Methods and systems for identifying, selecting and collecting analytes, such as cells, in a sample fluid - Patents.com

Abstract

A method for characterizing analytes, such as cells, in a sample fluid includes the steps of passing a sample fluid including a first type of analyte and a second type of analyte along a flow path through a fluidic channel, analyzing the first type of analyte and the second type of analyte in the sample fluid in a first analysis unit including a fluidic channel, thereby obtaining first parameter values ​​of analyte characteristics for the first type of analyte and the second type of analyte, storing the first parameter values ​​of the analyte characteristics in a processing unit, and further characterizing analyte characteristics for the first type of analyte by the second type of analyte. the step of comparing and changing the first and second analyte characteristics with a further analyte characteristic of the object; analyzing the first and second analyte types in the sample fluid in a second analysis unit including a fluid channel, thereby obtaining second parameter values ​​of analyte characteristics for the first and second analyte types; storing the second parameter values ​​of the analyte characteristics in the processing unit; and characterizing the first and second analyte types by comparing the second parameter values ​​with the first parameter values ​​in the processing unit.

Description

[Technical field]

[0001] This disclosure relates to methods and microfluidic system platforms used to characterize (identify), enumerate, classify, sort, and extract / collect target particles / cell populations in suspension, such as rare cells circulating in bodily fluids such as blood. This disclosure focuses primarily on circulating tumor cells (CTCs), but can be used for any analyte or rare cell population, such as circulating endothelial cells (CECs), circulating melanoma cells (CMCs), circulating hybrid cells (CHCs), etc. [Background technology]

[0002] According to the WHO, cancer is the second leading cause of death in the world, causing approximately 10 million deaths in 2020. Globally, approximately one in six deaths is due to cancer. There were approximately 20 million new cases of cancer worldwide in 2020, and this number is expected to reach approximately 30 million by 2040, resulting in 16 million deaths (Source: WHO IARC Globocan 2020).

[0003] Cancer is a fatal disease, but it is not the primary tumor that causes death, but the metastasis of cancer. 90% of cancer-related deaths are due to metastasis, so rapid identification of this process is crucial for cancer treatment. CTCs are the most powerful biomarkers of metastasis. CTCs detach from the primary tumor, enter the bloodstream, and eventually create secondary tumors at other sites. Because CTCs can form new tumors in other tissues, detecting CTCs in the blood is crucial for assessing the progression of metastasis, guiding treatment, and testing and developing drugs. Early diagnosis of metastasis is paramount to improve survival rates and shorten treatment times. In addition to diagnosis and prognosis, recurrence monitoring is also possible by detecting dormant CTCs in the blood.

[0004] Routine real-time assessment of CTCs in a non-invasive manner in metastatic cancer patients is crucial to assess the efficacy of treatment. CTC collection is potentially feasible through liquid biopsy, which involves drawing a few mL of blood from a patient and examining the blood sample for traces of cancer. Liquid biopsy is minimally invasive and has many advantages over solid biopsy, which involves surgically harvesting tumor tissue. However, recovery of CTCs remains a major challenge. While there are billions of peripheral blood cells in 1 mL of blood, there are only 1–10 CTCs. The extreme rarity and inherent heterogeneity of CTCs necessitates a highly sensitive, target-specific, and high-throughput system. Summary of the Invention [Problem to be solved by the invention]

[0005] The purpose of this disclosure is to provide a technical solution to the above problems. [Means for solving the problem]

[0006] According to a first embodiment of the present disclosure, a method for characterizing analytes, e.g. cells, in a sample fluid is proposed, the method comprising the steps of: passing a sample fluid containing a first type of analyte and a second type of analyte along a flow path through a fluidic channel, analyzing the first type of analytes and the second type of analyte in the sample fluid in a first analysis unit containing the fluidic channel, thereby obtaining first parameter values ​​of an analyte characteristic for the first type of analyte and the second type of analyte, and storing the first parameter values ​​of the analyte characteristic in a processing unit.

[0007] The exemplary method may further include varying a further analyte characteristic for the first type of analyte compared to a further analyte characteristic for the second type of analyte, and analyzing the first type of analyte and the second type of analyte in the sample fluid in a second analysis unit including a fluid channel, thereby obtaining second parameter values ​​of the analyte characteristic for the first type of analyte and the second type of analyte.

[0008] The exemplary method may further include storing, in the processing unit, a second parameter value of the analyte characteristic, and characterizing, in the processing unit, the first type of analyte and the second type of analyte by comparing the second parameter value to the first parameter value.

[0009] This allows for an in-line method that allows for characterization of analytes from other analytes, and in particular, very rare cells or analytes, referred to herein as second type analytes, can be effectively identified from peripheral blood cells, etc., referred to herein as first type analytes.

[0010] According to one example of a method of the present disclosure, altering a property of the further analyte may include exposing the first type of analyte and the second type of analyte to an electric field in a device including a fluid channel.

[0011] In some embodiments, the method according to the present disclosure may further comprise: separating the first type of analytes and the second type of analytes in a separation unit attached to the fluid channel using the altered further analyte property of the first type of analytes based on the characterization in the processing unit, and using the altered further analyte property of the first type of analytes, thereby allowing the separation of peripheral cells (first type of analytes) from the sample fluid, and also the efficient separation and analysis of rare cells and second type of analytes for further studies.

[0012] The step of separating the first and second types of analytes may include applying an electric field to the sample fluid and using the electric field to divert the second type of analytes from the flow path. Additionally or alternatively, a valve may be used. The valve may then be repositioned to direct the flow to a desired outlet to divert the second type of analytes from the flow path. After separating the first and second types of analytes, the second type of analytes may be collected in a collection reservoir.

