Cell killing monitoring system

Abstract

A system for monitoring effector cell mediated killing of target cells includes a containment unit with multiple discrete confinement locations, each capable of simultaneously holding at least one effector cell and one target cell. The system also features a lens-free imaging module for capturing images of all cells within the containment unit and a control unit configured to operate the imaging module to capture a sequence of images over time, extract features from these images, and monitor the effector cell mediated killing of the target cells.

Description

[0001] Cell Killing Monitoring System

[0002] Field of the Invention

[0003] The present invention relates to the field of cellular biology and more specifically to methods and systems for monitoring interactions between cells over time.

[0004] Background of the Invention

[0005] In the realm of cellular biology and medical research, the study of cell-cell interactions plays a crucial role in understanding various biological processes and disease mechanisms. One significant area of interest is the interaction between immune cells and cancer cells, particularly in the context of immunotherapy treatments such as CAR-T cell therapy. CAR-T cell therapy involves the modification of a patient's T-cells to target and destroy cancer cells, making the monitoring of these interactions vital for assessing the efficacy of the treatment.

[0006] Traditionally, cell interactions are monitored using various imaging techniques that capture snapshots of cell behavior at specific time points. These methods, while useful, often provide limited information as they capture only a momentary glimpse of the ongoing cellular processes. This snapshot approach can lead to significant gaps in data, particularly in dynamic and fast-paced cellular activities such as the immune response, where cells may exhibit critical behaviors between the captured time points.

[0007] Moreover, the reliance on snapshot imaging poses challenges in accurately characterizing cell behaviors and interactions over time. For instance, in the context of CAR-T therapy, the ability to observe the progression of T-cell interactions with cancer cells continuously would provide a more comprehensive understanding of the therapy's effectiveness at different stages. However, current methodologies typically focus on end-point analyses, which may not fully capture the nuances of cell behavior throughout the therapeutic process.

[0008] Despite advancements in imaging technologies and methodologies, there remains a substantial need for improved systems and methods.

[0009] Summary of the Invention

[0010] It is an object of embodiments of the present invention to enable massive characterization of cells by continuously monitoring cell-cell interactions. This objective is accomplished by a system and a method for monitoring effector cell mediated killing of target cells according to the invention.

[0011] In the first aspect, the present invention relates to a system for monitoring effector cell mediated killing of target cells, comprising: - a containment unit comprising a plurality of discrete confinement locations, the containment unit being adapted to hold simultaneously at least one effector cell and at least one target cell per confinement location, the containment unit comprising at least one effector cell and at least one target cell in one of the confinement locations;

[0012] - a lens-free imaging module for capturing images, each image depicting all the effector cells and target cells within the containment unit; and

[0013] - a control unit configured to operate the lens-free imaging module to capture a sequence of said images over a period of time, to extract effector cell and target cell features from said images, and to monitor effector cell mediated killing of the target cells.

[0014] In embodiments, the effector cell may be an immune cell. This allows monitoring immune cell killing activity.

[0015] In embodiments, the immune cell may be a T-cell. T-cells are a key component of the immune system involved in killing infected or cancerous cells.

[0016] In embodiments, the ratio of effector cell to target cell may be at most 10, e.g., from 1 to 10, for example, from 1:1 to 10:1; from 1:1 to 5:1; from 1:1 to 3:1; from 1:1 to 2:1; or from 1:1 to 3:2. For instance, the ratio may be 1:1; 3:2; 2:1; 3:1; 5:1; or 10:1. This provides an optimal balance for monitoring killing events. In embodiments, the number of target cells in a discrete confinement locations may be more than 1.

[0017] In embodiments, the confinement in the confinement locations may be achieved by electrical, optical, physical, or acoustic means. These techniques enable precise control over cell interactions.

[0018] In embodiments, the biological cell features may be selected from spatial features and temporal features. This provides comprehensive cell characterization.

[0019] In embodiments, the biological cell features may be selected from morphology, behaviors, and intra-cell activity. These features capture key aspects of cell state and activity.

[0020] In embodiments, the biological cell feature may be a biological cell morphology feature selected from static cell morphology features and dynamic cell morphology features. Morphology is a key indicator of cell state.

[0021] In embodiments, said static cell morphology features may be selected from cell size, circularity, nucleus / cell size ratio, and optical intensity contrast between different parts of the cell. These features enable quantitative cell morphology analysis.

[0022] In embodiments, said dynamic cell morphology feature may be selected from cell motility and changes in static cell morphology features. Dynamic features capture cell activity over time. In embodiments, the control unit is further configured to create time-lapse imaging data from said sequence. Time-lapse data enables monitoring cell interactions over time.

[0023] In embodiments, the control unit may be further configured to identify and track individual effector cells and target cells from said cell features. This enables analyzing interactions between specific cell pairs.

[0024] In embodiments, said effector cell and target cell features may be selected from static effector cell and target cell features and dynamic effector cell and target cell features. Both static and dynamic features are informative for interaction analysis.

[0025] In embodiments, said static effector cell and target cell features may be selected from cell size, circularity, nucleus / cell size ratio, and optical intensity contrast between different parts of cells. These enable quantitative analysis of cell state.

