EP1934873A1 - Method for determining the condition of a cell assembly and system therefor - Google Patents

Abstract

The invention concerns a method for determining the condition of at least one culture of prokaryotic or eukaryotic cells defined in greater detail herein, including in particular one or more steps for simultaneously analyzing the condition of a large number of biological markers of interest. The inventive method, enables, in some cases, the cellular response to a plurality of modifications of environmental conditions to be simultaneously determined, including, for example, the simultaneous determination of the cellular response to various compounds to be tested.

Description

 A method for determining the state of a set of cells and system for carrying out said method.

FIELD OF THE INVENTION The present invention relates to the field of in vitro evaluation of responses of a living organism to an event.

In particular, the invention relates to the field of in vitro evaluation of prokaryotic or eukaryotic cell responses to intracellular dysfunction or to a change in the environment outside the cells.

In particular, the invention relates to the field of determining phenotype change (s) of cells in response to the incubation of said cells with a compound whose effects on the organism are sought.

PRIOR ART

In many situations, both in the field of academic research and in the field of industrial research in biotechnology, it is important to determine, under given conditions, the physiological state of prokaryotic or eukaryotic cells.

In general, the physiological state of prokaryotic or eukaryotic cells may be, at least in certain aspects thereof, determined by qualitative and / or quantitative detection of one or more biological markers of interest possibly contained or possibly expressed by these cells.

Biological markers of interest commonly used include genes, gene transcripts and proteins. Other metabolites of the cell may also be used as biological markers, including intracellular enzymes. Numerous methods are known in the state of the art for the evaluation, at least partially, of the phenotypic state of prokaryotic or eukaryotic cells, by qualitative and / or quantitative detection of a biological marker or set of biological markers.

For example, PCT Application No. WO ⁰ 00/28091 describes methods of gene expression data analysis which include steps of comparing gene expression profiles to determine the evolution of these expression profiles with time.

Methods are also known for evaluating the response of cells to incubation with various compounds, including compounds with potential therapeutic interest or compounds potentially having toxic properties for the body.

For example, U.S. Patent Nos US 6,300,078 ⁰ and n ⁰ US 6,859,735 disclose target cellular components identification systems of a pharmaceutical composition comprising an RNA quantification step, cDNAs or proteins derived from the target cells of interest .

The same type of techniques for detecting and / or quantifying cellular constituents has also been used to produce qualitative and / or quantitative profiles of these cellular constituents, with a view to diagnosing a disease, as described, for example, in the application for US patent No. US 2001/0018182 or ⁰ in the PCT application WO 03/083140 n ^0.

The application of the results of gene expression profiles to the determination of the toxic properties of a compound for cells has also been described, for example in US Patent Application No. 2002/0192671.

Processing systems of information generated in this type of marker detection analysis technique are described in particular in US patent application No. US 2005/0042622 or ⁰ in the application of US Patent No. ⁰ US 2005/0060100. There is a need in the state of the art for methods for determining the physiological state of an organism or of prokaryotic or eukaryotic cells, which are alternative to known or improved methods compared to known methods.

SUMMARY OF THE INVENTION

The subject of the present invention is a method for determining the state of at least one prokaryotic or eukaryotic cell culture which is defined in detail in the present description and which notably comprises one or more steps allowing the simultaneous analysis of the state. of a large number of biological markers of interest.

As will be detailed later in the description, the method of the invention makes it possible, in certain cases, for the simultaneous determination of the cellular response to a plurality of changes in environmental conditions, including, for example, the simultaneous determination of the cellular response to various test compounds.

In addition, the method according to the invention makes it possible, in certain cases, to quickly perform a complete test, by implementing an early interruption step of this method, once sufficient information, although not exhaustive, on the state of the cells tested was generated.

The invention also relates to suitable systems for implementing the method for determining the state of at least one prokaryotic or eukaryotic cell culture above.

DESCRIPTION OF THE FIGURES

Figure 1 is a general diagram of a system for determining the state of a cell according to the invention. This general scheme also makes it possible to present the main steps of the method for determining the state of a cell according to the invention. In FIG. 1, the sequencing sequence of the steps of the method, which successively uses the various means of the system, is represented by a succession of simple arrows.

In Figure 1, the broken arrows indicate the transmission of data from storage means to processing means. The discontinuous arrows are (i) mono-directional or (ii) bi-directional, depending on whether (i) data is transferred from a storage means to a processing means, or conversely transferred from one means to another. processing to a storage means, or (ii) that the data can be interchangeably transferred in one direction or the other, according to the needs necessary for the execution of the method.

Figure 2 is a diagram representative of the operating loop of the control means (100), during the execution of the method. The operating loop includes a sub-loop 130, which controls the execution of the method during the stationary phase located in time between the start step and the process stop step.

Figure 3 is a representative diagram of the operation of the means (300) for performing tests and storing test results during the execution of the method.

Figure 4 is a representative diagram of the operation of the data evaluation means (400) during the execution of the method.

FIG. 5 is a representative diagram of the possible structure of the data storage means (050), which comprises means (051) for storing data relating to the relationship between biological markers and means (052) for storing the results of the tests carried out. during the execution of the process. The means (050) includes an updated set of relationship data between the markers and test results generated by the Resource Units (061). The means (050) constitutes a common global archive that can be used by the various means of a determination system according to the invention, for execution process steps that require access to the information that the storage means (050) contains.

Figure 6 is a diagram representative of the possible structure of the means (070) of Operational Planning, during the execution of the method. The means (070) notably comprises the data relating to the priority rank of the different biological markers not yet tested at a given instant, these data being used by the control means (100) during the execution of the method for establishing the chronology tests that remain to be performed. Figure 7 is a representative diagram of the set (060) including the Resource Units (061) selected during the execution of the method.

Figure 8 is a representative diagram of a random type strategy implemented according to the method of the invention, for Paraquat.

FIG. 9 is a representative diagram of a class marker selection strategy implemented according to the method that is the subject of the invention, for the Paraquat. On the abscissa: cumulative number of instances of execution of the process (= Number of test units). On the ordinate: number of markers expressed

Figure 10 is a representative diagram of a strategy of self-learning type implemented according to the method object of the invention, for Paraquat. On the abscissa: cumulative number of instances of execution of the process (= Number of test units). On the ordinate: number of markers expressed

Figure 11 is a representative diagram of a self-learning type strategy for Rotenone, following a preliminary analysis by QSAR. On the abscissa: cumulative number of instances of execution of the process. On the ordinate: number of markers expressed DETAILED DESCRIPTION OF THE INVENTION

The applicant has sought to develop a method for determining the state of at least one set of prokaryotic or eukaryotic cells that can be performed on a large scale, which is rapid and inexpensive.

In particular, the development of a method for simultaneously testing the status of a large number of potentially relevant biomarkers with respect to a given physiological situation has been investigated, in particular through time management. actual number of biological markers to be tested, and thanks to a real-time management of the order in which the different biological markers are tested.

According to the invention, a method has been developed for determining the state of at least one set of prokaryotic or eukaryotic cells by means of determining the state of a set of biological markers contained or expressed by said cells. said method comprising the following steps a, b, c, d, e, f, so that step a is only passed once at the beginning of the evaluation (initialization), the steps (b, c , d, e) forming a sequence of operations executed cyclically as many times as necessary, and the step f is crossed only once at the end of evaluation (termination).

Thus, the subject of the invention is a method for determining the state of at least one set of prokaryotic or eukaryotic cells comprising the following steps: a) an initialization step during which (i) charging in a or several storage means a set of reference data of biomarkers potentially relevant for the specific execution of the process, as well as marker metrics data (information on the similarity between the markers), a relevance model and data initial priority for all markers (these concepts being defined by the continued), and (ii) the state of the selected markers is tested, said devices consisting of "Resource Units"; b) a system start and advance step in which the status of the highest priority biological marker (s) is tested by the corresponding Resource Unit (s), the order tests being determined by the respective priority rank values of each marker; c) a step of recovering the raw results of the tests performed by the Resource Unit (s) in step b); d) a step of analysis of the raw results recovered in step c), which notably comprises a calculation of the relevance of each test that has been carried out; e) a step of updating the initial data relating to each marker tested, according to the results of the tests and the results of the analysis of these results, said step also comprising an update of the priority ranks of the markers not yet tested for the next execution of the cycle comprising steps b) to e) for the markers that remain to be tested; and f) a system shutdown step, when a process shutdown condition occurs.

The set of state parameters that are generated during the execution of the method of the invention with all the markers tested accounts for the state of the set of prokaryotic or eukaryotic cells.

The subject of the invention is a method for determining the state of at least one set of prokaryotic or eukaryotic cells by means of determining the state of a set of biological markers contained or expressed by said cells, said method being implemented with a system for determining the status of at least one a set of prokaryotic or eukaryotic cells, said system comprising:

1) data storage means (010) comprising a data set characterizing a number N _M of biological markers Gi;

2) means (020) for storing data characterizing a metric relationship R _M between two biological markers Gi among the N _M biological markers listed in the means (010), said means (020) comprising, for each data item of relation between two biological markers:

an identification reference of a first biological marker G1 included in the means (010);

an identification reference of a second biological marker G2 included in the means (010); a METRIC value (RM) defining the metric relation RM between the first and the second marker;

3) means (060-G) consisting of a set of Resource Units, comprising a number NU _R of Resource Units (061), each Resource Unit (061) having the function of transmitting at least one parameter of a state of a biological marker Gi, contained or expressed by a culture of C cells, to an evaluation means (300) of state parameters, each Resource Unit (061) comprising:

means (0611) for identifying said Resource Unit (061);

means (0612) for indicating the operating state of said Resource Unit (061) at a given instant;

means (0613) for determining at least one state parameter of a biological marker Gi, contained or expressed by a C cell culture; means (0614) for transmitting a signal between said Resource Unit (061) and the state parameter evaluation means (300);

4) means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a culture of C cells, said means (050) comprising:

means (051) for storing data relating to at least one or more biological markers selected from the group of N _M biological markers listed in the means (010), and to storage of relevance data, said means (051) comprising, for each of the biological markers listed in this one:

an identification reference of a first biological marker included in the means (010);

an identification reference of a second biological marker included in the means (010);

a METRIC value (RM) defining the metric relation RM between the first and the second marker; and

a value P (Gi) defining a relevance of said first marker in a test carried out for a determined marker Gi and for a determined set of cells, said value P (Gi) being calculated by means (400) of analysis;

means (052) for storing test results produced by one or more Resource Units (061) included in a means (060) consisting of a subset of the means (060-G), said means (052) of storage comprising a set of test result data, each test result data comprising:

an identification reference of a biological marker included in the means (010) and a state parameter of which is determined by means of a Resource Unit (061) included in the means (060); an order value specifying the test rank of said biological marker in the current evaluation;

at least one state parameter value defining the result of the test carried out with said biological marker by said Resource Unit (061).

