Patent Application
20210396738
The present invention relates to a method of characterizing a composition comprising two or more active drug compounds, the method comprising the steps of: a) a composition selection screen (CSS), in which screen a candidate composition comprising two or more active drug compounds is tested against a 3D microtissue derived from one or more cell line, and b) a composition validation screen (CVS), in which screen the candidate composition of step b) is tested against a 3D microtissue derived from a primary patient sample (
The present invention relates to the screening of drug combinations for therapeutic purposes. Generally, drugs for therapeutic purposes are screened for efficacy in a conventional screening system, where drugs from a library are tested in a suitable cell-based assay. Usually, the viability of the cells and/or the cytotoxicity of the candidate drug is investigated.
This approach can often be done in high throughput, but incurs a high risk that drugs identified in such approach as promising will disappoint in the subsequent clinical testing. Furthermore, it has turned out that in specific fields of indication, drug combinations are increasingly used, e.g., to avoid the development of resistances, or to exploit synergistic effects.
So far, almost no systematic approaches have been disclosed to screen potential drug combinations at early stage. Conventionally, drugs are combined empirically, by medical practitioners, and tested in patients. However, a systematic approach to really investigate the combinatorial effects of such drug combination is missing. This means that a huge potential of promising drug combination exists but never sees the patient, for lack of systematic investigation.
Also, the predictability of early stage experiments to the future in vivo situation needs to be improved, in order to reduce the risk of failure of drug combinations that have turned out promising in the pre-clinic.
Further, there is a need to determine novel drug combinations faster, more efficiently and with sustainable therapeutic efficacy.
WO 2013/050962A1 relates to a tumor microenvironment platform for culturing tumor tissue comprising drugs, a method of predicting the response of a tumor to drugs and a method of screening or developing anti-cancer agents.
WO 2017/081260A1 relates to the use of a three-dimensional spheroid for the screening of potentially therapeutic agents, wherein said screening is a high-throughput screening of a library of potentially therapeutic agents.
US 2016/040132A1 refers to bioprinted three-dimensional pancreatic tumor tissues and a method of identifying therapeutic agents therefor.
None of said documents mentions the necessity of studying the combinatorial effect of two or more drugs, and the advantages of such newly identified drug combinations.
These and further objects are met with methods and means according to the independent claims of the present invention. The dependent claims are related to preferred embodiments. It is yet to be understood that value ranges delimited by numerical values are to be understood to include the said delimiting values.
Before the invention is described in detail, it is to be understood that this invention is not limited to the particular component parts of the devices described or process steps of the methods described as such devices and methods may vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only and is not intended to be limiting. It must be noted that, as used in the specification and the appended claims, the singular forms “a,” “an” and “the” include singular and/or plural referents unless the context clearly dictates otherwise. It is moreover to be understood that, in case parameter ranges are given which are delimited by numeric values, the ranges are deemed to include these limiting values.
Further, it is to be noted that documents or contents which are incorporated by reference herein are mainly meant to provide enabling disclosure, so as to avoid lengthiness of the text.
According to one embodiment of the invention, a method of characterizing a physiological effect of a composition comprising two or more active drug compounds is provided. The method comprises the steps of:
b) a composition selection screen (CSS), in which screen a 3D microtissue derived from one or more cell lines is exposed to said composition comprising two or more active drug compounds, and/or
c) a composition validation screen (CVS), in which screen 3D microtissue derived from a primary patient sample is exposed to the composition of step b), so as to characterize a physiological effect of said composition on the 3D microtissue.
It is important to understand that steps b) and c) can be carried out in the same location or in different locations. Step b) can for example be carried out in a laboratory that has access to cell lines, while step b) can be carried out in a laboratory that is closes to clinical site, and has for that reason access to primary patient samples.
In one embodiment, the protocols carried out in steps b) and c), including parameters such as for example
This allows a high degree of reproducibility and comparability of results obtained in step b) (CSS) and c) (CVS), as well as a standardization between the two steps. Further, the 3D model enables to work within the same format, independent of the cell source. By contrast, in 2D models it is sometimes not easy to have tumor cells grow in culture. Further, this approach allows a high degree of automatization in both steps.
