Combined medicine development method based on 3D human cancer model

Abstract

The invention relates to a method for characterizing a composition containing two or more active pharmaceutical compounds. Comprising the following steps: a) a composition selective screening (CSS), in which a candidate composition containing two or more active pharmaceutical compounds is tested with one or more cell line-derived 3D microtissues, and b) a composition validation screening (CVS), in which the candidate composition of step b) is tested with primary patient sample-derived 3D microtissues.

Description

[0001] This application is a divisional of PCT China National Phase Application 201980075877.8, filed on November 20, 2019. Invention Field

[0002] This application relates to a method for characterizing a composition containing two or more active pharmaceutical compounds, the method comprising the steps of: b) composition selection screening (CSS), in which candidate compositions containing two or more active pharmaceutical compounds are tested with one or more cell line-derived 3D microtissue samples; and c) composition validation screening (CVS), in which candidate compositions from step b) are tested with primary patient sample-derived 3D microtissue samples. Figure 1 ). Background Technology

[0003] This application relates to the screening of combinations of therapeutic drugs. Generally, therapeutic drugs are screened for efficacy using conventional screening systems, in which drugs in a library are tested using appropriate cell assays. Typically, cell viability and / or the toxicity of candidate drugs are investigated.

[0004] These methods can typically be performed at high throughput, but they come with a higher risk that promising drugs identified in the method may fail to deliver in subsequent clinical trials. Furthermore, there has been an increasing use of drug combinations in specific indications, for example, to avoid drug resistance or to explore synergistic effects.

[0005] To date, there are virtually no publicly available systematic methods for early screening of potential drug combinations. Typically, physicians combine drugs based on their experience and test them in patients. However, there is a lack of systematic methods to truly study the combined effects of these drug combinations. This means that a large number of promising drug combinations may exist, but due to the lack of systematic research methods, patients have no opportunity to use them.

[0006] At the same time, it is necessary to improve the predictability of early experiments in future in vivo environments to reduce the risk of failure of drug combinations that have been shown to be effective in preclinical trials.

[0007] Furthermore, there is a need to identify new drug combinations with sustainable therapeutic effects more quickly and efficiently.

[0008] WO 2013 / 050962A1 relates to a drug-containing tumor microenvironment platform for culturing tumor tissues, a method for predicting tumor response to drugs, and a method for screening or developing anticancer drugs.

[0009] WO 2017 / 081260A1 relates to the use of three-dimensional spheres in screening potential therapeutics, where the screening is a high-throughput screening of a library of potential therapeutics.

[0010] US 2016 / 040132A1 relates to bioprinted three-dimensional pancreatic tumor tissue and methods for identifying therapeutic agents targeting the tumor.

[0011] The aforementioned literature does not mention the necessity of studying the combined effects of two or more drugs, nor the advantages of newly discovered drug combinations.

[0012] These and other objectives can be achieved through the methods and means described in the independent claims of this application. The dependent claims relate to preferred embodiments. It should be understood that numerical ranges defined by numerical values ​​are interpreted to include the defined endpoint values. Summary of the Invention

[0013] Before describing the invention in detail, it should be understood that the invention is not limited to the specific components of the device or the operational steps of the method, as these devices and methods can be varied. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not restrictive. It should be noted that, as used in the application and appended claims, the singular forms “a,” “an,” “an,” and “the” include both singular and / or plural forms, unless the context clearly indicates otherwise. Furthermore, it should be understood that when a parameter range is defined by a numerical value, the range is equivalent to including these defined endpoint values.

[0014] In addition, it should be noted that documents or content incorporated into this article through citation are primarily intended for public disclosure purposes, thereby avoiding excessive text length.

[0015] According to one embodiment of this application, a method is provided for characterizing the physiological effects of a composition containing two or more active pharmaceutical compounds. The method includes the following steps:

[0016] b) Composition Selection Screening (CSS), in which one or more cell line-derived 3D microtissues are exposed to a composition containing two or more active pharmaceutical compounds, and / or

[0017] c) Composition Validation Screening (CVS), in which 3D microtissue derived from primary patient samples is exposed to the composition of step b).

[0018] To characterize the physiological effects of the composition on 3D microtissues.

[0019] It is important to understand that steps b) and c) can be performed at the same location or at different locations. Step b) can be performed, for example, in a laboratory where cell lines are available, while step c) can be performed in a laboratory near the clinical trial site, where primary patient samples are available.

[0020] In one implementation, the experimental protocols in steps b) and c), including, for example, microtissue size, microtissue weight, or number of cells in the microtissue, administration of a composition containing two or more active pharmaceutical compounds, time points of exposure to a composition containing two or more active pharmaceutical compounds, composition of the culture medium, and / or parameters of culture conditions such as pH, temperature, O2 / CO2 flow rate, etc., are, where technically feasible, the same, nearly the same, or substantially the same.

[0021] This makes the results obtained in steps b) (CSS) and c) (CVS) highly reproducible and comparable, and allows for standardization between the two steps. Furthermore, the 3D model allows for testing in the same manner, regardless of the cell source. In contrast, with the 2D model, it is sometimes difficult to grow tumor cells in the culture medium. Moreover, this method allows for a high degree of automation in both steps.

[0022] In essence, some regulatory agencies require that when applying for a combination of two or more standard treatments, the additional patient value of that combination must be stated. The method described above can be achieved by setting up two independent screening phases with similar experimental conditions early in development, thereby releasing data supporting this additional value at an earlier stage of development.

[0023] The terms “exposing microtissue to the composition” and “testing the composition with microtissue” used in this article have essentially the same meaning. “A composition comprising two or more active pharmaceutical compounds” may also be referred to as a “pharmaceutical composition” or “combination of drugs” in this article.

[0024] As used herein, the term "active pharmaceutical compound" refers to the biologically active component of a drug. This term is used interchangeably with the term "active pharmaceutical ingredient (API)".

[0025] "3D microtissues derived from one or more cell lines" are 3D multicellular 3D microtissues containing at least one of the following cell lines:

[0026] - Immortalized cell lines

[0027] - Cancer cell line

[0028] - Cancer cells from xenograft tumors, and / or

[0029] - Cancer cells from a xenograft transplanted from a patient.

[0030] "3D microtissue derived from primary patient samples" refers to 3D multicellular 3D microtissue obtained from dissected tumors, such as from tumor biopsies, surgical removal of tumors, or organ donation.

