of lasers configured to provide laser light for discrete irradiation of a flowstream, e.g., two or more lasers, e.g., three or more lasers, e.g., four or more lasers, e.g., five or more lasers, e.g., ten or more lasers, and e.g., fifteen or more lasers configured to provide laser light for discrete irradiation of a flowstream. Depending on the desired wavelength of light for irradiating the flowstream, each laser may have a specific wavelength, e.g., 400 nm to 800 nm, varying from 200 nm to 1500 nm, e.g., 250 nm to 1250 nm, e.g., 300 nm to 1000 nm, e.g., 350 nm to 900 nm. In certain embodiments, the laser of interest may include one or more of the following: a 405 nm laser, a 488 nm laser, a 561 nm laser, and a 635 nm laser.

[0069] In certain embodiments, the light source is a light beam generator configured to generate two or more frequency-shifted light beams. In some cases, the light beam generator includes a laser and a high-frequency generator configured to apply a high-frequency drive signal to an acousto-optical device to generate two or more angle-deflected laser beams. In these embodiments, the laser may be a pulsed laser or a continuous-wave laser. For example, the laser in the light beam generator of interest may include the above.

[0070] The acousto-optic device may be any convenient acousto-optic protocol configured to frequency-shift laser light using applied acoustic waves. In certain embodiments, the acousto-optic device is an acousto-optic deflector. The acousto-optic device in this system is configured to generate an angularly deflected laser beam from light from a laser and an applied high-frequency drive signal. The high-frequency drive signal can be applied to the acousto-optic device using any suitable high-frequency drive signal source, such as a direct digital combiner (DDS), arbitrary waveform generator (AWG), or electric pulse generator.

[0071] In embodiments, the controller is configured to apply high-frequency drive signals to an acousto-optical device to generate a desired number of angularly deflected laser beams within the output laser beam, and includes being configured to apply, for example, three or more high-frequency drive signals, for example, four or more high-frequency drive signals, for example, five or more high-frequency drive signals, for example, six or more high-frequency drive signals, for example, seven or more high-frequency drive signals, for example, eight or more high-frequency drive signals, for example, nine or more high-frequency drive signals, for example, ten or more high-frequency drive signals, for example, fifteen or more high-frequency drive signals, for example, twenty-five or more high-frequency drive signals, for example, fifty or more high-frequency drive signals, and being configured to apply one hundred or more high-frequency drive signals.

[0072] In some cases, to create an intensity profile of an angularly deflected laser beam within the output laser beam, the controller is configured to apply a high-frequency drive signal having an amplitude including, for example, about 5V to about 25V, which varies, for example, from about 0.001V to about 500V, for example from about 0.005V to about 400V, for example from about 0.01V to about 300V, for example from about 0.05V to about 200V, for example from about 0.1V to about 100V, for example from about 0.5V to about 75V, for example from about 1V to 50V, for example from about 2V to 40V, for example from 3V to about 30V. Each applied high-frequency drive signal has a frequency range of approximately 5 MHz to approximately 50 MHz, for example, approximately 0.001 MHz to approximately 500 MHz, for example, approximately 0.005 MHz to approximately 400 MHz, for example, approximately 0.01 MHz to approximately 300 MHz, for example, approximately 0.05 MHz to approximately 200 MHz, for example, approximately 0.1 MHz to approximately 100 MHz, for example, approximately 0.5 MHz to approximately 90 MHz, for example, approximately 1 MHz to approximately 75 MHz, for example, approximately 2 MHz to approximately 70 MHz, for example, approximately 3 MHz to approximately 65 MHz, for example, approximately 4 MHz to approximately 60 MHz.

[0073] In certain embodiments, the controller has a processor having memory operably coupled to the processor such that the memory contains stored instructions for generating an output laser beam having an angle-deflected laser beam having a desired intensity profile when executed by the processor. For example, the memory may contain instructions for generating two or more angle-deflected laser beams having the same intensity, e.g., three or more, e.g., four or more, e.g., five or more, e.g., ten or more, e.g., 25 or more, e.g., 50 or more, and the memory may contain instructions for generating 100 or more angle-deflected laser beams having the same intensity. In other embodiments, the memory may contain instructions for generating two or more angle-deflected laser beams having different intensities, e.g., three or more, e.g., four or more, e.g., five or more, e.g., ten or more, e.g., 25 or more, e.g., 50 or more, and the memory may contain instructions for generating 100 or more angle-deflected laser beams having different intensities.

[0074] In certain embodiments, the controller has a processor having memory operably coupled to the processor such that the memory contains stored instructions, when executed by the processor, for generating an output laser beam having an intensity that increases from the edge to the center of the output laser beam along the horizontal axis. In these cases, the intensity of the angularly deflected laser beam at the center of the output beam may be in the range of 0.1% to about 99% of the intensity of the angularly deflected laser beam at the edge of the output laser beam along the horizontal axis, and may also include a range of about 10% to about 50%, such as 0.5% to about 95%, 1% to about 90%, 2% to about 85%, 3% to about 80%, 4% to about 75%, 5% to about 70%, 6% to about 65%, 7% to about 60%, 8% to about 55%, etc. In other embodiments, the controller has a processor having memory operably coupled to the processor such that the memory contains stored instructions, when executed by the processor, for generating an output laser beam having an intensity that increases from the edge to the center of the output laser beam along the horizontal axis. In these cases, the intensity of the angularly deflected laser beam at the edge of the output beam may be in the range of 0.1% to about 99% of the intensity of the angularly deflected laser beam at the center of the output laser beam along the horizontal axis, and may also include a range of about 10% to about 50%, such as 0.5% to about 95%, 1% to about 90%, 2% to about 85%, 3% to about 80%, 4% to about 75%, 5% to about 70%, 6% to about 65%, 7% to about 60%, 8% to about 55%, etc. In yet another embodiment, the controller has a processor having a memory operably coupled to the processor such that the memory contains stored instructions that, when executed by the processor, cause the processor to generate an output laser beam having an intensity profile having a Gaussian distribution along the horizontal axis.In yet another embodiment, the controller has a processor having a memory operably coupled to the processor such that the memory contains stored instructions that, when executed by the processor, cause the processor to generate an output laser beam having a top-hat intensity profile along the horizontal axis.

[0075] In some embodiments, the light beam generator of interest may be configured to generate spatially separated, angularly deflected laser beams within the output laser beam. Depending on the applied high-frequency drive signal and the desired irradiation profile of the output laser beam, the angularly deflected laser beams may be separated by 0.001 μm or more, e.g., 0.005 μm or more, e.g., 0.01 μm or more, e.g., 0.05 μm or more, e.g., 0.1 μm or more, e.g., 0.5 μm or more, e.g., 1 μm or more, e.g., 5 μm or more, e.g., 10 μm or more, e.g., 100 μm or more, e.g., 500 μm or more, e.g., 1000 μm or more, and may include 5000 μm or more. In some embodiments, the system is configured to generate angularly deflected laser beams within the output laser beam that overlap with adjacent angularly deflected laser beams along the horizontal axis of the output laser beam. The overlap between adjacent angle-deflected laser beams (e.g., beam spot overlap) may be an overlap of 0.001 μm or more, for example, an overlap of 0.005 μm or more, for example, an overlap of 0.01 μm or more, for example, an overlap of 0.05 μm or more, for example, an overlap of 0.1 μm or more, for example, an overlap of 0.5 μm or more, for example, an overlap of 1 μm or more, for example, an overlap of 5 μm or more, for example, an overlap of 10 μm or more, and may include overlaps of 100 μm or more.

[0076] In certain cases, a light beam generator configured to generate two or more frequency-shifted light beams is subject to U.S. Patent Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,036,699, 10,078,045, 10,222,316, 10,288,546, 10,324,019, 10,408,758, 10,451,538, 10,620,111, and 10,684,211. This includes laser excitation modules described in Patent Nos. 10,845,295, 10,935,482, 10,935,485, 11,105,728, 11,280,718, 11,327,016, 11,366,052, 11,371,937, 11,692,926, 11,630,053, 11,774,343, 11,940,369, and 11,946,851, the disclosures of which are incorporated herein by reference.

[0077] Furthermore, the flow cytometer includes a detector configured to collect light emitted by the irradiated particles. The photodetector is configured to detect particle-modulated light carried by an optical fiber focusing element and to generate a signal based on the characteristics of the light (e.g., intensity). For example, one or more particle-modulated photodetectors may include one or more side-scatter photodetectors for detecting the side-scatter wavelengths of light (i.e., light refracted and reflected from the surface and internal structure of the particles). In some embodiments, the flow cytometer includes a single side-scatter photodetector. In other embodiments, the flow cytometer includes a plurality of side-scatter photodetectors, e.g., two or more, e.g., three or more, e.g., four or more, e.g., five or more.

[0078] Any convenient detector for detecting the collected light can be used in the side-scattered light detector described herein. Among detectors of interest, optical sensors or detectors such as, but not limited to, active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCD), intensified charge-coupled devices (ICCD), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photovoltaic cells, photodiodes, photomultiplier tubes (PMT), phototransistors, quantum dot photoconductors or photodiodes and combinations thereof may be mentioned. In certain embodiments, the collected light is measured by a charge-coupled device (CCD), a semiconductor charge-coupled device (CCD), an active pixel sensor (APS), a complementary metal oxide semiconductor (CMOS) image sensor or an N-type metal oxide semiconductor (NMOS) image sensor. In certain embodiments, the detector is 0.01 cm 2 ~10 cm 2 , for example 0.05 cm 2 ~9 cm 2 , for example 0.1 cm 2 ~8 cm 2 , for example 0.5 cm 2 ~7 cm 2 and is a photomultiplier tube, such as a photomultiplier tube, having an active detection surface area in each region in the range including 1 cm 2 ~5 cm 2 .

[0079] In an embodiment, the flow cytometer also includes a fluorescence detector configured to detect one or more fluorescence wavelengths of light. In other embodiments, the flow cytometer includes a plurality of fluorescence detectors, such as two or more, such as three or more, such as four or more, five or more, ten or more, fifteen or more, including twenty or more.