[0026] In embodiments, said dynamic effector cell and target cell features may be selected from cell motility and changes in static cell features. Dynamic features capture interaction-induced cell changes.

[0027] In embodiments, the control unit may be further configured to detect the interaction of said effector cell with said target cell from an evolution of said effector cell and target cell features in said sequence. Analyzing feature evolution enables detecting specific interaction events.

[0028] In embodiments, the control unit may be further configured to extract cell-cell interaction patterns between the effector cells and target cells from the evolution of cell features in said sequence. Interaction patterns provide a high-level view of cell behavior.

[0029] In embodiments, said interaction patterns may be selected from frequency of interaction, type of interaction, and extent of interaction. These patterns capture key aspects of cell-cell interactions.

[0030] In embodiments, said interaction patterns may comprise frequency and / or duration of effector cell conjugation with target cells. Conjugation is a good indicator in the killing process.

[0031] In embodiments, the control unit may be further configured to classify the effector cells based on their killing potency determined from the extracted cell features and / or cell-cell interaction patterns. This enables assessing the functional state of effector cells.

[0032] In embodiments, said classification of effector cell killing potency may be performed using one or more decision-making method selected from statistical classification techniques, decision trees, rule-based systems, Bayesian methods, ensemble methods, support vector machines, nearest neighbor, clustering techniques, dimensionality reduction techniques, amongst others, and preferably comprises a machine learning algorithm. Machine learning enables robust, data-driven classification. In embodiments, the control unit may be further configured to determine which extracted cell-cell interaction patterns between the effector cells and target cells are cell killing interaction patterns. This enables specifically identifying killing events.

[0033] In embodiments, the control unit may be further configured to detect changes in target cell features indicative of cell death resulting from effector cell mediated killing. Detecting death events is particularly advantageous for assessing killing efficacy.

[0034] In embodiments, the control unit may be further configured to quantify the proportion of killed target cells based on the detected feature changes to determine the killing efficacy of the effector cells. Quantifying killing enables comparing efficacy between samples.

[0035] In embodiments, the control unit may be configured to quantify the feature change in said target cell resulting from their interaction with the effector cells. This quantification can be achieved by comparing the sample of interest with appropriate positive and negative control samples. For instance, when assessing the killing potency of effector cells, the sample to be evaluated might consist of effector cells from a patient co-cultured with target cells expressing a specific antigen. The positive control sample would include effector cells from a healthy donor co-cultured with target cells expressing the same antigen, while the negative control would involve effector cells from the patient co-cultured with target cells lacking the antigen. The expected outcome would typically show the highest level of feature change in the positive control, followed by the sample being assessed, and the lowest change in the negative control. The control unit can then derive a relative value representing the magnitude of the feature change based on the comparison of these three values obtained from the sample of interest and the control samples.

[0036] In embodiments, the effector cells may be CAR-T cells. The system is particularly useful for assessing CAR-T function.

[0037] In embodiments, the plurality of discrete confinement locations may be an array of microcavities or the containment unit may comprise a microfluidic unit configured for forming an array of droplets, said microcavities or droplets being for containing the effector cells and target cells. Microfluidics enables high-throughput interaction monitoring.

[0038] In embodiments, said droplets may be aqueous droplets either in air or in oil. Aqueous droplets provide a physiological environment for cells.

[0039] In embodiments, the microfluidic device may be configured to establish different assay conditions or cell ratios in different microwells or droplets. This enables testing multiple conditions in parallel. In embodiments, the system may further comprise a fluidic control system for introducing or removing fluids from the containment unit. Fluidic control enables dynamic modulation of the assay environment.

[0040] In embodiments, the plurality of discrete locations may be at least 20, preferably at least 200. For instance, it can be from 200 to 2000. A larger number of discrete locations is also possible such as at least 2000, at least 20000, at least 200000, or even at least 500000. A large number of locations enables high-throughput analysis.

[0041] In embodiments, the lens-free imaging module may perform holographic imaging. Holographic imaging enables both 2D and 3D cell analysis. In embodiments, the lens-free imaging module may be configured to capture 2D or 3D images depicting all the effector cells and target cells within the containment unit. Preferably, it is configured t capture 3D images depicting all biological cells within the containment unit.

[0042] In embodiments, at least one image every 30 seconds, preferably at least one image every 20 seconds may be captured during said sequence. For instance, at least one image every 10 seconds or at least one image every 5 seconds may be captured. High temporal resolution enables detecting rapid interaction events.

[0043] In the second aspect, the present invention relates to a method for assessing effector cell mediated killing of target cells, the method comprising: a. Arranging effector cells and target cells so that they are simultaneously present in a plurality of discrete locations within a containment unit, thereby enabling effector cell-target cell interactions; b. Employing a lens-free imaging module to capture a plurality of images, wherein each image simultaneously depicts all effector cells and target cells arranged within the containment unit; d. Extracting effector cell and target cell features from said sequence; e. Analyzing the evolution of the extracted cell features to identify cell-cell interaction patterns indicative of effector cell mediated killing of target cells; and f. Determining the killing efficacy and / or potency of the effector cells based on the identified cell-cell interaction patterns.