[0031] The cells used for this type of 3D microtissue can be fresh, such as those obtained directly after a biopsy or surgery, or they can be cryopreserved cells.

[0032] Typically, to prepare 50,000 3D microstructures, a total of 12.5 × 10⁻⁶ kilometres are required. 6 - 25×10 6 Cancer cells. Although large tumors surgically removed from a patient typically contain this many cells, tumor material obtained through a biopsy usually contains fewer cells.

[0033] For this reason, in step b), 3D microtissues derived from one or more cell lines are used. The advantage of this is that large quantities of this type of cellular material can be obtained, resulting in a large number of data points. This is particularly necessary for screening at different concentrations within a large library of drug compositions.

[0034] In step c), 3D microtissue derived from primary patient tumor samples is used. This material is typically not available in large quantities.

[0035] However, the concept of 3D micro-tissues allows for the generation of a sufficient number of tumor micro-models from patient samples. These micro-models faithfully reflect the physiological functions and genetic characteristics of real tumors, rather than cancer cell lines, which typically differ from those of real tumors.

[0036] Therefore, this method enables the screening of drug combinations for specific patient groups or patient classes, which is an important step in addressing the growing needs arising from increasing patient classifications in clinical practice or treatment.

[0037] 3D microtissues are preferably cultured in specific containers, such as microreaction containers or wells of microburette plates. Exposing 3D microtissues to drugs or drug combinations refers to, for example, adding anticancer drugs to the container via, for example, a suitable dropper, pipette, or dispenser.

[0038] 3D microtissues provide more representative organoid models for assessing tumor growth. They contain multiple layers of cells, exhibiting size- and gradient-dependent growth and survival more closely resemble in vivo conditions. Furthermore, 3D microtissues allow for the reproduction of the natural tumor microenvironment. For this reason, cells in 3D microtissues, such as 2D cell cultures, behave more physiologically because they are better able to create intercellular communication pathways and extracellular matrix. In addition, 3D microtissues better reflect the physicochemical conditions in real tissues or organs because they can better simulate the diffusion gradients of gases (such as oxygen) and chemicals. Moreover, they better simulate penetration barriers against macromolecules.

[0039] Another benefit is that cell line-derived 3D micro-tissues also allow for the specific simulation of drug action on each cell population by combining drug-resistant and drug-sensitive cells within the same tissue, thereby creating a cancer model that accurately reflects the real tumor.

[0040] Furthermore, compared to 2D cell cultures, 3D microtissues exhibit significantly longer survival. While 2D cell cultures containing non-immortalized primary cells have a detection survival of 3–7 days, 3D microtissues have a survival of up to 30 days or longer, making them suitable for long-term studies of drug exposure in 3D microtissues, as in the in vivo environment, where tumors respond to a single dose of drug over a longer period of time.

[0041] Another advantage is that 2D cell culture can only quantify drug-resistant populations (endpoint determination), while the 3D microtissue of this application allows for observation of short-term and long-term dynamics of tissue response to drug exposure.

[0042] In addition, optionally, in the CSS and / or CVS steps, a control experiment is performed, i.e., a reference drug is tested against one or more 3D microtissues derived from one or more cell lines and / or one or more 3D microtissues derived from primary patient samples.

[0043] Such a reference drug is preferably the standard treatment for the disease, and the selected drug combination should be effective for the disease.

[0044] Alternatively, such a reference drug is preferably a standard treatment (SOC) for a disease represented by 3D microtissues derived from one or more cell lines and / or 3D microtissues derived from primary patient samples, or modeled based on the aforementioned 3D microtissues.

[0045] The table below shows typical SOC treatment for pancreatic cancer and non-small cell lung cancer:

[0046]

[0047] In this way, the added value (efficacy) of the new drug combination compared to existing standard treatments can be demonstrated at a very early stage.

[0048] In one implementation, various drug combinations are tested against multiple 3D microtissues derived from one or more cell lines, and / or against multiple 3D microtissues derived from primary patient samples.

[0049] In one embodiment, the drug combinations are tested against ≥2, ≥3, ≥4, ≥5, ≥6, ≥7, ≥8, ≥9, ≥10, ≥15, ≥20, ≥25 or ≥30 3D microtissues derived from one or more cell lines.

[0050] In one implementation, the drug combinations are tested against ≥2, ≥3, ≥4, ≥5, ≥6, ≥7, ≥8, ≥9, ≥10, ≥15, ≥20, ≥25 or ≥30 3D microtissues from primary patient samples.

[0051] In one method, each drug combination is tested against ≥2 and ≤10 (preferably ≥3 and ≤5) 3D microtissues from one or more cell lines, and against ≥5 and ≤50 (preferably ≥10 and ≤30) 3D microtissues from primary patient samples.

[0052] This allows for very detailed patient-specific efficacy stratification of different drug combinations, thereby increasing the likelihood that drug combinations that demonstrate promising results in 3D microtissues derived from primary patient samples during the CVS procedure will also be successful clinically, particularly increasing the likelihood of success in patient populations corresponding to each 3D microtissue.

[0053] In one implementation, the method is combined with molecular maps of the tissues, as discussed below, to further stratify the 3D microtissues derived from primary patient samples and match them with the patient populations.

[0054] According to one embodiment of this application, at least one parameter representing the characterized physiological effect is generated or determined in the method. This parameter may be, for example, size or survival rate.

[0055] According to one embodiment of this application, the method further includes a range finding step (RFS), in which multiple 3D microtissues derived from one or more cell lines are exposed to each compound present in different concentrations in the candidate composition to determine a suitable concentration range of the compound.

[0056] The scope-finding step is particularly important, especially when selecting pharmaceutical compounds already used clinically. For these compounds, using clinically available doses is attractive; however, these doses may not be sufficient to scale down or scale up to the 3D microtissue environment. Typically, clinical doses are expressed in mg / kg or mg / m². 2 Dosage. It is clear that the dosage used for systemic administration to human patients cannot be simply extrapolated to in vitro protocols for 3D microtissues.

[0057] Again, in this step, 3D micro-tissues derived from one or more cell lines are used. The advantage of this is that large quantities of this type of cellular material can be obtained, thus enabling the acquisition of a large number of data points. This is particularly necessary when screening large drug libraries present at different concentrations.

[0058] Therefore, the dose range finding step provides useful information that allows subsequent screening steps to be performed at drug concentrations that mimic physiological conditions, which can provide relative dose predictions for preclinical assessment.