[0080] Any convenient detector for detecting the collected light may be used in the fluorescence detector described herein. Detectors of interest include, but are not limited to, optical sensors or detectors such as active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCDs), intensified charge-coupled devices (ICCDs), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes, photomultiplier tubes (PMTs), phototransistors, quantum dot photoconductors or photodiodes, and combinations thereof. In certain embodiments, the collected light is measured by a charge-coupled device (CCD), semiconductor charge-coupled device (CCD), active pixel sensor (APS), complementary metal-oxide-semiconductor (CMOS) image sensor, or N-type metal-oxide-semiconductor (NMOS) image sensor. In certain embodiments, the detector is 0.01 cm 2 ~10cm 2 For example, 0.05 cm 2 ~9cm 2 For example, 0.1 cm 2 ~8cm 2 For example, 0.5 cm 2 ~7cm 2 1cm 2 ~5cm 2 This is a photomultiplier tube, such as a photomultiplier tube, having an activity detection surface area in each region within the range including [specific region].

[0081] If the flow cytometer includes multiple fluorescence detectors, each fluorescence detector may be the same, or the array of fluorescence detectors may be a combination of different types of detectors. For example, if the flow cytometer in question includes two fluorescence detectors, in some embodiments, the first fluorescence detector is a CCD type device and the second fluorescence detector (or imaging sensor) is a CMOS type device. In other embodiments, both the first and second fluorescence detectors are CCD type devices. In yet another embodiment, both the first and second fluorescence detectors are CMOS type devices. In yet another embodiment, the first fluorescence detector is a CCD type device and the second fluorescence detector is a photomultiplier tube (PMT). In yet another embodiment, the first fluorescence detector is a CMOS type device and the second fluorescence detector is a photomultiplier tube. In yet another embodiment, both the first and second fluorescence detectors are photomultiplier tubes.

[0082] In embodiments of the present disclosure, the fluorescence detector of interest is configured to measure the collected light at one or more wavelengths, e.g., two or more wavelengths, e.g., five or more different wavelengths, e.g., ten or more different wavelengths, e.g., 25 or more different wavelengths, e.g., 50 or more different wavelengths, e.g., 100 or more different wavelengths, e.g., 200 or more different wavelengths, e.g., 300 or more different wavelengths, and includes measuring the light emitted by the sample in the flow stream at 400 or more different wavelengths. In some embodiments, two or more detectors in the module described herein are configured to measure the same or overlapping wavelengths of the collected light.

[0083] In some embodiments, the fluorescence detector of interest is configured to measure light collected over a range of wavelengths (e.g., 200 nm to 1000 nm). In certain embodiments, the detector of interest is configured to collect the spectrum of light over a range of wavelengths. For example, a flow cytometer may include one or more detectors configured to collect the spectrum of light over one or more wavelengths in the 200 nm to 1000 nm range. In yet another embodiment, the detector of interest is configured to measure light emitted by a sample in a flow stream at one or more specific wavelengths. For example, a module may include one or more detectors configured to measure light at one or more of the following wavelengths: 450 nm, 518 nm, 519 nm, 561 nm, 578 nm, 605 nm, 607 nm, 625 nm, 650 nm, 660 nm, 667 nm, 670 nm, 668 nm, 695 nm, 710 nm, 723 nm, 780 nm, 785 nm, 647 nm, 617 nm and any combination thereof. In certain embodiments, one or more detectors may be configured to pair with specific fluorophores, such as those used with a sample in a fluorescence assay.

[0084] The flow cytometer may include any suitable (one or more) mechanisms for supplying the sample solution and sheath solution to the sample solution input coupler and sheath solution input coupler. For example, the sample solution input coupler may be fluidly connected to a sample solution line (e.g., a tube) fluidly connected to a sample solution reservoir. Similarly, the sheath solution input coupler may be fluidly connected to a sheath solution line fluidly connected to a sheath solution reservoir. Similarly, the flow cytometer may include any suitable (one or more) mechanisms for managing waste from the flow stream. A fluid discharge coupler may be fluidly connected to a waste line fluidly connected to a waste reservoir. A fluid management system that may be adapted for use with this flow cytometer is described in U.S. Patent Application Publication No. 2022 / 0341838, the disclosure of which is incorporated herein by reference in its entirety.

[0085] Appropriate flow cytometry systems include: Ormerod (ed.), Flow Cytometry: A Practical Approach, Oxford Univ. Press (1997); Jaroszeski et al. (ed.), Flow Cytometry Protocols, Methods in Molecular Biology No. 91, Humana Press (1997); Practical Flow Cytometry, 3rd ed., Wiley-Liss (1995); Virgo, et al. (2012) Ann Clin Biochem. Jan; 49 (pt 1): 17-28; Linden, et al., Semin Throm Hemost. 2004 Oct; 30 (5): 502-11; Alison, et al. J Pathol, 2010 Dec; 222 (4): 335-344; and Herbig, et al. (2007) Crit Rev Ther Drug Carrier Examples include, but are not limited to, those described in Syst.24(3):203-255, which are incorporated herein by reference.In certain cases, the target flow cytometry system is the BD Biosciences FACSCanto® flow cytometer, BD Biosciences FACSCanto® II flow cytometer, BD Accuri® flow cytometer, BD Accuri® C6 Plus flow cytometer, BD Biosciences FACSCelesta® flow cytometer, BD Biosciences FACSLyric® flow cytometer, BD Biosciences FACSVerse® flow cytometer, BD Biosciences FACSymphony® flow cytometer, BD Biosciences LSRFortessa® flow cytometer, BD Biosciences LSRFortessa® X-20 flow cytometer, BD Biosciences FACSPresto® flow cytometer, BD Biosciences FACSVia® flow cytometer, and BD Biosciences FACSCalibur® cell sorter, BD Biosciences FACSCount® cell sorter, BD Biosciences This includes FACSLyric™ cell sorters, BD Biosciences Via™ cell sorters, BD Biosciences Influx™ cell sorters, BD Biosciences Jazz™ cell sorters, BD Biosciences Aria™ cell sorters, BD Biosciences FACSAria™ II cell sorters, BD Biosciences FACSAria™ III cell sorters, BD Biosciences FACSAria™ Fusion cell sorters, and BD Biosciences FACSMelody™ cell sorters, BD Biosciences FACSymphony™ S6 cell sorters, BD Biosciences FACSDiscover™ cell sorters, and others.

[0086] In some embodiments, this system is based on U.S. Patents No. 10,663,476, No. 10,620,111, No. 10,613,017, No. 10,605,713, No. 10,585,031, No. 10,578,542, No. 10,578,469, No. 10,481,074, and No. 10,302,545. , No. 10,145,793, No. 10,113,967, No. 10,006,852, No. 9,952,076, No. 9,933,341, No. 9, No. 726,527, No. 9,453,789, No. 9,200,334, No. 9,097,640, No. 9,095,494, No. 9,092,034, No. 8,975,595, No. 8,753,573, No. 8,233,146, No. 8,140,300, No. 7,544,326, No. 7,201, No. 875, No. 7,129,505, No. 6,821,740, No. 6,813,017, No. 6,809,804, No. 6,372,506, No. 5, Flow cytometry systems such as those described in Patent Nos. 700,692, 5,643,796, 5,627,040, 5,620,842, 5,602,039, 4,987,086, and 4,498,766 (these disclosures are incorporated herein by reference in their entirety).

[0087] In some embodiments, the flow cytometer is configured as an imaging flow cytometer. For example, in certain cases, this system is based on Diebold, et al. Nature Photonics. Vol.7(10), 806-810(2013), and U.S. Patent Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,036,699, 10,078,045, 10,222,316, 10,288,546, 10,324,019, 10,408,758, 10,451,538, 10,620,111, 10,684,211, 10,845,295, 10,935,482, 10,935,485, and Flow cytometry systems configured to image particles in a flow stream by fluorescence imaging using high-frequency tagged emission (FIRE), such as those described in Patent Nos. 11,105,728, 11,280,718, 11,327,016, 11,366,052, 11,371,937, 11,692,926, 11,630,053, 11,774,343, 11,940,369 and 11,946,851, are incorporated herein by reference. In some embodiments where the flow cytometer is a particle sorter, the particle sorter is an image-enabled particle sorter. Image-enabled particle sorters are described in U.S. Patent Nos. 10,324,019, 10,620,111, 11,105,728, and 11,774,343, and U.S. Patent Applications Nos. 18 / 537,103, 18 / 657,618, 18,657,623, and 18 / 657,633, the disclosures of which are incorporated herein by reference in their entirety.

[0088] Figure 2 shows a system 200 for flow cytometry according to an exemplary embodiment of the present disclosure. The system 200 includes a laser 201 configured to irradiate particles 211 in a flow stream 214 at an interrogation point 215 within a flow cell 210. Although the example in Figure 2 shows a single laser, it will be understood that multiple lasers can also be used. The laser beam from laser 201 is directed to a focusing lens 202, which focuses the beam onto the portion of the fluid stream where the particles 211 of the sample in the flow cell 210 are located. The flow cell 210 is part of a fluid system that guides particles in the stream to the focused laser beam, typically one at a time, for interrogation. Alternatively, a nozzle top may be used if the flow cytometer is a stream-in-air cytometer.

[0089] As shown in Figure 2, the flow cell 210 is fluidically connected to a sheath fluid reservoir 203 containing sheath fluid and a sample fluid reservoir 204 containing sample fluid. Sheath fluid from the sheath fluid reservoir 203 is supplied to at least one sheath fluid injection port 208 via a conduit (i.e., sheath fluid line) 207. In addition, sample fluid containing particles 211 from the sample fluid reservoir 204 is supplied to a sample injection port 206 via a conduit (i.e., sample fluid line) 205. The sample injection port 206 is fluidly connected to a sample injector 213 (e.g., a sample injection needle) configured to introduce particles 211 into the flow cell 210. The particles 211 are hydrodynamically focused through the sheath fluid entering from the sheath fluid injection port 208 so that a flowstream 214 is formed downstream of the tapered portion 212 of the flow cell 210. Particles released at the distal end of the flow cell 210 can be disposed of and / or collected via any suitable protocol. For example, depending on the type of flow cytometry performed, the particles may be collected at the distal end of the flow cell 210, for example, via a waste line. Alternatively, the particles may be sorted.

