WO2025172529A1 - New methods for assessing cell-specific drug response - Google Patents

Abstract

The invention relates to a new and time-saving method for determining disease-specific sensitivity and selectivity of test compounds in low volume samples based on high throughput flow-cytometry based cell recognition. The invention further relates to a test kit for performing the method.

Description

NEW METHODS FOR ASSESSING CELL-SPECIFIC DRUG RESPONSE

FIELD OF THE INVENTION

The invention relates to a new and time-saving method for determining diseasespecific sensitivity and selectivity of test compounds in low volume samples based on high throughput flow-cytometry based cell recognition. The invention further relates to a test kit for performing the method and associated data analysis.

BACKGROUND OF THE INVENTION

Treatment of diseases requires the rapid identification of agents that selectively induce a desired biological effect in particular cell types while not affecting other cells thus causing unwanted side effects. Thus, an agent that is capable of selectively inducing a desired biological effect in the desired cell type in an individual subject is likely to provide said subject with a medical benefit. A drug with lower selectivity can cause severe side effects, can require the increase of the treatment dosage, and may consequently not lead to the desired medical outcome.

Specifically in the field of cancer, yearly 1.9 million cancer deaths occur within the EU due to non-matching therapies. Personalized medicine aims to match the right drug with the right patient by using specific features of the individual patient’s tumor. However, current strategies of personalizing therapy largely rely on genetics that can match treatment to less than 10% of cancer patients with efficacy of less than 5% (Kornauth et al., 2022; Flaherty KT et al., 2020; Tourneau CL et al., 2015; Massard C et al., 2017). Patients suffering from the same disease have vastly different responses to the same treatment. It is estimated that up to 90% of all prescribed drugs only benefit 25% of the patients. Genetic approaches are state of the art for most diseases and have also been successful in some indications (e.g., chronic myeloid leukemia (CML) driven by the BCR- ABL oncogene). Most diseases, however, categorically differ from the rare monogenetic disease model and are driven by micro-evolutionary processes leading to broad genetic heterogeneity (Friedman, 2015) and making a purely correlational logic extremely challenging (Dagogo-Jack, 2018). An alternative precision medicine approach to optimizing individualized treatment strategies is the direct ex vivo assessment of drug efficacy, which is starting to show great promise. Currently, these methods aim to determine whether individual patient cells are responsive to a particular test compound under suitable ex vivo incubation conditions (Kravtsov I et al., 1998, US20100298255A1 and US 20170205395 or the Cell Titer Gio assay of Promega Corporation). There has been a number of different technologies utilized for this purpose from homogeneous methods measuring bulk cell viability and/or cell death to heterogeneous single-cell methods utilizing imaging or flow cytometry capable of discriminating between cell populations using fluorescent dyes and cell-surface markers. Other methods also rely on imaging such as microscopy, however with the need to fix cells (WO2019/086476A1 and US2021/181183A1), yet making technical and analytical workflow more labor intensive. These methods require at least 20 million living cells, which correlate (depending on the cell density) with an average 1-2 cm³ tissue sample. The needed size and amount of patient material can rarely be obtained in a biopsy and thus hinders the testing and broad implementations of these methods in clinical routine. In addition, despite the methodological need for larger biopsies, imaging-based technologies are restricted to analyzing only a fraction of the sample, in order to manage the size of the generated data volume and data storage requirements.

US2009/208493A1 discloses compounds which inhibit ABCB1 transporter protein for treating diseases in which ABCB1 transporter protein mediates the disease state, including numerous cancers, especially forms, which exhibit multiple drug resistance. US2009/208493A1 also discloses a flow cytometry based, high-throughput screening assay that quantifies ABCB1 efflux, as well as methods of identifying inhibitors of ABCB1 , ABCG2 and ABCC1 transporter proteins to overcome the drug resistance, however, no direct link between the inhibition of said ABC transporters and the survival of the cells expressing said transporters is made.

A doctoral thesis by Majumder M. M. (2018) discloses methods for improving precision medicine strategies. Said thesis discloses a high-content, multi-parametric flow cytometry assay using 2 x 10⁶ cells per mL to determine the diversity of responses in hematopoietic cell types to a selection of small molecules. Drug responses were quantified with a drug sensitivity score and selective drug sensitivity scores indicating tumor specific sensitivity to the drugs were obtained. However, selective drug responses in said thesis were calculated in relation to cell populations from different samples obtained from different subjects.

The biggest challenge in this field is how best to test and score cell-specific drug sensitivity patterns of fresh (real-time) biopsies so that the results obtained in the laboratory are predictive and translatable to the clinical situation and leading to an improvement in the patient’s outcome. Therefore, there is a high and yet unmet need in the art for improved tissue- and time-saving methods for assessing the selectivity and sensitivity of test compounds.

SUMMARY OF THE INVENTION

It is the object of the invention to provide an improved method for determining cell-specific drug response.

The object is solved by the subject matter of the present invention.

The present method allows the determination of the selectivity of test compounds while requiring only a low sample volume within a very short time. In contrast to known methods in the art, such as imaging methods, the inventive method specifically provides a simplified technical and analysis workflow based on low cell numbers and without the need of cell fixation on a carrier material. Said method also allows the recording of close to 100% of all cellular components present in a patient sample which therefore can be of significantly smaller size of less than 5 million living cells. Thus, the robustness and high reproducibility of a reliable diagnostic assay are met.

In contrast to known methods in the art which score the selectivity of test compounds in relation to cell populations from other samples, the method disclosed in herein allows the scoring of the selectivity of test compounds in regard to healthy cells present in the same sample, which means that each patient is its own control and leads to individually tailored therapy recommendations.

The method described herein allows an acute (overnight) incubation of cells with test compounds, which avoids differentiation and changes in cell properties ex vivo.

In contrast to known methods in the art, the method described herein does not require additional cell enrichment procedures, and the presence of microenvironmental cells can be critical for the predictive value of the method.

In contrast to known methods in the art, the method described herein requires significantly less cells compared to known methods for the determination of the selectivity of test compounds.

The method described herein does not need cytokine support or conditioned media containing growth factor(s). The method disclosed in the present invention further provides an individualized approach for individual patients or patient groups, in which the detection markers can be selected with respect to the disease or symptoms.

The method described herein also allows to correlate the effect of a test compound on a diseased population of cells in a sample composed of a complex population of cells. This not only allows to evaluate the effect of said test compound on a target diseased population of cells, but also provides information on possibly undesired effects on other, e.g. healthy, cells. Additionally, the method can be used for directly quantifying drug effects.

The present invention also allows real-time data acquisition and dynamic visualization of the results.

The invention provides a method for ex vivo determining disease-specific sensitivity and selectivity of test compounds, comprising the sequential steps:

(a) providing a sample of distinguishable cells from a single subject comprising at least one population of healthy cells and at least one population of diseased cells;

(b) preparing a suspension of single cells from said sample and seeding said single cells on a multi-well microtiter plate containing cultivation media, wherein each well contains one or more test compounds, specifically said test compounds are present at different concentrations, or one or more further control compounds;

(c) incubating said multi-well microtiter plate under conditions to obtain uniform cell growth of all cell populations,

(d) centrifuging the cells and aspirating the supernatant resulting in a remaining well volume below 10 pL;

(e) staining the cells with one or more markers, selected from one or more fluorescence-labeled antibodies binding to cellular antigens, specifically selected from antibodies binding to antigens of a cell population, and/or one or more cellular dyes, wherein at least one cellular dye binds to dead cells;

(f) screening of the cells obtained in (e) in each well on a high-throughput flow cytometer;

(g) performing a first gating of the cell populations, wherein the gating is based on the binding of said one or more antibodies and/or staining of said cellular dyes; (h) performing a second gating on viable single cells and selection of a population of interest selected from the group consisting of single marker positive, single marker negative, double marker positive, double marker negative, multiple marker positive, multiple marker negative cell population, and any combinations thereof based on the staining performed in (e) and screening performed in (f);

(i) determining the cell counts in each of the gates obtained in (g) and (h) in each well of the multi-well microtiter plate;

(j) comparing the cell counts obtained in (i) between cells exposed to the test compounds and cells exposed to the control compounds, and calculating percent of cell survival per well, percent of cell survival per cell population, and percent of cell survival per test compound concentration;

(k) generating a dose response curve for each test compound per each cell population with the percent of survival values obtained in (j);

(l) calculating minimum and maximum response, slope, and IC50 or EC50 for the dose-response curve obtained in (k) and calculating an area under the curve (AUC) thereby obtaining a range between 0 and 1 , wherein a value equal to or higher than 0.12 indicates sensitivity to the test compounds;

(m) ranking the AUC obtained in (I) for each cell population;

(n) determining test compound action in each cell population by subtracting the AUC of the viable cells and/or non-disease cell population from the AUC of the cell population of interest;

(o) ranking of test compounds action obtained in (n) for the cell population of interest; and

(p) optionally producing a report to aid clinical decision-making by prioritizing which test compound exhibits disease-specific effects in an individual patient.

According to a specific embodiment described herein, the sample can be any sample containing viable cells, specifically it is selected from peripheral blood, urine, bone marrow, skin, or any other organ of interest; more specifically the sample stems from fresh biopsies or was viably frozen.

Specifically, the diseased cells are cancer cells, specifically selected from the group of hematological cancer cells, leukemia cells, lymphoma cells, and solid cancer cells. According to an embodiment, the test compound is a drug, specifically an anticancer drug.

According to a further embodiment, the control compound is DMSO, or a drug solvent, specifically a solvent of the test compound.

Specifically, each well contains a single test compound at a single dose, combinations of two or more test compounds, or a control compound.

In a further embodiment provided herein, the multi-well microtiter plate contains 1 to 1000, specifically 10-1000, more specifically 50 to 500, or more different test compounds, specifically at different concentrations, specifically the test and control compounds are chosen based on the type of cells present in the sample.

Specifically, the cell density of the suspension is in the range of 1.6 * 10⁵ cells/ml to 4 x 1 Q⁵ cells/ml.

Specifically, in the method described herein the cells are incubated for about 16 to 24 hours.

According to a further embodiment, the centrifugal force of the centrifugation is determined to spin down the cells to the well bottom and to allow subsequent resuspension of the cells, specifically it is at 100 * g.

According to a specific embodiment, staining of the cells is performed at a volume of 1-3 pl/well, specifically at 2 pl/well.

In yet a further embodiment described herein, the cellular dye is selected from the group consisting of 4',6-Diamidin-2-phenylindol (DAPI), live-death cell staining fluorescent dyes, cell-surface marker, specifically a disease specific or patient specific cell-surface marker.

According to a specific embodiment of the method described herein, the fluorescence-labeled antibodies are selectively targeting diseased cells.