[0059] Another benefit is that the results of the range finding, combined with the single-drug treatment data from the CSS phase, can be used as quality control parameters to check reproducibility. This allows the reference drug combination to serve as a benchmark for testing single-drug effects. The single-drug effect should match the growth at that concentration in the range step.

[0060] According to one embodiment of this application, the method further includes the step of obtaining molecular maps of at least one of the following:

[0061] a) 3D microtissues derived from one or more cell lines, and / or

[0062] b) 3D microtissue derived from primary patient samples.

[0063] According to one embodiment of this application, a molecular mapping step is used to detect genomic abnormalities and / or mRNA or protein expression levels.

[0064] Such molecular mapping steps may include at least one of the steps in Table 1:

[0065] Table 1. Molecular mapping options

[0066]

[0067] Thus, the molecular profile (RFS) of the studied tissue exposed to drugs or drug combinations can be correlated with its physiological effects (CSS, CVS).

[0068] According to one embodiment of this application, the parameter representing the characterized physiological effect is determined over time in at least one of steps a), b) and / or c).

[0069] This allows for the simulation of the in vivo environment, changes in serum titers of tumors exposed to drugs or drug combinations, the development or non-development of drug resistance, or other dynamic effects. Furthermore, it allows for the acquisition of disease progression responses to drug exposure.

[0070] According to one embodiment of this application, the parameter representing the physiological effect being characterized is the size of the 3D microtissue.

[0071] According to one embodiment of this application, the size, relative size, and / or the relative size change over time are determined in at least one of steps a), b), and / or c).

[0072] These methods simulate the clinical characteristics of tumors according to the so-called RECIST criteria.

[0073] The Evaluation Criteria for Solid Tumor Treatment (RECIST) is a set of published rules used to define whether a cancer patient’s tumor condition improves (“response”), remains unchanged (“stable”), or worsens (“progress”) during treatment.

[0074] RECIST specifies a minimum size for measurable lesions and limits the number of lesions that can be linearly measured and standardized. Patients with baseline measurable disease are included in the guidelines, where objective tumor response is the primary endpoint, measured by changes in size over time.

[0075] According to various guidelines, CT and MRI are preferred methods for measuring size (optical slice thickness less than 10 mm). The guidelines emphasize that tumor markers alone cannot be used to assess response, while cytology and histology can be used for assessment.

[0076] Therefore, according to the method of the above embodiments, the clinical manifestations of tumor response to a specified treatment are simulated in vitro. This is unique and greatly enhances the predictive power of the method of this embodiment.

[0077] This indicates that drug combinations identified as potentially effective by the method of this embodiment are less likely to fail in subsequent preclinical or clinical evaluations. In other words, the probability that drug combinations identified by the method of this embodiment will prove effective in subsequent preclinical or clinical evaluations is significantly increased compared to methods according to the prior art.

[0078] According to one embodiment of this application, the size determination of 3D microstructures refers to at least one parameter selected from the following:

[0079] - size,

[0080] - Perimeter,

[0081] - Volume,

[0082] - Optical cross-sectional area.

[0083] Therefore, dimensions can be parameters that are directly measured or parameters that are calculated based on these measurements.

[0084] Preferably, the size of the 3D cell culture or tissue is determined by an imaging device.

[0085] One example of this type of imaging device is the Cell3iMager, manufactured by SCREEN Holding Co., LTD. in Japan. It can perform spheroid analysis by scanning a multi-well plate in a bright field. It calculates a predicted value based on the size and density of the spheroids, as well as the number and area of ​​spheroids in each well. Its operation is simple and efficient, and its vibration-free design protects cells from damage. It can also be well-suited for determining the growth of spheroids over time and measuring particle distribution in 3D cultures.

[0086] According to another preferred embodiment, the effect of anticancer drug exposure on 3D cell cultures or tissues is determined by dynamically measuring cell growth and / or by endpoint measurements of cell survival rate and / or cell growth and / or cell survival rate.

[0087] The term "dynamic measurement" (also known as "real-time measurement") refers to the measurement of a specified parameter that is continuously or frequently monitored during the exposure of a 3D cell culture or tissue to at least one anticancer drug (including the time of exposure interruption). Preferably, dynamic measurement of cell growth and / or cell viability refers to dimensional determination, such as diameter, volume, or optical cross-sectional area.

[0088] Common cell-based drug screening and monitoring methods are based on 2D cell culture, among which,

[0089] (i) Cells are plated at a density of 2,500–20,000 cells per well on a multi-well plate.

[0090] (ii) Exposing plate-forming cells to the test drug, and

[0091] (iii) Determine the cell response to exposure by means of cell viability assays or cytotoxicity assays (i.e., how many cells are killed within a specified treatment period, typically 48–72 hours).

[0092] Therefore, these assays rely on a single-point analysis of the drug's effect on cells. In contrast, the method described above analyzes the drug's effect on cells over time. This method truly reflects the in vivo situation more accurately, showing how tumors are exposed to a single dose and respond over time.

[0093] Furthermore, the parameters analyzed in these tests (survival rate or cytotoxicity) do not conform to the parameters specified in the RECIST guidelines (i.e., size). Therefore, the method according to the above-described implementation is more in line with RECIST standards and thus better reflects the clinical effects of successfully tested drugs.

[0094] In other words, drugs that exhibit activity in the methods described above are more likely to achieve clinical success than drugs that have been screened using existing cell-based drug screening methods.

[0095] According to one embodiment of this application, the size, relative size, and / or relative size variation are determined in a time period of more than 1 day and less than 30 days by any one of steps a), b), and / or c).

[0096] Preferably, the relative dimensions and / or relative size variations are determined over a period of more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, and / or 30 days.

[0097] According to one embodiment of this application, 3D microtissues are exposed to an active pharmaceutical compound (step a) or a composition containing two or more active pharmaceutical compounds (steps b and c) only once by administering a specified single dose.

[0098] The specified single dose reflects the dose determined in step a) of the above-mentioned range search.

[0099] According to one embodiment of this application, 3D microtissues are exposed to an active pharmaceutical compound (step a) or a composition containing two or more active pharmaceutical compounds (steps b and c) more than twice by each application of a specified single dose.

[0100] In this embodiment, a clinical dosing regimen can be reproduced, in which a patient receives multiple doses of a drug or combination of drugs, with a pause between doses. Under such a clinical regimen, tumors sometimes develop adaptive resistance to the specified therapy. The above-described embodiment is suitable for demonstrating whether a particular tumor type may develop adaptive resistance to a specific combination of drugs.