[0013] Additionally, further embodiments of the method according to the present disclosure may include separating at least the first and second types of analytes based on analyte size, which provides a pre-selection of the analytes in the sample fluid and further improves the efficiency and accuracy of the characterization and separation steps of the method.

[0014] Because the methods according to the present disclosure process large amounts of data, the step of characterizing the first type of analyte from the second type of analyte is preferably performed using one or more machine learning algorithms.

[0015] Furthermore, one or more of the analysis steps of methods according to some embodiments of the present disclosure may include electrical impedance spectroscopy (EIS), in particular multi-frequency electrical impedance spectroscopy.

[0016] According to one example of the present disclosure, the step of altering the further analyte property may include altering the membrane of the analyte or inducing mechanical cell deformation. The further analyte property may be the electrical impedance response of the analyte. In particular, if the altering step includes charging and / or electroporation of the outer membrane and the further analyte property is the electrical property of the analyte membrane, one of the analyte types may be effectively tagged for characterization, particularly identification.

[0017] Advantageously, the method according to the present disclosure may include the step of optically sensing a sensing region of the fluid channel.

[0018] According to another embodiment of the present disclosure, a method for characterization of analytes, e.g. cellular analytes, in a sample fluid is proposed, comprising simultaneously carrying out one or more steps of any of the aforementioned methods in a plurality of different characterization lines, which may receive analytes, e.g. sorted by size, during a first step of separating the analytes in the sample fluid into different of the plurality of characterization lines.

[0019] An example of a system for characterizing analytes, e.g. cells, in a sample fluid according to the present disclosure includes at least one characterization line, the line including a fluid channel defining a flow path having an inlet and an outlet, the fluid channel being configured to allow a sample fluid containing a first type of analyte and a second type of analyte to pass along the flow path between the inlet and the outlet, as viewed in the flow path direction. Between the inlet and the outlet, as viewed in the flow path direction, a number of units may be implemented for performing processing steps on the sample fluid, in particular on the first and second types of analytes.

[0020] A first exemplary analysis unit includes a fluid channel and is configured to analyze a first type of analyte and a second type of analyte in a sample fluid and obtain first parameter values ​​of analyte characteristics for the first type of analyte and the second type of analyte.

[0021] The modification unit comprises a fluid channel downstream of the first analysis unit. It is configured to modify a further analyte property of the first type of analyte compared to a further analyte property of the second type of analyte. In one embodiment, the modification unit may comprise an electric field generating unit. The electric field generating unit exposes the first type of analyte and the second type of analyte in the sample fluid to an electric field, thereby modifying the further analyte property of the first type of analyte compared to the further analyte property of the second type of analyte. In particular, the modification unit may modify a membrane or cause mechanical cell deformation of the analyte. The further analyte property may be an electrical impedance response.

[0022] A second analysis unit may be provided comprising a fluidic channel downstream from the modification unit, the second analysis unit configured to analyze the first type of analytes and the second type of analytes in the sample fluid and to obtain second parameter values ​​of the analyte characteristic for the first type of analytes and the second type of analytes.

[0023] The large amount of data is processed by a processing unit configured to obtain and store the first and second parameter values ​​from the first and second analytical units, and characterize the first type of analyte from the second type of analyte by comparing the second parameter values ​​to the first parameter values.

[0024] This allows for an in-line method that allows for characterization of analytes from other analytes, and in particular, very rare cells or analytes, referred to herein as second type analytes, can be effectively identified from peripheral blood cells, etc., referred to herein as first type analytes.

[0025] Moreover, an example of the system according to the present disclosure may further include a separation unit downstream of the second analysis unit, the separation unit including a fluidic channel, for separating the first type of analytes from the second type of analytes using the altered further analyte property of the first type of analytes based on the characterization signal generated and output by the processing unit.

[0026] By separating the first type of analytes from the sample fluid, the second type of analytes can also be efficiently separated and collected. For example, the separation unit may include an electric field generating unit that applies an electric field to the sample fluid upon receiving an activation signal from the processing unit to divert the second type of analytes from the flow path for collection thereof. Thus, exemplary embodiments of the system may include, for example, a collection unit that collects the second type of analytes. Some exemplary separation units may include a valve unit that diverts the second type of analytes from the flow path.

[0027] To further improve the efficiency and accuracy of characterization and separation of multiple types of analytes, the system according to the present disclosure may further comprise a sorting unit including a fluidic channel upstream from the first analytical unit, which may sort the first type of analytes and the second type of analytes based on analyte size.

[0028] In a further advantageous embodiment, to achieve improved processing of large amounts of data, the processing unit may execute a machine learning algorithm to characterize analytes of a first type from analytes of a second type.

[0029] Preferably, the first and second analysis units may comprise Electrical Impedance Spectroscopy (EIS) means, in particular Multi-frequency Electrical Impedance Spectroscopy means.Furthermore, the microfluidic device may be adapted to charge and / or electroporate the membrane of the first type of analyte.

[0030] Exemplary embodiments of the present disclosure may also further comprise an optical sensing unit for optically sensing the sensing region of the fluid channel.