Specifically, the test compound action refers to activation or inhibition of cell proliferation, cell viability, cell differentiation, mean fluorescent intensity of a cellular marker, induction of cell death, clonal/sub-clonal drug response tracking, potentiating, or diminishing the effect of cellular therapies such as CAR T cells or other immunotherapies.

According to an embodiment, sensitivity to the test compounds is determined based on dose response relationship and accompanying AUC that: i. if the percentage of survival per concentration is lower than 80% for at least two test compound concentrations and the AUC is equal to or higher than 0.12, the drug is determined to have activity in the cell population, and ii. if the percentage of survival per concentration is higher than 80% for majority of the tested compound concentrations and the AUC is below 0.12 the test compound is determined to have no activity in the particular cell population.

According to a specific embodiment of the method described herein, selectivity to the test compound is determined based on differences in the AUC between cell populations such that: i. if the difference in the AUC value is equal to or higher than 0.12, the test compound is considered to exhibit selective effects in a cell population, specifically in a disease cell population, and ii. if the difference in the AUC value is below 0.12, the test compound is deemed to exhibit non-selective or no effect in a population, specifically in a diseasecell population.

Specifically, the report comprises one or more of the following information: i. general information of sample and assay characteristics including staining information, quality control (QC) metrics of the instrument and screen, and gating strategy; ii. summary treatment recommendation; iii. overall test compound sensitivity results displayed as bar graphs providing a ranking of the effectiveness of the test compound on each of the cell populations with the test compounds, specifically annotated per drug class; iv. disease-specific drug action results displayed as bar graphs providing a ranking of the selective hits in each of the cell populations with the test compound, specifically annotated per drug class; v. the most relevant result graph highlighted for each subject in concordance to a pathology or laboratory medicine report from the same subject; and vi. dose response curves of the test compound per cell population.

According to an alternative embodiment of the invention, herein provided is also a test kit comprising i. a multi-well microtiter plate comprising 1 -1000, specifically 10-1000, or more immobilized test compounds, wherein said test compounds are present in at least at 2- 5 different concentrations, and wherein at least one of each test compound concentration corresponds to the concentration in which the test compound is present in a subject's body cells after administration at a prescribed dosage; ii. reagents for performing the method described herein; iii. cellular dyes, wherein at least one cellular dye binds to dead cells; iv. a list of candidate antibodies binding to two or more cellular antigens; and v. a leaflet or a QR code providing information for performing the method described herein.

FIGURES

Fig. 1 : General workflow

Fig. 2.: Comparison of detection of distinct immune cell populations with modified iQue3® protocol as described herein and a standard flow cytometry instrument (CytoFLEX®) which required significantly more sample input and volume.

Fig. 3 : Flow cytometry plots depicting the gating strategy of cells from a CD20 negative T-cell rich B-NHL case patient. According to the immunohistochemistry report from the Institute of Pathology tumor cells were positive for CD79A, CD22, and negative for CD3. Background immune T-cells were highly CD3 positive. A) Forward versus side scatter to identify cells of interest. B) Differentiation between live and dead cells with DAPI staining, whereas DAPI negative cell population signifies live cells. C-J) Density and histogram plots for CD19, CD79a, CD22, and CD3 staining. K-L) Overlay dot plots depicting the cancer cell populations in this sample (double positive CD22+CD79a+; K and CD3-CD79a+; L).

Fig. 4 : Dose response curves of copanlisib (PI3K inhibitor) and vandetanib (VEGFR/Ret inhibitor) in DAPI negative, CD3 positive, CD19 positive, CD22 positive, CD79a positive, and CD22-CD79a double positive cells expressed as percentage survival following normalization to DMSO controls. Cells are from the CD20 negative T- cell rich B-NHL case patient of Fig.3.

Fig. 5 : Case study of a CD20 negative T-cell rich B-NHL case patient. Selective AUC of DAPI negative, CD22 and CD79a positive relative to CD3 positive immune background cells are sorted. Note, among other compounds, vandetanib and copanlisib demonstrate a highly selective AUC score relative to CD3 cells of >0.2. Fig. 6 : Case study of a CD20 negative T-cell rich B-NHL case of a 37 year old patient. After failing 4 previous treatment lines, a real-time biopsy was undertaken and the method described herein was performed on the biopsy specimen. Based on the marker profile, the selective drug report, and the toxicity profile of the compounds, a molecular tumor board recommended the regimen: Anti-CD19 antibody tafasitamab plus copanlisib or vandetanib. After remission was achieved an allogeneic stem cell transplantation with an available donor was performed. The treating physician and the patient decided to start the treatment consisting of tafasitamab and vandetanib. The patient was treated accordingly for 6 months, achieved a complete metabolic remission, and thus underwent allogenic stem cell transplantation as consolidation. One year after allogenic stem cell transplantation, the patient remained in complete remission and leads a normal life.

Fig. 7 : Evaluation of outcome after the inventive method. A) Overall, scfcfPM was successful in 86% of cases (18/21 patient samples), whereas mbfPM in 64% (16/25). B) When the viable cell count of a patient sample was below 25 * 10⁶ cells, scfcfPM delivered a technically valid fPM test result in 83.3% of cases (5/6 patient samples) in contrast to 36% (5/14) of cases for mbfPM.

Fig. 8 : Detailed summary of genetic aberrations in B-NHL, T-NHL and leukemia subgroups. A) The number of genetic aberrations detected in an individual patient per disease entity. B) The percentage of pharmacologically targetable genetic aberrations per disease entity. C) Summary of the detected genetic aberrations per disease entity.

Fig. 9: Comparison of selective drug sensitivity analysis methods with a case study of a CD20 negative T-cell rich B-NHL case patient. Selective AUC of CD22 and CD79a double-positive cells relative to CD19 positive immune background cells from the same patient A) and from two different healthy donors B) are sorted and visualized with a bar graph. Note, among other compounds, vandetanib is top scoring when the patient’s own CD19 cell population is used as a comparator, whereas it does not score in the top 5 selective hits when compared to averaged drug response profiles from CD19 cell populations from two different healthy donors as in the method according to Majumder (2018) making it highly unlikely to be considered as a therapy recommendation. DETAILED DESCRIPTION

This invention is based on a concept and reduction to practice, for which the inventors have made a significant contribution, thereby providing a novel and inventive solution to the problem underlying the invention.

Unless indicated or defined otherwise, all terms used herein have their usual meaning in the art, which will be clear to the skilled person. Reference is for example made to the standard handbooks, such as “Molecular Biology of the Cell” (Alberts et al., 2022), “Vogel and Motulsky's Human Genetics: Problems and Approaches” (Speicher et al., 2010), “Human Molecular Genetics” (Strachan and Read, 2018), and “The Biology of Cancer” (Weinberg, 2014).

The subject matter of the claims specifically refers to artificial products or methods employing or producing such artificial products, which may be variants of native (wild type) products. Though there can be a certain degree of sequence identity to the native structure, it is well understood that the materials, methods, and uses of the invention, e.g., specifically referring to isolated nucleic acid sequences, amino acid sequences, fusion constructs, expression constructs, transformed host cells and modified proteins, are “man-made” or synthetic, and are therefore not considered as a result of “laws of nature”.

The terms “comprise”, “contain”, “have” and “include” as used herein can be used synonymously and shall be understood as an open definition, allowing further members or parts or elements. “Consisting” is considered as a closest definition without further elements of the consisting definition feature. Thus “comprising” is broader and contains the “consisting” definition.

The term “about” as used herein refers to the same value or a value differing by +/-5 % of the given value.

As used herein and in the claims, the singular form, for example “a”, “an” and “the” includes the plural, unless the context clearly dictates otherwise.

The present invention provides a fast method for ex vivo determining diseasespecific sensitivity and selectivity of test compounds allowing low sample volumes, which comprises the sequential steps (a) to (p) as described above. The method allows an assay miniaturization so that the cells are suspended and stained in a low volume of less than 10 pL, specifically less than 9, 8, 7, 6, 5 pL, or even less, thereby allowing the bulk of the sample to be analyzed in the shortest possible time. This is also achieved by optimizing centrifugation and media aspiration conditions, thus avoiding excessive and uneven cell loss per well.

Centrifugal force can be determined to spin down the cells to the well bottom and to allow aspiration of cell culture supernatant and subsequent resuspension of the cells. Specifically, centrifugation is performed in the present method in the range of about 100 to 500 x g, specifically at about 100 * g for about 2, 3, 4, 5, or 6 minutes, specifically for 5 minutes. According to an alternative embodiment, centrifugation is performed in the present method at about 200 x g, about 300 x g, about 400 x g, or about 500 x g for about 1 , 2, 3, 4, 5, or 6 minutes. Specifically, about 50 to 80%, more specifically 65 to 75%, of the cells per well are screened by the method, which captures the sample heterogeneity and complexity and thereby mimics the in vivo situation. As unlimiting example, one 384 well plate can take roughly 40 minutes to run on a high throughput flow cytometer, with sufficient wash and shaking steps for optimal sample separation and acquisition. The method described herein further can include the step of normalizing the generated data to vehicle controls per cell population thereby eliminating bias from overall cell viability of the sample during the incubation period with the test compounds. Further included herein is the scoring for cell-specific drug sensitivity by contrasting the drug response profile of the target cell population to that of the bulk cell population and in addition to non-disease cell population (e.g., drug response in healthy cells present in the patient specimen), thereby identifying truly disease(cell)-specific drug hits.

As used herein, the term “distinguishable” with respect to cells or cell populations refers to cells that can be distinguished from other cells in the same or a different population by means of a cell marker. Specifically, cells of two distinguishable populations, subgroups or subpopulations may belong to a different cell type or cell state as long as the cells show different expression of cell markers, which makes them distinguishable using high throughput flow cytometry. In order to easily determine whether cells belong to a subgroup of cells, the cells are present as single live cells in cell suspensions.

To distinguish between populations of healthy and diseased cells, healthy cells are defined as expressing antigens, such as surface antigens, or surface or cell markers characteristic for healthy cells or not expressing cell markers characteristic for diseased cells, i.e. disease cell markers. Exemplarily, the disease may be cancer. By selecting the respective cell markers, it is thereby possible to distinguish between these cell populations.

Cell markers can be, but are not limited to, proteins or polypeptides expressed by a cell of a particular type that alone or in combination with other proteins or polypeptides allow cells of this type to be discriminated from other cell types. These can be cell markers expressed on the surface of cells or within cells, within the cytoplasm or within an internal membrane, comprised in the total population of cells as used herein, e.g. as comprised in a sample obtained from a subject, which can be distinguished and thus attributed to distinguishable populations. Accordingly, the distinguishable groups of cells are not limited to cells belonging to different cell types. Rather, distinguishable cells may be of the same cell type as long as they are cells that are distinguishable by cell markers. These cells can be, but are not limited to, cells of the same cell type at different disease stages, cells of the same type but of different activation states, cells at different differentiation stages, or cells at different biological states.