[0101] Chemotherapy or antibody therapy is typically administered to patients using intermittent dosing regimens. In these treatment regimens, blood drug concentration is a function of dose and dosing interval.

[0102] See, for example, Cartron et al., 2007. Figure 1 B (in this article) Figure 9(Reproduced), which shows that in intermittent dosing regimens, blood drug titers decrease rapidly between different doses.

[0103] According to one embodiment of this application, a composition containing two or more active pharmaceutical compounds is removed after being exposed to micro-tissue for a specified period of time.

[0104] Removal can be performed by replacing the culture solution containing the composition with a suitable culture solution that does not contain the composition. This replacement can be done in one step or in multiple incremental steps to better reproduce the gradual decrease in the patient's drug titer between different drug administrations.

[0105] According to one embodiment, the 3D microtissue is exposed to an active pharmaceutical compound for a period of less than 8 hours (step a) or to a composition containing two or more active pharmaceutical compounds (steps b and c).

[0106] In one non-limiting embodiment, in any RFS, CSS, and / or CVS, tissues are exposed to a composition containing two or more active pharmaceutical compounds for 6 hours on day 1. Subsequently, the drug combination is gradually replaced with a drug-free culture medium over another 6 hours, or in one step. The tissues are then incubated in a drug-free culture medium, and on day 3, the tissues are again exposed to a composition containing two or more active pharmaceutical compounds for 6 hours.

[0107] In high-throughput systems, physiological parameters are routinely determined from day 1 up to, for example, day 30, to determine the long-term effects of exposure.

[0108] In another non-limiting embodiment, tissues are exposed to a composition containing two or more active pharmaceutical compounds for 6 hours on day 1. Subsequently, the drug combination is gradually replaced with a drug-free culture medium over another 6 hours, or in one step. The tissues are then incubated in a drug-free culture medium, and on day 3, the tissues are again exposed to a composition containing two or more active pharmaceutical compounds for 6 hours. In high-throughput systems, physiological parameters are routinely determined from day 1 until, for example, day 30, to determine the long-term effects of exposure.

[0109] Tables 2 and 3 below illustrate some preferred operating procedures that can be used in the content of this application. It should be noted that, contrary to what is shown in the tables, the determination of dimensions can be performed continuously, at intervals of one hour or one day, or at specific selected time points.

[0110] Table 2. Operation Plan 1

[0111]

[0112] Table 3. Operation Plan 2

[0113]

[0114] According to another embodiment of this application, an additional composition toxicity test (CTS) step is provided, in which (i) microtissues representing connective tissue are exposed to the composition of step b), and / or (ii) tissue-specific microtissues are exposed to the composition of step c), to characterize the physiological effects of the composition on the microtissues.

[0115] Different types of micro-tissues can be used. Specifically, it is important to understand that in this step, [the following is related to...] Figure 2 The different representations (i) represent connective tissue micro-tissues and / or (ii) tissue-specific micro-tissues are not necessarily 3D micro-tissues. However, in one embodiment, (i) represent connective tissue micro-tissues and / or (ii) tissue-specific micro-tissues are 3D micro-tissues.

[0116] As used in this article, “micro-tissue representing connective tissue” refers to micro-tissue containing connective tissue cells such as fibroblasts.

[0117] Methods for generating such micro-tissues are described, for example, in Kelm et al., J Biotechnol. 2005 Aug 4;118(2):213-29, the contents of which are incorporated herein by reference.

[0118] As used in this article, "tissue-specific microtissue" refers to microtissue composed of cells representing toxicity-sensitive tissues. Examples of cells representing toxicity-sensitive tissues include:

[0119] - Primary hepatocytes, hepatocyte lines, or hepatocyte-derived stem cells (also referred to as "liver models" in this article), or

[0120] - Primary cardiomyocytes, cardiomyocyte lines, or stem cells derived from cardiomyocytes (also referred to as “heart models” in this article).

[0121] The methods for generating this liver model are described in, for example, Tuschl et al, Chem Biol Interact. 2009 Sep 14; 181(l):124-37 (sandwich culture); Bokhari et al, J Anat. 2007 Oct; 211(4):567-76. (scaffolded liver model); Beckwitt et al, Exp Cell Res. 2018 Feb 1;363(1): 15-25 (liver microarray); Proctor et al., D. Arch Toxicol. 2017 Aug; 91(8):2849-2863 (3D liver microtissue), the contents of which are incorporated herein by reference.

[0122] Methods for generating heart models are documented in, for example, Sidorov et al., Acta Biomater. 2017 Jan15; 48:68-78 (Heart on a Chip); Giacomelli et al., Development. 2017 Mar 15;144(6): 1008-1017 (3D Microtissue); Hansen et al., T.Circ Res. 2010 Jul 9; 107(1):35-44 (Genetically Modified Heart Tissue), the contents of which are incorporated herein by reference.

[0123] Micro-tissues representing connective tissue and tissue-specific micro-tissues were used as reference models to obtain non-growth-specific cytotoxicity, as well as total cytotoxicity, such as hepatotoxicity and cardiotoxicity.

[0124] In addition to evaluating the combined effects of better tumor killing, the method of this application allows for the collection of information on the extent to which the combination increases in vitro toxicity. This enables not only the demonstration of combined effects but also the direct identification of any significant changes in toxicity before entering preclinical development.

[0125] Moreover, drug combinations allow for lower concentrations of individual drugs, potentially leading to reduced toxicity. This effect could be a very important value driver.

[0126] Therefore, the physiological effects characterized in CSS and CVS can be regarded as therapeutic effects, while the physiological effects characterized in CTS are toxic effects.

[0127] In one implementation, the operational procedures performed in the CTS, where technically feasible, are the same as or nearly the same as those in steps b) (CSS) and c) (CVS), including, for example, the following parameters:

[0128] - Microtissue size, microtissue weight, or number of cells in the microtissue.

[0129] - Dosage of a composition containing two or more active pharmaceutical compounds.

[0130] - Exposure time points for compositions containing two or more active pharmaceutical compounds.

[0131] - The composition of the culture medium, and / or

[0132] - Cultivation conditions, such as pH, temperature, O2 / CO2 flow rate, etc.

[0133] In one implementation, the physiological effects characterized in CTS are the size of micro-tissues representing connective tissue and / or tissue-specific micro-tissues.