[0090] Light from (one or more) laser beams interacts with particles 211 in the sample by diffraction, refraction, reflection, scattering, and absorption, with re-emission at various different wavelengths, depending on the particle's characteristics, such as particle size, internal structure, and the presence of one or more fluorescent molecules attached to or naturally present on or within the particles. The fluorescence emission, as well as the diffracted, refracted, reflected, and scattered light, can be sent to one or more detectors. In particular, forward scatter (FSC) is sent to a forward scatter detector 223. The forward scatter detector 223 is positioned slightly off-axis from the direct beam passing through the flow cell 210 and is configured to detect the diffracted light, i.e., the excitation light that travels mainly forward through or around the particles. The intensity of the light detected by the forward scatter detector 223 depends on the overall size of the particles. The forward scatter detector may include, for example, a photodiode. An optical filter 221a and a scattering bar 222 are positioned between the forward scatter detector 223 and the beam. The optical filter 221a may be configured to remove non-FSC light of at least one wavelength, while the scattering bar 222 may be configured to prevent the incident beam from the laser 201 (i.e., non-scattered light) from being detected by the forward scatter light detector 223.

[0091] Furthermore, side-scattered light (SSC) is detected by a side-scattered light detector 224. In other words, the side-scattered light detector 224 is configured to detect refracted and reflected light from the surface and internal structure of the particle 211, which tends to increase as the complexity of the particle structure increases. In the example in Figure 2, the flow cytometer 200 includes a dichroic mirror 220a configured to reflect SSC light to the side-scattered light detector 224 and allow non-SSC light (e.g., fluorescence) to pass through. An optical filter 221b is configured to prevent non-SSC light of at least one wavelength from being detected by the side-scattered light detector 224. Fluorescence detectors 225a-225c, each configured to detect fluorescence of different wavelengths, are also shown. For example, the dichroic mirror 220b may be configured to reflect fluorescence (FL) corresponding to a first wavelength (or wavelength range) to the fluorescence detector 225a and allow light of other wavelengths to pass through. The optical filter 221c may be configured to prevent at least one wavelength of light that does not correspond to a first wavelength (or wavelength range) from being detected by the fluorescence detector 225a. Similarly, the dichroic mirror 220c is configured to reflect FL light corresponding to a second wavelength (or wavelength range) to the fluorescence detector 225b and to allow light of a third wavelength (or wavelength range) to pass through for detection by the fluorescence detector 225c. The optical filter 221d is configured to prevent at least one wavelength of light that does not correspond to a second wavelength (or wavelength range) from being detected by the fluorescence detector 225b. Furthermore, the optical filter 221e is configured to prevent at least one wavelength of light that does not correspond to a third wavelength (or wavelength range) from being detected by the fluorescence detector 225c.

[0092] Those skilled in the art will recognize that the flow cytometer according to the embodiments of the present disclosure is not limited to the flow cytometer shown in Figure 2, but may include any flow cytometer known in the art. For example, the flow cytometer may have any number of lasers, beam splitters, filters, and detectors of various wavelengths and various different configurations. For example, the embodiment in Figure 2 shows three fluorescence detectors for illustrative purposes, but it will be understood that any suitable number of fluorescence detectors may be used.

[0093] During operation, the cytometer's operation is controlled by the controller / processor 290, and measurement data from the detector is stored in memory 295 and can be processed by the controller / processor 290. Although not explicitly shown, the controller / processor 290 is coupled to the detector to receive output signals from the detector and may also be coupled to the electrical and electromechanical components of the flow cytometer to control the laser 201, fluid flow parameters, etc. An input / output (I / O) function 297 may also be provided within the system. The memory 295, controller / processor 290, and I / O 297 may be provided as a single integrated part of the flow cytometer. In such embodiments, a display may also form part of the I / O function 297 for presenting experimental data to the user of the cytometer 200. Alternatively, some or all of the memory 295, controller / processor 290, and I / O functions may be part of one or more external devices, such as a general-purpose computer. In some embodiments, some or all of the memory 295 and controller / processor 290 can communicate with the cytometer 200 wirelessly or via a wired connection. The controller / processor 290 can be configured to work in conjunction with the memory 295 and I / O 297 to perform various functions related to the preparation and analysis of flow cytometer experiments.

[0094] Different fluorescent molecules in a fluorescent dye panel used in a flow cytometer experiment emit light in their own characteristic wavelength bands. Specific fluorescent labels used in the experiment, and their associated fluorescence emission bands, may be selected to substantially match the detector's filter window. I / O297 can be configured to receive data for flow cytometer experiments with a panel of fluorescent labels, and for multiple cell populations having multiple markers, with each cell population having a subset of multiple markers. I / O297 can also be configured to receive biological data assigning one or more markers to one or more cell populations, marker density data, emission spectral data, data assigning labels to one or more markers, and cytometer configuration data. Flow cytometer experiment data, such as label spectral characteristics and flow cytometer configuration data, can also be stored in memory 295. The controller / processor 290 can be configured to evaluate the assignment of one or more labels to the markers.

[0095] In some embodiments, the system is a particle sorting system configured to sort particles using an enclosed particle sorting module, such as that described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, whose disclosure is incorporated herein by reference. In certain embodiments, particles of a sample (e.g., cells) are sorted using a sorting decision module having multiple sorting decision units, such as that described in U.S. Patent Application Publication No. 2020 / 0256781, filed December 23, 2019, whose disclosure is incorporated herein by reference. In some embodiments, a system for sorting components of a sample includes a particle sorting module having deflection plates, such as that described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, whose disclosure is incorporated herein by reference.

[0096] In certain embodiments, the system is fluorescence imaging using a high-frequency tagged emission image-enabled particle sorter, as shown in Figures 3-1 and 3-2. Figure 3-2 is a continuation of Figure 3-1. The particle sorter 300 includes an optical irradiation component 300a, which includes a light source 301 (e.g., a 488 nm laser) that generates an output optical beam 301a, which is split into beam 302a and beam 302b using a beam splitter 302. The optical beam 302a is propagated through an acousto-optical device (e.g., an acousto-optic deflector, AOD) 303 to generate an output beam 303a having one or more angularly deflected optical beams. In some cases, the output beam 303a generated from the acousto-optical device 303 includes a local oscillator beam and multiple high-frequency comb beams. The optical beam 302b is propagated through an acousto-optical device (e.g., an acousto-optic deflector, AOD) 304 to generate an output beam 304a having one or more angularly deflected optical beams. In some cases, the output beam 304a generated from the acousto-optic device 304 includes a local oscillator beam and multiple high-frequency comb beams. The output beams 303a and 304a generated from the acousto-optic devices 303 and 304, respectively, are combined with a beam splitter 305 to generate an output beam 305a, which is then transported through an optical component 306 (e.g., an objective lens) to irradiate particles in the flow cell 307. In certain embodiments, the acousto-optic device 303 (AOD) splits a single laser beam into an array of beamlets, each having a different optical frequency and angle. A second AOD 304 adjusts the optical frequency of a reference beam, which is then superimposed with the array of beamlets in a beam combiner 305. In certain embodiments, the light irradiation system having a light source and an acoustic-optical device may also include those described in Schraivogel, et al. ("High-speed fluorescence image-enabled cell sorting," Science (2022), 375(6578):315-320) and U.S. Patent Application Publication No. 2021 / 0404943, which are incorporated herein by reference.

[0097] The output beam 305a irradiates sample particles 308 propagating through the flow cell 307 (e.g., together with the sheath fluid 309) in the irradiation area 310. As shown in the irradiation area 310, multiple beams (e.g., angle-deflected high-frequency shifted light beams shown as dots across the irradiation area 310) are superimposed on the reference local oscillator beam (indicated by diagonal lines across the irradiation area 310). Due to their different optical frequencies, the overlapping beams exhibit pulsating behavior, thereby giving each beamlet a distinct frequency f 1-n This is used to carry a sine wave modulation signal.

[0098] Light from the irradiated sample is delivered to a photodetection system 300b, which includes multiple photodetectors. The photodetection system 300b includes a forward scatter photodetector 311 for generating a forward scatter image 311a and a side scatter photodetector 312 for generating a side scatter image 312a. The photodetection system 300b also includes a bright-field photodetector 313 for generating an optical loss image 313a. In some embodiments, the forward scatter detector 311 and the side scatter detector 312 are photodiodes (e.g., avalanche photodiodes, APDs). In some cases, the bright-field photodetector 313 is a photomultiplier tube (PMT). Fluorescence from the irradiated sample is also detected by fluorescence detectors 314-317. In some cases, the photodetectors 314-317 are photomultiplier tubes. Light from the irradiated sample is directed through a beam splitter 320 to the side scatter detection channel 312 and the fluorescence detection channels 314-317. The photodetector system 300b includes bandpass optical components 321, 322, 323, and 324 (e.g., dichroic mirrors) for propagating light of a predetermined wavelength to photodetectors 314-317. In some cases, optical component 321 is 534 nm / 40 nm bandpass. In some cases, optical component 322 is 586 nm / 42 nm bandpass. In some cases, optical component 323 is 700 nm / 54 nm bandpass. In some cases, optical component 324 is 783 nm / 56 nm bandpass. The first number represents the center of the spectral band. The second number indicates the range of the spectral band. Thus, the 510 / 20 filter extends 10 nm on both sides of the center of the spectral band, i.e., from 500 nm to 520 nm.

[0099] Data signals generated in response to light detected in scattered light detection channels 311 and 312, bright-field light detection channel 313, and fluorescence detection channels 314-317 are processed by real-time digital processing by processors 350 and 351. Images 311a-317a can be generated in each light detection channel based on the data signals generated by processors 350 and 351. Image-responsive sorting is performed in response to sorting signals generated by sorting trigger 352. The sorting component 300c includes deflection plates 331 for deflecting particles into the sample container 332 or into the waste stream 333. In some cases, the sorting component 300c is configured to sort particles using an enclosed particle sorting module, such as that described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, whose disclosure is incorporated herein by reference. In certain embodiments, the sorting component 300c includes a sorting decision module having multiple sorting decision units, such as that described in U.S. Patent Application Publication No. 2020 / 0256781, the disclosure of which is incorporated herein by reference.

[0100] In some embodiments, the system is a particle analyzer and can analyze and characterize particles using the particle analysis system 401 (Figure 4), whether or not the particles are physically sorted into a collection container. Figure 4 shows a functional block diagram of the particle analysis system for computation-based sample analysis and particle characterization. In some embodiments, the particle analysis system 401 is a flow system. The particle analysis system 401 includes a fluid system 402. The fluid system 402 includes or can include a sample tube 405 and a moving fluid column in the sample tube through which sample particles 403 (e.g., cells) move along a common sample path 409.