5) evaluation means (300) for performing tests and storing test results performed by one or more Resource Units (061) included in the means (060), said means (300) comprising: means for storing at least one state parameter of a biological marker Gi, said state parameter being generated by a Resource Unit (061);

means for transmitting and receiving a signal between said means (300) and the Resource Units (061) included in the means (060);

control means for executing tests by one or more Resource Units (060);

means for transmitting a signal between said means (300) and the control means (100); means for transmitting a signal from said means (300) to means (400) for analyzing the test results.

6) means (030) for storing a calculation function of a value P (Gi) defining the relevance of a biological marker Gi listed in the means (010); 7) an analysis means (400) for calculating the P (Gi) value defining the relevance of a biological marker Gi listed in the means (010), for a given cell culture C, using the function stored in means (030) with at least one state parameter defining the result of the test performed with said biological marker Gi by a Resource Unit (061), said state parameter being supplied to means (400) by the means (300). ), said means (400) comprising means for receiving a signal transmitted by the means (300);

8) Operational Planning means (070) including:

a set of test execution priority data for the biological markers Gi, said means (070) comprising, at each instant of the evaluation and for each biological marker (Gi) not yet tested:

an identification reference of said biological marker Gi; and

a PRIORITY value defining the priority rank of said biological marker Gi;

signal transmission means between said means (070) and the control means (100);

means for initial configuration of the priority data for each marker; the priority data being positive or zero values

9) System initialization means (200), comprising:

means for transmitting a signal between said means (200) and the control means (100);

means for transmitting a signal between said means (200) and the means (010) comprising a set of data characterizing a number N _M of biological markers Gi;

- means for transmitting a signal between said means (200) and the means (020) for storing data characterizing a metric relation R _M between two biological markers Gi. means for transmitting a signal between said means (200) and means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a C cell culture.

means for transmitting a signal between said means (200) and the means (070) comprising a set of data characterizing the initial priorities of the Nm biological markers Gi. 10) control means (100) comprising:

means for transmitting a signal between said means (100) and each Resource Unit (061);

means for transmitting a signal between said means (100) and the operational scheduling means (070);

means for transmitting a signal between said means (100) and the means (300) for analyzing the test results;

means for transmitting a signal between said means (100) and the data storage means (050); operating control means of the units of

Resource (061), said method comprising the following steps: a) initializing the system in a step in which the control means (100) performs the following commands: ai) (i) loading in the storage means (051) the data contained in the means (010) and (020);

(ii) loading in the means (030) the information and instructions concerning the function of calculating the values of relevance used for the markers Gi contained in the means (051); (iii) loading in the means (070) the initial priority information for at least a portion of the biological markers Gi selected from the Nm biological markers; and a2) selecting, from a set (060-G) of Resource Units (061), a set (060) of Resource Units (061) capable of performing a state test for at least a part of the biological markers Gi referenced in step a1) in the means (051) and (070), and then initializing each of the Resource Units (061) of the means (060); b) starting the system in a step in which the control means (100) performs the following commands: b1) selecting the marker Gi listed in the means (070) having the highest PRIORITY priority value, and then deleting the data of said marker Gi from the content of the means (070); b2) adding, in the storage means (052), data associated with said selected marker Gi, respectively:

the identification reference of said biological marker Gi included in the means (051), and

an order value specifying the test rank of said biological marker Gi. b3) selecting a Resource Unit (061) capable of performing a status test of said biological marker Gi and transmitting by means (300) a command to execute a state test of said selected marker Gi, said test being executed by said Resource Unit (061) after configuration thereof with the marker

Gi, said resource unit being thereby assigned a "Blocked" status value; c) Retrieve the results of the tests performed in step b) starting the system, according to the following steps: d) load the state parameter (s) generated by each selected Resource Unit (061) at the end of the step b) in the storage means included in the evaluation means (300); c2) transmitting the one or more state parameters loaded in step d) to the storage means (052) and to the analysis means (400); d) Analyzing the results of the tests recovered in step c), according to the following steps: d1) calculating, for each biological marker Gi for which at least one state parameter has been transmitted by means of analysis (400), the value P (Gi) defining the relevance of said biological marker Gi, by using the function stored in the means (030) with said state parameter defining the result of the test carried out with said biological marker Gi by a Resource Unit

(061); d2) propagating the value P (Gi) calculated in step d1) for said biological marker Gi to the storage means (051), the propagation of assigning to each data of relationship between the markers Gj not yet tested and Gi a propagation value: PROPAGATION (Gj ₁ Gi) = P (Gi) in the storage means (051); d3) resetting the Resource Unit (061) used for said biological marker Gi by assigning to said Resource Unit the "Free" status value. e) Update the marker data contained in the system, according to the following steps: e1) Re-sort the order of the Gi markers not yet tested listed in the storage means (051), assigning each marker Gi not yet tested a command value, said command value consisting of a weight value Pi being a function of the value of the result of the following equation (1):

Pi = ΣMETRIC (Gi, Gk) * PROPAGATION (Gi, Gk); 1 <= k = N, in which:

- Σ is the operator "sum"

N is the number of markers present in the means (051);

METRIC (Gi ₁ Gk) is a parameter defining the metric relationship between the marker Gi and the marker Gk; - PROPAGATION (Gi ₁ Gk) is the parameter defining the value propagated in step d2) during the test of the marker Gk if it has already been tested; PROPAGATION (Gi ₁ Gk) = 0 if Gk has not been tested yet; and e2) update the data of the Operational Planning means (070) with the new classification induced by the values of weights obtained in step e1) for each Gi marker not yet tested. the cycles of steps b) to e) being repeated until the first occurrence of one of the following conditions f): f) termination conditions:

(i) interruption of the system by the user;

(ii) the value of a generated state parameter for a marker Gi by a Resource Unit (061) has been predefined as a system shutdown condition; (iii) the steps a) to e) of the method have been executed for all the markers Gi listed in the means (051) of storage, it being understood that all the state parameters contained in the means (052) of storage at the end of step f) constitutes the state of the prokaryotic or eukaryotic cell culture or cultures which is determined by the method, and it being understood that at the end of step f), the storage means ( 052) contains the information concerning the chronological order in which the markers were tested by the method.

According to the invention, "procayote" cells are understood to mean cells of bacteria. By "eukaryotic" cells is meant according to the invention animal or plant cells, including plants or algae, fungal cells, including yeasts, and protist cells.

By "set of cells" is meant according to the invention a plurality of cells, including a set of cells in vitro culture or a set of cells that has been previously removed. A set of cells can be obtained after taking a tissue sample from an animal multicellular organism, including human, or plant. A set of cells can also be obtained after sampling from the environment, including including a soil sample or an aquatic sample from the natural environment.

In addition, in the case mentioned above, the "set of cells" may be known or suspected to have been contacted with one or more arbitrary substances under defined concentration and exposure time conditions. or not.

By "set of cells" is meant cells among those described above which are under specified conditions. For example, if one seeks to test, with the method of the invention, the effects of a substance on a specific cell type, for example, on human hepatocytes, then the method of the invention is preferably carried out successively. or simultaneously with the following sets of cells:

a control group of cells consisting of a culture of hepatocytes in the absence of the substance to be tested,

a first series of sets of test cells, each set of cells consisting of a culture of hepatocytes incubated with a concentration C of said substance to be tested for a duration T1, each set of cells of said series being incubated with a concentration of C distinct from the substance to be tested,

a second series of sets of test cells, each set of cells consisting of a culture of hepatocytes incubated with a concentration C of said substance to be tested for a duration T2, each set of cells of said series being incubated with a concentration of C distinct from the substance to be tested,

a N ^th series of sets of test cells, each set of cells consisting of a culture of hepatocytes incubated with a concentration C of said substance to be tested for a duration Tn, each set of cells of said series being incubated with a concentration C distinct from the test substance. With the method as defined above, one tests a single

"Set of cells", ie in the illustrative example above, the cell control set or any of the sets of cells incubated with a given concentration of the test substance for a given period of time .

The method as defined above makes it possible to test any of the above-mentioned "sets of cells" compared to another set of reference cells defined as another "set of cells" mentioned above. In this case, the use of the set of reference cells at each step of the method is an intrinsic function of the resource units, which then simultaneously perform a "set of cells" test and a test of the set. of reference cells, and produces results regarding the difference in behavior between the two sets. In some embodiments of the method, the "set of cells" tested consists of culturing cells of a given type CELL incubated for a time T with a final concentration C of a substance S.

However, as will be described later in the description, it also forms part of the invention a method in which several sets of cells are tested in parallel, the possibility of testing in parallel a plurality of sets of cells depending essentially on the ability to processing and analysis of the system that is used for the execution, in parallel, of the methods of the invention. In this embodiment, several methods comprising steps a) to f) above are simultaneously performed, each method being executed from a single set of cells determined.

By "biological marker" contained or expressed by the cells is meant according to the invention any parameter associated with cellular operation whose presence or state can be detected. The biological marker can be "contained" in cells when this marker is an intrinsic parameter that generally does not vary during the lifetime of the cell, such as, for example, genomic nucleic acid sequences. The biological marker is "expressed" by the cells when the state of said biological marker is in general likely to change during the lifetime of the cell, such as the level of expression of certain genes or the level of activity certain enzymes.

In certain embodiments of the invention, a "biological marker" as used herein may be a combination of at least two distinct markers in the conventional technical sense of the term marker. For example, a single "biological marker" in the sense of the present disclosure may consist of a combination of at least two expression level markers of a gene. The state parameters of such a "biological marker" consist of the combination of the values of the state parameters that are determined for each of the conventional markers contained in said "biological marker". As an illustration of these particular embodiments of the invention, the state parameter (s) of a single "biological marker" may be indicative of the expression values of a combination of at least two distinct genes, or still expression values of at least two distinct proteins. In these particular embodiments of a "biological marker" of the invention, there is no limit to the numbers of conventional markers included in a single "biological marker", other than the practical limit of the number of conventional markers. available at the time of implementation of the method or system of the invention. At the extreme, a "biological marker" according to the invention whose purpose is to report the state of a complete cell metabolism under specific cell culture conditions may consist of the combination of all the conventional markers available. In the majority of cases, however, a "biological marker" as defined of the invention, when it comprises a combination of conventional markers, comprises less than 100 conventional markers.