[0134] Dimensions can be actual dimensions, relative dimensions, and / or relative changes in dimensions over time. Dimension determination refers to at least one parameter selected from the following:

[0135] - diameter,

[0136] - Perimeter,

[0137] - Volume, and / or

[0138] - Optical cross-sectional area.

[0139] In another implementation, the physiological effects characterized in CTS are survival and / or cytotoxicity. Examples of these assays are documented, for example, in Kijaska & Kelm J. In vitro 3D Spheroids and Microtissues: ATP-based Cell Viability and Toxicity Assays. Assay Guidance Manual [Internet]. Bethesda (MD): Eli Lilly & Company and the National Center for Advancing Translational Sciences; 2004–2016 Jan 21, the contents of which are incorporated herein by reference.

[0140] In general, long-term studies show that survival and cytotoxicity assays are more resource-intensive, requiring more sample material. This is typically because determining the IC (increased concentration) in survival or cytotoxicity assays involves significant resource requirements. 50 IC 50This indicates the drug concentration at which 50% of the sample material is killed. Therefore, in experimental protocols that measure cellular or tissue responses over time (e.g., to obtain the effect of long-term exposure or to identify potential resistance), each test requires its own micro-tissue; that is, if, for example, five measurements are needed over time, five tissues are required. This is the opposite of the approach in this application, where the method measures micro-tissue changes, such as size changes, as a response to drug exposure, in which the tissue survives; that is, if, for example, five measurements are needed over time, they can be performed on only one tissue.

[0141] As mentioned above, the 3D micro-tissue used in step c) (CVS) is derived from primary patient tumor samples. This material is typically not available in large quantities. For this reason, resources must be used efficiently, which makes the aforementioned sizing determination advantageous.

[0142] In contrast, the materials used to generate micro-tissues and / or tissue-specific micro-tissues representing connective tissue used in CTS are, in some cases, readily available, suggesting that the higher resource requirements associated with survival or cytotoxicity assays are tolerable.

[0143] On the other hand, the physiological effects characterized in CSS and CVS are therapeutic effects, which, as mentioned above, are advantageously determined through long-term size determination to specifically mimic the constantly changing serum titers of tumors exposed to drugs or drug combinations, and the in vivo conditions of developing or not developing resistance, or to obtain other dynamic effects. Furthermore, disease progression in response to drug exposure can be obtained.

[0144] Conversely, it is not necessary to measure toxic effects over time, as it is not necessary to determine the dynamics of the toxic response. Therefore, in one embodiment, in a CTS, the physiological effects of tissue exposure to the pharmaceutical composition are characterized only once, preferably by survival assays or cytotoxicity assays.

[0145] In one implementation, at least one of these micro-tissues further undergoes a step of obtaining a molecular map, as described above. Thus, the molecular map of the tissue under study can be correlated with the physiological response (CTS) to combination drug exposure.

[0146] By simultaneously or asynchronously detecting the in vitro toxicity of the screened combination drugs, an in vitro-based risk assessment can be generated and compared with the toxicity profile of standard therapeutic agents. In addition to increasing the potency of the combination drugs, drug concentrations can also be reduced, thereby reducing side effects without compromising potency. This can be assessed simply by incorporating toxicity evaluation at an early stage.

[0147] (i) micro-tissues representing connective tissue, and / or (ii) tissue-specific micro-tissues, can be obtained from the same patient from whom primary patient samples were obtained. This ensures a high degree of genetic matching between the two micro-tissues, thereby guaranteeing a high degree of cross-referencing between results obtained using different 3D micro-tissues.

[0148] In another embodiment, (i) a library of 3D micro-tissues representing connective tissue and / or (ii) tissue-specific micro-tissues may be prepared from different test individuals or patients, and the library may be used as a reference library of 3D micro-tissues representing connective tissue and / or tissue-specific micro-tissues for cytotoxicity testing.

[0149] This implementation is particularly useful if tissue samples for creating tissue-specific microtissues can be obtained from patients who have obtained tumor samples, for example, when the patient's condition is very serious.

[0150] In this context, different members of the library can be characterized at the molecular level and selected for corresponding tests based on their molecular maps.

[0151] like Figure 2 As exemplified, tests relating to (i) 3D micro-tissues representing connective tissue and / or (ii) tissue-specific micro-tissues can be performed simultaneously with steps b), c) and / or a), or can be performed at different times and / or locations, for example, to create a reference database containing toxicity data (non-growth-specific cytotoxicity and total cytotoxicity) for a particular pharmaceutical composition.

[0152] In this case, the heart and liver are the most common targets of toxic effects of anticancer chemotherapy drugs.

[0153] Hepatotoxicity refers to liver damage caused by compounds. Drug-induced liver injury is a cause of both acute and chronic liver disease. The liver plays a crucial role in the transformation and clearance of compounds and is highly susceptible to the toxicity of these drugs. Some drugs, when used in excess, or even sometimes within the therapeutic range, can damage the organ. Other chemicals, such as those used in laboratories and factories, natural chemicals (e.g., microcystins), and herbal remedies, can also cause hepatotoxicity. Chemicals that cause liver damage are called hepatotoxicants.

[0154] It has been shown that over 900 drugs can cause liver damage, and this is the most common reason for drug withdrawals from the market. Hepatotoxicity and drug-induced liver injury also lead to the failure of a large number of compounds, highlighting the urgent need for drug screening tests early in drug development that can detect cytotoxicity to hepatocytes, such as stem cell-derived cells. Chemicals often cause subclinical liver damage, which may only manifest as abnormal liver enzyme tests. Drug-induced liver injury accounts for 5% of hospitalizations and 50% of all acute liver failures.

[0155] Cardiotoxicity refers to the occurrence of cardiac electrophysiological dysfunction or muscle damage. The heart becomes fragile and no longer pumps and circulates blood efficiently.

[0156] Cardiotoxicity can be caused by chemotherapy, complications of anorexia nervosa, adverse reactions to heavy metal intake, or improper administration of drugs such as bupivacaine.

[0157] Therefore, this implementation method performs organ-specific toxicity assessments in a preclinical setting. Based on the above, optionally, the two screening steps convey the following information:

[0158] CSS (Composition Selection Screening)

[0159] • Combination therapy

[0160] • Permeability / Bioavailability

[0161] • Non-specific toxicity

[0162] CVS (Composition Validation Screening)

[0163] • Tumor-specific concentration

[0164] • Combination therapy

[0165] • Patient stratification

[0166] Organ-specific toxicity

[0167] According to one embodiment of this application, at least one 3D microtissue is generated in a hanging drop culture system or a low-adhesion pore culture system.