[0044] In embodiments, step a may consist of arranging effector cells and target cells within the containment unit so that at least two different discrete confinement locations differing in their effector cell-target cell conditions have therein simultaneously at least one effector cell and one target cell. This enables comparing killing under different conditions. In embodiments, the different effector cell-target cell conditions may be different effector cell-target cell ratio, different effector cells, and or different target cells. These parameters significantly impact killing dynamics.

[0045] In embodiments, the number of target cells per containment unit may be one or more. In embodiments, a single target cell per containment unit is present. This is often advantageous. In other embodiments, more than one target cell is present per containment unit. This is advantageous for instance in serial killing assays.

[0046] In embodiments, the effector cells may be CAR-T cells and the method is used for assessing CAR-T potency. The method is particularly suited for CAR-T functional assessment.

[0047] In embodiments, determining the killing efficacy and potency may comprise quantifying the proportion of killed target cells based on detected changes in target cell features in the image sequence. Quantifying killing events enables robust potency determination.

[0048] In embodiments, the method may further comprise comparing the determined killing efficacy and potency of test effector cells to reference effector cells with known killing efficacy and potency. Comparison to references enables standardization across assays.

[0049] In the third aspect, the present invention relates to a computer program comprising instructions to cause the system of any embodiments of the first aspect to execute the steps of the method of any embodiments of the second aspect. The computer program enables automated control of the system to implement the method.

[0050] In the fourth aspect, the present invention relates to a computer-readable medium having stored thereon the computer program of the fourth aspect. The computer-readable medium enables convenient storage and distribution of the program.

[0051] It is an advantage of embodiments of the present invention that comprehensive monitoring of cell-cell interactions over time can be facilitated, allowing for a detailed characterization of cellular activities and interactions. Another advantage of embodiments of the present invention is that the integration of lens-free imaging technology permits the observation of a large number of cells simultaneously, which is advantageous for high-throughput cell assays and significantly reduces the complexity and cost associated with traditional imaging systems. Moreover, the use of lens-free imaging allows for monitoring a large number of events with high temporal resolution (e.g., every 10 seconds) due to its large field of view, which is not possible with classical lens-based microscopy. This high temporal resolution is particularly meaningful for capturing fast-paced cell-cell interactions, where features can change within a matter of seconds (e.g., every 30 seconds).

[0052] Moreover, it is an advantage of embodiments of the present invention that cells can be isolated in microfluidic compartments, enhancing the precision of cell assays by preventing cross- contamination and allowing for the study of individual cell interactions in a controlled environment. It is also an advantage that this setup supports the analysis of various cell types and their interactions without the need for labels, which simplifies the preparation process and avoids potential interference caused by labeling substances. Additionally, the ability to monitor cell morphology and interaction patterns continuously provides a robust dataset from which detailed analyses of cell function and behavior can be derived, enhancing the understanding of cellular mechanisms in a variety of research and clinical contexts.

[0053] Particular and preferred aspects of the invention are set out in the accompanying independent and dependent claims. Features from the dependent claims may be combined with features of the independent claims and with features of other dependent claims as appropriate and not merely as explicitly set out in the claims.

[0054] The above and other characteristics, features and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of the invention. This description is given for the sake of example only, without limiting the scope of the invention. The reference figures quoted below refer to the attached drawings.

[0055] Brief description of the drawings

[0056] Fig. 1 is a schematic view of two systems for monitoring effector cell mediated killing of target cells according to embodiments of the present invention.

[0057] Fig. 2 is a flowchart of the method according to embodiments of the second aspect.

[0058] Fig. 3 is a flowchart illustrating the software method for time-lapse cell-cell interaction characterizations according to embodiments of the present invention.

[0059] Fig. 4 is a diagram of an example of algorithm pipeline for analyzing cell-cell interaction patterns according to embodiments of the present invention.

[0060] Fig. 5 is a workflow diagram for a typical CAR-T potency assay using the system according to embodiments of the present invention.

[0061] Fig. 6 is a graph illustrating the determination of cell potency by killing efficacy measurements over time according to embodiments of the present invention.

[0062] In the different figures, the same reference signs refer to the same or analogous elements.

[0063] Detailed description of Illustrative Embodiments

[0064] The present invention will be described with respect to particular embodiments and with reference to certain drawings but the invention is not limited thereto but only by the claims. The drawings described are only schematic and are non-limiting. In the drawings, the size of some of the elements may be exaggerated and not drawn on scale for illustrative purposes. The dimensions and the relative dimensions do not correspond to actual reductions to practice of the invention.

[0065] The terms first, second, third and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a sequence, either temporally, spatially, in ranking or in any other manner. It is to be understood that the terms so used are interchangeable under appropriate circumstances and that the embodiments of the invention described herein are capable of operation in other sequences than described or illustrated herein.

[0066] Moreover, the terms top and over and the like in the description and the claims are used for descriptive purposes and not necessarily for describing relative positions. It is to be understood that the terms so used are interchangeable under appropriate circumstances and that the embodiments of the invention described herein are capable of operation in other orientations than described or illustrated herein.