Generally, some regulatory authorities demand that, when a combination of two or more standard of care drugs is applied for, an added patient value of such combination is demonstrated. The above approach can deliver data supporting such added value already at a very early stage of development, by providing two independent screening stages early in the process under similar experimental conditions.
As used herein the terms “microtissue exposed to a composition” and “composition tested against a microtissue” mean essentially the same. A “composition comprising two or more active drug compounds” will also be called “drug combination” or “combination of drugs” herein.
As used herein the terms “active drug compound” relates to the ingredient in a pharmaceutic that is biologically active. The term is used interchangeably with the term “active pharmaceutical ingredient (API)”.
A “3D microtissue derived from one or more cell lines” is a 3D multi-cellular 3D microtissue comprising at least one cell line selected from the group consisting of
A “3D microtissue derived from a primary patient sample” is a 3D multi-cellular 3D microtissue as obtained from dissociated tumors, as e.g. obtained from tumor biopsies, tumors obtained from surgery, organ donations, and the like.
The cells used for such 3D microtissue can be fresh, e.g., taken directly after biopsy or surgery, or can be cryopreserved cells.
Generally, in order to produce 50.000 3D microtissues, a total of 12.5 mio-25 mio cancer cells are required. While large tumors surgically removed from a patient often comprise such large numbers of cells, patient tumor material obtained by a biopsy will usually have less cells.
For this reason, in step b), a 3D microtissue derived from one or more cell lines is used. This provides the advantage that such cell material is available in large quantities, hence allowing the acquisition of a large number of data points. This is necessary, inter alia, for screening through large libraries of drug combinations, at different concentrations.
In step c) such 3D microtissue derived from a primary patient tumor sample is used. This material is usually not available in large quantities.
However, the concept of 3D microtissues allows to generate a sufficient number of micromodels of tumors from a patient sample. These micromodels faithfully reflect the physiology and genetics of a real tumor, instead of cancer cell lines, which very often differ in physiology and genetics from a real tumor.
Hence, this approach allows already to screen drug combinations for a specific patient cohort or patient stratum, and is thus an important step to provide a clinical or therapeutic response to the demands posed by increasing patient stratification.
3D microtissues are preferably cultured in a particular vessel, e.g. a microreaction vessel or a well of a microtiter plate. Exposing the 3D microtissues to a drug or drug combination means, for example, that said anti-cancer agent means is added to that vessel, e.g., by means of a suitable pipette, pipetting robot or dispenser.
3D microtissues provide a more representative, organotypic model for assessment of tumor growth. They contain layers of cells that exhibit more in vivo-like size- and gradient-dependent proliferation and viability profiles. Further, 3D microtissues allow to recapitulate the native tumor microenvironment. For these reasons, cells in a 3D microtissue behave more physiologically than cells in 2-dimensional cell culture, because they can better establish intercellular communication pathways as well as extracellular matrices. Furthermore, 3D microtissues better reflect physicochemical conditions in a true tissue or organ, because it better simulates diffusion gradients of both gases, like oxygen, and chemical agents. Further, they better simulate penetration barriers for larger components.
Still another advantage is that a 3D microtissue derived from cell lines also allows to tailor a cancer model which faithfully reflects a true tumor, by combining drug resistant and sensitive cells within the same tissue to specifically monitor drug effects on either cell population.
Further, compared to 2-dimensional cell cultures, 3D microtissues have a significantly higher lifetime. While 2-dimensional cell cultures comprising non-immortalized primary cells have an assay lifetime of 3-7 days, 3D microtissues have a lifetime of up to 30 days or even longer, making them suitable for long term investigations of the 3D microtissues to drug exposure—just like in an in vivo situation, where a tumor responds on drug administration's given as singular bolus over an extended period of time.