[0101] The particle analysis system 401 includes a detection system 404 configured to collect a signal from each particle as it passes through one or more detection stations along a common sample path. The detection station 408 generally refers to a monitoring area 407 of the common sample path. In some implementations, detection may include detecting light or one or more other properties of a particle 403 as it passes through the monitoring area 407. Figure 4 shows one detection station 408 with one monitoring area 407. Some implementations of the particle analysis system 401 may include multiple detection stations. Furthermore, some detection stations may monitor two or more areas.

[0102] Each signal is assigned a signal value to form a data point for each particle. As mentioned above, this data can be called event data. The data points can be multidimensional data points containing the values ​​of each characteristic measured for the particle. The detection system 404 is configured to collect a series of such data points at a first time interval.

[0103] The particle analysis system 401 may also include a control system 406. The control system 406 may include one or more processors, amplitude control circuits and / or frequency control circuits. The illustrated control system can be operably associated with the fluid system 402. The control system may be configured to generate a calculated signal frequency for at least a portion of a first time interval based on a Poisson distribution and the number of data points collected by the detection system 404 during a first time interval. The control system 406 may be further configured to generate an experimental signal frequency based on the number of data points in a portion of the first time interval. The control system 406 may further compare the experimental signal frequency with that of a calculated signal frequency or a predetermined signal frequency.

[0104] Figure 5 shows a functional block diagram of an example of a particle analyzer control system, such as an analysis controller (i.e., processor) 500, for analyzing and displaying biological events. The analysis controller 500 can be configured to implement various processes for controlling the graphical display of biological events.

[0105] The particle analyzer or sorting system 502 can be configured to acquire biological event data. For example, a flow cytometer can generate flow cytometry event data. The particle analyzer 502 can be configured to provide biological event data to the analysis controller 500. A data communication channel can be included between the particle analyzer or sorting system 502 and the analysis controller 500. The biological event data can be provided to the analysis controller 500 via the data communication channel.

[0106] The analysis controller 500 can be configured to receive biological event data from a particle analyzer or sorting system 502. The biological event data received from the particle analyzer or sorting system 502 may include flow cytometry event data. The analysis controller 500 can be configured to provide a display device 506 with a graphic display including a first plot of the biological event data. The analysis controller 500 can be further configured to render a region of interest overlaid on the first plot, for example, as a gate around the collection of biological event data shown by the display device 506. In some embodiments, the gate may be a logical combination of one or more graphic regions of interest depicted in a histogram or bivariate plot of a single parameter. In some embodiments, a display may be used to display particle parameters or saturation detector data.

[0107] The analysis controller 500 can be further configured to display biological event data on the display device 506 within the gate in a different way from other events in the biological event data outside the gate. For example, the analysis controller 500 can be configured to render the colors of the biological event data contained within the gate differently from the colors of the biological event data outside the gate. The display device 506 can be implemented as a monitor, a tablet computer, a smartphone, or other electronic device configured to present a graphical interface.

[0108] The analysis controller 500 can be configured to receive gate selection signals from a first input device that identify gates. For example, the first input device can be implemented as a mouse 510. The mouse 510 can initiate gate selection signals to the analysis controller 500 that identify gates to be displayed on the display device 506 or operated via the display device (for example, by clicking on a desired gate when the cursor is positioned there). In some implementations, the first device can be implemented as a keyboard 508, or as other means for providing input signals to the analysis controller 500, such as a touchscreen, stylus, photodetector, or speech recognition system. Some input devices can include multiple input functions. In such implementations, each of those input functions can be considered an input device. For example, as shown in Figure 5, the mouse 510 may include a right mouse button and a left mouse button, each of which can generate a trigger event.

[0109] The trigger event can cause the analysis controller 500 to change how the data is displayed, which parts of the data are actually displayed on the display device 506, and / or provide input for further processing, such as selecting a population of interest for particle sorting.

[0110] In some embodiments, the analysis controller 500 can be configured to detect when gate selection is initiated by the mouse 510. The analysis controller 500 can be further configured to automatically modify the plot visualization to facilitate the gating process. The modification may be based on a specific distribution of biological event data received by the analysis controller 500.

[0111] The analysis controller 500 can be connected to the storage device 504. The storage device 504 can be configured to receive and store biological event data from the analysis controller 500. The storage device 504 can also be configured to receive and store flow cytometry event data from the analysis controller 500. The storage device 504 can be further configured to enable the analysis controller 500 to acquire biological event data, such as flow cytometry event data.

[0112] The display device 506 can be configured to receive display data from the analysis controller 500. The display data may include plots of biological event data and gates that outline sections of the plots. The display device 506 can be further configured to modify the information presented according to the input received from the analysis controller 500, in conjunction with input from the particle analyzer 502, the memory device 504, the keyboard 508, and / or the mouse 510.

[0113] In some implementations, the analysis controller 500 can generate a user interface for receiving exemplary events for selection. For example, the user interface may include controls for receiving exemplary events or exemplary images. The exemplary events or images or exemplary gates may be provided before the collection of event data for the sample, or based on an initial set of events for a portion of the sample.

[0114] Figure 6A is a schematic diagram of a particle sorting system 600 (e.g., a particle analyzer or sorting system 502) according to one embodiment presented herein. In some embodiments, the particle sorting system 600 is a cell sorting system. As shown in Figure 6A, a droplet-forming transducer 602 (e.g., a piezoelectric oscillator) is coupled to a fluid conduit 601, which may be coupled to a nozzle 603, may include a nozzle 603, or may be a nozzle 603. Within the fluid conduit 601, a sheath fluid 604 hydrodynamically focuses a sample solution 606 containing particles 609 into a moving fluid column 608 (e.g., a stream). Within the moving fluid column 608, the particles 609 (e.g., cells) are arranged in a line across a monitoring area 611 (e.g., where laser streams intersect) irradiated by an irradiation source 612 (e.g., a laser). The vibration of the droplet-forming transducer 602 divides the moving fluid column 608 into multiple droplets 610, some of which contain particles 609.

[0115] During operation, a detection station 614 (e.g., an event detector) identifies a particle (or cell) of interest as it crosses the monitoring area 611. The detection station 614 supplies power to a timing circuit 628, which supplies power to a flash charge circuit 630. A flash charge can be applied to the moving fluid column 608 so that the droplet of interest becomes charged at the droplet departure point, which is indicated by a timed drop delay (Δt). The droplet of interest may contain one or more particles or cells to be sorted. The charged droplet can then be sorted by activating a deflection plate (not shown) to deflect the droplet into a container such as a collection tube or a multi-well or microwell sample plate, and the well or microwell can be associated with a specific droplet of interest. As shown in Figure 6A, the droplets can be collected in a drain receptacle 638.

[0116] The detection system 616 (e.g., a droplet boundary detector) plays a role in automatically determining the phase of the droplet driving signal as particles of interest pass through the monitoring area 611. An exemplary droplet boundary detector is described in U.S. Patent No. 7,679,039, which is incorporated herein by reference in its entirety. The detection system 616 enables the instrument to accurately calculate the location of each detected particle in the droplet. The detection system 616 can supply amplitude signals 620 and / or phase signals 618, which supply amplitude signals and / or phase signals to amplitude control circuits 626 and / or frequency control circuits 624 (via amplifier 622). The amplitude control circuits 626 and / or frequency control circuits 624 control the droplet formation transducer 602. The amplitude control circuits 626 and / or frequency control circuits 624 may be included in a control system.

[0117] In some implementations, the sorting electronics (e.g., detection system 616, detection station 614, and processor 640) can be coupled with a memory configured to store detected events and sorting decisions based thereon. The sorting decisions can be included in the particle event data. In some implementations, the detection system 616 and detection station 614 can be implemented as a single detection unit, or they can be communicatively coupled so that either the detection system 616 or the detection station 614 can collect event measurements and provide them to non-collecting elements.

[0118] Figure 6B is a schematic diagram of a particle sorting system according to one embodiment presented herein. The particle sorting system 600 shown in Figure 6B includes deflection plates 652 and 654. An electric charge can be applied via a stream-charging wire in a barb. This creates a stream of droplets 610 containing particles 609 for analysis. The particles can be illuminated with one or more light sources (e.g., lasers) to generate light scattering and fluorescence information. Information about the particles is analyzed by sorting electronics or other detection systems (not shown in Figure 6B). The deflection plates 652 and 654 can be independently controlled to attract or repel charged droplets, guiding the droplets toward a target collection receptacle (e.g., one of 672, 674, 676, or 678). As shown in Figure 6B, deflection plates 652 and 654 can be controlled to direct particles toward receptacle 674 along the first path 662 or toward receptacle 678 along the second path 668. If the particles are not of interest (e.g., do not exhibit scattering or illumination information within a specified sorting range), the deflection plates may allow the particles to continue along the flow path 664. Such uncharged droplets may enter the waste receptacle via an aspirator 670 or the like.

[0119] Sorting electronics may be included to initiate measurement data collection, receive fluorescence signals from particles, and determine how to adjust the deflection plates to sort the particles. An exemplary implementation of the embodiment shown in Figure 6B includes the BD FACSAria® line of flow cytometers, commercially available from Becton, Dickinson and Company (Franklin Lakes, NJ).

[0120] method Aspects of the present disclosure also include methods for preparing samples for flow cytometry analysis. Aspects of the present disclosure also include methods for preparing samples and analyzing the samples by flow cytometry. A method according to a particular embodiment includes introducing a plurality of samples into a first sample processing module of a plurality of sample processing modules of a system, wherein the system comprises a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, the instructions, when executed by the processor, causing the processor to control the sample processing modules and robotic components to operate in order to prepare a plurality of samples for flow cytometry analysis, providing the system with sample preparation instructions, and activating the system to automatically prepare the samples in accordance with the sample preparation instructions.