[0067] It is to be noticed that the term "comprising", also used in the claims, should not be interpreted as being restricted to the means listed thereafter; it does not exclude other elements or steps. It is thus to be interpreted as specifying the presence of the stated features, integers, steps or components as referred to, but does not preclude the presence or addition of one or more other features, integers, steps or components, or groups thereof. Thus, the scope of the expression "a device comprising means A and B" should not be interpreted as being limited to devices consisting only of components A and B. It means that with respect to the present invention, the only relevant components of the device are A and B. The term "comprising" therefore covers the situation where only the stated features are present and the situation where these features and one or more other features are present. The word "comprising" according to the invention therefore also includes as one embodiment that no further components are present. When the word "comprising" is used to describe an embodiment in this application, it is to be understood that an alternative version of the same embodiment, wherein the term "comprising" is replaced by "consisting of", is also encompassed within the scope of the present invention.

[0068] Similarly, it is to be noticed that the term "coupled" should not be interpreted as being restricted to direct connections only. The terms "coupled" and "connected", along with their derivatives, may be used. It should be understood that these terms are not intended as synonyms for each other. Thus, the scope of the expression "a device A coupled to a device B" should not be limited to devices or systems wherein an output of device A is directly connected to an input of device B. It means that there exists a path between an output of A and an input of B which may be a path including other devices or means. "Coupled" may mean that two or more elements are either in direct physical or electrical contact, or that two or more elements are not in direct contact with each other but yet still co-operate or interact with each other.

[0069] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to one of ordinary skill in the art from this disclosure, in one or more embodiments.

[0070] Similarly it should be appreciated that in the description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

[0071] Furthermore, while some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention, and form different embodiments, as would be understood by those in the art. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0072] Furthermore, some of the embodiments are described herein as a method or combination of elements of a method that can be implemented by a processor of a computer system or by other means of carrying out the function. Thus, a processor with the necessary instructions for carrying out such a method or element of a method forms a means for carrying out the method or element of a method. Furthermore, an element described herein of an apparatus embodiment is an example of a means for carrying out the function performed by the element for the purpose of carrying out the invention.

[0073] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description. The following terms are provided solely to aid in the understanding of the invention.

[0074] As used herein, and unless otherwise specified, the term "effector cell" refers to a cell capable of mediating the killing of target cells, such as immune cells, including but not limited to T- cells, natural killer (NK) cells, macrophages, and neutrophils.

[0075] As used herein, and unless otherwise specified, the term "target cell" refers to a cell that can be killed by an effector cell, such as tumor cells, infected cells, or any other cell type that is targeted for elimination by the immune system.

[0076] As used herein, and unless otherwise specified, the term "containment unit" refers to a device or apparatus capable of holding and confining cells in discrete locations, such as a microfluidic device, a multi-well plate, or an array of microcavities or droplets.

[0077] As used herein, and unless otherwise specified, the term "confinement location" refers to a discrete region within the containment unit where cells are held and confined, such as a microwell, a microcavity, or a droplet. In embodiments, the microwell or microcavity may have a width of from 5 to 500 pm and an height to width ratio of from 1 to 2.

[0078] As used herein, and unless otherwise specified, the term "lens-free imaging module" refers to an imaging device capable of capturing images without the use of a conventional lens, such as a holographic imaging system or a shadow imaging system. Holographic imaging systems are preferred.

[0079] As used herein, and unless otherwise specified, the term "cell features" refers to characteristics or properties of cells that can be extracted from images, such as morphological features (e.g., cell size, shape, nucleus / cell size ratio), behavioral features (e.g., motility, interactions with other cells), and intracellular features (e.g., protein expression, organelle distribution).

[0080] As used herein, and unless otherwise specified, the term "cell-cell interaction patterns" refers to characteristic behaviors or events that occur between cells, such as the frequency, duration, or type of contact between an effector cell and a target cell, which may be indicative of cell killing or other cellular processes.

[0081] As used herein, and unless otherwise specified, the term "killing efficacy" refers to the ability of effector cells to successfully kill target cells, which can be quantified by the proportion of target cells that are killed within a given time period.

[0082] As used herein, and unless otherwise specified, the term "killing potency" refers to the relative strength or effectiveness of effector cells in killing target cells, which can be determined by comparing the killing efficacy of different effector cell populations or by evaluating the cell-cell interaction patterns associated with successful killing events. Typically, the killing potency is assessed by comparing the killing efficacy of the sample effector cells with positive and negative control samples. For example, the sample to be assessed might consist of CD19+ CAR-T cells from a patient co-cultured with CD19+ tumor cells. The positive control sample would include CD19+ CAR-T cells from a healthy donor co-cultured with CD19+ tumor cells, while the negative control would involve CD19+ CAR-T cells from the patient co-cultured with CD19- tumor cells. The expected killing efficacy is usually as follow: positive control > sample to be assessed > negative control. The killing potency is a relative value derived from the comparison of these three killing efficacy values, providing a measure of the effector cells' ability to eliminate target cells effectively.