A sample, as used herein, is any sample obtained from a subject, specifically containing viable cells, more specifically said sample is selected from the group consisting of peripheral blood, urine, bone marrow, skin, or any other organ of interest, fresh biopsies. Said sample contains 10⁶ to 10⁸ cells, or 10⁶ to 10⁷ cells, specifically 10⁶ cells, 2 x io⁶ cells, 3 x 1O⁶ cells, 4 x ⁶ cells, 5 x 1O⁶ cells, 6 x 1O⁶ cells, 7 x ⁶ cells, 8 x io⁶ cells, 9 x 10⁶ cells, 10⁷ cells, 2 x ⁷ cells, 3 x 1O⁷ cells, 4 x ⁷ cells, 5 x 1O⁷ cells, 6 x 10⁷ cells, 7 x 10⁷ cells, 8 x 10⁷ cells, 9 x 10⁷ cells, or 10⁸ cells. In a preferred embodiment of the invention, the sample contains at least 10⁷ cells, specifically not below 5 x 10⁶ cells.

As described herein, the samples can contain one or more populations of healthy cells and one or more populations of diseased cells, specifically they can contain 1 , 2, 3, 4, 5, or even more populations of healthy cells and 1 , 2, 3, 4, 5, or even more populations of diseased cells.

As used herein, the term “viable cells” refers to cells that are alive. Live cells can be distinguished from dead cells by staining cells with a cellular dye that binds to dead cells. Specifically, cellular dyes that predominantly bind to dead cells are selected from, but not limited to, Propidium Iodide (PI), 7-amino actinomycin D (7-AAD), and 4', 6- Diamidino-2-Phenylindole, Dihydrochloride (DAPI) which can enter the cell and bind to DNA. Moreover, intracellular and nuclear dyes can be used for determining cell viability. The samples can be obtained from real-time biopsy, such as, but not limited to solid tissue biopsy, bone marrow aspirate, peripheral blood draws, containing viable tumor cells.

The samples comprise viable cells, such as but not limited to, peripheral blood cells, urine cells, stem cells such as hematopoietic stem cells, bone marrow cells, skin cells, or cells from any other organ or tissue of interest.

Peripheral blood mononuclear cells (PBMCs) are blood cells. PBMCs can be lymphocytes such as B-cells, T-cells (CD4 or CD8 positive), NK cells, monocytes, such macrophage precursors; macrophages, or dendritic cells. In a specific embodiment, the selectivity of a test compound described herein can be determined with respect to a target cell comprised in a PBMC or bone-marrow cell sample, i.e. showing selectivity towards cells within the following groups of cells, and cells within the lineage of the cells, including terminal cell states: hematopoietic stem cells, including, but not limited to, common lymphoid progenitor, common myeloid progenitor, and their maturation lineage and terminal states including pro-B-cells, B-cells, double negative t- cells, positive T- cells, plasma-B-cells, NK-cells, monocytes, macrophages, dendritic cells. These can be e.g. found within peripheral blood, bone marrow (flat bone localized), cord blood, spleen, thymus, lymph tissue, and pleural fluid. Cells may be in healthy or diseased stage. Diseased state refers to a condition wherein medical treatment or intervention is needed.

PBMCs for use in the methods described herein can be isolated from whole blood using any suitable method known in the art or described herein. For example, the protocol described by Panda and Ravindran (2018) may be used. Alternatively, density gradient centrifugation is used for isolation, which separates whole blood into components separated by layers, e.g., a top layer of plasma, followed by a layer of PBMCs and a bottom fraction of polymorphonuclear cells (such as neutrophils and eosinophils) and erythrocytes. The polymorphonuclear cells can be further isolated by lysing the red blood cells, i.e. non-nucleated cells. Common density gradients useful for such centrifugation include, but are not limited to, Ficoll® gradient.

Bone-marrow cells for use in the methods described herein can be isolated from bone marrow using any suitable method known in the art. In particular, density gradient centrifugation and magnetic beads can be used to separate bone-marrow cells from other components of such samples. Diseased cells as used herein can be any cell that is not a viable cell, specifically a healthy cell, specifically it can be, but is not limited to hyperproliferative cells such as cancer cells, specifically selected from the group consisting of hematological cancer cells, leukemia cells, lymphoma cells, and solid cancer cells. Samples can also be from fresh biopsies, specifically obtained by surgical interventions.

Specifically, the method described herein can be used with samples comprising also other cell types, yet, no further purification is needed.

According to a specific embodiment, the sample can be frozen and thawed for preparing a single cell suspension as long as said suspension comprises living cells.

According to the method described herein, a suspension of single cells can be prepared by methods known in the art such as Ficoll® gradient centrifugation or mechanical dissociation. Optionally, said cells are resuspended in cell culture medium, specifically at a concentration in the range of 160.000 to 400.000 cells/ml, specifically 160* 10³ to 400* 10³ cells/ml, specifically the cell density is about 160 * 10³, 170 * 10³, 180 x 10³, 190 x 10³, 200 x 10³, 250 x 10³, 300 x 10³, 350 x 10³, 400 x 10³ cells/ml or even higher.

In contrast to known methods in the art, the method described herein requires significantly less cells compared to known methods for the determination of the selectivity of test compounds, specifically only 8-50 %, 20-50 %, or 25-50 % of the cells used by known methods, more specifically 8 %, 10 %, 12 %, 14 %, 16 %, 18 %, 20 %, 21 %, 22 %, 23 %, 24 %, 25 %, 26 %, 27 %, 28 %, 29 %, 30 %, 31 %, 32 %, 33 %, 34 %, 35 %, 36 %, 37 %, 38 %, 39 %, 40 %, 41 %, 42 %, 43 %, 44 %, 45 %, 46 %, 47 %, 48 %, 49 %, or 50 % cells compared to flow cytometry methods for determining drug sensitivity and/or selectivity described in prior art, specifically Majumder M. M. (2018).

The cells are then introduced onto multi-well microtiter plates, wherein each well contains one or more test compounds. Specifically, 5.000 to 20.000 viable cells are introduced into a single well, specifically 5 x 10³ to 2 x 10⁴ viable cells are introduced into a single well, more specifically about 5 x 10³, 6 x 10³, 7 x 10³, 8 x 10³, 9 x 10³, 1 x 1Q⁴, 1.1 x 1Q⁴, 1.2 x 1Q⁴, 1.3 x 10⁴, 1.4 x 1Q⁴, 1.5 x 10⁴, 1.6 x 10⁴, 1.7 x 1Q⁴, 1.8 x 1 o⁴, 1.9 x 1 o⁴, 2 x 1 o⁴ cells. If the percentage of the target population is larger than 25% of the total cell population, the number of seeded cells can be further reduced to a minimum of 1 .000 cells, more specifically 1 x 1 o³, 2 x 10³, 3 x 10³, 4 x 10³ cells. Incubation is carried out in a culture medium and is performed under conditions to allow uniform cell growth of all cell populations of the sample. The culture medium to be used in the methods of the invention can be any medium applicable for sample cell culture. Specifically, the culture medium is a liquid medium with nutrients and substances necessary for cultivation of the cells. Liquid culture media for culturing eukaryotic cells are well known to the person skilled in the art (e.g., DMEM (Dulbecco's Modified Eagle Medium), MEM (Minimum Essential Medium), RPMI (Roswell Park Memorial Institute Medium), RPMI 1640, DMEM F12). Suitable cultivation media may be selected depending on the type of cells to be cultured. Supplements can be added to culture media to induce or modify cell function (e.g. cytokines, growth and differentiation factors, mitogens, serum). Supplements are well known to the skilled person, such as fetal calf serum. The culture medium may further be supplemented with antibiotics, such as penicillin, amphotericin, streptomycin, ciprofloxacin etc.

For example, the cells can be cultivated in RPMI + 10% FCS + penicillin/streptomycin.

Incubation can specifically be performed at temperatures in the range of 35 °C to 38° C, specifically at about 37 °C.

Incubation is performed for a time period sufficient to allow cell growth, specifically uniform cell growth, e.g., growth and propagation of all or most of the different cell types present in the sample, specifically the time period can be a few hours, specifically 16 to 72 hours, specifically less than 72 hours, more specifically in the range of 24-48 hours, more specifically about 24 hours.

As used herein, the term “conditioned” with respect to media refers to media containing components secreted by cells or a cell line which are required by another set of cells or cell line. Specifically, a cell line is grown until 70-80 % confluency, and the supernatant is collected, filtered, and added to a medium, specifically regular RPMI, with a concentration of 25 % (v/v). Said supernatant may comprise growth factors, cytokines, and other factors that may contribute to better survival of cells of interest in culture.

The microtiter plate may be of any material compatible with cell culture, in particular, non-cytotoxic cell culture tested material. Examples for the material are plastic materials, e.g., thermoplastic or duroplastic materials. Examples of suitable plastics are polyethylene, polypropylene, polysulfone, polycarbonate, polyetherethylketone (PEEK) or polytetrafluorethylene (PTFE). Herein, multi-well plates are used, which can separately maintain multiple cultures, e.g., for multiple perturbations, with minimal material requirements, e.g., minimal cell numbers and minimum media volumes. Preferred culture plates include 96 well plates, 384 well plates and 1536 well plates. The culture plate may be sterilized. Herein, a multi-well plate is used.

The multi-well plate specifically is for use in automated systems. In a non-limiting example, the plate may be translucent. Culture plates of use for imaging, e.g., fluorescent imaging, are well known in the art and are commercially available.

According to the method described herein, test compounds and control compounds are present on each plate in separate wells.

The method described herein is for rapid determination of cell specific efficacy, i.e. sensitivity and selectivity of test compounds. Test compounds may be any pharmaceutical drugs, drug components or active agents used in the treatment or approved for the treatment of a disease, specifically cancer. According to the invention, the term “test compound” encompasses polypeptides, peptides, glycoproteins, antibodies, vaccines, nucleic acids, synthetic and natural drugs, small molecules, polyenes, macrocycles, glycosides, terpenes, terpenoids, aliphatic and aromatic compounds, metabolites, and derivatives thereof. In a specific embodiment, the test compound is a chemical compound such as a synthetic and natural drug. In another specific embodiment, the test compound effects amelioration and/or cure of a disease, disorder, pathology, and/or the symptoms associated therewith. Test compounds may also be known therapeutic agents, including without limitation compounds and biologies described in Goodman and Gilman's The Pharmacological Basis of Therapeutics, 14th Ed.) or the Merck's Index, 15th Ed. Genera of therapeutic agents include, without limitation, prodrugs, drugs, drugs influencing inflammatory responses, drugs affecting the composition of body fluids, drugs affecting electrolyte metabolism, chemotherapeutic agents (e.g., for hyperproliferative diseases, particularly cancer, for parasitic infections, and for microbial diseases), antineoplastic agents, immunosuppressive agents, drugs affecting the blood and blood-forming organs, hormones and hormone antagonists, vitamins and nutrients, vaccines, oligonucleotides, and gene therapies.