[0168] An example of a hanging drop culture system is GravityPLUS manufactured by InSphero AG, Schlieren, CH. TM Hanging drop system. This system enables the aggregation of single cells into functional 3D micro-tissues without the need for a scaffold, because it does not provide a liquid / solid interface for cell adhesion.

[0169] An example of a low-adhesion well culture system is the Costar® ultra-low adhesion multi-well plate manufactured by Coming®, or InSphero's GravityTRAP. TM Plates. These plates contain non-adhesive coated pores, which prevent cells from adhering to the solid interface, thus enabling the formation of 3D cell cultures or tissues.

[0170] According to one embodiment of this application, the molecular map of at least one 3D microtissue is associated with at least one parameter characterizing physiological effects obtained in composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

[0171] In addition, molecular mapping can be performed using microtissue samples used in the range finding step (RFS) and / or composition toxicity testing step (CTS) to correlate with at least one parameter characterizing physiological effects.

[0172] According to one embodiment, the molecular map of at least one 3D microtissue is associated with at least one parameter characterizing physiological effects obtained in composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

[0173] In addition, or independently, at least (i) a molecular map of a microtissue representing connective tissue and / or (ii) a tissue-specific microtissue may be associated with at least one parameter characterizing toxicity obtained in the composition toxicity test (CTS) step.

[0174] According to another implementation, the method further includes the step of creating or expanding a database using a data set containing at least the following entries:

[0175] a) At least one molecular map of at least one 3D microstructure, and

[0176] b) At least one parameter characterizing the physiological effect obtained in the composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

[0177] Alternatively, or independently, a database can be created or expanded using a data group that contains at least the following entries:

[0178] a) at least (i) a microtissue representing connective tissue and / or (ii) at least one molecular map of a tissue-specific microtissue, and

[0179] b) At least one parameter characterizing toxicity obtained in the composition toxicity test (CTS) step.

[0180] According to one embodiment of this application, the method further includes the step of creating or expanding a database using a data group that contains at least the following entries:

[0181] a) At least one molecular map of at least one 3D microstructure, and

[0182] b) At least one parameter characterizing the physiological effect obtained in the composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

[0183] In addition, molecular maps of microorganisms and parameters characterizing their physiological effects used in the Range Search Step (RFS) and / or Composition Toxicity Test Step (CTS) can also be included in this database.

[0184] According to another aspect of this application, a method is provided for screening a plurality of compositions containing two or more active pharmaceutical compounds, preferably from one or more libraries, the method comprising:

[0185] (i) Applying any two or more methods described above, using different compositions containing two or more active pharmaceutical compounds in each method, and / or

[0186] (ii) Several sets of steps b), c), and optionally a).

[0187] According to one embodiment of this application, the differences between compositions containing two or more active pharmaceutical compounds are as follows:

[0188] a) The composition of the active pharmaceutical compound, or

[0189] b) The dosage or concentration of the active pharmaceutical compound in the composition.

[0190] According to one embodiment of this application, the method further includes at least one step selected from the following:

[0191] a) Synthesize the active pharmaceutical compound contained in the composition.

[0192] b) To create a composition containing two or more active pharmaceutical compounds, and / or

[0193] c) Create a library of active pharmaceutical compounds contained in the above compositions and / or compositions containing two or more active pharmaceutical compounds.

[0194] According to another aspect of this application, a method for creating a database is provided, in which a molecular map of at least one 3D microorganism is associated with the results of a composition selection screening (CSS) or composition validation screening (CVS) of the 3D microorganism.

[0195] According to one embodiment, a molecular map of at least one 3D microtissue is associated with at least one parameter characterizing physiological effects obtained in composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

[0196] In addition, or independently, at least (i) a molecular map of a microtissue representing connective tissue and / or (ii) a tissue-specific microtissue may be associated with at least one parameter characterizing toxicity obtained in the composition toxicity test (CTS) step.

[0197] Similarly, in addition, or independently, a database can be created or expanded using a data set that contains at least the following entries:

[0198] a) at least (i) a microtissue representing connective tissue and / or (ii) at least one molecular map of a tissue-specific microtissue, and

[0199] b) At least one parameter characterizing toxicity obtained in the composition toxicity test (CTS) step. Attached Figure Description

[0200] Although this application has been explained and described in detail in the accompanying drawings and the foregoing description, these explanations and descriptions should be considered interpretive or exemplary, not restrictive. The invention is not limited to the disclosed embodiments. In carrying out the invention to be protected, based on a study of the drawings, description, and appended claims, those skilled in the art will be able to understand and effectively implement other modifications of the disclosed embodiments.

[0201] In the claims, the words "comprising" or "including" do not exclude the presence of other elements or steps, and the indefinite articles "a," "an," or "the" do not exclude a plurality. The fact that some methods are mentioned in different independent claims does not indicate that a combination of these methods cannot be used advantageously. No reference numerals in the claims should be interpreted as limiting the scope.

[0202] Figure 1 This illustrates various aspects of the concept of this application.

[0203] Figure 2 This document outlines the different methodological steps of this application. It should be noted that the steps indicated in italics are optional. It should also be noted that toxicity effect screening can be performed a) simultaneously or separately from RFS, CVS, and / or CSS, and / or b) using (i) 3D microtissues representing connective tissue and / or (ii) tissue-specific microtissues prepared from a library of (i) 3D microtissues representing connective tissue and / or (ii) tissue-specific microtissues prepared from the same patient from whom primary patient samples were obtained, or from different testers or patients.

[0204] Figure 3 This application illustrates one aspect of how tumor clinical characteristics can be modeled according to the so-called RECIST criteria. The tumor microtissue growth curve is relative to untreated or treated tumors treated with gemcitabine (500 mg / m²). 2 The study used pancreatic tumor microtissue samples to demonstrate that similar data can be generated from in vitro assays, preclinical animal data, and ultimately, in vivo human response data. It can be seen that the 3D microtissue size measurements accurately reflect the clinical characterization of the tumor in vivo. In vivo data were obtained from Lee et al., 2005.