[0031] Another embodiment of the present disclosure is a platform for characterization of analytes, e.g., cellular analytes, in a sample fluid, comprising the system described above, including different characterization lines, the system further comprising a sorting device arranged upstream from the system, for sorting analytes in the sample fluid to different characterization lines of the system. [Brief description of the drawings]

[0032] The present invention will now be described with reference to the drawings. [Figure 1] FIG. 1 illustrates a workflow of a platform or system according to the present disclosure. [Diagram 2] FIG. 1 illustrates the operating principle of a platform or system according to the present disclosure. [Diagram 3] FIG. 1 illustrates the physical parameters measured in multi-frequency and multi-parameter electrical impedance measurements of cells for tumor cell discrimination. [Figure 4] FIG. 1 shows raw data from multifrequency measurements of tumor cells, leukocytes, and clusters of tumor cells and leukocytes. [Diagram 5] FIG. 1 illustrates a method according to the present disclosure that combines electrical detection and modification to tag peripheral blood cells to maximize the specificity of detection. [Figure 6] 1 is a schematic diagram illustrating an example of a microfluidic device according to the present disclosure and a measurement method according to the present disclosure. [Figure 7] 7a and 7b are schematic diagrams of another example of a microfluidic device according to the present disclosure. [Figure 8] 8a and 8b show examples of downstream separation units. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0033] For a proper understanding of the present disclosure, in the following detailed description, corresponding elements or portions of the present disclosure are designated with the same reference numerals in the drawings.

[0034] The technology according to the present disclosure is designed for the detection, enumeration, purification, and collection of tumor cells. The design is formed of a versatile microelectrofluidic system (MEFS) based on fast and sensitive electrical impedance measurements, with the option to couple to optical systems to expand the capabilities such as real-time characterization. Techniques and devices for real-time characterization are described in the applicant's other PCT application filed concurrently with this application, which claims priority to Dutch application No. 2030787 entitled "A microfluidic device for detecting and characterizing at least one analyte, for example a cell, in a sample fluid", filed on January 31, 2022, the disclosure of which is incorporated herein by reference.

[0035] FIG. 1 illustrates a system level design of an example of a platform according to the present disclosure. On-chip dilution is applied to the blood sample before size-based pre-sorting. This first sorting step, performed in the sorting unit 2, is not for rejection but for size-based sorting and for parallelization. The output of the sorting unit 2 includes multiple fluidic channels containing analytes sorted by size designated as largest size, smaller size, ..., smallest size. The cells (generally analytes) of one or more, preferably multiple, output fluidic channels of the sorting device 2 are sent to a detection or analysis unit operating in parallel based on size distribution. In an exemplary embodiment, one or more fluidic channels containing analytes sorted by size designated as largest size, smaller size, ..., smallest size are directed to different modular parts of the device 1, such as sensor 1, sensor 2, ..., sensor n. Here, the analytes can be detected, counted and sorted in parallel. The dimensions of each analytical unit of the different modular components, such as sensor 1, sensor 2, ..., sensor n, are adjusted in size to the measurement volume to fit the size of the analyte, thus further improving the sensitivity and avoiding the simultaneous detection of multiple (overlapping) events.

[0036] After their identification in two or more of sensors 1, 2, ..., n, preferably simultaneously, a second type of analyte, such as rare cells, is separated from the first type of analyte in two or more fluid channels 1, 2, ..., n and delivered to two or more collection reservoirs 1, 2, ..., n.

[0037] FIG. 1 particularly illustrates the workflow of the system (platform) according to one embodiment of the present disclosure. The platform is designed as a modular system with three devices that can be separated by tube connections or fully integrated. The modularity makes the platform industrializable since the failure of one device does not require replacing the whole platform, but only the failed device can be replaced. Further design development of any device does not affect the design of other devices. This can be considered as an advantage in product development.

[0038] FIG. 2 shows how an exemplary unit or device functions within an overall system according to the present disclosure, the system being designated by reference numeral 10. After size-based preliminary sorting of analytes in a sample fluid or cell stream (stage I depicting sorting unit 18 in FIG. 2), cells in one or more (preferably two or more) branching or characterization lines 10a-10-10c are processed (preferably simultaneously) through detection and enumeration unit(s) exemplified by detection and enumeration unit 11 (first analytical unit: stage II). For simplicity, only one branching / characterization line 10b is depicted in more detail in FIG. 2. The other branching / characterization lines may have the same or similar structure, and preferably consist of components structured such that the measurement volume is dimensioned according to the size of the analytes.

[0039] The exemplary branching / characterization line 10b is configured around a fluidic channel 19b that defines a flow path having an inlet 19b-1 and an outlet 19b-2. The fluidic channel 19b is configured to allow a sample fluid containing at least a first type 20-1 and a second type 20-2 of analytes to pass from the sorting unit 18 along a flow path between the inlet 19b-1 and the outlet 19b-2. The illustration of different cell types in the channel branches 10a, 10b, 10c is representative, and any type of analyte can be sorted into 10a or 10b or 10c based on its size. Analytes of the first, second or any type may fall into the same size range and coexist in the same channel branch (10a, 10b or 10c). Thus, the operation of the size-based pre-sorting unit 18 is independent of the type of analyte, but is dependent on the size of the analyte.