[0121] Figure 7A shows a flowchart of a method according to one embodiment. Flowchart 700 corresponds to a method for preparing samples for flow cytometry analysis. Flowchart 700 begins with step 701, in which multiple samples are introduced into a first sample preparation module of multiple sample preparation modules of a system according to one embodiment. Such a system comprises multiple sample preparation modules, multiple robotic components integrated with the sample preparation modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, the instructions, when executed by the processor, causing the processor to control the sample preparation modules and robotic components to operate in order to prepare multiple samples for flow cytometry analysis, and operable connections between the processor, the sample preparation modules, and the multiple robotic components. After step 701 is completed, flowchart 700 proceeds to step 702. In step 702 of flowchart 700, a sample preparation instruction is provided to the system. After step 702 is completed, flowchart 700 proceeds to step 703. In step 703 of flow chart 700, the system is activated to automatically prepare the sample according to the sample preparation command. After step 703 is completed, flow chart 700 ends.

[0122] Figure 7B shows a flowchart of a method according to another embodiment. Flowchart 710 corresponds to a method for preparing a sample for flow cytometry analysis and for further performing flow cytometry analysis of the prepared sample. Flowchart 710 is used in connection with one embodiment of the system of the present disclosure further comprising a flow cytometer. Flowchart 710 begins with step 711. Steps 711, 712, and 713 are identical to steps 701, 702, and 703 of flowchart 700, respectively. After step 713 is completed, flowchart 710 proceeds to step 714. In step 714 of flowchart 710, the prepared sample is loaded into the flow cytometer using a robotic component. After step 714 is completed, flowchart 710 proceeds to step 715. In step 715 of flowchart 710, the sample is analyzed by flow cytometry using the flow cytometer. After step 715 is completed, flowchart 710 proceeds to step 716. In step 716 of flow diagram 710, the sample is removed from the flow cytometer using a robotic component. After step 716 is completed, flow diagram 710 ends.

[0123] A method according to a particular embodiment includes a computer implementation method for preparing samples for flow cytometry analysis. Such a method involves receiving a plurality of samples into a first sample processing module of a plurality of sample processing modules of a system, wherein the system comprises a plurality of sample processing modules, a plurality of robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, the instructions, when executed by the processor, causing the processor to control the sample processing modules and robotic components to operate the sample processing modules and robotic components to prepare a plurality of samples for flow cytometry analysis, and controlling the robotic components to manipulate the plurality of samples using the sample processing modules in order to prepare the plurality of samples according to instructions stored in memory.

[0124] Figure 7C shows a flowchart of a method according to another embodiment. Flowchart 720 corresponds to a computer-implemented method for preparing samples for flow cytometry analysis. Flowchart 720 begins with step 721, in which multiple samples are introduced into a first sample processing module of multiple sample processing modules of a system according to one embodiment. Such a system comprises multiple sample processing modules, multiple robotic components integrated with the sample processing modules, a processor having memory operably coupled to the processor, the memory containing stored instructions, which, when executed by the processor, cause the processor to control the sample processing modules and robotic components to operate in order to prepare multiple samples for flow cytometry analysis, and operable connections between the processor, the sample processing modules and the multiple robotic components. After step 721 is completed, flowchart 720 proceeds to step 722. In step 722 of flowchart 720, the robotic components are controlled to manipulate the multiple samples using the sample processing modules to prepare the multiple samples according to instructions stored in memory. After step 722 is completed, flowchart 720 ends.

[0125] In some embodiments, the method is a method for preparing samples sequentially. In other embodiments, the method is a method for preparing samples in a walkaway manner. In some embodiments, the method is a method for preparing multiple samples for flow cytometry analysis without requiring user interaction. In certain embodiments, the method is a method for preparing multiple samples for flow cytometry analysis without requiring user manipulation of the samples. In some cases, the method is a method for preparing multiple samples for flow cytometry analysis without requiring user control of the sample processing module. In other cases, the method further includes receiving instructions from the user. In such cases, the system may be configured to receive user instructions for preparing multiple samples for flow cytometry analysis. In certain cases, the first sample processing module comprises a sample receiving module. In certain cases, the sample receiving module comprises a sample storage module.

[0126] In some embodiments, a sample preparation command includes a command to instruct a robotic component to move a microwell plate from a first position to a second position. In other embodiments, a sample preparation command includes a command to instruct a robotic component to move a microwell plate from a first sample processing module to a second sample processing module. In some embodiments, a sample preparation command includes a command for one or more of the following: moving one or more system components; moving one or more plates; diluting and / or preparing one or more antibody solutions; dissolving a sample; combining an antibody solution with a sample; incubating a sample; resuspending a sample; washing a sample; and storing a sample. Embodiments of the method of the present disclosure further include using a robotic component to remove a sample from a sample loading station.

[0127] In relation to embodiments of the method of the present disclosure, the system further comprises a flow cytometer. In certain embodiments, the sample preparation command further includes a command to load the prepared sample into the flow cytometer using a robotic component, a command to analyze the sample by flow cytometry using the flow cytometer, and a command to remove the sample from the flow cytometer using a robotic component. In yet another embodiment of the method of the present disclosure, the method is a method for automating a manual laboratory workflow using a robotic component and a sample handling module.

[0128] In some cases, the samples prepared and / or analyzed in this method are biological samples. The term “biological sample” is used in its conventional sense to refer to a whole organism, a whole plant, a whole fungus, or, in certain cases, a subset of animal tissues, cells, or components that may be found in blood, mucus, lymph, synovial fluid, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, amniotic fluid, amniotic umbilical cord blood, urine, vaginal fluid, and semen. Thus, “biological sample” refers to, but is not limited to, both a naturally occurring organism or a subset of its tissues, as well as homogenates, lysates, or extracts prepared from a subset of an organism or its tissues, including, for example, plasma, serum, cerebrospinal fluid, lymph, skin, respiratory, gastrointestinal, cardiovascular and urogenital tract sections, tears, saliva, milk, blood cells, tumors, and organs. A biological sample may be any type of living tissue, including both healthy and diseased tissue (e.g., cancerous, malignant, necrotic, etc.). In certain embodiments, the biological sample is a liquid sample such as blood or its derivatives, e.g., plasma, tears, urine, semen, and in some cases, the sample is a blood sample containing whole blood, such as blood obtained from a venipuncture or fingertip puncture (the blood may or may not be combined with any reagents such as preservatives and anticoagulants before the assay).

[0129] In certain embodiments, the source of the sample is “mammal” or “mammalian,” and these terms are used broadly to describe organisms belonging to the class Mammalia, including carnivores (e.g., dogs and cats), rodents (e.g., mice, guinea pigs and rats), and primates (e.g., humans, chimpanzees and monkeys). In some cases, the subject is human. The method may also be applied to samples obtained from human subjects of both sexes and any developmental stage (i.e., neonatal, infant, juvenile, adolescent, adult), and in certain embodiments, the human subject is juvenile, adolescent, or adult. While this disclosure may be applied to samples derived from human subjects, it should be understood that the method may also be applied to samples from other animal subjects (i.e., “non-human subjects”), such as birds, mice, rats, dogs, cats, livestock, and horses, but is not limited to these.

[0130] Cells of interest can be targeted for characterization by various parameters, such as phenotypic features identified by attaching specific fluorescent labels to the cells of interest. In some embodiments, the system is configured to deflect analyzed droplets determined to contain target cells. Various cells can be characterized using this method. Target cells of interest include, but are not limited to, stem cells, T cells, dendritic cells, B cells, granulocytes, leukemia cells, lymphoma cells, viral cells (e.g., HIV cells), NK cells, macrophages, monocytes, fibroblasts, epithelial cells, endothelial cells, and erythroid cells. Target cells of interest include cells having favorable cell surface markers or antigens that can be captured or labeled by favorable affinity factors or their conjugates. For example, target cells may contain cell surface antigens such as CD11b, CD123, CD14, CD15, CD16, CD19, CD193, CD2, CD25, CD27, CD3, CD335, CD36, CD4, CD43, CD45RO, CD56, CD61, CD7, CD8, CD34, CD1c, CD23, CD304, CD235a, T cell receptor alpha / beta, T cell receptor gamma / delta, CD253, CD95, CD20, CD105, CD117, CD120b, Notch4, Lgr5 (N-terminus), SSEA-3, TRA-1-60 antigen, disialoganglioside GD2, and CD71. In some embodiments, target cells are selected from HIV-containing cells, Treg cells, antigen-specific T cell populations, tumor cells, or hematopoietic progenitor cells (CD34+) from whole blood, bone marrow, or umbilical cord blood.

[0131] When performing this method, a certain amount of initial fluid sample is injected into the flow cytometer. The amount of sample injected into the particle sorting module may vary, for example, 0.001 mL to 1000 mL, 0.005 mL to 900 mL, 0.01 mL to 800 mL, 0.05 mL to 700 mL, 0.1 mL to 600 mL, 0.5 mL to 500 mL, 1 mL to 400 mL, 2 mL to 300 mL, or any other amount including 5 mL to 100 mL.

[0132] The method according to embodiments of the present disclosure includes counting labeled particles (e.g., target cells) in a sample and selectively sorting them. When carrying out the method, a fluid sample containing particles is first introduced into the system's flow nozzle. Exiting the flow nozzle, the particles pass through the sample interrogation region substantially one at a time, where each particle is irradiated with a light source, and light scattering parameters and, in some cases, desired fluorescence emission measurements (e.g., two or more light scattering parameters and one or more fluorescence emission measurements) are recorded separately for each particle. Depending on the characteristics of the interrogated flowstream, the light may be irradiated to a length of 0.001 mm or more of the flowstream, e.g., 0.005 mm or more, e.g., 0.01 mm or more, e.g., 0.05 mm or more, e.g., 0.1 mm or more, e.g., 0.5 mm or more, e.g., 0.5 mm or more, e.g., 1 mm or more of the flowstream. In certain embodiments, the method includes irradiating a planar cross section of the flowstream within the sample interrogation region with a laser (as described above). In other embodiments, the method includes irradiating a sample interrogation region with a predetermined length of flowstream, for example, a length corresponding to the irradiation profile of a diffuse laser beam or lamp.

[0133] In certain embodiments, the method includes irradiating a flowstream at or near the nozzle orifice of the flow cell. For example, the method may include irradiating a flowstream at a position including 1 mm or more, for example, 0.001 mm or more, for example, 0.01 mm or more, for example, 0.05 mm or more, for example, 0.1 mm or more, for example, 0.5 mm or more, from the nozzle orifice. In certain embodiments, the method includes irradiating a flowstream immediately adjacent to the nozzle orifice of the flow cell.