[0083] As used herein, and unless otherwise specified, the term "control unit" refers to a device or system capable of controlling the operation of the lens-free imaging module and processing the captured images to extract biological cell features. The control unit can be a computer, a microcontroller, or any other suitable processing device. Examples of control units include personal computers, embedded systems, and dedicated image processing units. The control unit must be configured to operate the lens-free imaging unit so that it captures a sequence of said images over a period of time, and it extracts biological cell features from said images.

[0084] The invention will now be described by a detailed description of several embodiments of the invention. It is clear that other embodiments of the invention can be configured according to the knowledge of persons skilled in the art without departing from the technical teaching of the invention, the invention being limited only by the terms of the appended claims.

[0085] We now refer to Fig. 1, which shows a schematic view of systems (1) for monitoring effector cell (3) mediated killing of target cells (2). A typical setup comprises a lens-free imaging (LFI) system with a light source and one or multiple imagers, and a fluidic device configured to allow LFI and provide compartments for cell confinement. The use of LFI allows massively parallel monitoring of many cell-cell interaction events with a large field of view and high time resolution, while cell encapsulation in isolated compartments enables heterogeneous assays and prevents cell aggregate formation.

[0086] Each system (1) comprises a containment unit (100) with a plurality of discrete confinement locations (110). The containment unit (100) is adapted to hold simultaneously at least one effector cell (3) and at least one target cell (2) per confinement location (110), with at least one effector cell (3) and at least one target cell (2) present in one of the confinement locations (110).

[0087] In embodiments, the confinement locations (110) may be microdroplets in air or oil, as shown in Fig. 1(a). In other embodiments, the confinement locations (110) may be microwells formed by micromachining or microfabrication, as shown in Fig. 1(b). The effector cells (3) and target cells (2) are distributed in the confinement locations (110) either deterministically or randomly, with at least the two cell types confined in at least some of the locations for cell-cell interaction monitoring.

[0088] The system (1) also includes a lens-free imaging module (120) for capturing images, each image depicting all the effector cells (3) and target cells (2) within the containment unit (100). In embodiments, the lens-free imaging module (120) may perform holographic imaging to enable 3D cell analysis. A control unit (130) is configured to operate the lens-free imaging module (120) to capture a sequence of said images over a period of time, to extract effector cell (3) and target cell (2) features from said images, and to monitor effector cell (3) mediated killing of the target cells (2). In embodiments, at least one image may be captured every 30 seconds, preferably at least every 20 seconds, during the image sequence to provide high temporal resolution for detecting rapid interaction events.

[0089] We now refer to Fig. 2, which presents a flowchart illustrating the method according to the second aspect. It shows the main steps in a method for assessing effector cell (3) mediated killing of target cells (2), the method comprising: a. Arranging effector cells (3) and target cells (2) so that they are simultaneously present in a plurality of discrete locations (110) within a containment unit (100), thereby enabling effector celltarget cell interactions; b. Employing a lens-free imaging module (120) to capture a plurality of images, wherein each image simultaneously depicts all effector cells (3) and target cells (2) arranged within the containment unit (100); d. Extracting effector cell (3) and target cell (2) features from said sequence; e. Analyzing the evolution of the extracted cell features to identify cell-cell interaction patterns indicative of effector cell (3) mediated killing of target cells (2); and f. Determining the killing efficacy and / or potency of the effector cells (3) based on the identified cell-cell interaction patterns.

[0090] We now refer to Fig. 3, which presents a flowchart illustrating a software method for timelapse cell-cell interaction characterizations. The method involves identifying and tracking cells per time frame, with each identified cell given a cell identifier (ID). The same cell ID is assigned to the same cell across adjacent images in time.

[0091] Cell features are extracted for each cell, e.g., for both tumor cells and CAR-T cells, including static features such as cell size, circularity, nucleus / cell size ratio, and optical intensity contrast between different parts of cells, as well as dynamic features like cell motility. In embodiments, the biological cell features may be selected from spatial features and temporal features to provide comprehensive cell characterization, including morphology, behaviors, and intra-cell activity to capture key aspects of cell state and activity.

[0092] Cell-cell interaction patterns are also extracted, describing how cells of interest interact with each other, such as frequency and extent of cell conjugation. In embodiments, the cell-cell interaction patterns extracted may comprise frequency and / or duration of effector cell conjugation with target cells, as conjugation is a typical step in the killing process. In the case of CAR-T - tumor cell interactions, this may comprise one or more of the following: interaction frequency with tumor cells, engagement duration (between merging and departing), aggregation frequency, aggregate size, fused CART-T -tumor aggregate size variation (expansion, shrinkage), amongst others. In embodiments, each cell-cell interaction may be given an event ID and followed over time.