[0040] There are three subunits 11, 12 and 13 operated sequentially within one exemplary embodiment of the system. Subunit 11 (first analytical unit) includes a detector or sensor unit. Subunit 11 is responsible for detecting one or more analyte properties, such as size, membrane properties, cytoplasmic properties, nuclear properties and genomic content or nucleic acid, and sending the information to processing unit 14. Subunit 12 (change unit) is structured to change an analyte property, such as the membrane of WBCs, for example, by charging or electroporating the outer (plasma) membrane of WBCs, while leaving the outer (plasma) membrane of CTCs intact. Subunit 13 (second analytical unit) includes a detector or sensor unit, which may be the same as subunit 11, and is responsible for detecting one or more analyte properties, such as the same properties as subunit 11, and identifying in subunit 12 a shift in signal due to the changed analyte property, e.g. a property of WBCs due to the changed membrane. Subunit 13 then sends a signal to processing unit 14 for tagging WBCs with subunit 13. The data generated by the detection and enumeration unit is processed by the processing unit 14 using machine learning algorithms for identification of each cell type (at least the first and second types of analytes) and this information is used to activate the valve 15a of the purification device 15 (sorting unit 15) to either sort and collect the tumor cells (analytes of the second type 20-2) in a collection chamber (reservoir) 16 or to discard the remaining cells (analytes of the first type 20-1) via a waste outlet 17 (phase III).

[0041] As shown generally in Figure 2, the operating principle of the method and system according to the present disclosure employs a "sample in, result out" approach. The system of the present disclosure not only separates and collects tumor cells (second type of analyte) from peripheral blood cells (first type 20-1 analyte), but also identifies and enumerates them in situ. Thus, the composition of the system's output (collected analytes 20-2) is already known.

[0042] The proposed system aims to detect and combine known physical differences between tumor cells (e.g., denoted as second type analyte 20-2) and peripheral blood cells (correspondingly denoted as first type analyte 20-1). Figure 3 shows some non-limiting examples of physical features that have been commonly used to identify tumor cells. In particular, Figure 3 illustrates physical parameters (first parameter values ​​of at least one analyte characteristic) that are measured using multi-frequency and multi-parameter electrical impedance measurements of cells for tumor cell identification. The first characteristic (first analyte characteristic) that is measured is the specific area A of the cell membrane. The specific area A is the total area of ​​the cell membrane normalized by the perimeter of the cell. For the same size, the specific area A1 of the plasma membrane of tumor cells is generally much larger than the specific membrane area A2 of white blood cells, so A1>>A2. This difference can be measured for a certain frequency range, as shown in the right graph (section (1)) of Figure 3.

[0043] The second property (second analyte property) is the cytoplasmic content, such as the nuclear-cytoplasmic (N / C) ratio, cytoplasmic conductivity, cytoplasmic composition, and genome content. Tumor cells usually have a higher N / C ratio (n1 / c1) compared to white blood cells (n2 / c2). This property can be derived by measuring the cells in a certain frequency range (part (2) in the right graph of Figure 3). The third property (third analyte property) is the size (diameter) d, which can be used for identification and / or to normalize (opacity calculation) the data obtained for the first and second properties. This is to increase the sensitivity and specificity of the measurement, since disturbances in the flow rate and slight changes in the position of the cell within the measurement volume can affect the signal. Normalization removes those effects from the collected signal and improves the quality of the signal.

[0044] To further increase the specificity of the measurement, the membranes of white blood cells are altered, producing a shift in their electrical impedance response, allowing the cells to be tagged and accurately identified.

[0045] Typically, before applying a liquid biopsy, a blood sample is diluted with a red blood cell (RBC) lysis buffer to remove the RBCs from the solution, a process that also affects the (electrical) properties of the outer membrane of leukocytes, but preserves their viability.

[0046] The red blood cell lysis buffer changes the membrane properties of white blood cells by inducing reversible pore formation (similar to electroporation) in the membrane, resulting in a change in electrical response. Thus, immersion in red blood cell lysis buffer can be used as an alternative to electrical charging or electroporation of cell membranes.

[0047] As an alternative to electroporation or immersion in red blood cell lysis buffer, mechanical alternation of leukocytes can also be performed. As an example, cells can be forced to fly through converging-diverging channels due to mechanical changes such as nucleus relocation, which also alters their electrical response. Differences in deformability levels between tumor cells and leukocytes result in differences in their electrical impedance response.

[0048] The change in the electrical response of the white blood cells is measured after immersion in a red blood cell lysis buffer, after which it is verified that the tumor cells remain intact and their electrical impedance response is unchanged.

[0049] Figure 4 shows a typical dataset. This dataset is collected as a proof of how electrical impedance measurements (further analytical properties) clearly show this difference and that tagging of leukocytes is possible. In particular, the raw data relates to multi-frequency measurements of tumor cells, leukocytes and clusters (tumor cells and leukocytes). Data from frequencies of 10 MHz and 20 MHz reveal different electrical responses for tagging. Processing the entire dataset using machine learning algorithms provides enough information to identify or characterize the different types of cells (first and second type of analyte).

[0050] To better control the process and further increase specificity, electrical alterations of the outer (plasma) membrane of the white blood cells can be applied. The system according to the present disclosure can comprise three-dimensional electrodes for forming an electric field with high precision in terms of magnitude and homogeneity, for example as described and illustrated in relation to Figures 6, 7a and 7b. This allows charging or reversible electroporation of the white blood cells while the tumor cells remain intact, as in the chemical case (immersion in red blood cell lysing solution).

[0051] FIG. 5 further illustrates the steps of combining detection and modification of cells. In particular, FIG. 5 illustrates a method according to the present disclosure of combining electrical detection and modification to tag white blood cells to further increase detection specificity. The electric field for cell membrane charging and / or electroporation (e.g., step 2 of FIG. 5 using microfluidic device 12 of FIG. 2) is kept below the electroporation limit of tumor cells and therefore does not change the membrane properties (further analyte properties) of tumor cells. This poration process is reversible, i.e., the membrane recovers quickly and the pores close. Comparing the signals from method step 1 of sensing intact cells (first and second type of analyte) and method step 3 of sensing intact cells (second type of analyte) and treated cells (first type of analyte) provides the possibility to identify differences in the electrical impedance response of treated cells, which can be used for identification and characterization.