"Biological markers", which may also be referred to as Gi markers in the present description, include Gi markers that include a marker or combination of markers, among the following conventional markers:

the presence or absence of a nucleic acid in the genome of the cells tested, including the presence or absence of a polynucleotide encoding a protein, or the presence or absence of a polynucleotide regulating the expression of a gene;

the presence or absence of polymorphic sites in the sequence of a genomic nucleic acid of the tested cells;

the presence or absence of a specific allele in a polymorphic site contained in a genomic nucleic acid of the cells tested;

the presence or absence of a transcription product of a gene contained in the genome of the cells tested, including a messenger RNA (mRNA) or a complementary DNA (cDNA); the presence or absence of a small RNAi-type interfering RNA, a small RNAsi-like interfering RNA, an RNAmi-type interfering microRNA, a small RNAsno-type nucleolar RNA, and a small RNA nuclear RNA sn;

the level of transcription of a gene contained in the genome of the cells tested;

the presence or absence of a protein encoded by the genome of the cells tested, or the presence or absence of a protein encoded by an organism hosted in the cells tested, for example a viral or fungal organism; the level of translation of a protein encoded by the genome of the cells tested, or the level of translation of a protein encoded by an organism hosted in the cells tested;

the intracellular or extracellular quantity of a protein encoded by the genome of the cells tested, or the intracellular or extracellular quantity of a protein encoded by an organism hosted in the cells tested;

- the presence or absence or quantity of any other detectable cellular metabolite, including transcription factors, epigenetic control factors, hormones, enzyme cofactors, intracellular or extracellular receptor cofactors, cells, lipids, fatty acids, polysaccharides, vitamins or trace elements.

For the sake of clarity of the disclosure of the method or system according to the invention, a "biological marker" below will generally comprise a single conventional marker.

By "set of biological markers" is generally meant a plurality of biological markers that may be of one or more of the types of biological markers that are described above.

Preferably, for the implementation of the method of the invention, a set of biological markers is used.

"Homogeneous", ie a set of markers comprising biological markers belonging to a single type of markers, for example among the types of biological markers described above. By way of illustration, the set of biological markers may comprise exclusively "gene transcription level" markers. In this illustration, the tests providing the state parameter of each biological marker can be performed on the same type of test device, for example, DNA chips. Preferentially, a set of biological markers whose state is determined by the above method does not result from a purely arbitrary choice. Thus, for the implementation of the above method for determining whether the set of cells tested are in a given physiological state, a set of biological markers is chosen from among the biological markers whose state is likely to provide relevant information. on said given physiological state.

For example, if the method is implemented to determine whether a substance or compound is toxic to cells, the set of biomarkers that is selected will comprise at least one or more biomarkers whose state, for example presence, absence or quantity, is informative about the response of cells to a toxic compound.

In general, when the biological markers are not chosen in a purely arbitrary manner, they are selected on the basis of their degree of informative relevance with respect to the physiological state of the cells that are to be determined. . The degree of informative relevance of a biological marker to a given physiological situation can be determined from the information contained in the state of the art for said biological marker. The degree of informational relevance of a biomarker to a given physiological situation can also be determined based on relevance data generated for that specific biomarker, in one or more prior enforcement instances. of the method of the invention with a set of biological markers comprising this specific marker.

Another starting variable of the above process is the set of prokaryotic or eukaryotic cells that are tested. Depending on the question that is asked at the beginning of the process, a set of cells of a suitable type is used. For example, when it is sought to determine, with the method of the invention, whether a substance is neurotoxic, said method is preferably carried out with at least one set of neuronal cells. Most preferably, in such an embodiment, the method is performed with a "set of cells" consisting of the combination of (i) a neuronal cell culture and (ii) a set of biological markers including state is informative with respect to cytotoxicity, and better neurotoxicity. Even better, in this particular embodiment, the method is carried out successively or simultaneously with various types of brain cells, for example unipolar or bipolar neurons, astrocytes, glial cells or even Schwann cells.

The method of the invention provides, after stopping in step f), a set of state parameters comprising the state parameter (s) determined for at least a portion of the biological markers of the invention. set of initially selected biomarkers, and more specifically a set of state parameters comprising the determined state parameter (s) for all biological markers tested before the shutdown event of the process. In addition, the method of the invention provides, after stopping in step f), the chronological sequence of the use of the markers carried out during the execution of the method for a set of CELL1 cells, so that the method of the invention makes it possible to reuse this chronological sequence later in the context of another execution instance using the same markers on an arbitrary cell culture CELL2 in order to be able to compare in real time the progress of the evaluation of CEL2 with respect to results obtained for CELL1.

The set of state parameters of the biological markers tested which is provided at the end of the method of the invention defines the state of the set of cells tested, in a given environment situation. For example, if the set of state parameters that is provided at the end of the method includes one or more informational marker state parameters to a cell apoptosis situation, the execution of the method will have made it possible to detect a situation of cellular apoptosis under the environmental conditions to which the set of cells was subjected before the execution of the process. These environmental conditions to which the set of cells has been subjected before the execution of the process may be, for example, the incubation of the cells in the presence of a compound whose detrimental or beneficial effects for the cells are sought.

As an illustration, if the set of biological markers selected at the beginning of the process comprises a marker consisting of the level of production of the p53 protein and if the set of state parameters provided at the end of the process comprises a parameter of state meaning the intracellular presence of a large amount of p53 protein, then the set of state parameters provided at the end of the process is informative on the existence of a physiological apoptosis situation of the entire cells tested in the process.

The example above illustrates the extreme case where a state parameter of a single biological marker of the set of biological markers selected at the beginning of the process is, in itself, informative on the physiological situation of the cells tested.

Also, in certain embodiments of the method, when attempting to determine the existence of a given physiological situation of the cells tested, the set of biological markers selected at the beginning of the process may comprise both one or more biological markers. whose state parameter provided for each marker is only indicative but not sufficiently informative vis-à-vis said physiological situation, only the combination of several state parameters being informative, vis-à-vis said physiological situation to be determined . In general, the physiological situation of the set of cells tested is defined by a combination of several biological marker state parameters included in the set of state parameters provided at the end of the method. For example, the stimulation of a particular metabolic pathway can be determined when a combination of state parameters, which is included in the set of state parameters provided at the end of the process, indicates, independently or simultaneously:

a high level of expression of the genes encoding one or more proteins involved in the operation of said metabolic pathway;

a large amount of the proteins involved in the operation of said metabolic pathway;

a high level of enzymatic activity, for example when the protein or proteins involved in said metabolic pathway consist of one or more enzymes.

In some cases, a given biological marker may be informative for various distinct physiological situations.

As defined above, the process of the invention is carried out using various means, which will be specified below when necessary, before describing in detail the various steps of the process.

For clarity of the description of the system and method of the invention, these are described below in particular with reference to the particular embodiment described in Figures 1 to 7. In Figures 1 to 7, the various means may consist of physical means or logical means of performing the various steps of the method of the invention.

The method of the invention, which has been generally defined above, is described below with its various specific features and preferred embodiments. For the sake of clarity, the system and method are described below for a process execution instance with a single set of cells.

Step a) of the process

Step a) consists of an initialization step of the system during which biological marker data is transferred from a global tag data storage means (010) to a storage means (050) used for a cycle or specific instance of execution of the process (step ai)); the initial priority data for the markers used are updated in the means (070); the data defining the relevance calculation function for the markers used are transferred in the means (030); and the test devices, called "Resource Units" are also initialized (step a2)).

The method of the invention is performed with at least a portion of the biological markers that are listed in a data storage means (010), as shown in Figure 1.

The storage medium (010)

The means (010) comprises a set of data characterizing a number N _M of biological markers Gi. The number N _M of biological markers listed in the means (010) is really limited only by the storage and / or treatment capacities of said system, and also by the absolute number of biological markers available at the time of execution of the method, when the storage capacity and / or treatment of said system to list all the known or available biological markers. However, a set of limited biomarker size is generally sufficient to perform the method in multiple applications.

Thus, in general, the number N _M of biological markers Gi listed in the means (010) is at most 30,000, and often at most 10,000.

In many embodiments of the invention, in step a) at most 1000 biological markers are selected from those listed in the means (010). In some applications of the process, only the test of a small number of biological markers is required. In such applications, fewer than 100 biological markers may be selected in step a), among those listed in the means (010). The means (010) may comprise exclusively, for each biological marker listed, an identification reference of said biological marker.

As previously indicated, the method of the invention is performed for a combination of (i) a set of biological markers and (ii) a set of cells.

Depending on the cell type or the state of cell differentiation of the set of cells, a set of biological markers Gi listed in the means (010) that can be expressed or be informative for the type of cells used is advantageously selected. .

The medium (020) of storage

The means (020) used in step a) of the method consists of a means for storing data of relations between each possible pair of biological markers, among the biological markers referenced in the storage means (010) and which are selected at step a). The storage means (020) may include a maximum number of marker pair relationship data which follows the following equation (2):

Nb_relations = N _M (N _M -1) / 2 (2), in which:

- Nb_relations is an integer consisting of the maximum number of data of relations between markers that can be included in the means (020); and

- N _M is the total number of biomarkers that are listed in the means (010) for storing.

Each relationship data R _M between any two markers G1 and G2 among the N _M markers referenced in the means (010), consists of a distance value between two markers, which is also called the "metric" relation value, or METRIC ( RM) for the purposes of this description.

The value of METRIC (RM) between two markers G1 and G2 is all the greater as the two markers G1 and G2 are close to an informative point of view, in a given metabolic context.

The value of METRIC (RM) between two markers G1 and G2 contained in a means (010) depends on the informational context of the evaluation, so that two separate evaluations using markers G1 and G2 for different purposes can use the values of METRIC (RM) different.