[0093] The cell features from multiple time frames are compared for each cell and event to characterize the cells and cell-cell interactions. The statistics of one or multiple events are used to characterize the sample, such as determining CAR-T potency based on the percentage of tumor cell death. In embodiments, the control unit (130) may be further configured to classify the effector cells (3) based on their killing potency determined from the extracted cell features and / or cell-cell interaction patterns to assess the functional state of effector cells. In embodiments, the control unit (130) may be further configured to detect changes in target cell (2) features indicative of cell death resulting from effector cell (3) mediated killing and quantify the proportion of killed target cells (2) to determine the killing efficacy of the effector cells (3).

[0094] We now refer to Fig. 4, which shows a diagram of an example of algorithm pipeline for analyzing cell-cell interaction patterns. The pipeline starts with a hologram captured by the lens-free imaging module (120). The hologram is processed to detect droplets within the containment unit (100). If a droplet moves, the pipeline performs droplet tracking to follow the movement of the droplet over time. Multi-depths recognition is then performed using auto-focusing to identify objects at different depths within each droplet, including debris.

[0095] Object detection is performed to detect and locate individual cells within each droplet. Segmentation is then performed to delineate the boundaries of each detected cell. Then, cell feature extraction is performed to extract various features of each segmented cell, such as morphology, behaviors, and intra-cell activity.

[0096] Then, in the early frames, the pipeline identifies the class and status of each object, such as tumor cells that are alive, dead, or debris, as well as active or inactive / dead CAR-T cells and other unknown objects.

[0097] Across all frames, the pipeline tracks all objects and their features / type / status information to analyze the cell-cell interactions over time. This enables killing analysis to determine the potency of the CAR-T cells based on the proportion of tumor cells killed and eventually other interaction dynamics observed in the time-lapse data.

[0098] We now refer to Fig. 5, which illustrates a typical workflow for a CAR-T potency assay using the system (1). CAR-T cells from the product are encapsulated with tumor cells in droplets or microwells at stochastic or controlled ratios. The CAR-T and tumor cell interactions are monitored by LFI, measuring cell feature changes to derive the CAR-T cell killing efficacy. This process can be repeated for positive and negative control samples with standard CAR-T cells and non-CAR-T cells, respectively, using the same tumor cell line. The cell killing efficacy from all these samples may be compared to determine the potency of the CAR-T product. In embodiments, the method may further comprise comparing the determined killing efficacy and potency of test effector cells (3) to reference effector cells with known killing efficacy and potency to enable standardization across assays.

[0099] We now refer to Fig. 6, which shows a graph of the killing efficacy over time, illustrating the determination of cell potency by killing efficacy measurements. The killing efficacy of the test CAR-T cells is compared to that of the positive and negative control samples to assess the potency of the CAR-T product. The cell mixing and droplet generation confines the effector cells (3) and target cells (2) in the discrete locations (110). Image processing of the time-lapse LFI image sequence and killing efficacy determination based on the evolution of cell features and interaction patterns provides a quantitative potency assessment. As the graph shows, the method of the invention is much faster for determining cell potency than the method of the prior art.

[0100] Example 1: Massive Cell Characterizations by Time-Lapse Cell-Cell Interaction Monitoring in droplets

[0101] The invention aims to develop a method for accurately characterizing cells by monitoring cell-cell interactions over time, overcoming the limitations of snapshot imaging approaches. The significance of this invention lies in part in its potential applications for cell therapy, such as CAR-T cell characterization, where monitoring the tumor cell killing process by CAR-T cells is very advantageous for quality control during cell manufacturing and assay optimizations in the CAR-T product development.

[0102] The materials and equipment used in this example include a lens-free imaging (LFI) system comprising of a light source and one or multiple imagers, and a containment unit comprising a microfluidic unit configured for forming on a substrate an array of droplets for containing cells. The fluidic device is configured with a sufficiently transparent substrate to allow LFI to work. The confinement locations are either micro droplets in air or oil. The cells to be characterized are distributed in the droplets either deterministically or randomly, with at least two types of cells confined in some of the droplets for cell-cell interaction assays. The experimental setup involves encapsulating the cells of interest, such as CAR-T cells and tumor cells, in the droplets of the fluidic device. The cell-cell interaction events are then continuously monitored using the LFI system. The time-lapse method involves identifying and tracking cells per time frame, extracting cell morphology features and cell-cell interaction patterns, and comparing the cell features from multiple time frames to characterize the cells and events accordingly.

[0103] The results of this experiment demonstrate the effectiveness of using time-lapse data to characterize cells. By synthesizing data from multiple time points, comprehensive information about the entire cell activity process is acquired without missing any crucial details. This approach drastically improves cell characterization accuracy compared to snapshot imaging methods. Moreover, it enables the prediction of cell activity and character based on early phase data, without the need to complete the entire process.

[0104] The analysis of the findings can reveal several innovative aspects of this invention. First, the use of LFI allows massively parallel monitoring of many cell-cell interaction events, which would be challenging and expensive with conventional optics. Second, LFI enables high time resolution imaging, very advantageous for capturing fast cellular events such as cell killing. Third, the segmentation of cells in isolated droplets allows for heterogeneous assays and prevents cell aggregate formation, facilitating the identification and tracking of individual cells.