[0052] Highly controlled electroporation of cells could enable other applications such as enhanced cell / organ delivery. One prominent example is the controlled electroporation of cells for genome introduction for biological production. This technique, which does not require post-treatment purification, would replace expensive chemical techniques. However, this technique also generates by-products, e.g. bioburden, which makes purification a necessity. Furthermore, by combining electrical sensing with electroporation, it is also possible to monitor the efficiency of nucleic acid delivery and the replication process online. This can be applied to any cell or organism with an outer membrane (e.g., mammalian cells) and / or a wall (e.g., bacteria, yeast cells).

[0053] The present disclosure allows for analysis at the single cell level, preventing any cell (analyte) from being discarded or sent to waste before being fully examined. Currently known prior art systems only provide blind separation routines based on specific target properties by processing bulk quantities. Unlike existing solutions, the present disclosure implements a sensor unit instead of a blind splitting approach. This sensor unit allows for an active decision-making approach for the collection of tumor cells or any target group / analyte in the sample. The detection and isolation of tumor cells outlined in this disclosure is optionally label-free, with the cells remaining intact. This allows for further downstream analysis, such as evaluation of drug response to guide treatment or molecular analysis for drug development. The platform according to the present disclosure can utilize such analysis on the go in real time, for example by coupling optical sensors or utilizing optics integrated into the device, as described with reference to Figures 6, 7a, 7b.

[0054] By using artificial intelligence (AI) and / or machine / deep learning techniques, decision-making regarding tumor cell detection and separation can already be performed at the device level by integrating a microprocessor instead of a computer. Thus, the device platform and method according to the present disclosure are versatile since the sensors used can be adjusted, activated or deactivated depending on the desired application mode.

[0055] The system requires only dilution of the blood sample as sample preparation, therefore the total analysis time is very short and the cost is low compared to most of the state-of-the-art systems offering multiple antibody-based and / or multi-step approaches.

[0056] To further expand the capabilities of the system (e.g., on-the-fly characterization of cells), optical sensing can be combined. One embodiment of the present disclosure includes an optical sensing unit configured to optically sense the sensing region of the fluid channel, preferably between at least one pair of electrodes. This results in a system capable of electrically and optically sensing analytes such as particles and cells in an electrolyte solution. For example, full-spectrum optical spectrometers and high-speed cameras can be used to collect optical data for label-free and / or fluorescence measurements, as well as integrated optical waveguides. High-speed optical data via the spectrometer is provided, and on-demand imaging via the high-speed CMOS camera allows visualization of events of interest to the end user.

[0057] FIG. 6 shows an exemplary configuration of a microfluidic device that can be applied to one or more exemplary analysis and / or modification units, e.g., 11, 12, 13. Some exemplary embodiments also incorporate an optical sensing unit. The microfluidic device 100 according to the present disclosure allows for performing multi-frequency electrical impedance measurements on analytes 1, 2, 3 (such as blood cells) passing through a fluidic channel 110 having a longitudinal channel axis 110z, using a pair of three-dimensional curved first and second electrodes 120a and 120b centered about the longitudinal channel axis 110z. As shown in the figure, the first and second electrodes 120a and 120b have three-dimensional structured electrode surfaces positioned with respect to the longitudinal channel axis 110z, thereby at least partially surrounding the fluidic channel 110.

[0058] The microfluidic device 100 may include a first substrate 130a and a second substrate 130b. Suitable materials for manufacturing the one or more substrates 130a, 130b preferably include transparent materials compatible with microfabrication and thin film processing techniques. Examples include glass and silica. At least a portion of the walls of the fluidic channel 110 may be formed by a first recess 131a in the first substrate 130a. Additionally or alternatively, at least a portion of the walls of the fluidic channel 110 may be formed by a second recess 131b in the second substrate 130b. Preferably, the first recess 131a has the same shape as the second recess 131b. This greatly simplifies the manufacture of the microfluidic device. Most preferably, the first recess 131a and the second recess 131b are symmetrical with respect to a mid-plane or central plane 160c (shown in FIG. 7) of the fluidic channel 110.

[0059] The electrodes 120a, 120b may be disposed opposite each other on different (preferably opposite) sides of the fluidic channel 110. The first electrode 120a may be disposed in a recess 131a of the first substrate 130a, and the second electrode 120b may be disposed in a recess 131b of the second substrate 130b. Alternatively, one or more three-dimensionally curved electrodes of the present disclosure, such as the electrodes 120a, 120b, may be disposed in another selected location such that the electrodes face each other or may be otherwise disposed in another manner consistent with the principles of the present disclosure. Examples of processes that can be used to dispose the electrodes include, but are not limited to, metal deposition, sputtering, or direct printing. In the present disclosure, the term "disposed" shall be construed to include within its meaning any type of deposition, disposition, attachment, integration, or other manner of providing one or more electrodes in any other manner consistent with the present disclosure.

[0060] Reference numeral 140 indicates generally a known arrangement of an electric field generating unit, which is connected to both electrodes 120a, 120b and is capable of impressing an electric field distribution in the channel 110 between both electrodes 120a, 120b. The electric field distribution in the channel 110 between both electrodes 120a, 120b is indicated generally by electric field lines 141.