By way of illustration, in a context of inflammation situation, (i) a G1 marker consisting of the level of expression of the IL-1 gene and (ii) a G2 marker consisting of the expression level of the gene TNFα will have a large METRIC (R _M ) value, since a high level of expression of each of these two genes is physiologically associated with an inflammatory reaction of the body. Also for illustrative purposes, in a context of an inflammation situation, (i) a G1 marker consisting of the level of expression IL-1 gene and (ii) a G2 marker consisting of the expression level of the IL-2 gene will have a small METRIC (R _M ) value, since the level of expression of the IL-1 gene IL-2 gene is not strictly associated with the occurrence of an inflammatory reaction. The METRIC (R _M ) value of the metric relationship between two markers is expressed in arbitrary units.

The METRIC (RM) value of the metric relationship between two markers G1 and G2 is zero if the two markers have no common informative value, in a given informative context. By way of illustration, in a context of inflammation situation, (i) a G1 marker consisting of the level of expression of the IL-1 gene and (ii) a G2 marker consisting of the expression level of the gene of actin will have a value of METRIC (R _M ) equal to zero, since the level of expression of the actin gene is independent of the occurrence of an inflammatory reaction.

Given three distinct biological markers G1, G2 and G3, the marker G1 is more similar of G2 than G3 when the value of METRIC (GI, G2) is greater than the value of METRIC (GI, G3).

Prior to the first initialization of the system, the metric data are stored in the means (020) for at least a portion of the possible Nb_relations between pairs of markers. For example, METRIC (RM) values of metric relationships are calculated from known data in the state of the art relating to a plurality of pairs of markers among the possible Nb_parations of markers.

At the first initialization of the system, the means (020) does not necessarily contain relationship data for all possible Nb_relations of markers. By default, for marker pairs for which the means (020) does not contain relationship data, the present system assigns a null METRIC value. At the first initialization of the system, the means (020) comprises in general, relationship data for only a portion of the possible marker pairs. Then, with the cycles or instances of successive executions of the method, the information of relations between pairs of markers are completed, in view of the result of tests using markers belonging to pairs of markers for which no data of relationship n ' was still included in the storage means (020).

Storage means (030) The relevance model storage means (030) makes it possible to load the necessary information (description, instructions) into the definition and implementation of an arbitrary function for calculating the relevance value specific to the application. Execution instance of the current system. The relevance calculation function will subsequently be applied in the execution instance of the current system to a test result concerning any marker Gi selected in step a) and contained in the storage means (051).

The Operational Planning Medium (070) The Operational Planning Medium (070) consists of an essential means used during the execution of the current process. The operative planning means (070) comprises, for each marker Gi selected in step a) and contained in the storage means (051), at least one identification reference of said marker Gi and a value of PRIORITY, positive or null, for said marker Gi. The means (070) contains, at the initialization of the execution instance of the current system, predefined values for each marker Gi, the values being positive, zero or positive infinity (+ ∞). The system may in some cases change the content of the means (070) dynamically, as the test results of the G markers are known, as shown below. In some embodiments of the method, the values PRIORITY initials are null for all Gi markers. In some other embodiments, the initial PRIORITY values, for at least some of the Gi markers, which are then designated "seed" markers, are positive or are + ∞. In this case, the initial priorities of non-seed markers are zero. The means (070) thus contains in step a) the seed markers specific to the execution instance of the current system.

As already mentioned above, the system and method are described below for an execution instance of the method with a single set of cells.

In step a), the initialization of the system is controlled by the control means (100) and executed by the initialization means (200), which initialization means (200) controls the execution of the steps respectively. ) and a2). Steps a1) and a2) can be performed simultaneously or successively. The order in which steps ai) and a2) are performed is irrelevant.

In step a1), the initialization means (200) controls the loading, in the storage means (051), of marker data initially contained in the means (010) and (020), for at least a part of biological markers listed respectively in the means (010) and (020).

Thus, in step a1) a selection of data is made for only some of the biological markers listed in the system. As an illustration, if the execution of the method aims to obtain a set of biological marker state parameters likely to be informative (i) with respect to a cancer situation, or ( ii) vis-à-vis an ignition situation, it is realized in step ai):

- or loading in the means (051) of data storage markers likely to be informative vis-à-vis a situation inflammation, from the marker data contained in the means (010) and (020), or

or loading in the means (051) for storing data of the markers that may be informative with respect to a cancer situation, from the marker data contained in the means (010) and (020) , respectively.

As shown in FIG. 5, the storage means (051) comprises at least, for each biological marker Gi selected in step a1): an identification reference of said marker Gi;

a series of identification references of pairs of markers between said marker Gi and each of the other markers Gi selected and listed in the means (051) of storage;

for each identification reference R _M of marker pairs above, a METRIC value (R _M ) of metric relation between the two markers constituting the pair of markers, when the value METRIC (R _M ) is known. If the value METRIC (R _M ) for a given pair of markers is not known, this value is set to NULL (0) by default in the medium (051). In Figure 5, the value METRIC (Gi, Gj) between two markers Gi and Gj is indicated "M (Gi, Gj)".

for each marker pair identification reference above, a relevance value "P (Gi)" which is indicative of the informative value of said pair of markers. In step a1) of the method, the relevance value P (Gi) for all the pairs of markers listed in the means (051) is zero.

In step ai), a zero PROPAGATION value (equal to zero) is assigned for all the values P (Gi) contained in the storage means (051). In step a1), the means (052) for storing the results is empty. In step a2) of the method, a set (060) of Resource Units (061) is selected from among all the possible Resource Units (061) included in the system, and then the Resource Units (061) are initialized. thus selected. The system includes a global set (060-G) of Resource Units (061). However, for the implementation of the method for determining the state of a given set of cells, it is not necessary to test all the available biomarkers with all the Resource Units (061) included. in the global set (060-G). In step a2) of the method, only the units of

Resource (061) which makes it possible to carry out a state test for the only biological markers selected in step a1). Thus, in step a2) a set (060) of Resource Units (061) is selected for testing the markers Gi selected in step ai), this set (060) of Resource Units (061) consisting of in a subset of the global set (060-G) of Resource Units (061) that can be used for carrying out an execution instance of the method according to the invention.

In step a2), all of the Resource Units (061) of the set (060) are reset. All Resource Units (061) are in the "Free" (or "Free") state.

A set (060) of Resource Units (061) is shown in Figure 7.

By "Resource Unit" is meant according to the invention any device which is adapted to determine a state parameter of a biological marker Gi listed in the means (051).

A Resource Unit (061) consists of a logical unit that includes a physical test device. The test device may consist of a combination of elementary components that are associated. A Resource Unit can consist of a logical assembly of several elementary components. It is said assembly, with its combination of components, which is suitable for performing a test for determining a state parameter of a biological marker Gi. In some embodiments, a particular component may be used as an elementary component of several distinct Resource Units.

Resource Units are generic in that they are not coupled a priori to a given marker or to a cell culture. In contrast, the Resource Units can each be configured on demand with a given G tag and a given CELL cell culture to perform a measurement. This specialization is hereinafter called the configuration of the resource unit with the marker G and cell culture CELL. Once a Resource Unit has been configured, it can be executed, that is, it will perform the operation of evaluating a Gi marker state parameter for which it is intended. The unit test results are obtained by extracting the state and values of the internal components of the Resource Unit. A Resource Unit can be reset, ie it returns to its initial state (recycling) where no cell culture and no markers are configured. Thus, after a reset operation of the Resource Unit, the Resource Unit can be reused to perform another unit test.

As previously mentioned, a Resource Unit includes at least:

means (0611) for identifying said Resource Unit (061), which is indicated "Ressourceld" in FIG. 7;

means (0612) for indicating the operating state of said Resource Unit (061) at a given instant, which is indicated "Status" in FIG. 7. The means (0612) can take either the value " Blocked "(or" Lock "in Figure 7), the value" Free "(or" Free "in Figure 7"). ; means (0613) for determining at least one state parameter of a biological marker Gi, contained or expressed by a C cell culture;

means (0614) for transmitting a signal between said Resource Unit (061) and the control means (100);

A set (060) of Resource Units (061) is shown schematically in Figure 7. In Figure 7, the set (060) comprises a number M of Resource Units (061) each uniquely referenced "Ressourceldi "At Resource Id M", at a time of the process for which Resource Units "Ressourceldi", "Ressourceld4" and "RessourceldM" are in the "Free" state (or "Free") and for which the Units of Resources Resources "Ressourceld2", "Ressourceld3", "Ressourceldδ" and "Ressourceldβ" are in the "Locked" (or "Lock") state. In many cases, a single Resource Unit (061) is adapted to determine a state parameter of a marker for a plurality of biological markers Gi listed in the means (051).

The Resource Units (061) include any device capable of performing the identification, and possibly also the quantification, the simultaneous presence in cells or in their culture environment, a substance or a plurality of substances involved in cellular metabolism (anabolism or catabolism). The Resource Units (061) may consist of devices suitable for carrying out the detection and / or quantification of Gi markers by genomic, epigenomic, proteomic, metabolomic or even glycomic analysis.

For example, the biological marker state parameters that are to be determined may consist of the level of expression of a plurality of distinct genes. In this case, a Resource Unit (061) may consist of a set of automated means for handling one or more DNA chips on which which are immobilized a plurality of distinct nucleic probes, capable of hybridizing respectively to the different messenger RNAs or to the different complementary DNAs corresponding to the transcripts of said distinct genes. In this illustrative example, a single Resource unit (061) may allow the determination of the state parameter (s) of all of the biological markers Gi listed in the means (051).

Still in this illustrative example, the initialization of the Resource Units (061) may consist in: (i) immobilizing on a suitable support a plurality of nucleic probes hybridizing specifically to the transcription products of the various genes whose state parameter expression level is searched for and then

(ii) contacting a biological sample, for example an mRNA cell extract or a cDNA sample with the DNA chip prepared in step (i) above.

The execution of the Resource Units consists in collecting, after a time of arbitrary exposure of the chip with the biological sample, the values provided by the chip. Resetting Resource Units consists of cleaning or replacing their components using automated means.

In some embodiments of the method, the various

Resource Units (061) can be of different types. For example, the selected set (060) of Resource Units may comprise both Resource Units (061) using DNA chips and

Resource Units (061) using protein chips.

Step b) of the process

Step b) consists of the step of starting and progressing the system, during which the markers Gi selected in step a), and whose data were transferred to step a) in the means of storage (051), will be successively tested by means of the Resource Units (061).

At the beginning of step b1) of the method, the marker is selected.

Gi having the highest precedence priority PRIORITY value referenced in the operational scheduling means (070). The means (070) of

Operational Planning is referenced in Figure 1. The content of the Operational Planning Medium (070) is shown in Figure 6.