[0105] The implications of this example are significant in the context of cell therapy and drug development. By providing a label-free, accurate, and efficient method for characterizing cell-cell interactions, this example shows that the invention can greatly enhance the quality control processes in CAR-T cell manufacturing and other cell-based therapies, thus allowing more timely product delivery and therapy to save the patient life. The ability to predict cell potency based on early phase data can also accelerate the development and optimization of these therapies.

[0106] Example 2: Advanced Cell Characterizations by Time-Lapse Cell-Cell Interaction Monitoring in Microwells

[0107] This example builds on Example 1 by utilizing an array of microwells created through micromachining or microfabrication instead of droplets. The goal remains to accurately characterize cells by monitoring cell-cell interactions over time, with applications in cell therapy, particularly CAR- T cell characterization.

[0108] The materials and equipment include a lens-free imaging (LFI) system and a microfluidic unit with transparent microwells for containing cells. The microwells confine the cells in a controlled environment, enabling precise monitoring of interactions. The experimental setup involves encapsulating cells, such as CAR-T cells and tumor cells, in the microwells. Continuous monitoring using the LFI system allows for the identification and tracking of cells over time. The method extracts cell morphology features and interaction patterns, improving characterization accuracy compared to snapshot imaging.

[0109] Key advantages of this approach include massively parallel monitoring, high time resolution imaging for capturing fast events, and prevention of cell aggregate formation by isolating cells in microwells. These benefits are similar to those discussed in Example 1.

[0110] This method enhances quality control in CAR-T cell manufacturing and other cell-based therapies by providing a label-free, accurate, and efficient means of characterizing cell interactions. Early phase data can predict cell potency, accelerating therapy development and optimization, thus improving patient outcomes.

[0111] Example 3: Evaluating the Efficacy of Engineered T Cells Using Dynamic Cell-Cell Interaction Analysis

[0112] In this example, the system is employed to evaluate the efficacy of engineered T cells, such as T cells expressing a chimeric antigen receptor (CAR), in killing target cells. The containment unit consists of a microfluidic device capable of generating an array of 1,000 aqueous droplets in oil. Each droplet encapsulates engineered T cells and target cells at different ratios, ranging from 1:1 to 5:1.

[0113] The lens-free imaging module captures an image of the droplet array every 20 seconds for a duration of 4 hours (1 hour already deliver very useful results). The control unit analyzes the image sequence to extract cell features and identify cell-cell interaction patterns. It focuses on dynamic features such as cell motility and changes in cell morphology over time. The frequency and duration of T cell conjugation with target cells are also measured.

[0114] By comparing the cell-cell interaction patterns across droplets with different effector-to- target cell ratios, the control unit assesses the dose-dependent efficacy of the engineered T cells. It identifies the minimum ratio at which significant target cell killing is observed, providing insights into the potency of the engineered T cells. This dynamic analysis of cell-cell interactions enables a comprehensive evaluation of T cell efficacy.

[0115] Example 4: Classifying Effector Cells Based on Their Killing Potency Using Machine Learning

[0116] In this example, the system is used to classify effector cells based on their killing potency using machine learning algorithms. The containment unit comprises a microfluidic device with 5,000 microcavities, each containing a single effector cell and a single target cell. The effector cells are derived from different donors or have undergone different manufacturing processes.

[0117] The lens-free imaging module captures an image of the microcavity array every 30 seconds for a duration of 8 hours. The control unit extracts cell features and cell-cell interaction patterns from the image sequence. It quantifies parameters such as the frequency and duration of effector cell conjugation with target cells, changes in target cell morphology, and the proportion of killed target cells.

[0118] These parameters serve as input features for a machine learning algorithm, such as a support vector machine or a neural network. The algorithm is trained on a dataset of effector cells with known killing potency, using the extracted features as predictors and the potency as the target variable. Once trained, the algorithm can classify new effector cells into different potency categories based on their cell-cell interaction patterns.

[0119] This machine learning-based approach enables the automated and objective classification of effector cells, facilitating the selection of highly potent cells for therapeutic applications. The method also helps classify and quantify the actual CAR-T cells from the non-CAR-T cells which are substantially present in the CAR-T cell population (e.g. 50%) due to today's cell engineering technology limitations. It also allows for the identification of critical cell-cell interaction patterns that are predictive of killing potency, providing valuable insights into the mechanisms of effector cell function.

[0120] Example 5: Monitoring Effector Cell-Mediated Killing of Target Cells in a High-Throughput Manner

[0121] In this example, the system is used to monitor the killing of tumor cells by natural killer (NK) cells in a high-throughput manner. The containment unit comprises a microfluidic device with an array of 10,000 microwells. In some embodiments, the microfluidic device has an array of at least 10,000 microwells, or even at least 100,000 microwells. Each microwell is loaded with a single NK cell and a single tumor cell, achieving a 1:1 effector-to-target cell ratio. In some embodiments, the effector-to-target cell ratio can be more than 1:1, such as from 1:1 to 3:2; from 1:1 to 2:1; from 1:1 to 3:1; from 1:1 to 5:1 or from 1:1 to 10:1. The lens-free imaging module captures an image of the entire microwell array every 15 seconds for a duration of 6 hours (1 hour already provides meaningful results).