[0061] The microfluidic device 100 according to the present disclosure may further include an optical sensing unit 150 arranged to optically sense or detect a region of the fluidic channel 110 between at least one pair of the first electrodes 120a and the second 120b. The optical sensing unit 150 may be configured as or include an optical waveguide, a laser device, and / or an optical sensor. In another useful example, the optical sensor may be a charge-coupled device (CCD), a CMOS device, etc. In one embodiment of the present disclosure, the optical measurement using the optical sensing unit 150 is performed simultaneously (preferably synchronously) with the electrical measurement, for example using the electrodes 120a and 120b. The electrodes 120a, 120b are arranged on only a portion of the inner surface wall 110' of the fluidic channel 110. Thus, they do not obstruct the optical sensing axis 150a of the optical sensing unit 150. Thus, label-free (LED illumination, multi-focal or multi-depth configuration, transmitted or reflected light, lens-free imaging, waveguide integration, PMT integration, etc.) or fluorescent (using specific biomarkers for staining) measurements are possible. In one exemplary microfluidic device 100, the optical sensing axis 150a may be perpendicular to the flow direction through the fluidic channel 110, and in other exemplary embodiments, may be horizontal. In general, the optical sensing axis 150a may form any angle with respect to the direction of flow through the fluidic channel 110 that provides optical measurements through the portion(s) of the first and second substrates 130a and 130b that are not obstructed by the electrodes 120a and 120b.

[0062] Figures 7a and 7b further illustrate exemplary configurations of microfluidic devices that may be employed in one or more exemplary analysis and / or modification units, e.g., 11, 12, 13. These exemplary embodiments may also incorporate an optical sensing unit.

[0063] FIG. 7A showing the example 100' illustrates an exemplary embodiment of an integrated optical system utilizing waveguide units 160a and 160b. One or more waveguide units, e.g. 160a, 160b, may be disposed in an intermediate region between substrates 130a and 130b, generally designated by an intermediate or central surface 160c. In this exemplary embodiment, the waveguide units 160a, 160b are disposed between a first substrate 130a and a second substrate 130b, preferably with substrates 130a and 130b glued or bonded to each other. The material of the waveguide is selected based on the required refractive index difference compared to the substrate material associated with the intended application. This difference defines how light is trapped and guided. Waveguide units suitable for use in the embodiments of the present disclosure can be created, for example, by depositing / coating and patterning a material (e.g., silica or a polymeric material) onto substrates 130a and 130b using microfabrication techniques similar to those used to fabricate the substrates. As an alternative to an integrated waveguide unit, a focused laser beam from laser device 180 can be aligned with plane 160c as an external component serving the same purpose, resulting in easier and cheaper manufacture, albeit with lower performance.

[0064] FIG. 7B shows an alternative configuration, designated by reference numeral 100″. The waveguide units 160a and 160b may be disposed on the bottom surface 110b and the top surface 110a of the channel 110, respectively. The waveguide units may be disposed on or within the substrates 130a and 130b. In one embodiment, the optical axis of one or more of the waveguide units 160a and 160b is disposed along a plane 160d. The plane 160d is oriented at a non-zero angle, preferably generally orthogonal to the intermediate or central plane 160c. In this configuration, the integration of the waveguides is required after forming the recesses 131a and 131b in the substrates 130a and 130b, respectively.

[0065] The fabrication process and material options can be the same as those described in connection with the previous configuration shown in Figure 7a. The material can be deposited on a template or deposited and then patterned to form the waveguide. The thickness of the waveguide is about two orders of magnitude smaller than the depth of the fluidic channel 110, so it can be placed on the surface of the fluidic channel 110. Thus, the flow path is not obstructed by the waveguide unit. For shallow channels where the thickness of the waveguide would cause disturbances in the flow field, a recess can be made after the waveguide is placed by removing material from the substrate to obtain a horizontal surface of the channel 110.

[0066] As an alternative to an integrated waveguide, far-field optics can be used in this configuration. Optical components such as a light source to focus light and an image sensor to focus and sense the scattered light can be located on the top and bottom of the device (externally). The waveguide units 160a and 160b in both embodiments 100' and 100'' of Fig. 7A and Fig. 7B are optically coupled to the sensing region of the fluidic channel between at least two electrodes 120a and 120b, providing an additional integrated optical path. This integrated optical path allows illumination of the analytes 1, 2, 3 (particles or cells) by the (focused) light source and collects the scattered light in different planes, optionally with several angles, in combination with a sensor 170 to analyze the analytes. The sensor 170 may be located off the optical path 160c or 160d of the waveguide units 160a, 160b. In such an embodiment of the present disclosure, the optical axis of the sensor forms a non-zero angle with the optical axis of the waveguide. By using external optics as an alternative or in combination with the integrated waveguides, more functionality can be added to the system and the overall cost can be reduced.

[0067] In a first embodiment shown in Fig. 7(A), when light exiting the waveguide unit 160a or a focused (laser) beam 180 arranged at the plane 160c of the channel 110 illuminates the analytes (cells or particles) 1, 2, 3, forward (FSC) and side (SSC) scattering occurs, which can be read, sensed or detected by the optical sensing / sensing unit 150 including the waveguide unit 160b and a sensor 170, respectively. The sensor 170 may be located at a position off the optical path 160c of the waveguide units 160a and 160b. The sensor 170 may be directly attached to the device 100'-100'' or placed at a distance based on the requirements of the optical sensing application or the placement of the optical setup or peripheral components.