At the first initialization of the system, the means (070) of Operational Planning comprises, for each marker Gi which is listed in the means (051) of storage, at least (i) an identification reference of said marker Gi. At the first initialization of the system, the operational planning means (070) also comprises, for all the markers Gi selected in step a), a value of positive or zero priority rank or positive infinity arbitrarily set as initial priorities of the markers. In the Operational Planning means (070), the markers Gi are therefore ranked in descending order of PRIORITY priority rank, the marker Gi having the highest priority rank being selectable first, in step b1) of the method.

In step b1), the marker Gi is indexed in the means (070) having the highest PRIORITY priority value, and the data of said marker Gi is deleted from the content of the means (070). If several markers share the same highest priority value in (070), the selection between these markers is random. The identification references of the marker Gi which has just been selected in step b1) are added, in step b2) of the method, in the storage means (052), as shown in FIG. 5.

In step b2), a value of order specifying the rank of the test of said biological marker Gi is also added in the means (052). Then, in step b3), we reserve a Resource Unit whose state

(0612) is "free" that is configured with said biological marker Gi; or waiting for a Resource Unit to be free to perform the reservation and configuration and transmitting by means (300) a command to execute a status test of said selected marker Gi, said test being performed by said Unit of Resource (061), to which is assigned a status value "Blocked"; The means (300) for executing step b3) is shown diagrammatically in FIG. 3.

Thus, at the first execution of step b3), a first Resource Unit (061) is selected from the set (060), by means of a test command sent by the evaluation means (300), the means (300) being itself under the control of the control means (100).

Once the Resource Unit (061) has been selected, a "Blocked" status value is assigned to it. This Resource Unit (061) can no longer be selected again for the duration of the test that this Resource Unit is running.

Then, the steps b1), b2) and b3) above are successively repeated for the markers Gi having a descending priority rank, as referenced in the means (070) of Operational Planning, until all the Resource Units (061) included in the set (060) of Resource Units that was selected in step a) are in the "Blocked" state.

In those embodiments of the method in which a high number of markers Gi are selected in step a1) of the method, at least a portion of the selected Resource Units (061) have executed the entire test for the marker. Gi corresponding. Each Resource Unit (061) that performed the entire test for the corresponding Gi marker is then inactive and is again assigned a "Free" status value. Resource Units (061) with a "Free" state value are likely to be selected again, during a given execution cycle of step b3), to execute a state parameter test for another marker Gi.

For example, a Resource Unit (061) consisting of a DNA chip can be selected a first time, in step b3), to perform a test for determining the expression level of a first gene (Gx tag) . At the end of the test run for this first gene, said Resource Unit (061) is again assigned a "Free" status value. This Resource Unit (061) is then likely to be selected again during a subsequent execution of step b3), to execute a test for determining the level of expression of a second gene (Gy marker).

Thus, in step b) of a cycle or instance of execution of the method, a single Resource Unit (061) can be selected a plurality of times, according to its availability and according to its ability to perform the test ordered for a Gi marker given.

In other embodiments of the method, a total of as many Resource Units (061) are selected as there are Gi markers to be tested listed in the storage means (051).

In the embodiments of the method in which an attempt is made to evaluate the effects of a given substance S on a set of CELL cells and using N _M markers Gi, a set (060) of Resource Units (061), which may also be referred to as a "resource pool", comprising a maximum of N _M Resource Units (061). As will be explained later in the description, it is possible, in some embodiments of the method, to vary the number of Resource Units (061) included in the set (060) of Resource Units that was initially selected in step a) of the process. Thus, in some embodiments of the method, one or more Resource Units (061) may be added to the set (060) or on the contrary subtracted from the set (060), during the execution of the process.

The theoretical execution time of step b), if this is achieved by the simultaneous or almost simultaneous implementation of the N _M Resource Units (061), is equal to the time required for the Unit of

Resource (061) for performing the test of determining a state parameter for the corresponding marker Gi.

However, the difference between the theoretical execution time of step b) and the actual execution time of step b) increases with the increasing values of N _M.

Step c) of the process

In step c) of the method, the results of each test performed in step b) are retrieved for analysis by the system. In step d), the state parameters for a marker Gi tested in step b) and that have been generated by a Resource Unit are loaded into a storage means that is included in the means (300). evaluation of the tests.

Then, in step c2), the state parameters of the marker Gi which have been previously loaded into the means (300) are respectively transmitted to the storage means (052) and the analysis means (400). .

By "state parameter" of a marker Gi is meant according to the invention any information concerning said marker at the time of the test. A state parameter of a marker Gi encompasses (i) the presence or absence of the Gi marker in the test sample, (ii) the amount of the Gi marker in the test sample, or (iii) the physical properties. -chemical of said marker at the time of the test. In some embodiments of the method, a given Resource Unit (061) may generate, in step c), a plurality of state parameters for a single marker Gi. For example, for a Resource Unit (061) consisting of a DNA chip on which are immobilized nucleic probes hybridizing specifically to the product (s) of transcription of a given gene, said Resource Unit (061) can generate two state parameters for the same marker Gi, respectively (i) the presence or absence of the transcript (s) of said gene in the test sample and (ii) the amount or concentration of the transcript (s) of said gene in the test sample.

An illustration of one embodiment of the storage means (052) is shown in Figure 5.

At the start of the system, the storage means (052) does not include any data.

Then, with the successive executions of the cycle of steps b1), b2) and b3), the data associated with the markers Gi successively selected in step b1) are added to the storage means (052) in step b2). Thus, for each marker Gi listed in the storage means (052), said means (052) comprises, in addition to the identification reference of said marker Gi, also a command value specifying the test rank of said marker Gi, the order value being referenced, in Figure 5, "Iter (Gi)". The test rank of a marker Gi "Iter (Gi)" is expressed in arbitrary units. As an illustration, the test rank of a marker Gi may consist of the date and time at which the test for determining a state parameter was executed for said marker Gi. Then, with the successive executions of the cycle of steps b1), b2) and b3), the state parameters of the Gi markers tested which are generated by the Resource Units (061) are added, for each marker Gi, in the medium (052) of storage, via the evaluation means (300).

Thus, at the end of step c), the means (052) contains at least one state parameter value, for each of the markers Gi listed in said means (052), unless the test ordered for this marker has failed, and for this marker, no state parameter was generated by the corresponding Resource Unit (061).

As will be described later in the present description, the process can be stopped before the complete cycles of steps b1), b2) and b3) for all the markers Gi selected in step a), for example a premature stop command of the process that is performed by the user, or by the occurrence of a condition controlling the automatic shutdown of the process.

In the embodiments in which the method is interrupted before the complete execution of the cycles of steps b1), b2) and b3) for each of the initially selected markers Gi, only a portion of the markers Gi listed in the medium (051) storage are also listed in the storage medium (052).

Step d) of the process

Step d) consists of a step of analyzing and quantifying the results for each test recovered in step c). After each execution of a Resource Unit for a given marker Gi of (051), in step d1) the state parameters of the tag Gi transmitted by means of analysis (400) are calculated in step c ), the value P (Gi) defining the relevance of said biological marker Gi, by using the function stored in the means (030) with said one or more state parameter (s) defining the result of the test carried out with said biological marker Gi by a Resource Unit (061); Then, in step d2), the value P (Gi) calculated in step d1) for said biological marker Gi is transmitted to the storage means (051);

Then, in step d3), the Resource Unit (061) used for said biological marker Gi is reset by assigning said "Resource" status value to said Resource Unit. In step d1), the raw results of the tests carried out in step b) and transmitted to the storage means (052) via the evaluation means (300) are analyzed by the analysis means (400).

The analysis means (400) comprises means for calculating the relevance of the raw results stored in the means (052). The relevance calculations are carried out in the means (400) using instructions for implementing one or more algorithms that are initially contained in a means (030) designated "Relevance Model". For reasons of simplification of the presentation, the "Relevance Model" also designates, for the purposes of this description, the set of instructions for implementing the algorithm or the combination of algorithms for carrying out the process. calculation of relevance of the raw results of determination of the state parameters of the markers Gi.

The Relevance Model is introduced into the means (030) of the system prior to step a) of initializing the execution instance of the method.

As an illustration, in certain embodiments of the method for which the Gi markers consist of the level of expression of various genes, the Relevance Model consists of a function whose arguments are the level of expression of the gene corresponding to each marker. Gi.

Thanks to the establishment of an Relevance Model stored in the means (030) and executed by the means (400), the user can, at the execution of the step d1) of the method, have a value P (Gi) for each previously generated marker state parameter Gi.

Preferably, for the establishment of the Relevance Model which will then be stored in the means (030) before the initialization of a process execution instance, the following conditions must be followed: (i) given a set of cells CELL; and (ii) given the execution of a Resource Unit "Ressourceldi" configured with a marker G1 and the sample derived from CELL; (iii) then: - Relevance (G1) = 0 if the execution of the Resource Unit

"Ressourceldi" does not generate any significant result, in the context of the state test of the set of cells that is the subject of the execution of the process - Otherwise, Relevance (G1)> 0 According to the method, a phase of Propagation follows the step of calculating the values of Relevance.

The relevance value P (Gi) of a given marker which is determined in step d), on the basis of the raw results of one or more state parameters generated for said marker Gi in step b), is then used in the means (400) as indicated above. The value of relevance P (Gi) is then used by the system to update the means (070) of Operational Planning, for an optimal conduct of the test suite for the markers not yet tested.

In step d2), the relevance value P (Gi) is propagated in the storage means (051). The propagation consists, for each marker Gj of the set of markers not yet tested or evaluated, to assign to the relation between Gj and Gi the propagation value:

PROPAGATION (Gi ₁ Gj) = Relevance (Gi) (= P (Gi)), which is stored in the means (051) of storage corresponding to the reference of relationship between the markers Gi and Gj. Since the relations are bidirectional (in other words the relation between Gi and Gj is the same as between Gj and Gj), and as in the present case Gj is not yet tested, by extension we can note indifferently PROPAGATION (Gi ₁ Gj) = PROPAGATION (Gj ₁ Gi) = P (Gi), which will be useful for the rest of the process In step d3), the Resource Unit is reset, which has the effect of making it "free" and unconfigured, so that it can be reused in a next cycle of steps (b, c, d, e).

Figure 4 shows the sequence of operations performed in the means (400).