[0205] Figure 4Examples of dose- and growth association studies using different concentrations of irinotecan are presented to determine which concentration ranges will be used in combination drug testing. To assess whether a concentration-dependent effect on tumor microtissue growth is observed, pancreatic microtumors were used and treated with specified concentrations of irinotecan. In short, pancreatic cancer cell line Panc-1 (ATCC® CRL-1469) TM ) and mouse fibroblast cell line NIH3T3 (ATCC®CRL-1658) TM Pancreatic microtumors were prepared through co-incubation. Both cell types were expanded in cell culture flasks using Dulbecco Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum. After confluence, the cells were digested with trypsin in the cell culture flasks. Cell counts of both cell types were assessed using a Neubauer cell counting chamber, and the cell counts were mixed to prepare co-cultured microtumors. 70 μl of the cell mixture was seeded into non-adhesive 96-well plates (GravityTRAP) using Dulbecco Modified Eagle Medium (DMEM) supplemented with 10% horse serum. TM Pancreatic microtumors were cultured in each well of a mammalian cell culture incubator at 37°C and 5% CO2. Four days after cell formation of pancreatic tumor microtissues, irinotecan was administered at a specified concentration adjusted for clinical use. The size of the pancreatic microtumors was continuously monitored before and after administration using a bright-field microscope 48 hours after drug removal by replacing the medium with drug-free medium. Growth is presented as a relative measure of the pancreatic tumor microtissue size (t0) before compound treatment (adjusted according to RECIST criteria). A clear dose-to-growth correlation was observed.

[0206] Figure 5 This demonstrates the preparation method for pancreatic microtumors (in...). Figure 4 The single-drug and combination effects (as described in the text) were evaluated. All drugs used were dissolved according to the manufacturer's instructions. Gemcitabine (approved for PC), docetaxel (approved for PC), and pemetrexed (not approved), which inhibit DNA and RNA synthesis, were administered at 8-hour intervals of 48 hours. Figure 5 A). Pemetrexed did not affect tumor growth compared to gemcitabine and docetaxel, confirming the specificity of the method described in this application. Gemcitabine exerted its effect quickly, while the response to docetaxel was much slower. However, microtumor recurrence occurred after 10 days of gemcitabine treatment, while docetaxel treatment was more durable. Figure 5 A). Combining the two drugs elicits a faster and more lasting response. Figure 5 B).

[0207] Figure 6This illustrates single-drug and combination treatments for a non-small cell lung cancer (NSCLC) model. The NSCLC model was modeled using non-adhesive 96-well plates (GravityTRAP). TM A549 NSCLC cells (ATCC® CCL-185) were mixed in TM ) and human lung fibroblasts (Wi38, ATCC® CCL-75) TM The drug was prepared by [preparation method]. It was administered twice, 8 hours apart, with a 48-hour interval. Although pemetrexed had no effect on pancreatic microtumors, we observed tumor remission in NSCLC microtumors. Figure 6 A). Combining gemcitabine and irinotecan resulted in a slightly higher potency compared to monotherapy.

[0208] Figure 7 The basic steps of the method according to this application are shown, along with optional implementations (in italics). The entire method enables the generation of a database containing these data sets based on 3D-based functional data on the efficacy and toxicity of a specified drug combination, and corresponding 3D microtissues from one or more cancer cell lines, 3D microtissues from primary patient samples, 3D microtissues representing connective tissue, and / or gene maps of tissue-specific microtissues.

[0209] Figure 8 This demonstrates that the key to efficient discovery of combination drugs is maintaining high throughput without losing biological relevance. Figure 8 The example illustrates the verification phases that yield the best results from the selected combinations, with the number of relevant data points decreasing progressively in each phase. "B" refers to step b) (CSS) in claim 1, while "C" refers to step c) (CVS) in claim 1.

[0210] Figure 9 The image shows serum drug titers as a function of time during eight injections administered every 21 days. Serum titers decreased rapidly again between administrations. Tumor tissue retention time was measured in almost hours due to drug clearance from the body. Image courtesy of Cartron et al, 2007.

[0211] Figure 10This study demonstrates a combination drug test in mice using xenografts derived from two different non-small cell lung cancer (NSCLC) cell lines (A549 and FICC827) and a patient-derived xenograft (HCC4087). Data show a significant synergistic effect between erlotinib (approved for NSCLC, a tyrosine kinase) and thalidomide (unapproved, an immunomodulatory agent) as monotherapy in mouse models. The work by Gong et al. forms the basis for evaluating whether 3D in vitro assays can be extrapolated to in vivo results (Gong et al., 2018), such as… Figure 11 and Figure 12 As shown.

[0212] Figure 11 The study demonstrates single-drug and combination treatments using cell line-based non-small cell lung cancer models (A549, Wi38), such as... Figure 6 As described in [the original text]. Single-drug and drug combination administration were performed twice, 8 hours apart, with growth monitored over time. Drug concentrations were adjusted according to Gong et al. As shown by Gong et al., thalidomide had no significant effect on slowing tumor growth in vivo, while erlotinib caused reduced growth, but growth recovered after 7 days. Administration of the drug combination at twice the concentration resulted in a significantly better response over time, confirming the preclinical, animal-based results published by Gong et al.

[0213] Figure 12 For example, non-small cell lung cancer (NSCLC) cells directly derived from patients can be used to achieve... Figure 10 and 11 Similar results were shown. NSCLC excised tissue was dissociated, and the cell suspension was used to prepare porous microtumors. Figure 12 A). The drug was administered twice, 8 hours apart, with a 48-hour interval. Erlotinib and thalidomide monotherapy had little effect on tumor growth, but a significant response was observed when the two drugs were combined at a concentration three times lower. Figure 12 B displays the numerical values ​​of the relative dimensions for day 0 and day 9, which are normalized to day 0 according to the RECIST standard.

[0214] Figure 13 Examples of single-agent toxicity tests using connective / stromal microtissue (Wi38) and efficacy tests using non-small cell tumor microtissue (A549, Wi38) are presented. Vinorelbine and docetaxel, which disrupt microtubules, were administered twice, 8 hours apart. High-dose vinorelbine (0.68 μg / ml) showed higher toxicity compared to untreated stroma microtissue (4.05 μg / ml). Figure 13(A and C). In terms of efficacy, high concentrations of vinorelbine had a smaller impact on tumor growth compared to low and high concentrations of docetaxel. Figure 13 (B and D). Within the framework of compound classification, docetaxel is favorable for future development due to its lower toxicity and higher potency. Detailed Implementation

[0215] Example

[0216] This application enables coordinated analysis, from screening to testing using patient materials. This allows screening data to be retrospectively correlated with patient data. Two embodiments are summarized below in Tables 6 and 7.