Yet another advantage is that, while 2-dimensional cell cultures allow mere quantification of resistant colonies (endpoint measurement), 3D microtissues according to the invention allow to observe the short- and longtime kinetic of a tissue response on drug exposure.
Furthermore, optionally, in either the CSS step and/or in the CVS step, control experiments are performed in which a reference drug is tested against one or more 3D microtissues derived from one or more cell lines and/or one or more 3D microtissue derived from a primary patient sample.
Such reference drug is preferably the standard of care for the disease against which the drug combination that is screened for should be active.
As an alternative, such reference drug is preferably the standard of care (SOC) for the disease represented, or modeled, by the 3D microtissue derived from one or more cell lines and/or the 3D microtissue derived from a primary patient tumor sample.
The following table shows typical SOC treatments for pancreatic and non-small cell lung cancer:
In such way, an added value (efficacy) of a novel drug combination compared to current standard of care drugs can be demonstrated very early on.
In one embodiment, each drug combination is tested against a plurality of 3D microtissues derived from one or more cell line, and/or against a plurality of 3D microtissues derived from a primary patient sample.
In one embodiment, each drug combination is 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.
In one embodiment, each drug combination is tested against ≥2, ≥3, ≥4, ≥5, ≥6, ≥7, ≥8, ≥9, ≥10, ≥15, ≥20, ≥25, or ≥30 3D microtissues derived from a primary patient sample.
In one approach, each drug combination is tested against between ≥2 and ≤10 (preferably against between ≥3 and ≤5) 3D microtissues derived from one or more cell lines, and against between ≥5 and ≤50 (preferably against between ≥10 and ≤30) 3D microtissues derived from a primary patient sample.
This allows a very detailed patient specific efficacy stratification of the different drug combinations, and hence increases the likelihood that a drug combination that demonstrates promising results in the CVS step in a given 3D microtissue derived from a primary patient sample will also be successful in the clinic, in particular in a patient cohort that corresponds to the respective 3D microtissue.
In one embodiment, this approach is combined with molecular profiling of the respective tissues, as discussed below, to further stratify the respective 3D microtissues derived from primary patient samples and match them with respective patient cohorts.
According to one embodiment of the invention, at least one parameter representing the characterized physiological effect is generated or determined in the method. Such parameter is for example size or viability.
According to one embodiment of the invention, the method further comprises a range finding step a) (RFS), in which step a plurality of 3D microtissues derived from one or more cell lines are exposed to different concentrations of each compound of the candidate composition, so as to determine suitable concentration ranges of the compounds.
This range finding step can have a particular importance, in particular when drug compounds are chosen which have already been used in the clinic. It might be tempting, for such drug compounds, to use the dosage that has been established in the clinic, however, such dosage may turn out difficult to down- or upscale to the 3D microtissue environment. Generally, clinical dosages are indicated as mg/kg or mg/m2. It is obvious that such dosages, which have been established for systematic administration in a human patient, cannot simply be extrapolated to an in vitro setting with 3D microtissues.
Again, in this step, 3D microtissues derived from one or more cell lines are used. This provides the advantage that such cell material is available in large quantities, hence allowing the acquisition of a large number of data points. This is necessary, inter alia, for screening through large libraries of drugs, at different concentrations.
Hence, the dosage range finding step provides useful information which allows the subsequent screening steps to operate with physiologically relevant drug concentrations which may give indications for the relative doses in pre-clinical assessment.
Another advantage is that the range finding results in combination with the single treatment data from the CCS stage can be used as quality control parameter to check reproducibility. This helps to benchmark drug combinations can be benchmarked against single drug effects. Single drug effects should match growth profiles of the range step of respective concentrations.
According to one embodiment of the invention, the method further comprises a step of obtaining a molecular profile of at least one of:
a) the 3D microtissues derived from one or more cell line, and/or
b) the 3D microtissues derived from a primary patient sample,
According to one embodiment of the invention, the step of molecular profiling is used to detect genomic aberrations, and/or mRNA or protein expression levels.