FIG. 5 shows the content of the storage means (051), at a given instant of the execution of the method, after the evaluation of the test results of the marker Gi has been performed, the markers Gj ₁ Gk and Gl being again not tested. After the updating of the storage means (051) in step d), updating the operational planning means (070) in step e) of the method which is described later in the present description.

Step e) of the method The step e) consists of a step of updating the priority of the markers present in the means (051) of storage allowing the system to manage in a dynamic way, in real time, the continuation of the execution of the process.

More precisely, the calculations of relevance of the raw results initially generated by the Resource Units (061) are used by the system to, if necessary, modify the order of priority of the tests to be carried out for the Gi markers not yet tested.

For example, if the result of a test for a given Gx marker is informative with respect to a situation of deregulation of cell division, step e) of Propagation of the results can be used to modify the test order of certain Gi markers not yet tested and informative about a cancer situation, so as to assign a higher priority to these information markers Gi on a cancer situation, for the execution of the tests with these markers as a priority. Step e) therefore consists in updating, in real time, the data contained in the system, in order to execute the method optimally, in particular to execute the method in order to generate an informative set of parameters of state of the markers Gi in a process execution time which can be as short as possible.

In step e1) a new classification is made of the order of the markers Gi listed in the means (051) of storage and not yet tested at this time, by assigning to each marker Gi not yet tested a value of order, said order value consisting of a weight value Pi obtained by an equation defined below. In step e2), when step e1) has calculated the weights of each marker Gi not yet tested, the data of the means (070) of Operational Planning are updated with the weight values obtained for these markers. step e1), the update being described later. More precisely, during the execution of the method, the Gi markers can be classified into two subsets, respectively (i) the subset of the Gi markers already tested and (ii) the subset of the Gi markers n have not been tested yet.

Preferably, the system maintains permanently in the means (070) a classification of the markers in the second subset of markers above, ie the subset of markers not yet tested. The establishment of this classification continuously during the entire execution time of the process allows an adaptation of the order in which the different unit tests for each marker Gi will be executed, taking into account the results already generated for the sub-component. set of Gi markers already tested.

Preferentially, the real-time adaptation of the order in which the different unit tests for each Gi marker not yet tested will be executed is controlled by the control means (100), by means of a specific storage means for the order of the markers not yet tested, according to the priority rank assigned to them, said storage means consisting of Planning means (070)

Operational.

An illustration of the content of the Planning medium (070)

The operational scheduling means (070) comprises, for each marker Gi not yet tested at a given instant of the execution of the method, (i) an identification reference of said marker Gi, and ( ii) a priority value for said marker Gi.

The update of the content of the operational planning means (070) is carried out at the end of each execution of a test for a given marker Gi.

In other words, the data updating step e) is executed at each end of the successive execution cycle of steps b), c) and d) for a determined marker Gi. The weighting calculation consists of a numeric function

Weight () positive or zero which assigns to each marker Gi not yet tested contained in the means (051) a value Weight (Gi) calculated according to the following equation:

Weight (Gi) = Σ {Metric (Gi, Gk) * PROPAGATION (Gi, Gk)}, (K = k <= N), in which:

N is the number of total markers present in the medium (051),

- Σ is the operator "sum"

- Metric (Gi, Gk) is the metric value associated with the relation between Gi and Gk in the medium (051), - PROPAGATION (Gi ₁ Gk) is the value of propagation assigned to the relation between Gi and Gk in the medium (051) in step d2) when testing the marker Gk, the value is zero by default if Gk is not yet tested Weight () is necessarily positive or zero.

It is recalled that the value of PROPAGATION is equal to zero at the beginning of step a) of initialization of the method, so that, for example, the relations between a marker Gj and any other Gi marker not yet tested or evaluated does not contribute to the weight of

Gj.

After processing the entire subset of markers not yet tested or evaluated, the Weight value (Gj) determines the priority of Gj in this subset.

In step e), the operational planning means (070) is updated by adding the weighted (Gi) weighted data of the markers that have not yet been tested or evaluated. Thus, for any marker Gj not yet tested or evaluated, if the new value of Weight (Gj) is greater than the current value of PRIORITY of Gj in the middle (070) of Operational Planning, the value PRIORITY for Gj is fixed at Weight (Gj) in the medium (070).

As seen in FIG. 2, when the control means (100) receives an UPDATE signal, the means (100) performs a weighting calculation with the data contained in the storage means (051) to realize a new one. classification of markers not yet tested or evaluated in the means (070) of Operational Planning.

After updating the operational scheduling means (070), the next marker to be tested on returning to step b) succeeding step e) is the marker having, in the means (070), the value of PRIORITY the higher. In some cases, several markers referenced in the means (070) will have the same value of PRIORITY. These markers will be processed by the method in a random order.

In some embodiments of the method according to the invention, the subset of markers not yet tested or evaluated at a given instant of the execution of the method, which are referenced in the means (070), can be distinguished according to whether they belong to two smaller subsets, respectively (i) a first subset comprising "significant" markers (Gi) having a PRIORITY value greater than a predefined significance threshold, designated ACCEPT, and (ii) a second subset subset including the "insignificant" markers (GI) having a PRIORITY value less than or equal to the ACCEPT predefined significance level.

The ACCEPT value is an arbitrary value, positive or null, which is defined by the user prior to a process execution instance, and which may in some cases be adjusted by the user during the execution instance of the method . The acceptance value ACCEPT sets the relative sizes of the first and second subsets of markers not yet tested or evaluated, which vary with the execution time of the process. As described above, the content of the means (070) of

Operational Planning is modified after each execution of a cycle of steps b) to d) of test, then evaluation, then analysis of the results for a Gi marker tested. According to this characteristic of the method, the system is capable of adapting the order of execution of the tests that must be performed incrementally, depending on the results already obtained with the Gi markers tested and evaluated, at each moment during an instance execution of the process.

In certain specific embodiments of the method, the user may arbitrarily set the PRIORITY values for a subset of markers Gi, prior to step a), this subset of markers being designated "seed" markers for the purposes of of the present description. During the execution of the method, the PRIORITY values arbitrarily set by the user will constitute parameters used during step d) of evaluating the test results for these markers, in a transient operating regime of the method. Then, the system will self-adapt as test results are generated for these markers, along with the progress of the process execution.

Preferentially, the PRIORITY values that are arbitrarily given by the user to the "seed" markers are positive, zero or infinite positive, with the consequence that: seed markers whose initial PRIORITY value is +00 are tested first, at the beginning of the execution of the process, which constitutes a stable initial order;

seed markers for which the user has arbitrarily set a value of initial PRIORITY strictly positive are tested according to a descending order of PRIORITY value. But the order of these "seed" markers is likely to be modified, according to the results obtained during the evaluation of these "seed" markers, as has already been described above. Ultimately, when the user initially sets for each marker used in the process a priority, ie all markers are seed markers, and a null metric is specified (ie say whatever pairs of markers Gi and Gj, Metric (Gi, Gj) = 0), it follows that the evaluation proceeds in the order specified by the user.

It will be recalled that, at the beginning of step a) of initialization of the method, markers Gi which do not consist of "seed" markers have a value of PRIORITY equal to zero.

Moreover, in the embodiments of the method in which no arbitrary PRIORITY value is assigned for all the markers Gi, then the value of PRIORITY is equal to zero for all the markers Gi and the method begins its execution by a random selection of the first Gi markers to be tested.

The difference between the theoretical execution time of steps b), c) and d), on the one hand, and the actual execution time of these steps, on the other hand, increases with the increasing values of N _M . In particular, with high values of N _M , the duration of the execution and analysis of the tests becomes a limiting factor

In order to overcome this disadvantage, the method can be interrupted prematurely, before the execution of the tests for all the markers Gi initially listed in the means (051) of storage, either at the request of the user, or at the occurrence of a predetermined condition of stopping the process.

In general, the process is stopped, manually or automatically, if the tests which have already been carried out with only part of the Gi markers are such that the combination of the state parameters of the Gi markers already tested is sufficiently informative on the state of the set of tested cells that one seeks to determine.

By way of illustration, the method can be stopped automatically in the case where, for a given marker Gi, the value of the state parameter generated by the Resource Unit (061) used to test said marker Gi, is at least equal to, or at most equal to, depending on the case, a value predefined by the user. For example, in the case where the method according to the invention is implemented to determine the inflammatory state of the set of cells tested, the method can be stopped automatically if the state parameter of the marker "level of expression of the gene encoding TN Fa "is at least equal to a determined amount of mRNA or cDNA encoding TNFα.

Auto-aoorentissaae way of the system

As already described above in the present description, the means (070) of Operational Planning is an essential means used during an execution instance of the method according to the invention, since the means (070) comprises, for each marker Gi selected in step a), a PRIORITY value for said marker. Thus, for a given execution instance of the method, the order in which each marker Gi is tested is determined in the means (070), whose data are updated at each execution cycle of the steps b) to e ). According to advantageous embodiments of the method of the invention, it is advantageous, in a given execution instance of the method with a set of Gi markers, test results previously made with common Gi markers, during the previous execution instance (s) of the method. According to these advantageous embodiments of the method, the order of priority of the markers Gi to be tested during the instance during the execution of the method, as well as the values of the metrics of the relations between the markers Gi, is at least partially determined at from the results of tests previously carried out with identical markers. This is a means of self-learning of the method or system according to the invention, an illustrative embodiment of which is described below.

Consider a set G of N markers Gi, designated G1, G2, ... GN.

We also consider a set E of M previous evaluations of each marker included in the set G of N markers. The means for self-learning of the method or system of the invention consists in automatically producing a set of P priority markers and in producing a metric, designated MET STAT, for the purpose of carrying out, in the course of a new embodiment of the method of the invention, an M + 1st evaluation of markers Gi of the set G of N markers above.

Said self-learning means comprises the following steps: I) a step during which is generated, for each evaluation Ei (with 1 <= i <= M), a column-type vector designated Res (Ei), said vector Res (Ei) comprising N rows and a single column. In said vector Res (Ei), there is for example, for the marker Gj, Res (Ei) (j, 1) (with 1 <= j <= N) which contains the evaluation result (state parameter) obtained for the marker Gj during the evaluation Ei, said result being initially stored in the means (052) during the corresponding execution instance of the method. Alternatively, it is possible to form the Res (Ei) vectors from data, for Gi markers, obtained in the specific literature or in databases. data. Thus, in the example where the markers used are genes, it is possible to compose the vector Res (Ei) from genomic data obtained in a database of the MIAME type.