[0217] Table 4. RECIST criteria for evaluating treatment outcomes

[0218] (Eisenhower et al. 2009, European Journal of Cancer)

[0219]

[0220] Table 5. Clinical adjustment test criteria for evaluating the success of a therapy

[0221]

[0222] Table 6. Case I

[0223] Pancreatic cancer treated with gemcitabine and irinotecan

[0224]

[0225] Table 7. Case II

[0226] Lung cancer treated with gemcitabine and irinotecan or combinations thereof

[0227]

[0228] References

[0229] Cartron G et al., Crit Rev Oncol Hematol. 2007 Apr;62(l):43-52. Epub2007 Feb 6.

[0230] Lee TK et al., Carcinogenesis. 2004 Dec;25(12):2397-405. Epub 2004Aug 5.

[0231] Gong et al., The Journal of Clinical Investigation 2018 June, 128(6)

[0232] Kelm et al., J Biotechnol. 2005 Aug 4;118(2):213-29

[0233] Tuschl et al., Chem Biol Interact. 2009 Sep 14; 181 (1): 124-37

[0234] Bokhari et al., J Anat. 2007 Oct; 211(4):567-76

[0235] Beckwitt et al., Exp Cell Res. 2018 Feb 1;363(1): 15-25

[0236] Proctor et al., D. Arch Toxicol. 2017 Aug;91(8):2849-2863

[0237] Sidorov et al., Acta Biomater. 2017 Jan 15; 48:68-78

[0238] Giacomelli et al., Development. 2017 Mar 15; 144(6): 1008-1017

[0239] Hansen et al., T. Circ Res. 2010 Jul 9;107(l):35-44

[0240] Kijanska & Kelm J. In vitro 3D Spheroids and Microtissues: ATP-basedCell Viability and Toxicity Assays. Assay Guidance Manual [Internet].Bethesda (MD): Eli Lilly & Company and the National Center for AdvancingTranslational Sciences; 2004-2016 Jan 21

[0241] Kelm et al, Drug Discov Today. 2018 Jul 30. Water: S1359-6446(18)30225.

Claims

1. A method for characterizing the physiological effects of a composition containing two or more active pharmaceutical compounds, the method comprising the following steps: b) Composition Selection Screening (CSS), in which one or more cell line-derived 3D microtissues are exposed to a composition containing two or more active pharmaceutical compounds, and / or c) Composition Validation Screening (CVS), in which 3D microtissue derived from primary patient samples is exposed to the composition of step b). To characterize the physiological effects of the composition on 3D microtissues.

2. The method according to claim 1, wherein, This method generates or determines at least one parameter representing the physiological effect being characterized.

3. The method according to claim 1 or 2, further comprising: a) Range finding step (RFS), in which multiple 3D microtissues from one or more cell lines are exposed to various compounds present in the composition at different concentrations to determine the appropriate concentration range of the compounds.

4. The method according to any one of the preceding claims, further comprising the step of obtaining a molecular map of at least one of the one or more cell line-derived 3D microtissues and / or 3D microtissues derived from the primary patient sample.

5. The method according to any one of the preceding claims, wherein the step of obtaining the molecular map is used to detect genomic abnormalities and / or mRNA or protein expression levels.

6. The method according to any one of the preceding claims, wherein the parameter representing the physiological effect is determined over time in at least one step of step a), b) and / or c).

7. The method according to any one of the preceding claims, wherein the parameter representing the physiological effect is the size of the 3D microtissue.

8. The method according to any one of the preceding claims, wherein the size is the actual size, relative size, and / or relative size change over time determined in at least one step in steps a), b) and / or c).

9. The method according to claim 7 or 8, wherein determining the size of the 3D microstructure refers to at least one parameter selected from diameter, perimeter, volume and / or optical cross-sectional area.

10. The method according to any one of claims 7-9, wherein the dimensions are determined in at least one step of steps a), b) and / or c) within a time period of more than 1 day and less than 20 days.

11. The method according to any one of the preceding claims, wherein the 3D microtissue is exposed to the active pharmaceutical compound of step a) or the composition containing two or more active pharmaceutical compounds of steps b) and c) only once by administering a specified single dose.

12. The method according to any one of the preceding claims, wherein the 3D microtissue is exposed to the active pharmaceutical compound of step a) or the composition containing two or more active pharmaceutical compounds of steps b) and c) more than twice by each application of a specified single dose.

13. The method according to any one of the preceding claims, wherein the composition containing two or more active pharmaceutical compounds is removed after exposure of the microtissue for a specified period of time.

14. The method according to any one of the preceding claims, further comprising a step of composition toxicity testing, wherein, (i) exposing micro-tissues representing connective tissue to the composition of step b), and / or (ii) Exposing tissue-specific micro-tissues to the composition of step c), To characterize the physiological effects of the composition on microtissues.

15. The method according to any one of the preceding claims, wherein at least one 3D microtissue is generated in a hanging drop culture system or a low-adhesion plate culture system.

16. The method according to any one of the preceding claims, wherein the molecular map of at least one 3D microtissue is associated with at least one parameter characterizing physiological effects obtained in composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

17. The method of claim 16, further comprising the step of creating or expanding the database with a data set containing at least the following entries: a) At least one molecular map of at least one 3D microstructure, and b) At least one parameter characterizing the physiological effect obtained in the composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

18. A method for screening multiple compositions containing two or more active pharmaceutical compounds, preferably from one or more libraries, the method comprising: (i) Applying two or more methods according to any one of the preceding claims, using different compositions containing two or more active pharmaceutical compounds in each method, and / or (ii) Steps b), c), and optional a) in multiple groups.

19. The method of claim 18, wherein the composition containing two or more active pharmaceutical compounds differs from each other in that... a) The composition of the active pharmaceutical compound, or b) The dosage or concentration of the active pharmaceutical compound in the composition.

20. The method according to any one of the preceding claims, further comprising at least one step selected from: a) Synthesize the active pharmaceutical compound contained in the composition. b) To create a composition containing two or more active pharmaceutical compounds, and / or c) Create a library of active pharmaceutical compounds contained in the above compositions and / or compositions containing two or more active pharmaceutical compounds.

21. A method for creating a database, wherein a molecular map of at least one 3D microtissue is associated with the results of a composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

22. The method of claim 21, wherein the molecular map of at least one 3D microtissue is associated with at least one parameter characterizing physiological effects obtained in composition selection screening (CSS) or composition validation screening (CVS) of the 3D microtissue.

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