[0134] In embodiments of the method, a detector such as a photomultiplier tube (PMT) is used to record the light passing through each particle (called forward scattering in certain cases), the light reflected perpendicular to the direction of particle flow through the detection region (called orthogonal or side scattering in some cases), and, if the particles are labeled with a fluorescent marker, the fluorescence emitted from the particles as they pass through the detection region and are illuminated by an energy source. Each of forward scattering (FSC), side scattering (SSC), and fluorescence emission involves distinct parameters for each particle (or each “event”). Thus, for example, two, three, or four parameters can be collected (and recorded) from particles labeled with two different fluorescent markers. The data recorded for each particle can, if desired, be analyzed in real time or stored in data storage and analysis means such as a computer.

[0135] In certain embodiments, particles are detected and uniquely identified, as desired, by exposing the particles to excitation light and measuring the fluorescence of each particle in one or more detection channels. The fluorescence emitted in the detection channels used to identify the particles and the associated binding complexes may be measured after excitation by a single light source or separately after excitation by individual light sources. If separate excitation light sources are used to excite particle labels, the labels may be selected so that all labels are excitable by each of the excitation light sources used.

[0136] The method, in certain embodiments, also includes data acquisition, analysis, and recording using a computer or the like, with multiple data channels recording data from each detector about the light scattering and fluorescence emitted by each particle as it passes through the sample interrogation area of ​​the particle sorting module. In these embodiments, the analysis includes sorting and counting the particles so that each particle is presented as a set of digitized parameter values. The system may be set up with a trigger on a selected parameter to distinguish the particle of interest from background and noise. A “trigger” refers to a preset threshold for detecting the parameter and may be used as a means to detect the passage of a particle through a light source. Detection of an event exceeding the threshold of the selected parameter triggers the acquisition of light scattering and fluorescence data for the particle. For particles or other components in the assayed medium that cause a response below the threshold, no data is acquired. The trigger parameter may be the detection of forward scattered light caused by the passage of a particle through a light beam. The flow cytometer then detects and collects the light scattering and fluorescence data for the particle.

[0137] Next, a specific subpopulation of interest is further analyzed by “gating” based on data collected for the entire population. To select an appropriate gate, the data is plotted to obtain the best possible subpopulation separation. This procedure can be performed by plotting forward light scattering (FSC) versus side (i.e., orthogonal) light scattering (SSC) on a two-dimensional dot plot. Then, a subpopulation of particles (i.e., their cells in the gate) is selected, and particles not in the gate are excluded. If desired, the gate may also be selected by drawing a line around the desired subpopulation using a cursor on a computer screen. Then, only those particles in the gate are further analyzed by plotting other parameters of these particles, such as fluorescence. If desired, the above analysis may be configured to yield a count of the particles of interest in the sample.

[0138] The methods of interest may further include the use of particles in research, laboratory testing, or therapy. In some embodiments, the methods include obtaining individual cells prepared from biological samples of a target fluid or tissue. For example, the methods include obtaining cells from fluid or tissue samples used as research or diagnostic specimens for diseases such as cancer. Similarly, the methods include obtaining cells from fluid or tissue samples used in therapy. Cell therapy protocols are protocols in which viable cellular material, including, for example, cells and tissues, is prepared and can be introduced into a subject as a therapeutic procedure. Conditions that can be treated by administration of samples sorted by flow cytometry include, but are not limited to, blood disorders, immune system disorders, and organ damage.

[0139] A typical cell therapy protocol may include the following steps: sample collection, cell isolation, genetic modification, culture and in vitro growth, cell harvesting, sample volume reduction and washing, biopreservation, storage, and introduction of cells into the subject. The protocol may begin with the collection of viable cells and tissues from the subject's source tissues to generate cell and / or tissue samples. Samples may be collected by any appropriate procedure, including, for example, administering a cell recruiter to the subject, drawing blood from the subject, or removing bone marrow from the subject. After sample collection, cell enrichment may be performed by several methods, including, for example, centrifugation-based methods, filter-based methods, elutriation, magnetic separation, and fluorescence-activated cell sorting (FACS). In some cases, enriched cells may be genetically modified by any convenient method, such as nuclease-mediated gene editing. Genetically modified cells can be cultured, activated, and grown in vitro. In some cases, cells are preserved, for example, by cryopreservation, and stored for future use, where they can be thawed and administered to a patient, for example, by injection.

[0140] Computer control system Aspects of the present disclosure further include a computer-controlled system for carrying out the subject method, the system further including one or more computers for fully or partially automating the system for carrying out the method described herein. In some embodiments, the system includes a computer having a computer-readable storage medium in which a computer program is stored, the computer program including instructions for automatically preparing a sample for flow cytometry analysis when loaded into the computer, and in some cases for automatically performing flow cytometry analysis of a sample prepared according to an embodiment of the method of the present disclosure.

[0141] The system may include a display and an operator input device. The operator input device may be, for example, a keyboard, a mouse, etc. The processing module includes a processor that can access memory in which instructions for performing the steps of this method are stored. The processing module may include an operating system, a graphical user interface (GUI) controller, system memory, memory storage devices, as well as input / output controllers, cache memory, a data backup unit, and many other devices. The processor may be a commercially available processor or one of several other processors that are available or will be available. The processor runs an operating system, which interfaces with firmware and hardware in a well-known manner and facilitates the processor to coordinate and execute the functions of various computer programs that can be written in various programming languages, such as Java, Perl, C++, Python, other high-level or low-level languages, and combinations thereof, as is known in the art. The operating system typically works with the processor to coordinate and execute the functions of other components of the computer. The operating system also provides scheduling, input / output control, file and data management, memory management, and communication control and related services, according to all known technologies. In some embodiments, the processor includes analog electronics that provide feedback control, such as negative feedback control.

[0142] System memory may be any of the various known or future memory storage devices. Examples include any commonly available random access memory (RAM), magnetic media such as permanent hard disks or tapes, optical media such as read-and-write compact disks, flash memory devices, or other memory storage devices. Memory storage devices may be any of the various known or future devices, including compact disk drives, tape drives, or floppy disk drives. Such types of memory storage devices typically read from and / or write to program storage media such as compact disks (not shown). Any of these program storage media, or others currently in use or to be developed in the future, may be considered computer program products. As is understood, these program storage media typically store computer software programs and / or data. Computer software programs, also known as computer control logic, are typically stored in program storage devices used in conjunction with system memory and / or memory storage devices.

[0143] In some embodiments, a computer program product is described that includes a computer-usable medium on which control logic (a computer software program including program code) is stored. When the control logic is executed by the computer's processor, it causes the processor to perform the functions described herein. In other embodiments, some functions are implemented primarily in hardware, for example, using a hardware state machine. Implementations of a hardware state machine for performing the functions described herein will be obvious to those skilled in the art.

[0144] Memory may be any suitable device on which the processor can store and retrieve data, such as a magnetic storage device, an optical storage device, or a solid-state storage device (including magnetic or optical disks, or tapes or RAM, or any other suitable fixed or portable device). The processor may include a general-purpose digital microprocessor appropriately programmed from a computer-readable medium having the necessary program code. The programming may be supplied to the processor remotely via a communication channel, or it may be pre-stored in a computer program product such as memory or some other portable or fixed computer-readable storage medium using any of the memory-related devices. For example, a magnetic or optical disk may have a program which can be read by a disk writer / reader. The system of this disclosure also includes programming in the form of a computer program product, algorithms for use in carrying out the methods described above. The programming according to this disclosure may be recorded on a computer-readable medium, for example, any medium which can be directly read and accessed by a computer. Such media include, but are not limited to, magnetic storage media such as floppy disks, hard disk storage media, and magnetic tape; optical storage media such as CD-ROMs; electrical storage media such as RAM and ROM; portable flash drives; and hybrids of these categories such as magnetic / optical storage media.

[0145] The processor can also access communication channels to communicate with users in remote locations. Remote locations mean that the user is not in direct contact with the system, but rather relays input information to the input manager from an external device such as a computer connected to a wide area network ("WAN"), telephone network, satellite network, or any other suitable communication channel, including a mobile phone (i.e., a smartphone).

[0146] In some embodiments, the systems according to this disclosure may be configured to include a communication interface. In some embodiments, the communication interface includes a receiver and / or transmitter for communicating with a network and / or another device. The communication interface may be configured for wired or wireless communication, including, but not limited to, radio frequency (RF) communication (e.g., radio frequency identification (RFID), Zigbee communication protocol, Wi-Fi, infrared, wireless universal serial bus (USB), ultra-wideband (UWB), Bluetooth® communication protocol, and cellular communication such as code division multiple access (CDMA) and global system for mobile communications (GSM).

[0147] In one embodiment, the communication interface is configured to include one or more physical ports or interfaces, such as a USB port, a USB-C port, an RS-232 port, or any other suitable electrical connection port that enables data communication between the system and other external devices, such as computer terminals configured for similar complementary data communication (e.g., in a doctor's office or hospital environment).

[0148] In one embodiment, the communication interface is configured for infrared communication, Bluetooth® communication, or any other suitable wireless communication protocol that enables the target system to communicate with computer terminals and / or networks, other devices such as communication-enabled mobile phones, personal digital assistants, or any other communication devices that the user may use in conjunction with it.

[0149] In one embodiment, the communication interface is configured to provide a connection for data transfer using Internet Protocol (IP), Short Message Service (SMS), wireless connection to a personal computer (PC) on a local area network (LAN) connected to the Internet, or Wi-Fi connection to the Internet via a Wi-Fi hotspot.

[0150] In one embodiment, the system is configured to communicate wirelessly with a server device via a communication interface using common standards such as 802.11, Bluetooth® RF protocol, or IrDA infrared protocol. The server device may be another portable device such as a smartphone, personal digital assistant (PDA), or notebook computer, or a larger device such as a desktop computer or electrical appliance. In some embodiments, the server device has a display such as a liquid crystal display (LCD), as well as input devices such as buttons, a keyboard, a mouse, or a touchscreen.

[0151] In some embodiments, the communication interface is configured to communicate automatically or semi-automatically with a network or server device using one or more of the communication protocols and / or mechanisms described above, for example, data stored in the system, for example, an optional data storage unit.