II) a step during which a composite vector, called ResComp, is generated.

The ResComp vector consists of a column vector which comprises N rows and a single column. Each row of the ResComp vector contains, for a marker Gi included in the set G above, the value of the sum of the evaluation results (state parameters) determined during the M prior execution instances of the method of the invention. invention for said Gi marker.

The value of ResComp is thus calculated according to the following formula: ResComp = Σ (Res (Ei)), in which:

- Σ represents the symbol of the vector sum;

Res (Ei) represents the column vector Res for the process execution instance Ei for the set G of the markers Gi; with 1 <= i <= M. III) From the ResComp composite vector above, we generate a matrix, called MATSTAT, which consists of a positive symmetric matrix having N rows and N columns.

The matrix MATSTAT is defined by the following formula: MATSTAT = ResComp * transpose (ResComp), in which: - the symbol "*" means the product vector operator, and

- "transpose ()" means the matrix transposition operator.

The MATSTAT matrix thus obtained makes it possible to select, for the M + 1 st evaluation, in terms of seed markers, the P markers Gs1 ... GsP having been most relevant in the context of the M evaluations. These markers are the P markers Gs1 ... GsP such that MATSTAT (GSI, GSI) ... MATSTAT (GSP ₁ GSP) are the highest P values, in descending order, of the diagonal of the MATSTAT matrix.

The matrix MATSTAT thus obtained also makes it possible to define the metric model MET_STAT for the M + 1 th evaluation by choosing for all i (1 <= i <= N), for all j (1 <= j <= N) a value of metric for the relation between Gi and Gj: M ET-STAT (Gi, Gj) = MATSTAT (ij). Since MATSTAT is symmetrical, one checks that MET_STAT (Gi, Gj) = MET_STAT (Gj, Gi). One then chooses a model of relevance identical to that used for the previous M evaluations, then one carries out the M + 1 th evaluation proper. The results obtained can then be integrated into the statistics.

The self-learning is therefore implemented incrementally, as and when evaluation markers Gi, during successive instances of the process of the invention. This is the self-learning means above which was used in the examples, with the set G of 51 markers presented thereafter. In this example, a collection of results already obtained for a series of distinct substances S (defined later) is used, before performing a statistical analysis of the results, as previously described in the present description.

In the example with the 51 markers, a symmetric MATSTAT matrix of 51 lines and 51 columns was generated during the statistical analysis. As described above, such a matrix MATSTAT is generated automatically during the current execution instance of the method of the invention, without requiring intervention of the user.

As an illustration, at the beginning of an instance of execution of the method, the user selects an arbitrary number Ns of seed markers. The system then selects Ns markers denoted G1 ... GNs such that the values corresponding to each of these markers, on the diagonal of the MATSTAT matrix, are the Ns highest values of the diagonal, with the following marker succession relationship:

MATSTAT (G 1, G 1)> = MATSTAT (G2, G2)> = ...> = MATSTAT (GNs, GNs).

Thus, at this stage, the system assigns the priority values successively to the markers G1,..., GNs and stores the PRIORITY values in the means (070), as already described previously in the present description.

Illustratively, the system stores in the means (070) the priority value value 1000 * MATSTAT (G ₁ G) to seed markers Gi (1 <= i <= Ns), and the priority value is 0 to other Gi markers.

In addition, the system uses the metric values present in the matrix MATSTAT, by applying a MET_STAT metric model configured in (020): Whatever (Gi, Gj) in all 51 markers,

MET_STAT (Gi, Gj) = MATSTAT (Gi ₁ Gj)

Finally, the relevance model loaded in (030) is the PERT_STAT model: Whatever the RES result of a test from RU1 for a G gene under specific exposure conditions,

PERT_ STAT (G) = 0 if 0.5 <RES <2;

PERT_ STAT (G) = 1 otherwise.

Parallel testing

In some embodiments of the method, the control means (100) may (i) add one or more Resource Units (061) in the set (060), (ii) subtract one or more

Resource (061) to set (060), or both. In these embodiments of the method, one and the same physical system can perform simultaneously several processes. distinct according to the invention. For example, in these embodiments, a single physical system can simultaneously perform a determination of the effects of several different substances or compounds on a given set of cells, or simultaneously perform a determination of the effects of a substance or compound. given over several sets of distinct cells, or even perform much more complex determinations simultaneously, for example the effects of several substances, each on a plurality of sets of distinct cells. In these embodiments, each determination method, which is distinct from the other determination methods simultaneously executed, uses means (051), (052) and (070) specific to this method, from a general set (060). -G) of Resource Units (061) that can be shared by all the processes that are simultaneously executed. In these embodiments, the general set (060-G) of Resource Units (061) may also be referred to as "Cluster" (060-G) of Resource Units (061).

In the Resource Unit Cluster (060-G) (061), each Resource Unit (061) is assigned a unique identification reference, as shown in Figure 7.

At a time T, several sets (060) of Resource Units (061) are defined, each set (060) of Resource Units consisting of a subset of the Cluster (060-G). A given Resource Unit (061) is included in a single set (060) of Resource Units.

However, at a given instant T during the parallel execution of the separate determination methods, a given Resource Unit (060) which was initially included in a set (060) of Resource Units selected to perform a P1 instance of execution of the method according to the invention can be subtracted from this set (060) dedicated to P1 and be added to a set (060) initially selected to perform an execution instance P2 of the method according to the invention.

Thus, in these embodiments of the invention, the size of the different sets (060) of Resource Units (061) assigned to each of the execution instances P1, P2, ..., Pn of the method according to FIG. The invention can vary dynamically.

In these embodiments, a Cluster Monitor means (1000) controls and controls the assignment of each Resource Unit (061) of the Cluster (060-G) to a single set (060) of Resource Units selected to perform. a single instance Pn of execution of the method according to the invention.

For this purpose, the Cluster Monitor (1000) performs an evaluation, at each instant T, of the number of Resource units (061) required for the execution of a given method Pn. The Cluster Monitor applies the following general rule: the number of Resource Units (061) assigned at a given instant to a set (060) for the execution of a method Pn according to the invention depends on the number of markers Gi referenced as "significant" on the basis of the acceptance value ACCEPT (defined above), in the means (070) of Operational Planning used for this method Pn at this time.

Thus, if RP (T) is the value of the number of Resource Units (061) required for the execution of the Pn process at time T, and SG (T) is the value of the number of "significant" markers. referenced at this time T in the means (070) of Operational Planning used by said method Pn, then we have the following relation:

RP (T) = O (SG (T)), with:

Y = O (X) meaning that Y is of the order of X, in other words a linear function of X (Y = aX + b). Thus, the more "significant" markers referenced in the Planning medium (070) Operational at a given instant T given for a given method Pi (1 <= i <= n), the greater the number of Resource Units (061) required in the set (060) of Resource Units of Pi is large.

However, for an optimal implementation of the realization in parallel of a plurality of execution instances P1, P2,..., Pn of the method according to the invention, it is advantageous to predefine a maximum value that RP ( T) can take for any one of the execution instances P1, P2,..., Pn in progress, in order to prevent the realization of a given execution instance Pn for which the means (070) of Operational Planning includes a very large number of "significant" markers mobilizes too many Resource Units (061) that would no longer be available, although required, for the simultaneous implementation of other P1 execution instances , P2, ..., Pn of the process. The Cluster Monitor (1000) therefore implements a Resource Unit assignment protocol (061) allowing an equitable sharing of the resource units (061) between the execution instances P1, P2, ..., Pn.

The assignment protocol of Resource Units (061) to the different sets (060) of Resource Units used by the simultaneous execution instances P1, P2, ..., Pn can be for example the protocol described above. below.

Let a cluster (060-G) containing a number RU (T) (variable in time) of Resource Units, and N execution instances Pi of determination according to the invention [with 1 <= i <= N] which are executed simultaneously. A dynamic partition of the Resource Units (061) of the Cluster (060-G) is performed in the N sets (060) of Resource Units Rbi dedicated to the execution instances Pi (1 <= i <= N). To ensure smooth execution of each process execution instance, each set (060) of Resource Units (060) is assigned a minimum number of Resource Units. A fraction F (0 <F <= 1) of RU (T) is assigned to this minimum, so that each set (060) Rbi (1 <= i <= N) of Resource Units (061) surely includes at least MINi (T) = F * RU (T) / N Resource Units (061) at time T.

The remaining (1-F) * RU (T) Resource Units (061) are dynamically distributed between the N sets (060) of Resource Units Rbi (1 <= i <= N), depending on the number of "significant" markers Sgi (T) referenced at time T in the operational planning means (070) used by each of the simultaneous execution instances Pi (1 <= i <= N) of the method. At each execution instance Pi, are allocated, in addition to

MINi (T) Resource Units (061) starting, also DYNi (T) Additional Resource Units (061), so that at time T, we have the following relation:

DYNi (T) = (I -F) * RU (T) * Sgi (T) / (ΣSgj (T), K = j <= N) We introduce arbitrarily the following rule: if Sgi (T) = 0, then

Sgi (T) = 1.

A variant of the above rule is preferred in situations in which each execution instance Pi uses a collection Ci of markers, such that the variance of Ci (1 <= i <= N) is large; say in situations in which the number of markers referenced in the storage means (051) and (052) is very variable from a execution instance Pi to a separate execution instance Pj. In this specific situation, the minimum number of Resource Units (061) can advantageously follow then the following rule: MINi (T) = F * RU (T) * (Ci / ΣCj, 1 <= j <= N))

Each execution instance Pi is allocated, in addition to the starting MINi (T) Resource Units (061), also DYNi (T) additional Resource Units (061), so that at time T, we have the following relation: DYNi (T) = (I -F) * RU (T) * Sgi (T) * Ci / (ΣCj * SGj (T), 1 <= j <= N) We introduce arbitrarily the following rule: if Sgi (T) = 0, then Sgi (T) = 1.

The above rules are easily extended by those skilled in the art to the number of execution instances of the method according to the invention which depends on the time N (T). Fraction F can also depend on time, ie Fraction F can be adjusted by the user at time T. Finally, the number RU (T) of resource units

(061) contained in the Clsuter (060-G) may vary over time to allow the user to dynamically adjust the size of the Resource Unit Cluster (060-G) (061) by dynamic addition / removal of resource units.