Specifically, different concentrations of each of the test compounds are contained in the wells. The test components can be present in the wells at concentrations that correspond to the concentrations of these components as they are present in the subject's body upon administration. Specifically, the concentration of the test compound is in the range of 0.01 to 100.000 nM, specifically in the range of 0.01 nM to 100 pM, more specifically 1 nM, 10nM, 50nM, 100nM, 500nM, 1000 nM, 2000 nM, 3000 nM, 4000 nM/ 5000 nM, 6000 nM, 7000 nM, 8000 nM, 9000 nM, 10.000 nM, 20.000nM, 30.000nM, 40.000nM, 50.000nM, 60.000nM, 70.000nM, 80.000nM, 90.000nM, 100.000nM, 10 pM, 20 pM, 30 pM, 40 pM, 50 pM, 60 pM, 70 pM, 80 pM, 90 pM, 100 pM.

Specifically, combinations of one or more test compounds can be comprised in a single well. Thereby, a set of different conditions can be established in each well.

Specifically, the multi-well microtiter plate contains about 1 to 1000, specifically 10 to 1000, specifically 100 to 1000 different test compounds, specifically about specifically about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 131 , 132, 133, 134, 135, 136, 137, 138, 139, 140, 150, 160, 170, 180, 190, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1100, 1200 or even more test compounds.

The method described herein can be used to rapidly assess whether a response in a subject is triggered by a therapeutic agent or its delivery vehicle, excipient, solvent, or carrier.

Control compounds can be, but are not limited to drug solvents, i.e. solvents used as the medium in which the active pharmaceutical ingredients are solubilized or preserved. Solvents are chemical in nature and can suspend, extract, or dissolve other substances without bringing any change in the chemistry of either the substance or the solvent. Solvents can be classified as inorganic, organic, and green solvents; they are generally grouped as oxygenated solvents, halogenated solvents, and hydrocarbon solvents. Currently, green solvents are one of the most used solvents in pharmaceutical industry. Various types of solvents used in pharmaceutical industry are: cyclopentyl methyl ether solvents, water, octanoic acid-based supramolecular solvent, n-butanol and acetone, bio-based green solvent disulfides, and eutectic solvents. SA comprehensive list of solvents is given by the US FDA (Q3C, Tables and List; August 2018, Revision 4, https://www.fda.gov/media/133650/download, accessed on Dec 13, 2023). Specifically, the solvents are solvents or excipients of a test compound, e.g. dimethyl sulfoxide (DMSO).

Subsequent to centrifugation, the cells are stained with one or more markers. Specifically, 2, 3, 4, 5, or more markers can be used to define a certain cell population, specifically in combination with 1 , 2, 3, 4, or 5 markers for healthy cells, i.e. as exclusion marker. More specifically, 3 cell surface markers and 1 marker for healthy cells are used in the herein described method.

Due to the low volume, low amounts of markers are needed thus making the method even more advantageous and cost-effective.

Said markers are fluorescence-labeled antibodies binding to one, two, three, four, five, six, seven, eight, nine, ten, or more cellular antigens. Such fluorescence-labeled antibodies allow the targeting of discrete cellular structures. Combinations of antibodies may be used to simultaneously visualize multiple targets, cellular structures, or cellular components. The fluorescent label may be selected from the group consisting of: Alexa Fluor™ 350, Alexa Fluor™ 405, Alexa Fluor™ 430, Alexa Fluor™ 488, Alexa Fluor™ 514, Alexa Fluor™ 532, Alexa Fluor™ 546, Alexa Fluor™ 555, Alexa Fluor™ 568, Alexa Fluor™ 594, Alexa Fluor™ 610, Alexa Fluor™ 633, Alexa Fluor™ 635, Alexa Fluor™ 647, Alexa Fluor™ 660, Alexa Fluor™ 680, Alexa Fluor™ 700, Alexa Fluor™ 750 and Alexa Fluor™ 790, fluoroscein isothiocyanate (FITC), Texas Red, SYBR Green, DyLight Fluors, green fluorescent protein (GFP), TRIT (tetramethyl rhodamine isothiol), NBD (7- nitrobenz-2-oxa-1 ,3-diazole), Texas Red dye, phthalic acid, terephthalic acid, isophthalic acid, cresyl fast violet, cresyl blue violet, brilliant cresyl blue, paraaminobenzoic acid, erythrosine, biotin, digoxigenin, 5-carboxy-4',5'- dichloro-2',7'- dimethoxy fluorescein, TET (6-carboxy-2\4,7,7 :etrachlorofluorescein), HEX (6-carboxy- 2\4,4\5\7,74iexaehlorofluorescein), Joe (6-carboxy-4',5'-dichloro- 2', 7'- dimethoxyfiuorescein) 5-carboxy-2\4\5\7'-tetrachlorofluorescein, 5- carboxyfluorescein, 5-carboxy rhodamine, Tamra (tetramethylrhodamine), 6- carboxyrhodamine, Rox (carboxy-X-rhodamine), R6G (Rhodamine 6G), phthalocyanines, azomethines, cyanines (e.g. Cy3, Cy3.5, Cy5), xanthines, succinylfluoresceins, N,N-diethyl-4-(5 - azobenzotriazolyl)-phenylamine, aminoacridine, and quantum dots.

Also antibodies directly or indirectly coupled to a fluorescent molecule can be used herein, such as ethidium bromide, SYBR Green, fluorescein isothiocyanate (FITC), DyLight Fluors, green fluorescent protein (GFP), TRIT (tetramethyl rhodamine isothiol), NBD (7-n itrobenz-2-oxa- 1 , 3-d iazole) , Texas Red dye, phthalic acid, terephthalic acid, isophthalic acid, cresyl fast violet, cresyl blue violet, brilliant cresyl blue, paraaminobenzoic acid, erythrosine, biotin, digoxigenin, 5- carboxy-4',5'-dichloro-2',7'- dimethoxy fluorescein, TET (6-carboxy-2^!,4,7,7'- tetrachlorofluorescein), HEX (e- carboxy^A'^AA'.S' J'-hexachl rofluorescein), Joe (6- carboxy^A'.S'-dichloro^A'J'- dimethoxyfluorescein) S-carboxy-^A'^A'.S'J'- tetrachlorofluorescein, 5-carboxyfluorescein, 5-carboxy rhodamine, Tamra (tetramethylrhodamine), 6-carboxy rhodamine, Rox (carboxy-X-rhodamine), R6G (Rhodamine 6G), phthalocyanines, azomethines, cyanines (e.g. Cy3, Cy3.5, Cy5), xanthines, succinylfluoresceins, N,N-diethyl-4-(5'- azobenzothazolyl)-phenylamine, and aminoacridine.

Specifically, the antibodies are used to identify if a cell is malignant or healthy. As an example, antibodies used to detect target cancer cell populations are based on established antigens for a given indication, as well as on pathology or laboratory medicine reports for each individual patient.

Specifically, one or more cellular dyes are used for assessing the viability of the cells in the sample. A dye is a molecule, compound, or substance that can provide an optically detectable signal, such as a colorimetric, luminescent, bioluminescent, chemiluminescent, phosphorescent, or fluorescent signal. Cellular dyes for labeling proteins are known in the art. In a preferred embodiment of the invention, the dye is 4',6- diamidin-2-phenylindol (DAPI) for intact cell staining, live-death cell staining fluorescent dyes, cell-surface marker, specifically a disease specific or patient specific cell-surface marker thereby allowing identification of cells that express at least two different markers of the target cell types. Cells may also be stained using at least two, three, four, five, or more different labels that can be distinguished from one another, thereby allowing detection of cells that express greater numbers of markers of the target cell type. Optionally, a cell may be identified as a cell of the target type if it expresses a preselected number of markers or certain preselected combinations of markers or a cell may be identified as a cell of the target type if it does not express a preselected marker.

Additionally, it is not necessary that the marker(s) of the target cell type be unique to the target cells, as long as they allow distinction of the target cells from other cells in the population. In the case of PBMCs, major components of PBMC cell populations are represented by CD11C for dendritic cells, CD14 for macrophages, CD3 (CD4 or CD8 with CD3) for T-cells and CD19 for B-cells. While the foregoing markers overlap on subsets of these major classes of PBMCs, staining with these markers for identifying subpopulations of PBMCs is widely accepted in the field. Further markers suitable for use in methods of the present invention may be found in the CD marker handbook (Becton, Dickinson and Co. 2016, CA, USA). Major cell subpopulations comprised in bone-marrow cells are neutrophilic metamyelocytes, neutrophilic myelocytes, segmented neutrophils, normoblasts and lymphocytes.

According to an embodiment described herein, 1 , 2, 3, 4, 5, or more cellular dyes bind to dead cells.

Screening is performed on a high-throughput flow cytometer. In contrast to automated microscopy, it allows screening of viable cells that are not fixed with formaldehyde or any other similar agent. Specifically, it is excluded to fix the cells with formaldehyde or any other similar agent.

Appropriate models of high throughput flow cytometers are well known to the skilled person. Exemplarily, but without limitation, the cytometer can be DxFLEX™, iQue®, Multiflow FX, Cellcyte X™, HyperCyt®’ cytometers commercially available from Beckman Coulter, Sartorius, Bio-Rad, or Amnis Corporation. High-throughput flow cytometers are capable of running multiplexed screening assays at speeds of up to or even more than 40 wells per minute, enabling the processing of 96- and 384-well plates in a very short time. Embedded in the system can be a data analysis software package that allows rapid identification of hits from multiplexed high-throughput flow cytometry screening campaigns. In addition, the software can be incorporated into a server-based data management platform that enables seamless data accessibility and collaboration across multiple sites.

According to the herein described method, a first gating of the cell populations is performed based on the binding of antibodies and/or staining of cellular dyes. Gating refers to the separation of events of interest from other events obtained by the flow cytometry.

The gating of sub-populations can be individualized per sample and antibody and/or dye staining with common considerations of forward scatter (FSC, proxy for size) and side scatter (SSC, proxy for granularity), duplets elimination and live/dead cell discrimination based on DAPI staining intensity and live/dead cells.