Such step of molecular profiling can comprise at least one of the steps shown in the following table 1:
In such way, the molecular profile of the tissue under investigation can be correlated to the physiological response thereof to exposure to the drug (RFS) or drug combination (CSS, CVS).
According to one embodiment of the invention, the parameter representing the characterized physiological effect is determined over time in at least one of step a), b) and/or c).
This allows to, to inter alia mimic the in vivo situation where a tumor is exposed to changing serum titers of a drug or drug combination, and may or may not develop resistances, or to capture other kinetic effects. Further, disease progression in response to the drug exposure can be captured.
According to one embodiment of the invention, the parameter representing the characterized physiological effect is the size of the 3D microtissue.
According to one embodiment of the invention, the size, relative size and/or the relative size change over time is determined in at least one of step a), b) and/or c).
These approaches mimic the clinical characterization of tumors, which is subject to the so-called RECIST criteria.
Response evaluation criteria in solid tumors (RECIST) is a set of published rules that define when tumors in cancer patients improve (“respond”), stay the same (“stabilize”), or worsen (“progress”) during treatment.
The RECIST specification establishes a minimum size for measurable lesions, limits the number of lesions to follow and standardizes unidimensional measures. Patients with measurable disease at baseline are included in protocols where objective tumor response is the primary endpoint, measured as size changes over time.
According to the respective guidelines, such size is preferably measured with CT and MRI (optical slice thickness of 10 mm or less). The guidelines emphasize that tumor markers alone cannot be used to assess response, while cytology and histology can be used in order to do so.
Hence, the approach according to the embodiment outlined above mimics, on an in vitro basis, the clinical characterization of a tumor's response to a given treatment. This is unique, and greatly enhances the predictive effect of the method according to this embodiment.
This means that drug combinations identified with the method according to this embodiment as potentially efficacious are less prone to fail in subsequent preclinical or clinical evaluation. In other words: the chance that drug combinations identified with the method according to this embodiment will prove successful in subsequent preclinical or clinical evaluation increases significantly as compared to methods according to the prior art.
According to one embodiment of the invention, the size determination of the 3D microtissue refers to at least one parameter selected from the group consisting of:
The size can thus either be a parameter that has directly been measured, or a parameter which has been calculated on the basis of such measurements.
Preferably, the size determination of the 3-dimensional cell culture or tissue is carried out by means of an imaging device.
One example of such imaging device is the Cell3iMager manufactured by SCREEN Holding Co., LTD, Japan. It allows analysis of spheroids by scanning multi-well plates in a bright-field. It computes estimated values based on spheroid size and density, together with spheroid number and area in each well. With easy and efficient operability, its vibration-free design protects cells from damage. An excellent application is also available to determine spheroid proliferation over time and to measure the granular distribution in 3D culture.
According to another preferred embodiment the determination of the effect of the anti-cancer agent exposure on the 3-dimensional cell culture or tissue is determined by
The term “kinetic measurement” (also called “real time measurement”) is related to those types of measurement in which a given parameter is monitored continuously or frequently during the exposure of the 3-dimensional cell culture or tissue to the at least one anti-cancer agent, including times of interruption of the exposure. Preferably, said kinetic measurement of cell proliferation and/or cell viability is a size determination, e.g., diameter, volume or area of an optical cross section.
Conventional cell-based drug screening assays work on the basis of 2D cell cultures, where
(i) cells are plated to a plating density of 2,500-20,000 cells per well of a multi-well plate
(ii) plated cells are exposed to the drugs to be tested, and
(iii) the cellular response on the exposure is measured by means of a cell viability assay or a cytotoxicity assay (i.e., how many cells have been killed after a defined treatment time, usually 48-72 h).
Hence, these assays rely on a one-point analysis of the drug impact on the cells. In contrast thereto, the method according to the above embodiment analyses the drug impact on the cells over time. This approach does more faithfully reflect the in vivo Situation, where a tumor is exposed to a drug bolus and then responds on it over time.