[0152] The output controller may include a controller for any of the various known display devices for presenting information to a user, whether human or machine, local or remote. If one of the display devices provides visual information, this information may typically be logically and / or physically organized as an array of pixels. The graphical user interface (GUI) controller may include any of the various known or future software programs for providing a graphical input / output interface between the system and the user and for processing user input. Functional elements of the computer may communicate with each other via a system bus. Some of these communications may be achieved in alternative embodiments using a network or other type of remote communication. The output manager may also provide information generated by the processing module to a remote user, for example, via the internet, telephone or satellite network, according to known techniques. The presentation of data by the output manager may be implemented according to various known techniques. As some examples, the data may include SQL, HTML or XML documents, email or other files, or data in other formats. The data may also include Internet URL addresses so that the user can retrieve additional SQL, HTML, XML, or other documents or data from remote sources. One or more platforms present in this system may be any type of known computer platform or a type to be developed in the future, but they are typically computers of a class commonly referred to as servers. However, they may also be mainframe computers, workstations, or other types of computers. They may be connected via any known or future type of cabling or other communication systems, including wireless systems, whether networked or not. They may be located in the same place or physically separated. Depending perhaps on the type and / or manufacturer of the selected computer platform, various operating systems may be used on any of the computer platforms.Suitable operating systems include Windows® NT®, Windows® XP, Windows® 7, Windows® 8, Windows® 10, iOS®, macOS®, Linux®, Ubuntu®, Fedora®, OS / 400®, i5 / OS®, IBM i®, Android®, SGI IRIX®, Oracle Solaris®, and others.

[0153] Figure 8 shows a general architecture of an exemplary computing device 800 according to a particular embodiment. The general architecture of the computing device 800 shown in Figure 8 includes the configuration of computer hardware and software components. However, not all of these generally conventional elements need to be illustrated in order to provide an implementable disclosure. As shown, the computing device 800 includes a processing unit 810, a network interface 820, a computer-readable media drive 830, an input / output device interface 840, a display 850, and an input device 860, all of which can communicate with each other via a communication bus. The network interface 820 may provide a connection to one or more networks or computing systems. Thus, the processing unit 810 can receive information and instructions from other computing systems or services via the network. The processing unit 810 also communicates with memory 870 and may further provide output information to an optional display 850 via the input / output device interface 840. For example, analytical software (e.g., data analysis software or program such as FlowJo®) stored as executable instructions in the non-temporary memory of the analysis system can display flow cytometry event data to the user. The input / output device interface 840 may also accept input from an optional input device 860, such as a keyboard, mouse, digital pen, microphone, touchscreen, gesture recognition system, voice recognition system, gamepad, accelerometer, gyroscope, or other input devices.

[0154] Memory 870 may include computer program instructions (grouped as modules or components in some embodiments) that the processing unit 810 executes to implement one or more embodiments. Memory 870 generally includes RAM, ROM, and / or other persistent, auxiliary, or non-temporary computer-readable media. Memory 870 may store an operating system 872 that provides computer program instructions for use by the processing unit 810 in the general management and operation of the computing device 800. Data may be stored in a data storage device 890. Memory 870 may further include computer program instructions and other information for implementing aspects of the present disclosure, such as module 873 for operating sample preparation modules and robot components to prepare multiple samples for flow cytometry analysis, module 874 for receiving sample preparation commands to the system, and module 875 for controlling robot components to manipulate multiple samples using the sample preparation module to prepare multiple samples according to instructions stored in memory.

[0155] kit Aspects of this disclosure further include a kit, which includes one or more of the following: programming for the System in the form of a computer-readable medium (e.g., a flash drive, USB storage, compact disc, DVD, Blu-ray disc, etc.), or instructions for downloading the programming from the Internet Web Protocol or a cloud server or a non-temporary computer-readable recording medium as described herein.

[0156] In addition to the components described above, the kit may further include instructions (in some embodiments). These instructions may be present in the kit in various forms, and one or more of them may be present in the kit. One possible form of these instructions is information printed on a suitable medium or substrate, such as one or more sheets of paper on which the information is printed, the kit's packaging, or accompanying documents. Yet another form of these instructions is a computer-readable medium on which the information is recorded, such as a diskette, compact disc (CD), or portable flash drive. Yet another possible form of these instructions is a website address that can be used via the internet to access the information at a remote site.

[0157] usefulness Embodiments of the present disclosure are used in applications where samples, such as biological samples or cells, require preparation, such as staining, before flow cytometry analysis. Embodiments are further used in the context of applications that benefit from the automation of such sample preparation steps, from the viewpoint of increased efficiency, which is possible when a large number of samples require such preparation and the user does not need to perform the sample preparation step, as well as from the viewpoint of improved consistency of the overall prepared sample.

[0158] Embodiments of this disclosure are used in a variety of applications where it is desirable to analyze and sort particulate components in a sample in a fluid medium, such as a biological sample. In some embodiments, the systems and methods described herein are used for flow cytometry characterization of a biological sample labeled with a fluorescent tag. Embodiments of this disclosure are used when it is desirable to provide a flow cytometer with improved cell sorting accuracy and enhanced particle collection.

[0159] Embodiments of this disclosure are used in applications where cells prepared from biological samples may be desired for use in research, laboratory testing, or therapeutic settings. In some embodiments, the methods and devices may facilitate obtaining and / or analyzing individual cells prepared from biological samples of target fluids or tissues. For example, the methods and systems may facilitate obtaining cells from fluid or tissue samples used as research or diagnostic specimens for diseases such as cancer. Similarly, the methods and systems may facilitate obtaining cells from fluid or tissue samples used in therapeutic settings.