As a non-limiting specific example, the first gating can be performed wherein FSC signal /SSC signal make a first all cells gate. FSC signal can be used for the discrimination of cells by size. SSC is from the light refracted or reflected at the interface between the laser and intracellular structures, such as granules and nucleus. SSC can provide information about the internal complexity (i.e. granularity) of a cell. Then duplets are eliminated by plotting the height or width against the area for forward scatter or side scatter. Doublets have increased area whilst similar height to single cells. Dead cells are eliminated by gating for DAPI-negative cells from the singlets gate.

The gating is continued by a second gating which is performed on viable single cells and selection of population of interest selected from the group consisting of single marker positive, single marker negative, double marker positive, double marker negative, multiple marker positive, multiple marker negative cell population, and any combinations thereof, based on the staining performed of the cells with the fluorescent- labeled antibodies and cellular dyes and the screening of the so labeled cells by high throughput flow cytometry.

In the next step, the cell counts are determined in each of the gates obtained by the first and second gating in each well of the multi-well microtiter plate.

Further, the cell counts are compared between cells exposed to the test compounds and cells exposed to the control compounds, and percent of cell survival per well, percent of cell survival per cell population, and percent of cell survival per test compound concentration are calculated. Specifically, control compound containing wells (e.g. DMSO or a solvent) can be averaged out for each cell population of interest. Calculation can then be performed e.g. by setting the survival of control compound (e.g. DMSO) wells to 100 and apply it to each well per cell population and drug concentration. E.g.:

% Survival = (well cell count I mean control compound count (e.g. DMSO) for that cell population) * 100

Then a dose response curve is generated for each test compound per each cell population with the percent of survival values obtained above, specifically with a 4- parameter logistic regression.

Specifically, the method can be specified by the following steps:

An input file is generated for dose-response curves for each drug tested per each cell population with % Survival values obtained above. a. Fit a four-parameter log-logistic model for the dose-response curves with a script adapted from the drc R package b. Calculate a summary metric for each drug tested in each cell population that can be used for downstream analysis with the “compute AUC” function of the PharmacoGx R package, i.e. an open-source package for analysis of large pharmacogenomic datasets (Smirnov P. et al., 2016).

The minimum and maximum response, slope, and IC50 or EC50 are calculated for the dose-response curve described above and an area under the curve (AUC) is calculated thereby obtaining a range between 0 and 1 , wherein a value higher or equal to 0.12 indicates sensitivity to the test compounds.

The cutoff for evaluating the sensitivity of the test compounds based on the AUC depends on the indication, specifically the cutoff for evaluating the sensitivity of the test compounds based on the AUC is between 0.10 and 0.30, more specifically the cutoff for evaluating the sensitivity of the test compounds based on the AUC is 0.10, 0.11 , 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.20, 0.21 , 0.22, 0.23, 0.24, 0.25, 0.26, 0.27, 0.28, 0.29, or 0.30. In a preferred embodiment the cutoff is 0.12. Herein, the 0.12 cutoff for a significant effect is demonstrated.

The AUC values can be sorted out from high to low in each cell population of interest.

Then the AUC obtained above is ranked for each cell population.

The test compounds’ action specifically refers to the activation or inhibition of cell proliferation, cell viability, cell differentiation, mean fluorescent intensity of a cellular marker, induction of cell death, clonal/sub-clonal drug response tracking, potentiating, or diminishing the effect of cellular therapies such as CAR T cells or other immunotherapies. The test compound action is ranked in each cell population by subtracting the AUC of the viable cells and/or non-disease cell population from the AUC of the cell population of interest.

Then the test compounds’ action obtained above is ranked for the cell population of interest.

Specifically, a report can then be produced to aid clinical decision-making by prioritizing which test compound exhibits disease-specific effects in an individual patient.

The methods of the present invention quantify the selective ability of a test compound such to kill diseased over non-diseased cells in order to determine whether a subject suffering from a disease will respond or is responsive to treatment with the test compound. The methods of the present invention give a highly accurate information about whether a subject suffering from a disease will respond or is responsive to treatment with a test compound. Specifically, the AUC value as a measure of the quality by which a method can distinguish two classes using the method of the present invention.

In a further embodiment, the sensitivity to the test compounds may be determined based on dose response relationship and accompanying AUC such that: i. if the percentage of survival per concentration is lower than 80% for 2, 3, 4, 5, 6, 7,8, 9, 10, ... , 1000 or more test compound concentrations and the AUC is higher or equal to 0.12, the drug is determined to have activity in the cell population, and ii. if the percentage of survival per concentration is higher than 80% for majority of the tested compound concentrations and the AUC is below 0.12, the test compound is determined to have no activity in the particular cell population. AUC is 0 in cases where the maximum response is 10% or lower or IC50/EC50 equals or is beyond the maximum drug concentration tested.

In a further embodiment selectivity to the test compound is determined based on the differences in the AUC between cell populations such that: i) if the difference in the AUC value is higher or equal to 0.12, the test compound is considered to exhibit selective effects in a cell population, specifically in a disease cell population, and ii) if the difference in the AUC value is below 0.12, the test compound is deemed to exhibit non-selective or no effect in a population, specifically in a disease-cell population.

The results can be provided as a report containing general information of sample and assay characteristics, specifically including staining information, QC metrics of the instrument and screen, and gating strategy; summary treatment recommendation; overall test compound sensitivity results displayed as bar graphs providing a ranking of the effectiveness of the test compound on each of the cell populations with the test compounds, specifically annotated per drug class; disease-specific drug action results displayed as bar graphs providing a ranking of the selective hits in each of the cell populations with the test compound, specifically annotated per drug class; the most relevant result graph highlighted for each subject in concordance to a pathology or laboratory medicine report from the same subject; and/or dose response curves of the test compound per cell population.

Specifically, a test kit is provided comprising i) a multi-well microtiter plate comprising 1 to 1000, specifically 10 to 1000, specifically 100 to 1000 different test compounds, specifically about specifically about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 131 , 132, 133, 134, 135, 136, 137, 138, 139, 140, 150, 160, 170, 180, 190, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1100, 1200 or even more immobilized test compounds, wherein said test compounds are present in 2, 3, 4, 5, 6, 7, 8, 9, 10, or more different concentrations, and wherein at least one of each test compound concentration corresponds to the concentration in which the test compound is present in a subject's body cells after administration at a prescribed dosage; ii) reagents for performing the method described herein; iii) cellular dyes, wherein at least one cellular dye binds to dead cells; iv) a list of candidate antibodies binding to two or more cellular antigens; and v) a leaflet or a QR code providing information for performing the method described herein.

As used herein, the term “reagent” refers to any substance necessary to execute the method described herein, specifically the term reagent may include but is not limited to one or more of culture media, antibodies, dyes, buffers, compounds, beads or DMSO.

As used herein, the term “reagent” refers to any substance necessary to execute the method described herein, specifically the term reagent may include but is not limited to antibodies against CD1a, antibodies against CD1c, antibodies against CD2, antibodies against CD3, antibodies against CD4, antibodies against CD5, antibodies against CD7, antibodies against CD8, antibodies against CD8a, antibodies against CD10, antibodies against CD11 b, antibodies against CD13, antibodies against CD14, antibodies against CD16, antibodies against CD19, antibodies against CD20, antibodies against 22, antibodies against CD24, antibodies against CD27, antibodies against CD30, antibodies against CD33, antibodies against CD34, antibodies against CD38, antibodies against CD45, antibodies against CD45RA, antibodies against CD56, antibodies against CD64, antibodies against CD66b, antibodies against CD68, antibodies against CD79a, antibodies against CD79b, antibodies against CD114, antibodies against CD115, antibodies against CD116, antibodies against CD117, antibodies against CD123, antibodies against CD138, antibodies against CD184, antibodies against CD235a, antibodies against CD274, antibodies against CD279, antibodies against CD319, antibodies against CDCD371 , antibodies against HI-A-DR, antibodies against Annexin V, antibodies against TCRgd, antibodies against K-light chain, antibodies against X-light chain, DAPI dye, live/dead cell counting dyes, 7-AAD, Propidium Iodide, DRAQ7™, calcein AM, MitoTracker dyes, Caspase 3/7, FACS buffer, PBS buffer, RBS lysis buffer, isotype controls, compensation beads, cell-counting beads, calibration and size reference beads, or DMSO.

The present invention also encompasses the following embodiments:

1. Method for ex vivo determining disease-specific sensitivity and selectivity of test compounds, comprising the sequential steps:

(a) providing a sample of distinguishable cells, specifically from a single subject, comprising at least one population of healthy cells and at least one population of diseased cells;

(b) preparing a suspension of single cells from said sample and seeding said single cells on a multi-well microtiter plate containing cultivation media, wherein each well contains one or more test compounds at different concentrations, or one or more further control compounds;

(c) incubating said multi-well microtiter plate under conditions to obtain cell growth of all cell populations,

(d) centrifuging the cells and aspirating the supernatant resulting in a remaining well volume below 10 pL;

(e) staining the cells with one or more markers, selected from one or more fluorescence-labeled antibodies binding to cellular antigens, specifically selected from antibodies binding to antigens of a cell population, and/or one or more cellular dyes, wherein at least one cellular dye binds to dead cells;

(f) screening of the cells obtained in (e) in each well on a high-throughput flow cytometer;

(g) performing a first gating of the cell populations, wherein the gating is based on the binding of said one or more antibodies and/or staining of said cellular dyes;

(h) performing a second gating on viable single cells and selection of a population of interest selected from the group consisting of single marker positive, single marker negative, double marker positive, double marker negative, multiple marker positive, multiple marker negative cell population, and any combinations thereof based on the staining performed in (e) and screening performed in (f); (i) determining the cell counts in each of the gates obtained in (g) and (h) in each well of the multi-well microtiter plate;

(j) comparing the cell counts obtained in (i) between cells exposed to the test compounds and cells exposed to the control compounds, and calculating percent of cell survival per well, percent of cell survival per cell population, and percent of cell survival per test compound concentration;

(k) generating a dose response curve for each test compound per each cell population with the percent of survival values obtained in (j);

(l) calculating minimum and maximum response, slope, and IC50 or EC50 for the dose-response curve obtained in (k) and calculating an area under the curve (AUC) thereby obtaining a range between 0 and 1 , wherein a value equal to or higher than 0.12 indicates sensitivity to the test compounds;

(m) ranking the AUC obtained in (I) for each cell population;

(n) determining test compound action in each cell population by subtracting the AUC of the viable cells and/or non-disease cell population from the AUC of the cell population of interest;

(o) ranking of test compounds action obtained in (n) for the cell population of interest; and

(p) optionally producing a report to aid clinical decision-making by prioritizing which test compound exhibits disease-specific effects in an individual patient.

2. The method of embodiment 1 , wherein the sample is any sample containing viable cells, specifically it is selected from peripheral blood, urine, bone marrow, skin, or any other organ of interest, fresh biopsies, more specifically the sample was frozen.