Further, the parameters that are analyzed in these assays (viability or cytotoxicity) do not comply with the parameters that are referred to by the RECIST guidelines (=size). Hence, the method according to the above embodiment is more compliant with the RECIST criteria, and hence more translatable with regard to the clinical impact of a drug that has successfully been tested.
In other words: A drug that has shown to be active in the method according to the above embodiment is more likely to be clinically successful than a drug that has stood a conventional cell-based drug screening assay.
According to one embodiment of the invention, the size, relative size and/or the relative size change is determined in at least one of step a), b) and/or c) over a period of >1 and <30 days.
Preferably, the size, relative size and/or the relative size change is 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.
According to one embodiment of the invention, the 3D microtissue is exposed to the active drug compound (step a) or to the composition comprising two or more active drug compounds (steps b and c) only once, by application of a defined bolus.
Said defined bolus reflects one dosage as determined in the range finding step a) as discussed above.
According to one embodiment of the invention, the 3D microtissue is exposed to the active drug compound (step a) or to the composition comprising two or more active drug compounds (steps b and c) two or more times, by application of a defined bolus each.
In this embodiment, a clinical administration scheme can be reproduced, where a patient receives a drug or drug combination several times, with pauses in between. In such clinical scenarios, tumors sometimes develop adaptive resistances to the given therapy. The embodiment discussed above is suitable to reveal whether a given tumor type would be likely to develop an adaptive resistance against a given drug combination.
Very often, chemotherapy or antibody therapy is given to a patient in an intermittent dosage regimen. In such treatment regimen, the serum concentration of the drug is a function of the amount of the dosage and the administration interval.
See for example
According to one embodiment of the invention, the composition comprising two or more active drug compounds is removed after the microtissue was exposed thereto for a given period of time.
Such removal may take place in such way that the culture solution comprising the composition is replaced by a suitable culture solution devoid of the composition. Such replacement can take place in one step, or in several incremental steps, to better reproduce the gradual decrease of drug titer in a patient, between the different drug administrations.
According to one embodiment, the 3D microtissue is exposed to the active drug compound (step a) or to the composition comprising two or more active drug compounds (steps b and c) for a duration of <8h.
In one non-limiting example, in any RFS, CSS and/or CVS, the tissue is exposed at day 1 to the composition comprising two or more active drug compounds for 6 hours. Then, the drug combination is replaced by drug free culture medium stepwise over further 6 hours, or in one step. The tissue is then incubated in drug free culture medium, and at day 3, the tissue is exposed again to the composition comprising two or more active drug compounds, again for 6 hours.
The determination of the physiological parameter takes place routinely, in a high throughput system, from day 1 one, and continues for example until day 30, to capture long term effects of the exposure.
In another non-limiting example, the tissue is exposed at day 1 to the composition comprising two or more active drug compounds for 6 hours. Then, the drug combination is replaced by drug free culture medium stepwise over further 6 hours, or in one step. The tissue is then incubated in drug free culture medium, and at day 3, the tissue is exposed again to the composition comprising two or more active drug compounds, again for 6 hours. The determination of the physiological parameter takes place routinely, in a high throughput system, from day 1 one, and continues for example until day 30, to capture long term effects of the exposure.
The following tables 2 and 3 show some preferred protocols that can be used in the context of the present invention. Note that, contrary to what is shown in the tables, the size determination can be carried out continuously, in hourly or daily intervals, or at specifically selected time points.
According to a further embodiment of the invention, a further step of composition toxicity testing (CTS) is provided, in which step
(i) a microtissue representing connective tissue is exposed to the composition of step b), and/or
(ii) a tissue specific microtissue is exposed to the composition of step c), so as to characterize a physiological effect of said composition on said microtissue.
Different types of microtissues can be used. In particular, it is important to understand that in this step, the (i) microtissue representing connective tissue and/or the (ii) tissue specific microtissue do not necessarily have to be a 3D microtissue, different to what
As used herein, a “microtissue representing connective tissue” is a microtissue that comprises connective tissue cells, like, e.g., fibroblasts.