[0068] In a second embodiment, as shown in FIG. 7(B), the waveguide units 160a and 160b are integrated into the top surface 110a and / or bottom surface 110b of the channel 110 for illumination and collection of forward and backscattered light. The waveguide unit 160a illuminates the analytes 1, 2, 3 and collects the backscattered light. The waveguide unit 160b collects the forward scattered light. The second option is more suitable for shallow fluidic channels 110. In some embodiments of the present disclosure, the first waveguide unit 160a and / or the second waveguide unit 160b are integrated into the first substrate 130a and / or the second substrate 130b.

[0069] Advantageously, the exemplary microfluidic device described above can be included in the exemplary transformation unit to perform charging or reversible electroporation of analytes of interest. Thus, in addition to being used as a sensor, some embodiments of the microfluidic device can be used for transformation, such as electrical processing and manipulation of analytes, such as cells and particles in suspension. By defining the coverage angle of the concave electrode, the electrode area in contact with the electrolyte can be controlled, thus allowing a high degree of control over the parameters applied for electrical processing or manipulation. The transformation or processing of particles and cells can be, but is not limited to, electroporation of cells for delivery of contents after bioproduction or extraction of the contents inside the cells. Pore formation during electroporation can be reversible or irreversible, as this process (electrode area, applied voltage, etc.) is well controlled and efficient in the proposed configuration. The transformation or manipulation of particles and cells can be induced, but is not limited to, by generating dielectrophoretic forces on these particles / cells. These forces can be generated by targeting specific properties, such as size, morphology, phenotype, and adjusting the frequency and amplitude of the excitation voltage based on the selected properties. The dielectrophoretic force can then be used to guide and direct particles or cells through a flow, or to collect and focus them in defined regions within the device for downstream follow-up analysis.

[0070] Additional optical data obtained with the optical sensing unit provides information regarding physical properties such as internal and external morphology, size, shape, phenotype, etc. By combining these electrical and optical data sets, the system and method according to the present disclosure can be used as a flow cytometer for sensing, enumeration, characterization, and / or classification of target analytes or target particles in suspension, such as biological cells in blood. The system and method according to the present disclosure can also be used as a hematology analyzer for blood cell classification and counting.

[0071] The processing unit 14 implements machine / deep learning algorithms to process the large amount of data collected by the various measurement channels. The measurements collected from the sensors are processed and a decision is made to direct the tumor cells to a collection reservoir downstream from the sensing area using an on / off valve (dielectrophoretic valve, magnetic valve, thumb valve, etc.). Figures 8a and 8b show examples of the operation of a dielectrophoretic valve and a two-way valve, respectively.

[0072] In the case of the dielectrophoretic valve (FIG. 8A), the liquid flow is continuous towards the collection reservoir 16 and towards the waste reservoir 17. The cells approach the valve unit 15 in step (i), at which point the dielectrophoretic valve 15a is turned off. The tumor cells (second type of analyte 20-2) pass through the valve unit 15 in step (ii). At this point the valve 15a is switched on, not affecting the liquid flow, while diverting the tumor cells 20-2 towards the flow path connecting to the collection reservoir 16. The other cells (or the first type of analyte 20-1) pass through the valve unit 15 in step (iii). The valve 15a is then turned off, and they move towards the waste reservoir 17. This "off" state is the default state of the dielectrophoretic valve 15a, which is only activated when it receives a signal for collection from the sensing unit. As soon as the tumor cells 20-2 leave the valve unit 15, the valve 15a is returned to its default state. The advantage of this valve unit 15 is that it can be integrated into the device, i.e., it can be an in-line unit, since the integration of the electrodes is already taken care of during the manufacturing of the sensing unit, so no additional effort is required to integrate this dielectrophoretic valve unit.

[0073] In the case of the two-way valve 150a of FIG. 8B, the liquid flow is directed to the waste reservoir 17 or to the collection reservoir 16. Cells approach the valve 150a in step (i). At that time the valve is in position 1 and the flow is directed to the waste reservoir. At step (ii) tumor cells (analytes of the second type 20-2) pass through the valve. At that time the valve is in position 2 and the flow is directed towards the collection reservoir 16. At step (iii) other cells (or analytes of the first type) pass through the valve. The valve 150a is now in position 1 and the flow is directed towards the waste reservoir 17. Position 1 is the default position of the two-way valve 150a. It is set to position 2 only when a signal for collection is received from the sensing unit. As soon as the tumor cells leave the valve, the valve is returned to its default position. The advantage of this type of valve is that many alternatives are commercially available and it is easy to install in the system. This option does not increase the complexity of the device and is easy to operate.

[0074] High throughput requirements can be met by multiplexing the analytical units by utilizing modular size-based pre-sorting units. This approach not only allows reaching the required throughput levels, but also significantly improves the signal-to-noise ratio since the measurement volume matches the size of the pre-sorted cells.

[0075] Combining these elements, this disclosure provides the first tumor cell analysis system that can purify and collect tumor cells without losing a single cell. Intact and viable tumor cells are ready for downstream analysis. Online enumeration, digitalization and automation of the system are the main advantages.