3. The method of embodiment 1 or 2, wherein the diseased cells are cancer cells, specifically selected from the group consisting of hematological cancer cells, leukemia cells, lymphoma cells, and solid cancer cells.

4. The method of any one of embodiments 1 to 3, wherein the test compound is a drug, specifically an anti-cancer drug.

5. The method of any one of embodiments 1 to 4, wherein the control compound is DMSO, or a drug solvent, specifically a solvent of the test compound. 6. The method of any one of embodiments 1 to 5, wherein each well contains a single test compound at a single dose, combinations of two or more test compounds, or a control compound.

7. The method of any one of embodiments 1 to 6, wherein the multi-well microtiter plate contains 1 to 1000, specifically 10-1000, more specifically 50 to 500, or more different test compounds, specifically at different concentrations.

8. The method of any one of embodiments 1 to 7, wherein the test and control compounds are chosen based on the type of cells present in the sample.

9. The method of any one of embodiments 1 to 8, wherein the cell density of the suspension is in the range of 1 .6 * 10⁵ cells/ml to 4 x 10⁵ cells/ml.

10. The method of any one of embodiments 1 to 9, wherein the cells are incubated for 16 to 24 hours.

11. The method of any one of embodiments 1 to 10, wherein centrifugal force of the centrifugation is determined to spin down the cells to the well bottom and to allow subsequent resuspension of the cells, specifically it is at 100 x g.

12. The method of any one of embodiments 1 to 11 , wherein staining of the cells is performed at a volume of 1-3 pl/well, specifically at 2 pl/well.

13. The method of any one of embodiments 1 to 12, wherein the cellular dye is selected from the group consisting of 4',6-Diamidin-2-phenylindol (DAPI), live-death cell staining fluorescent dyes, cell-surface marker, specifically a disease specific or patient specific cell-surface marker.

14. The method of any one of embodiments 1 to 13, wherein the fluorescence- labeled antibodies are selectively targeting diseased cells.

15. The method of any one of embodiments 1 to 14, wherein the test compound action refers to activation or inhibition of cell proliferation, cell viability, cell differentiation, mean fluorescent intensity of a cellular marker, induction of cell death, clonal/sub-clonal drug response tracking, potentiating, or diminishing the effect of cellular therapies such as CAR T cells or other immunotherapies.

16. The method of any one of embodiments 1 to 15, wherein sensitivity to the test compounds is determined based on dose response relationship and accompanying AUC such that: i. if the percentage of survival per concentration is lower than 80% for at least two test compound concentrations and the AUC is equal to or higher than 0.12, the drug is determined to have activity in the cell population, and ii. if the percentage of survival per concentration is higher than 80% for majority of the tested compound concentrations and the AUC is below 0.12 the test compound is determined to have no activity in the particular cell population.

17. The method of any one of embodiments 1 to 15, wherein selectivity to the test compound is determined based on differences in the AUC between cell populations such that: i. if the difference in the AUC value is equal to or higher than 0.12, the test compound is considered to exhibit selective effects in a cell population, specifically in a disease cell population, and ii. if the difference in the AUC value is below 0.12, the test compound is deemed to exhibit non-selective or no effect in a population, specifically in a disease-cell population.

18. The method of any one of embodiments 1 to 17, wherein the report comprises one or more of: i. general information of sample and assay characteristics including staining information, quality control (QC) metrics of the instrument and screen, and gating strategy; ii. summary treatment recommendation; iii. overall test compound sensitivity results displayed as bar graphs providing a ranking of the effectiveness of the test compound on each of the cell populations with the test compounds, specifically annotated per drug class; iv. disease-specific drug action results displayed as bar graphs providing a ranking of the selective hits in each of the cell populations with the test compound, specifically annotated per drug class; v. the most relevant result graph highlighted for each subject in concordance to a pathology or laboratory medicine report from the same subject; and vi. dose response curves of the test compound per cell population.

19. Test kit comprising i. a multi-well microtiter plate comprising 1-1000, specifically 10-1000, or more immobilized test compounds, wherein said test compounds are present in at least 2-5 different concentrations, and wherein at least one of each test compound concentration corresponds to the concentration in which the test compound is present in a subject's body cells after administration at a prescribed dosage; ii. reagents for performing the method of any one of embodiments 1 to 18; iii. cellular dyes, wherein at least one cellular dye binds to dead cells; iv. a list of candidate antibodies binding to two or more cellular antigens; and a leaflet or a QR code providing information for performing the method of any one of embodiments 1 to 18.

The examples described herein are illustrative of the present invention and are not intended to be limitations thereon. Different embodiments of the present invention have been described according to the present invention. Many modifications and variations may be made to the techniques described and illustrated herein without departing from the scope of the invention.

EXAMPLES

Example 1 : General workflow

A schematic representation of a general workflow in the case of a patient diagnosed with cancer is shown in Fig. 1.

A cancer biopsy which contains cancer and normal microenvironmental cells is taken from the patient diagnosed with cancer. Next, the single cells from the biopsy are incubated with drugs. The plate is centrifuged and the supernatant is aspirated. The goal of the latter step is to miniaturize the assay and increase the sample concentration. This reduces the sample volume, the antibody staining volume and, hence, the costs. Subsequently, the cells are stained with patient-specific markers and High-throughput - flow cytometry is performed. Then, the drugs are ranked based on their cancer selective effect. Finally, the results lead to an informed patient treatment decision.

Example 2: Protocol - High-throughput flow cytometry drug screening (single-cell flow cytometry fPM (scfcfPM))

1. Prewarm cell culture media of choice (for example RPMI + 10% FCS + 1 % penicillin/streptomycin) at 37 °C. 2. Take drug-printed 384-well plates from the -20 °C freezer to thaw and bring them to room temperature.

3. Thaw cells or isolate freshly from blood, bone marrow (BM), or lymph node to generate a single cell suspension by either Ficoll® gradient centrifugation or mechanical dissociation. For other starting materials use appropriate cell dissociation procedure.

4. Resuspend cells in cell culture media at a concentration of 2 x 10⁵ - 4 x 10⁵ cells per ml.

5. 5 000 - 20 000 cells/well are needed. The assay volume can be between 25-50 pl per well. When the target cell content is 25% or higher 1 000 cell/well are sufficient.

6. Pour the cells into a reagent reservoir.

7. Cell seeding: Cells can be seeded using an 8 or 12-channel electronic pipette with multi-dispense setting or a peristaltic dispenser. The settings are adjusted based on the wanted assay volume.

8. Incubate the assay plates (e.g., 384 well plates) at 37 °C 5% CO2 overnight (specifically, at least about 16h).

9. Turn on the iQue3® screener (Sartorius) or other high-throughput flow cytometer and perform QC according to the manufacturer’s instructions

10. Once the instrument has passed QC it is ready for operation a. Choose “drug screening template” containing the run settings (e.g., reading direction, sip volume, shake and rinse steps) and enter information of the current experiment. b. Laser and filter: Enter the markers (of the antibodies that will be used for staining the cells) for the respective lasers. c. Example protocol is as follows i. Prepare stage

1 . Automatic prime 60 seconds

2. Pre-plate shake the entire 384 well-plate before data acquisition starts 30 seconds at 2400 RPMI

3. Make sure shake speeds are synchronized ii. Sample

1 . Sample order from left to right or top to bottom 2. sample sipping time per well of 3 seconds with an additional up time of 0.5 seconds

3. Pump speed - standard (29 RPM)

4. Plate Model 3764 384-well Corning Black with Clear Flat Bottom a. Sample height: 0.2 mm b. XY Offset: -0.50; -0.10 mm iii. Cleaning steps

1 . Enable Mid-Plate Clean after every 8 wells iv. Shaking steps

1. Inter-well Shake at 2400 RPMI after every 8 wells for 4 seconds v. Flush and Clean

1 . Flush duration 30 seconds

2. Enable Post-Plate Clean a. Decon 30 seconds b. Clean 30 seconds c. Rinse 60 seconds vi. Detector

1. Thresholds a. FSC-H < 100000 d. Leave the instrument idle until the plates are ready to be screened Centrifuge plates: 100 * g for 5 minutes at room temperature Use an automated multimode dispenser-washer (e.g., Multiflo FX (Agilent)) to aspirate the supernatant such that remaining well volume will be less than 10 pl and the cell pellet is not disturbed Prepare the staining mixture of antibodies and dyes (dilution 1 :300-1 :500) a. According to an embodiment, 3 cell surface markers can be used that define the cancer cell population based on lab medicine or pathology reports and 1 or more markers for healthy cells (= exclusion marker) b. In addition, DAPI can be used for assessing the viability of the sample cells Install a low-volume peristaltic pump (e.g., Random Access Dispensing (RAD) module for the Multiflo FX) 15. Wash and prime the peristaltic pump with the staining cocktail

16. Prime the antibody solution a. after priming with the antibody mix, do not prime with air again as the mix will be used for the second plate 1 h later. b. The antibodies are diluted 1 :300 or 1 :500 in PBS

17. Dispense 2 pl antibody mix to each well

18. Stain the plate for 40 minutes at RT in the dark

19. Prime the iQue 3® for 5 minutes

20. Place the plate on the plate holder and start the screening

21. If more than one assay plate is screened, the second plate can be stained while the first is running on the iQue 3® screener

22. If more than one assay plate is screened, the second plate can be run after the first plate is finished on the iQue 3® screener

23. Perform well identification of the acquired data by taking into account both data acquisition and timing.

24. Gating strategy (Fig. 3) a. FSC/SSC make a first all cells gate b. Eliminate duplets by plotting the height or width against the area for forward scatter or side scatter. Doublets have increased area whilst similar height to single cells. c. Eliminate dead cells by gating for DAPI-negative cells from the singlets gate d. Continue gating on viable singlet cells to select single marker positive, double marker positive, and/or triple marker positive cells and corresponding negative cell populations. The double and triple-marker positive cell populations are selected with overlay graphs of the respective single-marker positive populations. e. Determine the cell counts and percentages in each of the gates in each well from the 384-well assay plate. f. Export cell counts from all populations of interest and match with the drug well annotation sheet

25. Average out the DMSO controls for each cell population of interest 26. Calculate the percent of survival by setting the survival of DMSO wells to 100 and apply it to each well per cell population and drug concentration a. % Survival = (well cell count I mean DMSO cell count for that cell population) * 100

27. Generate dose-response curves for each drug tested per each cell population by fitting a four-parameter log-logistic model

28. Calculate a summary metric for each drug tested in each cell population that can be used for downstream analysis (e.g., Area under the curve) a. AUC values range between 0 and 1 (the higher the value the more activity the drug has in a given cell population).