[0122] The control unit processes the image sequence to extract NK cell and tumor cell features. It tracks the morphology changes of each cell over time, specifically focusing on cell size, circularity, and optical intensity contrast. The evolution of these features is analyzed to identify cell-cell interaction patterns indicative of NK cell-mediated killing of tumor cells. For instance, a rapid decrease in tumor cell size and circularity, accompanied by an increase in optical intensity contrast, suggests cell death. Another example is the frequency and duration of NK cell engagement and disengagement with tumor cells. By quantifying the proportion of tumor cells exhibiting these morphological changes, the control unit determines the killing efficacy of the NK cells. This high-throughput approach allows for the simultaneous assessment of thousands of NK cell-tumor cell interactions, providing a statistically robust measure of NK cell potency.

[0123] It is to be understood that although preferred embodiments, specific constructions and configurations, as well as materials, have been discussed herein for devices according to the present invention, various changes or modifications in form and detail may be made without departing from the scope of this invention. For example, any formulas given above are merely representative of procedures that may be used. Functionality may be added or deleted from the block diagrams and operations may be interchanged among functional blocks. Steps may be added or deleted to methods described within the scope of the present invention.

Claims

Claims1. A system (1) for monitoring effector cell (3) mediated killing of target cells (2), comprising:- a containment unit (100) comprising a plurality of discrete confinement locations (110), the containment unit (100) being adapted to hold simultaneously at least one effector cell (3) and at least one target cell (2) per confinement location (110), the containment unit (100) comprising at least one effector cell (3) and at least one target cell (2) in one of the confinement locations (110);- a lens-free imaging module (120) for capturing images, each image depicting all the effector cells (3) and target cells (2) within the containment unit (100); and- a control unit (130) configured to operate the lens-free imaging module (120) to capture a sequence of said images over a period of time, to extract effector cell (3) and target cell (2) features from said images, and to monitor effector cell (3) mediated killing of the target cells (2).

2. The system (1) according to claim 1, wherein the control unit (130) is further configured to create time-lapse imaging data from said sequence.

3. The system (1) according to claim 1 or 2, wherein the control unit (130) is further configured to identify and track individual effector cells (3) and target cells (2) from said cell features.

4. The system (1) according to claim 3, wherein the control unit (130) is further configured to extract cell-cell interaction patterns between the effector cells (3) and target cells (2) from the evolution of cell features in said sequence.

5. The system (1) according to any one of the preceding claims, wherein the control unit (130) is further configured to classify the effector cells (3) based on their killing potency determined from the extracted cell features and / or cell-cell interaction patterns.

6. The system (1) according to any one of the preceding claims, wherein the control unit (130) is further configured to detect changes in target cell (2) features indicative of cell death resulting from effector cell (3) mediated killing.

7. The system (1) according to any one of the preceding claims, wherein the containment unit (100) comprises a microfluidic unit (200) comprising either an array of microcavities (210) or being configured for forming an array of droplets (220), said microcavities (210) or droplets (220) being for containing the effector cells (3) and target cells (2).

8. The system (1) according to claim 7, wherein the microfluidic unit is configured to establish different assay conditions or cell ratios in different microwells or droplets (220).

9. The system (1) according to any one of the preceding claims, further comprising a fluidic control system (1) for introducing or removing fluids from the containment unit (100).

10. The system (1) according to any one of the preceding claims, wherein the lens-free imaging module (120) performs holographic imaging.

11. A method for assessing effector cell (3) mediated killing of target cells (2), the method comprising: a. Arranging effector cells (3) and target cells (2) so that they are simultaneously present in a plurality of discrete locations (110) within a containment unit (100), thereby enabling effector celltarget cell interactions; b. Employing a lens-free imaging module (120) to capture a plurality of images, wherein each image simultaneously depicts all effector cells (3) and target cells (2) arranged within the containment unit (100); d. Extracting effector cell (3) and target cell (2) features from said sequence; e. Analyzing the evolution of the extracted cell features to identify cell-cell interaction patterns indicative of effector cell (3) mediated killing of target cells (2); and f. Determining the killing efficacy and / or potency of the effector cells (3) based on the identified cell-cell interaction patterns.

12. The method according to claim 11, wherein step a consists of arranging effector cells (3) and target cells (2) within the containment unit (100) so that at least two different discreteconfinement locations (110) differing in their effector cell-target cell conditions have therein simultaneously at least one effector cell (3) and one target cell (2).

13. The method according to claim 12, wherein the different effector cell-target cell conditions are different effector cell-target cell ratio, different effector cells, and or different target cells.

14. The method according to claim 13, wherein the effector cells (3) are CAR-T cells and the method is used for assessing CAR-T potency.

15. The method according to claim 13 or 14, wherein determining the killing efficacy and potency comprises quantifying the proportion of killed target cells (2) based on detected changes in target cell (2) features in the image sequence.

16. A computer program comprising instructions to cause the system (1) of any one of claims1 to 10 to execute the steps of the method of any one of claim 11 to 15.

17. A computer-readable medium having stored thereon the computer program of claim 16.

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