Methods to generate such microtissues are for example disclosed in Kelm et al., J Biotechnol. 2005 Aug. 4; 118(2):213-29, the content of which is incorporated herein by reference.
As used herein, a “tissue specific microtissue” is a microtissue that has a cell composition that is representative for toxicity sensitive tissues, like e.g.
Methods to generate such liver models are for example disclosed in
Methods to generate such cardiac models are for example disclosed in
The microtissue representing connective tissue and the tissue specific microtissue serve as reference models to capture non-proliferation specific cytotoxicity, as well as general cytotoxicity, like e.g. hepatotoxicity and cardiac toxicity.
Next to assessing combinatorial effects to better kill a tumor, this approach allows to gather information to which extent the combination leads to increased toxicity in vitro. This allows not only to demonstrate combinatorial effects but directly whether there any severe changes in the toxicological profiles prior entering the pre-clinical development.
Moreover, drug combinations may allow to reduce single drug concentrations, which might lead to less toxicity effects. Capturing this effect can become an important value driver.
Hence, while in the CSS and CVS, the physiological effect that is characterized can be qualified as therapeutic efficacy, the physiological effect that is characterized in the CTS is a toxicity effect.
In one embodiment, the protocols carried out in the CTS are identical, or almost identical, as technically feasible, to those used in steps b) (CSS) and c) (CVS), including Parameters such as for example
In one embodiment, the characterized physiological effect in the CTS is the size of the microtissue representing connective tissue and/or the tissue specific microtissue.
The size can be is actual size, relative size and/or relative size change over time, and the size determination can refer to at least one parameter selected from the group consisting of:
In another embodiment, the characterized physiological effect in the CTS is viability and/or cytotoxicity. Examples for such assays are for example disclosed in Kijanska & 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 content of this document is incorporated by reference herein.
Generally, in long term studies, viability assays and cytotoxicity assay are much more resource intensive, i.e., they require more sample material. This is because, usually, in a viability assay or a cytotoxicity assay, an IC50 is determined, meaning the drug concentration upon which 50% of the sample material is dead. Hence, in a protocol where the cell or tissue response is to be measured over time (e.g., to capture the effects of elongated exposure, or the capture the development of potential resistances, each measurement would require its own microtissue (meaning that, if for example 5 measurements would be carried out over time, five tissues would necessary). This is contrary to an approach where e.g. size changes of a microtissue are measured as a response to drug exposure (which leaves the tissues alive), so (meaning that, if for example five measurements would be carried out over time, this can be done with only one tissue).
Now as discussed above, the 3D microtissues used in step c) (CVS) are derived from a primary patient tumor sample. This material is usually not available in large quantities.
For this reason, a responsible use of resources is necessary, which also makes the size determination as discussed above advantageous.
In contrast thereto, the material used for the production of the microtissue representing connective tissue and/or the tissue specific microtissue as used in the CTS can, under some circumstances, be available in larger quantities, suggesting that the higher demands as regards resources that are associated with a viability assay or cytotoxicity assay can be tolerated.
On the other hand, in the CSS and CVS, the physiological effect that is characterized is therapeutic efficacy, which is advantageously measured by size determination over time, as discussed above, to inter alia mimic the in vivo situation where a tumor is exposed to changing serum titers of a drug or drug combination, and may or may not develop resistances, or to capture other kinetic effects. Further, disease progression in response to the drug exposure can be captured.
In contrast thereto, a toxicity effect does not necessarily have to be measured over time, because the kinetics of the toxicity response are not always necessary to be determined. So, in one embodiment, in the CTS, the physiological effect of the tissue exposure to the drug combination is only characterized once, preferably by a viability assay or cytotoxicity assay.
In one embodiment, at least one of these microtissues is also subjected to a step of obtaining a molecular profile, as discussed above. In such way, the molecular profile of the tissue under investigation can be correlated to the physiological response thereof to exposure to the drug combination (CTS).