29. Sort the AUC values from high to low in each cell population of interest a. Plot bar graphs of the AUC values in each cell population of interest b. Label each bar according to drug class or category

30. Subtract the AUC values of each drug in the DAPI- cell population from the AUC values of each drug in each of the cancer-cell populations a. Sort the selective AUC (sAUC) values from high to low b. Plot bar graphs of the selective AUC values in each population of interest with a cutoff of sAUC of higher or equal to 0.12 c. Label each bar according to drug class or category

31. Subtract the AUC values of each drug in the non-cancer (exclusion marker) cell population from the AUC values of each drug in each of the cancer-cell populations a. Sort the selective AUC (sAUC) values from high to low b. Plot bar graphs of the selective AUC values in each population of interest with a cutoff of sAUC of higher or equal to 0.12 c. Label each bar according to drug class or category

32. Compile a drug screening report a. Provide general information i. Assay performed by: ii. Analysis performed by: iii. Report produced by: iv. Report created on (date): v. Plates (barcodes): vi. Plate Type: vii. Instrument: viii. Acquisition Lasers: ix. Diagnosis: x. Sample type: xi. Cell concentration: xii. Incubation time: xiii. CV DMSO controls: xiv. Stain information: b. Quality control of the instrument i. Take a screenshot of QC results with beads c. Export dot plots and histograms of all the gates to demonstrate the gating strategy i. Import the plots in the report d. Export plate heatmaps of counts of all cells gate i. Import the heatmaps in the report e. Drug screening results i. Provide a ranking of the effectiveness of the drugs on the target population

1 . Provide ranking of the overall hits in all cell populations gated

2. Provide ranking of the selective hits in all the cell populations gated ii. Provide dose-response curves for the selective hits across all cell populations presented as % Survival in relation to DMSO wells in the same channel.

Example 3

Fig. 2 shows a comparison of the detection of distinct immune cell populations in peripheral blood mononuclear cells (PBMCs) with the protocol of Example 2 and a standard flow cytometry method for measuring different cell populations, which requires significantly more sample input and volume. Briefly, for the analysis according to the protocol of Example 2 cells were seeded at a density of 12000 cells/well in 50pl in a 384 well plate and incubated overnight at 37°C. The next day, the plate was centrifuged at 100 x g for 5 min, the supernatant was aspirated, and cells were stained with antibodies against CD4, CD8a, CD19, CD14, DAPI, or a combination thereof. After 30 min incubation, the plate was run on the iQue 3® instrument as described in Example 2 (“inventive method”). For the CytoFLEX comparison (“comparative method”), approximately 50000 cells per condition were washed with PBS and were either left unstained or stained (1 :500 antibody dilution) with DAPI or antibodies against CD4, CD8a, CD19, CD14, or multistained. The samples were incubated for 30min, washed with PBS, resuspended in 300pl FACS buffer, and measured on a benchtop flow cytometry instrument.

Example 4: CD20 negative T-cell rich B-NHL case

A CD20 negative T-cell rich B-NHL case of a 37 years old patient. After failing 4 previous treatment lines, a real-time biopsy was undertaken and analyses as demonstrated above (Example 2) were performed on the biopsy specimen.

Fig. 3-6 show examples of a workflow of a CD20 negative T-cell rich B-NHL case patient who has failed multiple prior treatment lines and whose biopsy sample has undergone the procedure described in detail in Example 2.

Fig. 3 shows the gating strategy of the flow-cytometry plots of the indicated patient case. According to the immunohistochemistry report from the Institute of Pathology, the tumor cells were positive for CD79A, CD22, and negative for CD3. Background immune T-cells were highly CD3 positive. Fig. 3A shows the forward versus side scatter to identify cells of interest. Fig. 3B shows the differentiation between live and dead cells with DAPI staining, whereas DAPI negative cell population signifies live cells. Fig. 3C-J show the density and histogram plots for CD19, CD79a, CD22, and CD3 staining. Fig. 3K-L show the overlay dot plots depicting the cancer cell populations in this sample (double positive CD22+CD79a+; Fig. 3K and CD3-CD79a+; Fig. 3L).

Fig. 4 shows dose response curves of copanlisib (PI3K inhibitor) and vandetanib (VEGFR/Ret inhibitor) in DAPI negative, CD3 positive, CD19 positive, CD22 positive, CD79a positive and CD22-CD79a double positive cells expressed as percentage survival following normalization to DMSO controls.

Fig. 5: shows sorted selective AUC of DAPI negative, CD22and CD79a positive relative to CD3 positive immune background cells. Note, among other compounds, vandetanib and copanlisib demonstrate a highly selective AUC score relative to CD3 cells of >0.2.

Fig. 6 shows a case study of a CD20 negative T cell rich B-NHL case of a 37 years old patient. Based on the marker profile, the selective drug report, and the toxicity profile of the compounds, a molecular tumor board recommended the regimen: Anti- CD19 antibody tafasitamab plus copanlisib or vandetanib. After a remission was achieved, an allogeneic stem cell transplantation with an available donor was performed. The treating physician and the patient decided to start the treatment consisting of tafasitamab and vandetanib. The patient was treated accordingly for 6 months, achieved a complete metabolic remission and thus underwent allogenic stem cell transplantation as consolidation. One year after allogenic stem cell transplantation, the patient remained in complete remission and leads a normal life.

Example 5: Functional and genomic based precision medicine in blood cancer patients: Feasibility results of a multicentric, prospective, randomized controlled trial

Precision medicine (PM) seeks customized treatment strategies on a patientspecific basis aiming to provide comprehensive personalized healthcare. In oncology, genomics has been the dominant tool in performing PM. Since many cancer patients lack actionable alterations to accurately match patients to effective therapies, there is a need to extend the advantages of PM to a larger proportion of cancer patients. Additional methods need to be explored, and one important alternative approach is functional PM, a strategy by which living patient cancer cells are exposed to therapies and measured to predict clinical response.

Prognosis is dismal for aggressive hematological cancer patients relapsing or refractory upon standard treatments. If tumor-containing biopsies can be obtained timely and safely, these patients are candidates for PM programs or studies. The inventive method, referred to as drug-screening-based single-cell (sc) high-throughput (HT) flow cytometry (fc) functional PM (scfcfPM) (see Example 3 for details), provides clinical benefit to advanced hematological cancer patients. Below is a feasibility analysis of a multicentric, prospective, randomized controlled trial directly comparing:

- high-throughput (HT) scfcfPM as described herein,

- comparative genomic based precision medicine (gPM), - microscopy based (mb) fPM (mbfPM), and

- physicians’ choice (PC).

Patients with confirmed relapsed/refractory aggressive hematologic cancers were eligible. Detailed inclusion/exclusion criteria as well as details on study conduct are shown in Table 1.

Table 1: Patients' characteristics

A “real-time biopsy” (solid tissue biopsy, bone marrow aspirate, or peripheral blood draws) containing viable tumor cells was collected from each patient. Samples are subjected to image-based (mbfPM) and/or high-throughput (HT) flow cytometry-based fPM (scfcfPM), as well as gPM testing.

Screening drug collection used herein:

The compounds used in the screening drug collection were as follows: Venetoclax, Selinexor, Azathioprine, Capecitabine, Cladribine, Clofarabine, Cytarabine, Decitabine, Fludarabine, 5-fluorouracil, Gemcitabine, 6-mercaptopurine, Methotrexate, Nelarabine, Leflunomide, Pemetrexed, 5-azacitidine, Bendamustine, Busulfan, Carboplatin, Carmustine, Chlorambucil, Cisplatin, Cyclophosphamide, Ifosfamide, Melphalan, Mitomycin C, Temozolomide, Docetaxel, Paclitaxel, Vinblastine, Vincristine, Vindesine, Hydroxyurea, Arsenic trioxide, Bortezomib, Carfilzomib, Ixazomib, ATRA, Bexarotene, Etoposide, Mitoxantrone, Topotecan, Pixantrone, Daunorubicin, Doxorubicin, Amsacrine, Belinostat, Panobinostat, Romidepsin, Vorinostat, Tazemetostat, Olaparib, Rucaparib, Lenalidomide, Pomalidomide, Thalidomide, Tacrolimus, Dexamethasone, Methylprednisolone, Prednisolone, Palbociclib, Ribociclib, Duvelisib, Idelalisib, Copanlisib, Everolimus, Temsirolimus, Trametinib, Cobimetinib, Selumetinib, Dabrafenib, Vemurafenib, Bosutinib, Dasatinib, Imatinib, Nilotinib, Ponatinib, Ceritinib, Crizotinib, Brigatinib, Ibrutinib, Acalabrutinib, Zanubrutinib, Erlotinib, Gefitinib, Lapatinib, Gilteritinib, Lenvatinib, Nintedanib, Ruxolitinib, Tofacitinib, Baricitinib, Crenolanib, Midostaurin, Quizartinib, Entrectinib, Larotrectinib, Cabozantinib, Pazopanib, Axitinib, Sorafenib, Sunitinib, Regorafenib, Vandetanib, Tivozanib, Anagrelide, Erismodegib, Vismodegib, Glasdegib, and Ivosidenib.

Patients were randomized into three study arms, either fPM, gPM, or Physicians’ Choice (PC), in a 4:4:2 allocation ratio. The tumor board consisted of at least two hemoncologists, one pathologist, one molecular biologist, and one pharmacist. If a PM assay failed or did not identify a treatment rationale, the study protocol allowed switching to the other experimental arm.

42 patients were randomized to the three study arms. 32 of these patients suffered from malignant lymphoma (B-NHL: n=17 patients, T-NHL: n=15 patients), and 10 patients from leukemia (AML: n=7, ALL: n=2, CML: n=1). 13 patients dropped out early due to clinical deterioration and/or disease progression (fPM: n=7, gPM: n=2, PC: n=4) and were recorded as early drop-outs. 29 patients (fPM: n=7, gPM: n=8, PC: n=14) completed at least one cycle of the respective therapy and were evaluable per protocol, representing the final efficacy analysis patient cohort. Treatment was initiated after a median of 25 days (range: 7-46 days) after biopsy and a median of 7 days (range: 0- 28 days) following the weekly tumor board with no significant difference between study arms.

Flow cytometry-based scfcfPM was feasible in 86% of tests; microscopy-based mbfPM was feasible in 64% of tests; gPM was feasible in 86% of tests.

Actionable hits were detected with both fPM assays in 100%, and with gPM in 76% of feasible tests. Thus, PM assays identified a treatment rationale in 86% (scfcfPM), 64% (mbfPM), and 65% (gPM) of tested patient samples, respectively (Table 2). Fig. 7 shows the evaluation of the outcome after the inventive method. Overall, scfcfPM was successful in 86% of cases (18/21 patient samples), whereas mbfPM in 64% (16/25) (Fig. 7A). When the viable cell count of a patient sample was below 25 * 10⁶ cells, scfcfPM delivered a technically valid fPM test result in 83.3% of cases (5/6 patient samples) in contrast to only 36% (5/14) of cases for mbfPM (Fig. 7B). There was no relationship between the disease entity and both fPM assay performances.