[0160] Notwithstanding the attached claims, this disclosure is also defined by the following clauses: 1. A robotic system for automated sample preparation, wherein the system is Multiple sample processing modules, Multiple robotic components integrated with a sample processing module, A processor comprising memory operably coupled to the processor, wherein the memory contains instructions, and when an instruction is executed by the processor, the processor causes the processor to control a sample processing module and robot components. A processor operates the sample processing module and robot components to prepare multiple samples for flow cytometry analysis. A movable connection between the processor, the sample processing module, and multiple robot components. A robotic system equipped with [the necessary components]. 2. Flow cytometer Furthermore, Multiple robotic components are further integrated with the flow cytometer. The memory further contains stored instructions, which, when executed by the processor, cause the processor to control the sample processing module, robot components, and flow cytometer. Each prepared sample of multiple samples is loaded into the flow cytometer. The flow cytometer is operated to analyze each prepared sample of multiple samples. The operational connection unit operationally connects the processor, the sample processing module, the flow cytometer, and multiple robotic components. The system described in Clause 1. 3. The system described in Clause 1 or 2, configured to automatically prepare multiple samples for flow cytometry analysis. 4. The system according to any one of clauses 1 to 3, configured to automatically and continuously prepare multiple samples for flow cytometry analysis. 5. The system described in any one of clauses 1 to 4, configured to prepare multiple samples for flow cytometry analysis in a walkaway manner. 6. The system described in any one of clauses 1 to 5, configured to prepare multiple samples for flow cytometry analysis without requiring user interaction. 7. The system described in any one of clauses 1 to 6, configured to prepare multiple samples for flow cytometry analysis without requiring user manipulation of the samples. 8. The system described in any one of clauses 1 to 7, configured to prepare multiple samples for flow cytometry analysis without requiring user control of the sample processing module. 9. The system described in any one of clauses 1 to 8, configured to receive user instructions requesting the preparation of multiple samples for flow cytometry analysis. 10. The system is configured to receive user instructions before preparing a sample, as described in Clause 9. 11. The system described in any one of clauses 1 to 10, which is configured to automatically prepare multiple samples for flow cytometry analysis. 12. The system is a robotic system for automated sample preparation and flow cytometry analysis, as described in any one of clauses 1 to 11. 13. The instruction includes one or more of the following systems as described in any one of Clauses 1 to 12: scheduling software, software for defining liquid handling parameters, and software for defining system setup. 14. The system described in any one of Clauses 1 to 13, wherein multiple sample processing modules are configured to prepare samples for flow cytometry analysis. 15. Multiple sample processing modules comprising independent laboratory equipment, as described in any one of clauses 1 to 14. 16. A system as described in any one of Clauses 1 to 15, comprising one or more modules: an antibody dilution module, a cell staining module, a sample washing module, a sample resuspension module, a sample transfer module, and a sample analysis module. 17. The cell staining module is configured for cell staining with a fluorescence-coupled antibody, as described in Clause 16. 18. A system according to any one of Clauses 1 to 17, comprising one or more modules: an incubator, a storage unit, a cooling device, a plate washer, a well washer, a compressor, a vacuum pump, a static nest, a bottle, a flow cytometer, a plate rotator, a barcode scanner, a plate storage section, a centrifuge, a handover nest, an automated liquid handling platform, a pipette, a sample receiving area, a reagent receiving area, and a waste receiving area. 19. The system according to any one of clauses 1 to 18, wherein multiple modules comprise a flow cytometer configured to perform flow cytometry analysis on samples prepared by the system. 20. The system according to any one of clauses 1 to 19, wherein multiple sample processing modules are configured to perform cell staining on a sample. 21. A system according to any one of Clauses 1 to 20, wherein multiple sample processing modules are configured to incubate samples. 22. A system according to any one of clauses 1 to 21, wherein multiple sample processing modules are configured to manipulate samples in a multiwell plate. 23. A system according to any one of clauses 1 to 22, wherein multiple sample processing modules are equipped with pipettes. 24. The system according to any one of clauses 1 to 23, wherein multiple sample processing modules are configured to pipette fluid into and out of a multiwell plate. 25. A system according to any one of clauses 1 to 24, wherein multiple sample processing modules are equipped with centrifuges. 26. The system according to any one of Clauses 1 to 25, wherein multiple sample processing modules are configured to rotate the sample and separate the sample components. 27. A system according to any one of clauses 1 to 26, wherein multiple sample processing modules are configured to wash samples. 28. A system described in any one of clauses 1 to 27, wherein the robotic component is configured to move one or more multiwell plates. 29. A system described in any one of Clauses 1 to 28, wherein the robotic component is configured to move a multiwell plate in and out of a module. 30. A system according to any one of Clauses 1 to 29, wherein the robotic component comprises fingers configured to grip a multiwell plate. 31. A robotic component is a system described in any one of clauses 1 to 30, configured to operate a module. 32. A system according to any one of Clauses 1 to 31, comprising a rail and actuators for translating the robot component. 33. A system according to any one of clauses 1 to 32, wherein the robotic component comprises a robotic arm. 34. A system as described in any one of Clauses 1 to 33, comprising modules and robotic components configured to manipulate one or more of the following: test tubes, multiwell plates, deepwell plates, and standard well plates. 35. A system described in any one of Clauses 1 to 34, comprising modules and robotic components configured to operate a 96-well standard depth plate. 36. A system as described in any one of clauses 1 to 35, further comprising one or more tables. 37. A system described in any one of the clauses 1 to 36, further comprising a user interface. 38. The user interface includes one or more of the following systems as described in Clause 37: a display, keyboard, mouse, trackpad, user tag-out device, system status light, and emergency stop button. 39. A system described in any one of clauses 1 to 38, further comprising an electrical interface for supplying power to the system. 40. A system as described in any one of clauses 1 to 39, further comprising an electrical interface for supplying power to the system. 41. A system as described in any one of the clauses 1 to 40, further comprising a data interface for transmitting and / or receiving control signals or data signals from the system. 42. The system described in any one of the clauses 1 to 41, further comprising a gas interface for supplying pressurized gas to the system. 43. A system described in any one of clauses 1 to 42, further comprising a network interface. 44. A system as described in any one of the clauses 1 to 43, further comprising one or more protective shields. 45. A system as described in any one of the clauses 1 to 44, further comprising one or more light curtains. 46. ​​A method for preparing a sample for flow cytometry analysis, the method being: The system involves introducing multiple samples into a first sample processing module among multiple sample processing modules of the system, and the system Multiple sample processing modules, Multiple robotic components integrated with a sample processing module, A processor comprising memory operably coupled to the processor, wherein the memory contains instructions, and when an instruction is executed by the processor, the processor causes the processor to control a sample processing module and robot components. A processor operates the sample processing module and robot components to prepare multiple samples for flow cytometry analysis. A movable connection between the processor, the sample processing module, and multiple robot components. To be equipped with, To provide the system with sample preparation instructions, The system is activated to automatically prepare the sample according to the sample preparation command. Methods that include... 47. A computer-implemented method for preparing a sample for flow cytometry analysis, wherein the method is: The system accepts multiple samples into a first sample processing module of multiple sample processing modules of the system, and the system Multiple sample processing modules, Multiple robotic components integrated with a sample processing module, A processor comprising memory operably coupled to the processor, wherein the memory contains instructions, and when an instruction is executed by the processor, the processor causes the processor to control a sample processing module and robot components. A processor operates the sample processing module and robot components to prepare multiple samples for flow cytometry analysis. A movable connection between the processor, the sample processing module, and multiple robot components. To be equipped with, The robot components are controlled to manipulate multiple samples using a sample processing module in order to prepare multiple samples according to instructions stored in memory. Computer implementation methods, including those mentioned above. 48. The method is a method for preparing samples in a continuous manner, as described in clause 46 or 47. 49. The method according to any one of the clauses 46 to 48, wherein the method is a method of preparing a sample in a walkaway manner. 50. The method according to any one of the clauses 46 to 49, wherein the method is a method for preparing multiple samples for flow cytometry analysis without requiring user interaction. 51. The method according to any one of the clauses 46 to 50, which is a method for preparing multiple samples for flow cytometry analysis without requiring user manipulation of the samples. 52. The method according to any one of the clauses 46 to 51, wherein the method is a method for preparing multiple samples for flow cytometry analysis without requiring user control of the sample processing module. 53. The method described in any one of the clauses 46 to 52, further comprising receiving an order from the user. 54. The method according to any one of the clauses 46 to 53, wherein the system is configured to receive user instructions requesting the preparation of multiple samples for flow cytometry analysis. 55. The method according to any one of the clauses 46 to 54, wherein the first sample processing module comprises a sample receiving module. 56. The method according to any one of the clauses 46 to 55, wherein the sample receiving module comprises a sample storage module. 57. The method according to any one of the clauses 46 to 56, wherein the sample preparation command includes a command to instruct a robotic component to move a microwell plate from a first position to a second position. 58. The method according to any one of the clauses 46 to 57, wherein the sample preparation command includes a command to instruct a robotic component to move a microwell plate from a first sample processing module to a second sample processing module. 59. The method according to any one of Clauses 46 to 58, wherein a sample preparation instruction includes instructions for moving one or more system components, moving one or more plates, diluting and / or preparing one or more antibody solutions, dissolving a sample, combining an antibody solution with a sample, incubating a sample, resuspending a sample, washing a sample, and storing a sample. 60. Using robotic components to retrieve a sample from the sample loading station. The method described in any one of the clauses 46 to 59, further including the method described in any one of the clauses 46 to 59. 61. The method according to any one of the clauses 46 to 60, further comprising a flow cytometer. 62. The instruction for sample preparation is: Commands for loading the prepared sample into the flow cytometer using robotic components. Instructions for analyzing a sample by flow cytometry using a flow cytometer, and Instructions for removing a sample from a flow cytometer using robotic components. The method described in any one of the clauses 46 to 61, further including the method described in any one of the clauses 46 to 61. 63. The method according to any one of the clauses 46 to 62, wherein the method is a method for automating a manual laboratory workflow using robotic components and sample handling modules.

[0161] While the foregoing disclosure has provided some detail as examples and illustrations to clarify understanding, it will be readily apparent to those skilled in the art that several changes and modifications may be made in light of the teachings of this disclosure without departing from the spirit or scope of the attached claims.

[0162] Therefore, the foregoing is merely illustrative of the principles of the present disclosure. Those skilled in the art will understand that various configurations embodying the principles of the present disclosure and that fall within its spirit and scope can be devised, although not expressly described or shown herein. Furthermore, all examples and conditional statements described herein are primarily intended to help the reader understand the principles of the present disclosure and the concepts to which the inventors have contributed to advancing the art, and should be interpreted as not being limited to such specifically described examples and conditions. Furthermore, all descriptions herein listing the principles, aspects, and embodiments of the present disclosure, as well as specific examples thereof, are intended to encompass both structural and functional equivalents. Moreover, such equivalents are intended to include both currently known equivalents and equivalents to be developed in the future, i.e., any developed elements that perform the same function regardless of their structure. Furthermore, nothing disclosed herein is intended to be made available to the public, whether such disclosure is expressly described in the claims or not.

[0163] Accordingly, the scope of this disclosure is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of this disclosure are embodied in the appended claims. In the claims, 35 U.SC § 112(f) or 35 U.SC § 112(6) are expressly defined as applying to the limitation in the claims only if the exact phrase “means” or the exact phrase “step” is stated at the beginning of such limitation in the claims, and if such exact phrase is not used in the limitation of the claims, 35 U.SC § 112(f) or 35 U.SC § 112(6) does not apply.

Claims

1. A robotic system for automated sample preparation, wherein the system is Multiple sample processing modules, Multiple robotic components integrated with the aforementioned sample processing module, A processor comprising memory operably coupled to the processor, wherein the memory includes instructions stored therein, and when an instruction is executed by the processor, the processor causes the processor to control the sample processing module and the robot components. A processor operates the sample processing module and the robot components to prepare multiple samples for flow cytometry analysis. A movable connection between the processor, the sample processing module, and the plurality of robot components. A robotic system equipped with [the necessary components].

2. Flow cytometer Furthermore, The aforementioned plurality of robotic components are further integrated with the flow cytometer, The memory further includes stored instructions, which, when executed by the processor, cause the processor to control the sample processing module, the robot components, and the flow cytometer. Each of the prepared samples of the plurality of samples is loaded into the flow cytometer. The flow cytometer is operated to analyze each of the prepared samples of the plurality of samples, The operable connection unit operablely connects the processor, the sample processing module, the flow cytometer, and the plurality of robot components. The system according to claim 1.

3. The system according to claim 1 or 2, wherein the system is configured to automatically prepare a plurality of samples for flow cytometry analysis.

4. The system according to any one of claims 1 to 3, wherein the system is configured to automatically and continuously prepare a plurality of samples for flow cytometry analysis.

5. The system according to any one of claims 1 to 4, wherein the system is configured to automatically prepare a plurality of samples for flow cytometry analysis.

6. The system according to any one of claims 1 to 5, wherein the system is a robotic system for automated sample preparation and flow cytometry analysis.

7. The system according to any one of claims 1 to 6, wherein the instruction includes one or more of scheduling software, software for defining liquid handling parameters, and software for defining system setup.

8. The system according to any one of claims 1 to 7, wherein the plurality of sample processing modules are configured to prepare samples for flow cytometry analysis.

9. The system according to any one of claims 1 to 8, wherein the plurality of sample processing modules are equipped with independent experimental facilities.

10. The system according to any one of claims 1 to 9, wherein the plurality of modules include one or more of an antibody dilution module, a cell staining module, a sample washing module, a sample resuspension module, a sample transfer module, and a sample analysis module.

11. The system according to any one of claims 1 to 10, wherein the plurality of modules comprises one or more of the following: an incubator, a storage unit, a cooling device, a plate washer, a well washer, a compressor, a vacuum pump, a static nest, a bottle, a flow cytometer, a plate rotator, a barcode scanner, a plate storage section, a centrifuge, a handover nest, an automated liquid handling platform, a pipette, a sample receiving area, a reagent receiving area, and a waste receiving area.

12. The system according to any one of claims 1 to 11, wherein the plurality of modules include a flow cytometer configured to perform flow cytometry analysis on a sample prepared by the system.

13. The system according to any one of claims 1 to 12, further comprising a user interface.

14. The system according to any one of claims 1 to 13, further comprising a network interface.

15. A method for preparing a sample for flow cytometry analysis, wherein the method is: The process involves introducing multiple samples into a first sample processing module of a plurality of sample processing modules in a system, wherein the system The plurality of sample processing modules, Multiple robotic components integrated with the aforementioned sample processing module, A processor comprising memory operably coupled to the processor, wherein the memory includes instructions stored therein, and when an instruction is executed by the processor, the processor causes the processor to control the sample processing module and the robot components. A processor operates the sample processing module and the robot components to prepare multiple samples for flow cytometry analysis. A movable connection between the processor, the sample processing module, and the plurality of robot components. To be equipped with, To provide the system with a sample preparation command, The system is activated to automatically prepare the sample in accordance with the sample preparation command. Methods that include...

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