By simultaneously or not simultaneously assessing in vitro toxicity of the screened combinations it is possible to generate an in vitro-based risk-assessment and compare the toxicology profile against standard of care drugs. In addition to increased efficacy of combination drugs, it is hence possible to reduce drug concentrations, and, in such way, reduce side effects, without compromising efficacy. This can only be assessed by an early incorporation of toxicity assessment.
The (i) microtissue representing connective tissue, and/or (ii) the tissue specific microtissue, can be taken from the same patient as the primary patient sample. This ensures a high genetic match between the two microtissues, so as to warrant a high cross-referenceability of results obtained with the respective different 3D microtissues.
In another embodiment, a library of (i) 3D microtissues representing connective tissue, and/or (ii) tissue specific microtissues can be prepared from different test person or patients, which library then serves as a reference library for 3D microtissues representing connective tissue and/or tissue specific microtissues for testing cytotoxicity.
This embodiment can be useful in case it is impossible to obtain, from the patient from which the tumor sample has been obtained, also tissue samples for creating the tissue specific microtissues—e.g., when the patient is severely ill.
In such case the different members of said library can be characterized, molecularly, and can be selected for corresponding testing according to their molecular profiles.
As exemplarily shown in
In this context, cardiac and hepatic are the most frequent adverse event targets of anti-cancer chemotherapeutic drugs.
Hepatotoxicity implies chemical-driven liver damage. Drug-induced liver injury is a cause of acute and chronic liver disease. The liver plays a central role in transforming and clearing chemicals and is susceptible to the toxicity from these agents. Certain medicinal agents, when taken in overdoses and sometimes even when introduced within therapeutic ranges, may injure the organ. Other chemical agents, such as those used in laboratories and industries, natural chemicals (e.g., microcystins) and herbal remedies can also induce hepatotoxicity. Chemicals that cause liver injury are called hepatotoxins.
More than 900 drugs have been implicated in causing liver injury and it is the most common reason for a drug to be withdrawn from the market. Hepatotoxicity and drug-induced liver injury also account for a substantial number of compound failures, highlighting the need for drug screening assays, such as stem cell-derived hepatocyte-like cells, that are capable of detecting toxicity early in the drug development process. Chemicals often cause subclinical injury to the liver, which manifests only as abnormal liver enzyme tests. Drug-induced liver injury is responsible for 5% of all hospital admissions and 50% of all acute liver failures.
Cardiotoxicity is the occurrence of heart electrophysiology dysfunction or muscle damage. The heart becomes weaker and is not as efficient in pumping and therefore circulating blood.
Cardiotoxicity may be caused by chemotherapy treatment, complications from anorexia nervosa, adverse effects of heavy metals intake, or an incorrectly administered drug such as bupivacaine.
Hence, this embodiment delivers, at a preclinical state, organ specific toxicity assessments. One the basis of the above, the two screening steps deliver, optionally, the following information:
CSS (Combinatorial selection screen)
CVS (Combinatorial validation screen)
According to one embodiment of the invention, at least one 3D microtissue has been produced in a hanging drop culture System or a low adhesion well culture System.
One example of such hanging drop culture System is the GravityPLUS™ hanging drop system manufactured by InSphero AG, Schlieren, CH. This system allows scaffold-free re-aggregation of single cells into functional 3D microtissues, because it avoids the Provision of liquid/solid interfaces to which cells can adhere.
One example of such low adhesion well culture system Costar® ultra-low attachment multiple well plate manufactured by Coming® or the GravityTRAP™ plate from InSphero. These plates comprise non-adhesively coated wells which allow the formation of 3-dimensional cell cultures or tissues by avoiding adherence of the cells to the solid interface.
According to one embodiment of the invention, the molecular profile of at least one 3D microtissue is correlated with at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) or the composition validation screen (CVS) of said 3D microtissue.
Further, such correlation between molecular profile and the at least one parameter that characterizes the physiological response can also be done regarding the microtissues used in the range finding step/RFS) and/or the step of composition toxicity testing (CTS).