Claims

1. 1. A method for characterizing an analyte, such as a cell, in a sample fluid, comprising the steps of: (a) passing a sample fluid including a first type of analyte and a second type of analyte along a flow path through a fluid channel; (b) analyzing a first type of analyte and a second type of analyte in the sample fluid in a first analysis unit including a fluid channel, thereby obtaining first parameter values ​​of analyte characteristics for the first type of analyte and the second type of analyte; (c) storing in a processing unit a first parameter value of the analyte characteristic; (d) varying a further analyte characteristic for the first type of analyte relative to a further analyte characteristic for the second type of analyte; (e) analyzing the first type of analyte and the second type of analyte in the sample fluid in a second analysis unit including a fluid channel, thereby obtaining second parameter values ​​of analyte characteristics for the first type of analyte and the second type of analyte; (f) storing in the processing unit a second parameter value of the analyte characteristic; (g) characterizing the first type of analyte and the second type of analyte in the processing unit by comparing the second parameter value with the first parameter value; The method according to claim 1, further comprising:

2. 2. The method of claim 1, wherein step (d) comprises exposing the first type of analyte and the second type of analyte in the sample fluid to an electric field in a device that includes the fluid channel.

3. 3. The method according to claim 1 or 2, characterized in that after step (g), it comprises a step (h) of separating the first type of analytes and the second type of analytes in a separation unit attached to the fluid channel using a changed further analyte property of the first type of analytes based on the characterization in the processing unit.

4. The step (h) (h1) applying an electric field to the sample fluid or using a valve; (h2) directing the flow to a desired outlet by activating the applied electric field or by changing the position of the valve to divert the second type of analyte from the flow path; 4. The method of claim 3, comprising:

5. 5. The method of claim 4 further comprising the step of collecting the second type of analyte in a collection reservoir.

6. The method of any one of claims 1 to 5, wherein step (g) is performed using a machine learning algorithm.

7. 7. The method according to any of claims 1 to 6, wherein steps (b) and (e) comprise Electrical Impedance Spectroscopy (EIS), in particular Multi-frequency Electrical Impedance Spectroscopy.

8. Step (d) comprises altering a membrane of the analyte or inducing mechanical cell deformation; 8. The method of claim 1, wherein the further analyte characteristic is an electrical impedance response of the analyte.

9. 9. The method of claim 1, further comprising the step of optically sensing a sensing region of the fluid channel.

10. 1. A method for characterizing an analyte, such as a cell, in a sample fluid, comprising:

10. A method comprising simultaneously carrying out one or more steps of any one of claims 1 to 9 in a plurality of different characterization lines.

11. 11. The method of claim 10, further comprising the step of separating analytes in the sample fluid into a plurality of different characterization lines prior to step (a).

12. 1. A system for characterizing an analyte, such as a cell, in a sample fluid, comprising: Equipped with a characteristic evaluation line, The characterization line comprises: a fluid channel defining a flow path having an inlet and an outlet, the fluid channel being configured to allow a sample fluid containing a first type of analyte and a second type of analyte to pass along the flow path between the inlet and the outlet when viewed in the flow direction; a first analysis unit including the fluid channel and configured to analyze the first type of analyte and the second type of analyte in the sample fluid and obtain first parameter values ​​of analyte characteristics for the first type of analyte and the second type of analyte; a modification unit comprising a fluidic channel downstream of the first analysis unit, the modification unit being configured to modify a further analyte characteristic of the first type of analyte compared to a further analyte characteristic of the second type of analyte; a second analysis unit including a fluid channel downstream from the transformation unit, the second analysis unit configured to analyze the first type of analyte and the second type of analyte in the sample fluid and to obtain second parameter values ​​of an analyte characteristic for the first type of analyte and the second type of analyte; a processing unit configured to obtain and store the first and second parameter values ​​from the first and second analytical units, and to characterize the first type of analyte from the second type of analyte by comparing the second parameter values ​​with the first parameter values; A system comprising:

13. The change unit comprises an electric field generating unit; 13. The system of claim 12, wherein the electric field generating unit subjects the first type of analytes and the second type of analytes in the sample fluid to an electric field, thereby altering a further analyte characteristic of the first type of analytes relative to a further analyte characteristic of the second type of analytes.

14. a separation unit downstream from the second analytical unit, the separation unit including the fluid channel; 13. The system of claim 12, wherein the separation unit separates the first type of analyte from the second type of analyte using an altered further analyte characteristic of the first type of analyte based on the characterization signal generated and output by the processing unit.

15. 15. The system of claim 14, further comprising a collection unit downstream from the separation unit for collecting the second type of analytes.

16. 16. The system according to claim 14 or 15, wherein the separation unit comprises an electric field generating unit for applying an electric field to the sample fluid which diverts the second type of analyte from the flow path.

17. 16. The system of claim 14 or 15, wherein the separation unit comprises a valve unit for diverting the second type of analytes from the flow path.

18. a sorting unit including a fluid channel upstream from the first analytical unit; 17. The system of claim 12, wherein the sorting unit sorts the first type of analytes and the second type of analytes based on analyte size.

19. 18. The system of claim 12, wherein the processing unit executes a machine learning algorithm to characterize the first type of analytes from the second type of analytes.

20. 19. The system according to any of claims 12 to 18, characterized in that the first and second analysis units comprise Electrical Impedance Spectroscopy (EIS) means, in particular Multi-frequency Electrical Impedance Spectroscopy means.

21. 20. The system according to claim 12, wherein the modification unit modifies a membrane of the analyte or induces mechanical cell deformation.

22. 22. The system of claim 12, further comprising an optical detection unit for optically detecting a detection region of the fluid channel.

23. 1. A platform for characterizing analytes, such as cells, in a sample fluid, comprising: A system according to any one of claims 12 to 22, The system is a platform comprising different characterization lines.

24. 24. The platform of claim 23, further comprising a sorting device disposed upstream from the system of any one of claims 12 to 23, for sorting analytes in the sample fluid to different characterization lines of the system.

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