Median time from biopsy to report was also shorter for scfcfPM than for mbfPM and gPM tests (scfcfPM: 6.5 days, mbfPM: 7 days, gPM: 19 days, p<0.0001). gPM identified a median of 5 (range: 1-13) genetic aberrations per patient, of which a median of 1 (range: 0-5) aberration was conceived as an actionable genetic target (Table 2). A detailed summary of genetic aberrations in B-NHL, T-NHL and leukemia subgroups is shown in Fig. 8 A-C.

When both, scfcfPM and gPM results, were available overlapping therapy was identified in 67% (8/12 patients) Concordance was defined as positive if at least one drug targeting the detected genetic aberration featured in the list of top 10 drug hits identified by the scfcfPM assay.

Table 2: Precision Medicine Assay Performance.

The feasibility analysis of the randomized trial demonstrates that genomic and functional PM approaches can efficiently and safely be integrated into clinical routine. A unidirectional, mutational-based approach to PM might be underpowered to bring long- lasting clinical benefit to individual patients. Results of trials using functional testing encourage expectations that the addition of scfcfPM can provide further information in this situation and significantly improve the clinical benefit that is conferred by genomic testing alone. Taken together, PM can be integrated as a clinical decision-making tool in advanced aggressive hematologic malignancies. Conclusion

For fPM tests, a high level of concordance between image- and flow cytometrybased assays with a mean overlap of 49% among the top 10 drug hits in the 7 patient samples with results from both platforms was received (range 30-70%).

However, the inventive scfcfPM method described herein surprisingly provided the best results in that feasibility of therapy and availability of report were significantly better and the results were also received in a shorter time period which is very important to allow early onset of targeted cancer therapy. Moreover, it was shown by the inventors that the scfcfPM method could deliver technically valid test results with 5 * 10⁶ cells. This low cell number has the potential to maximize clinical benefit since it is oftentimes difficult or even impossible to obtain enough viable cells suitable for other fPM methods, such as mbfPM.

Example 6: Comparative example

To further demonstrate the difference in the data analysis and consequences thereof, the data of example 4 were compared to the state of the art, specifically Majumder (2018). The following was compared; the outcome of ranking selective drug responses with the inventive method (using the non-cancer cell population present in the same biopsy), in this case, the CD19+ cell population, versus using the mean drug response profile of CD19+ cell populations from two different healthy donors as used in the method of Majumder (2018). With the inventive method, vandetanib, the therapy the patient of example 4 was treated with and achieved complete remission, came up as one of the 3 top hits (Fig. 9A). However, vandetanib did not score in the top 5 selective hits with the method according to Majumder (2018) (Fig. 9B). Clinically speaking, the top 3 hits are considered for a therapy recommendation, and even if extended to the top 5 selective hits, only one drug is an overlapping hit with both analysis methods. Doramapimod, the top selective hit with the inventive method, is an investigational compound that could not be considered a treatment choice.

Fig. 9 shows a comparison of selective drug sensitivity analysis methods with a case study of a CD20 negative T-cell rich B-NHL case patient. The results of the inventive method and the state of the art method are shown in Fig.9A and Fig. 9B, respectively. Selective AUC of CD22 and CD79a double-positive cells relative to CD19 positive immune background cells from the same patient A) and from two different healthy donors B) are sorted and visualized with a bar graph. Note, among other compounds, vandetanib is top scoring when the patient’s own CD19 cell population is used as a comparator, whereas it does not score in the top 5 selective hits when compared to averaged drug response profiles from CD19 cell populations from two different healthy donors as in the method according to Majumder (2018) making it highly unlikely to be considered as a therapy recommendation.

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Claims

1. Method for ex vivo determining disease-specific sensitivity and selectivity of test compounds, comprising the sequential steps:

(a) providing a sample of distinguishable cells from a single subject comprising at least one population of healthy cells and at least one population of diseased cells;

(b) preparing a suspension of single cells from said sample and seeding said single cells on a multi-well microtiter plate containing cultivation media, wherein each well contains one or more test compounds at different concentrations, or one or more further control compounds;

(c) incubating said multi-well microtiter plate under conditions to obtain cell growth of all cell populations,

(d) centrifuging the cells and aspirating the supernatant resulting in a remaining well volume below 10 pL;

(e) staining the cells with one or more markers, selected from one or more fluorescence-labeled antibodies binding to cellular antigens, specifically selected from antibodies binding to antigens of a cell population, and/or one or more cellular dyes, wherein at least one cellular dye binds to dead cells;

(f) screening of the cells obtained in (e) in each well on a high-throughput flow cytometer;

(g) performing a first gating of the cell populations, wherein the gating is based on the binding of said one or more antibodies and/or staining of said cellular dyes;

(h) performing a second gating on viable single cells and selection of a population of interest selected from the group consisting of single marker positive, single marker negative, double marker positive, double marker negative, multiple marker positive, multiple marker negative cell population, and any combinations thereof based on the staining performed in (e) and screening performed in (f);

(i) determining the cell counts in each of the gates obtained in (g) and (h) in each well of the multi-well microtiter plate;

(j) comparing the cell counts obtained in (i) between cells exposed to the test compounds and cells exposed to the control compounds, and calculating percent of cell survival per well, percent of cell survival per cell population, and percent of cell survival per test compound concentration;

(k) generating a dose response curve for each test compound per each cell population with the percent of survival values obtained in (j);

(l) calculating minimum and maximum response, slope, and IC50 or EC50 for the dose-response curve obtained in (k) and calculating an area under the curve (AUC) thereby obtaining a range between 0 and 1 , wherein a value equal to or higher than 0.12 indicates sensitivity to the test compounds;

(m) ranking the AUC obtained in (I) for each cell population;

(n) determining test compound action in each cell population by subtracting the AUC of the viable cells and/or non-disease cell population from the AUC of the cell population of interest;

(o) ranking of test compounds action obtained in (n) for the cell population of interest; and

(p) optionally producing a report to aid clinical decision-making by prioritizing which test compound exhibits disease-specific effects in an individual patient.

2. The method of claim 1 , wherein the sample is any sample containing viable cells, specifically it is selected from peripheral blood, urine, bone marrow, skin, or any other organ of interest, fresh biopsies, more specifically the sample was frozen.

3. The method of claim 1 or 2, wherein the diseased cells are cancer cells, specifically selected from the group consisting of hematological cancer cells, leukemia cells, lymphoma cells, and solid cancer cells.

4. The method of any one of claims 1 to 3, wherein each well contains a single test compound at a single dose, combinations of two or more test compounds, or a control compound.

5. The method of any one of claims 1 to 3, wherein the multi-well microtiter plate contains 1 to 1000, specifically 10-1000, more specifically 50 to 500, or more different test compounds, specifically at different concentrations.

6. The method of any one of claims 1 to 5, wherein the test compound is a drug, specifically an anti-cancer drug.

7. The method of any one of claims 1 to 6, wherein the control compound is DMSO, or a drug solvent, specifically a solvent of the test compound.

8. The method of any one of claims 1 to 8, wherein the cell density of the single cell suspension is in the range of 1.6 * 10⁵ cells/ml to 4 x 10⁵ cells/ml.

9. The method of any one of claims 1 to 8, wherein the cells are incubated for 16 to 24 hours.

10. The method of any one of claims 1 to 9, wherein centrifugal force of the centrifugation is determined to spin down the cells to the well bottom and to allow subsequent resuspension of the cells, specifically it is at 100 x g.

11. The method of any one of claims 1 to 10, wherein staining of the cells is performed at a volume of 1-3 pl/well, specifically at 2 pl/well.

12. The method of any one of claims 1 to 11 , wherein the cellular dye is selected from the group consisting of 4',6-Diamidin-2-phenylindol (DAPI), live-death cell staining fluorescent dyes, and cell-surface marker; specifically, the cellular dye is a disease specific or patient specific cell-surface marker.

13. The method of any one of claims 1 to 12, wherein the fluorescence-labeled antibodies are selectively targeting diseased cells.

14. The method of any one of claims 1 to 13, wherein the test compound action refers to activation or inhibition of cell proliferation, cell viability, cell differentiation, mean fluorescent intensity of a cellular marker, induction of cell death, clonal/sub-clonal drug response tracking, potentiating, or diminishing the effect of cellular therapies such as CAR T cells or other immunotherapies.

15. The method of any one of claims 1 to 14, wherein sensitivity to the test compounds is determined based on dose response relationship and accompanying AUC such that: i. if the percentage of survival per concentration is lower than 80% for at least two test compound concentrations and the AUC is equal to or higher than 0.12, the drug is determined to have activity in the cell population, and ii. if the percentage of survival per concentration is higher than 80% for majority of the tested compound concentrations and the AUC is below 0.12 the test compound is determined to have no activity in the particular cell population.

16. The method of any one of claims 1 to 15, wherein selectivity to the test compound is determined based on differences in the AUC between cell populations such that: i. if the difference in the AUC value is equal to or higher than 0.12, the test compound is considered to exhibit selective effects in a cell population, specifically in a disease cell population, and ii. if the difference in the AUC value is below 0.12, the test compound is deemed to exhibit non-selective or no effect in a population, specifically in a disease-cell population.

17. The method of any one of claims 1 to 16, wherein the report comprises one or more of: i. general information of sample and assay characteristics including staining information, quality control (QC) metrics of the instrument and screen, and gating strategy; ii. summary treatment recommendation; iii. overall test compound sensitivity results displayed as bar graphs providing a ranking of the effectiveness of the test compound on each of the cell populations with the test compounds, specifically annotated per drug class; iv. disease-specific drug action results displayed as bar graphs providing a ranking of the selective hits in each of the cell populations with the test compound, specifically annotated per drug class; v. the most relevant result graph highlighted for each subject in concordance to a pathology or laboratory medicine report from the same subject; and vi. dose response curves of the test compound per cell population.

18. Test kit comprising i. a multi-well microtiter plate comprising 1-1000, specifically 10-1000, or more immobilized test compounds, wherein said test compounds are present in at least 2-5 different concentrations, and wherein at least one of each test compound concentration corresponds to the concentration in which the test compound is present in a subject's body cells after administration at a prescribed dosage; ii. reagents for performing the method of any one of claims 1 to 17; iii. cellular dyes, wherein at least one cellular dye binds to dead cells; iv. a list of candidate antibodies binding to two or more cellular antigens; and v. a leaflet or a QR code providing information for performing the method of any one of claims 1 to 17.