According to one embodiment, the molecular profile of at least one 3D microtissue is correlated with at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) or the composition validation screen (CVS) of said 3D microtissue.
In addition, or independently, the molecular profile of at least (i) one microtissue representing connective tissue and/or (ii) one tissue specific microtissue can be correlated with at least one parameter which characterizes the toxicity effect as obtained in the step of composition toxicity testing (CTS).
According to one other embodiment, the method further comprises the step of creating or feeding a database with datasets comprising at least the following entries each:
a) at least one molecular profile of at least one 3D microtissue, and
b) at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) or the composition validation screen (CVS) of said 3D microtissue.
In addition, or independently, a database can be created, or fed, with datasets comprising at least the following entries each:
a) at least one molecular profile of at least (i) one microtissue representing connective tissue and/or (ii) one tissue specific microtissue, and
b) at least one parameter which characterizes the toxicity effect as obtained in the step of composition toxicity testing (CTS).
According to one embodiment of the invention, the method further comprises the step of creating or feeding a database with datasets comprising at least the following entries each:
a) at least one molecular profile of at least one 3D microtissue, and
b) at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) or the composition validation screen (CVS) of said 3D microtissue.
Further, into such data base also molecular profiles and parameters that characterizes the physiological response regarding the microtissues used in the range finding step (RFS) and/or the step of composition toxicity testing (CTS) can be entered.
According to another aspect of the invention, a method of screening a plurality of compositions comprising two or more active drug compounds, preferably from one or more libraries, is provided, which method comprises
(i) the application of two or more methods as set forth in any of the aforementioned description, with a different composition of two or more active drug compounds in each individual method, and/or
(ii) several pairs of steps b), c) and optionally a).
According to one embodiment of the invention, the compositions comprising two or more active drug compounds differ from one another by
a) the composition of active drug compounds, or
b) the dosages or concentrations of the active drug compounds in the composition
According to one embodiment of the invention, the method further comprises at least one step selected from the group consisting of a) synthesizing the active drug compounds that are comprised in the compositions,
b) composing the compositions comprising two or more active drag compounds, and/or
c) creating a library comprising active drug compounds that are comprised in the compositions and/or compositions comprising two or more active drug compounds.
According to another aspect of the invention, the method of creating a database is provided, in which method the molecular profile of at least one 3D microtissue is correlated with the result of a composition selection screen (CSS) or a composition validation screen (CVS) of said 3D
According to one embodiment, the molecular profile of at least one 3D microtissue is correlated with at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) and/or the composition validation screen (CVS) of said 3D microtissue.
In addition, or independently, the molecular profile of at least (i) one microtissue representing connective tissue and/or (ii) one tissue specific microtissue can be correlated with at least one parameter which characterizes the toxicity effect as obtained in the step of composition toxicity testing (CTS).
Likewise, in addition, or independently, a database can be created, or fed, with datasets comprising at least the following entries each:
a) at least one molecular profile of at least (i) one microtissue representing connective tissue and/or (ii) one tissue specific microtissue, and
b) at least one parameter which characterizes the toxicity effect as obtained in the step of composition toxicity testing (CTS).
While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims.
In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent Claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the Claims should not be construed as limiting the scope.
a) simultaneously or not simultaneously with the RFS, CVS and/or CSS, and/or
b) with (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues taken from the same patient as the primary patient sample, or from a library of (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues prepared from different test person or patients. Note that the screen for toxicity effects can be done a) simultaneously or not simultaneously with the RFS, CVS and/or CSS, and/or
b) with (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues taken from the same patient as the primary patient sample, or from a library of (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues prepared from different test person or patients.
The present invention allows for a harmonized analysis starting from a screening to a test using patient material. This makes it possible to align the screening data retrospectively with patient data. In the following, two examples are summarized in tables 6 and 7.
| Number | Date | Country | Kind |
|---|---|---|---|
| 1818885.4 | Nov 2018 | GB | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2019/081977 | 11/20/2019 | WO | 00 |