Thus, another object of the invention is a method for simultaneously determining the state of a plurality of sets of prokaryotic or eukaryotic cells by means of determining the state of a set of contained or expressed biological markers. by the cells of each set of cells, said method comprising the following steps:

1) performing, for each set of cells of the plurality of sets of cells, a method according to the invention comprising the steps a) to f) described above;

2) recover, for each set of cells, all the state parameters contained in the storage means (052) at the end of step f) of the method executed with said set of cells, the set of data recovered constituting the state of the plurality of sets of cells determined by the method;

As indicated previously in the description, the term "cell set" encompasses cell cultures exposed to specific environmental conditions. For example, a "set of cells" encompasses a culture of cells of a given type, for example of a specific cell line, placed under determined temperature, culture medium and gas atmosphere conditions. Also, a "set of cells" encompasses cells of a given type that are exposed to a determined substance S, for example a candidate substance S to be tested. Also, a "set of cells" includes cells of a given type that are exposed to said substance S for a given duration of exposure.

To carry out the above method, a plurality of execution instances of the general method of the invention are performed, each execution instance of the general method for determining the state of a set of cells, included in the a plurality of sets of cells whose state is evaluated.

As will be explained later in the present description, an execution instance of the general method according to the invention is carried out using a system for determining the state of at least one set of prokaryotic or eukaryotic cells, whose characteristics will be defined. To perform the above method of determining the state of a plurality of cell sets in the shortest possible time, it is advantageous to simultaneously implement a plurality of systems for determining at least one set of cells, in order to simultaneously perform as many instances of execution of the general method of the invention as there are distinct sets of cells to evaluate. In this particular embodiment of the above method, a plurality of systems according to the invention are implemented simultaneously, or almost simultaneously, said plurality of systems according to the invention constituting a device according to the invention.

To perform the method of determining the state of a plurality of above cell sets, the number of systems used will depend on the number of cell sets to be evaluated as well as economic considerations. Indeed, in some embodiments, it may be advantageous to implement a number of systems according to the invention is less than the number of sets of cells to be tested, for reasons of costs of each system. In these embodiments, the above method will be initiated with a limited number of systems according to the invention, in order to realize as many instances of execution of the general method and to determine the state of said number of sets of cells, less than the number of all the sets of cells to be evaluated. Then, after stopping each first execution instance of the general method on a given system, a next execution instance of the method is started, in order to evaluate the state of the sets of cells not yet tested. In these particular embodiments, a device according to the invention, capable of determining the state of all the sets of cells to be tested, comprises a number of systems according to the invention less than the number of sets of cells to be tested.

In some embodiments of the method according to the invention, it is characterized in that the set of test execution priority data in the operational planning means (070) is initialized so as to induce a global order markers Gi, the method using a zero metric so that the chronology of the markers tested during the execution of the process faithfully reproduce the specified initial order.

In certain other embodiments of the method according to the invention, it is characterized in that the test execution priority data in the operational planning means (070) for all or part of the markers contained in (051) are initialized with positive or infinite positive priority values, the method using an arbitrary metric and an arbitrary relevance model.

The method according to the invention can in particular be applied to the determination of the effect of a substance (S) to be tested on a set (CELL) of prokaryotic or eukaryotic cells. In this particular embodiment of the method, the effect of the substance (S) on the whole (CELL) of cells can be tested (i) for several values. concentration (C1, C2, ..., Cn) of the substance (S) for a given duration of exposure (T), (ii) for several exposure time values (T1, T2, ..., Tn) of the set (CELL) of cells to the substance (S) for a concentration value (C) of (S) determined or (iii) for a combination of concentration (C) and duration of exposure ( T). In this particular embodiment of the method, steps a) to e) are performed for a concentration value (C) of the substance (S) and a value of exposure time (T) of the cells (CELL) at said substance (S) determined during a process execution instance. Thus, each execution instance of the method allows the determination of the state of the set (CELL) of prokaryotic or eukaryotic cells, for a determined combination of concentration (C) of (S) and exposure duration (T). ) cells (CELL) to (S). Thus, in order to determine the effect of the substance (S) on the set of cells (CELL), as many process execution instances are made as there are combinations of concentration values (C) with the values duration of exposure (T). The number of useful combinations is generally set by the user, before starting the process. The number of combinations is set in particular according to the volume of test results necessary to obtain a final effect value of the substance (S) on the set of cells (CELL) that is statistically significant. The skilled person can easily set the number of combinations necessary to obtain a statistically significant result, using his general technical knowledge.

The plurality of process execution instances necessary to fully determine the effect of substance (S) on the whole (CELL) of prokaryotic or eukaryotic cells can be performed (i) simultaneously, (ii) spread over time, or (iii) simultaneously for part of the number of instances of execution and successively in time for the remaining part of the number of execution instances.

Thus, the present invention also provides a method for testing the effect of a substance (S) on a set (CELL) of prokaryotic or eukaryotic cells comprising the steps of: a) determining a number of combinations of (i) concentration (C) of said substance (S) and (ii) duration of exposure (T) of the set (CELL) of cells to said substance (S) to perform the test; b) performing as many instances of execution of the general method of the invention as combinations determined in step a); c) determining the effect of the substance (S) on the whole (CELL) of prokaryotic or eukaryotic cells, said effect being determined from the totality of the state parameters of the markers Gi contained in the storage means (052 ) after completion, in step b), of the last execution instance of the general method of the invention.

Thus, the subject of the invention is also a process as defined above, whose purpose is to evaluate the impact of a substance S disrupting a CELL cell culture under conditions of concentration and exposure time ( Cref.Tref), taking into account the results of a set of N evaluations {E1 ... EN} earlier, knowing that:

each evaluation Ei (1 <i≤N) was obtained by a system Sys (i) according to claims 10 and 11

- each system Sys (i) (1 <i≤N) aimed to evaluate the impact of a substance Sub (i) identical or not to S disrupting a cell culture C (i) identical or not to C under conditions of concentration and time of exposure (Cs (i) .Ts (i)) identical or not to (Cref.Tref) by means of a set of marker Gset (i), so that the process can define by a third means, for a subset M of markers Gi of UNION (Gset (i)), (1 <i≤N), UNION representing the set union, a weighting POND_M of markers Gi of M, the weight of each marker G of M in POND_M taking into account values RELEVANCE (G), Result (G) and Iter (G) obtained in the means (051) and (052) evaluations Ei (1) <i≤N) in which G participated, the weight of each marker G of M in POND_M accounting for the overall relevance of the marker G in the N evaluations {E1 ... EN}.

The invention also relates to a method of the above type using to perform the evaluation of the impact of substance S on cell culture CELL under the conditions of concentration and exposure (Cref.Tref), such as as defined above, a set of markers Gset of which a subset M is known to have participated in N prior evaluations Ei, 1 <= i <= N, so that the weighting POND_M of all or some of the markers of M can being established by the system according to the description given in claim 12, the weighting information obtained making it possible to establish the initial priority data of the markers of M in the means (070) of said system, said initial priority of each marker Gi of M being proportional to the weight of the marker Gi in the weighting POND_M.

The subject of the invention is also a method of the above type, using to perform the evaluation of the impact of the substance S on the culture of CELL cells under the conditions of concentration and exposure (Cref.Tref), as defined above, a set of markers Gset of which a subset M is known to have participated in N prior evaluations Ei, 1 <= i <= N, so that the weighting POND_M of all or part of the markers of M can be established by the system according to the description given above, the weighting information obtained making it possible to establish the metric data of the relationships between markers of M in the means (020) of said system, the metric value between any two markers Gi and Gj of M being obtained by comparing the weights of the markers Gi and Gj obtained in POND_M. The subject of the invention is also a method of the above type using a set of Gi markers, the method being used to perform multiple impact evaluations of arbitrary substances on arbitrary cell cultures under concentration and time conditions. arbitrary exposure with all or some of the markers Gi, the method accumulating the weighting data Gi markers as successive evaluations and, by successive correction weighting data, self-learning priority data initials and metrics for all or part of the set of Gi markers used.

Thus, the general method for determining the state of at least one set of prokaryotic or eukaryotic cells according to the invention can also be applied to the determination of the effect of a substance (S) on a plurality of whole of cells (CELL1, CELL2, ..., CELLn), for example on a plurality of cultures of cell lines and / or cultures of cells in primary culture. To perform such a test, the number and identity of each set (CELL1, CELL2, ..., CELLn) of cells to be tested, (ii) the number of concentration values (C1, C2, ..., Cn) of said substance (S) to be tested and (iii) the number of exposure time values (T1, T2, ..., Tn) of the cells to said substance (S), then the number of combinations of these three parameters which are necessary to perform said test is determined. Then, as many execution instances of the general method for determining the state of at least one set of cells of the invention as there are combinations determined above for the three parameters of the type of cells, concentration and duration of exposure. The number of combinations necessary to obtain a statistically significant final result can be easily determined by those skilled in the art, using his general technical knowledge. The subject of the invention is therefore a method for testing the effect of a substance (S) on a plurality of sets (CELL) of prokaryotic or eukaryotic cells comprising the following steps: a) determining a number of combinations of i) sets of cells (CELL1, CELL2, ..., CELLn) contained in said plurality of sets of cells, (ii) concentration values (C1, C2, ..., Cn) of said substance (S) and (iii) the duration of exposure (T1, T2, ..., Tn) of the cells to said substance (S), to carry out the test; b) performing as many instances of execution of the general method of the invention as combinations determined in step a); c) determining the effect of the substance (S) on the plurality of sets (CELL) of prokaryotic or eukaryotic cells, said effect being determined from the totality of the state parameters of the markers Gi contained in the storage means (052) after completion, in step b), of the last execution instance of the general method according to the invention.

Illustrative Examples of Process Execution with Self-Learning and Oarallelization of Tests The features of the method according to the invention allow (i) self-learning of the system with an increasing number of process execution instances and (ii) a possibility of simultaneously executing separate instances of execution of the method, have been described previously in the present description. Below are presented some embodiments of the method which illustrate technical advantages related to self-learning and the possibility of parallelization of the tests, especially when the method according to the invention is applied to the determination of the effect of a substance or a compound to be tested on a set of prokaryotic or eukaryotic cells. Thus, in certain embodiments of the method according to the invention, the operator can optimize the execution time of a process instance, for example by informing the system on (i) the type of activity sought for the compound to test or (ii) the type of chemical structure of the test compound, prior to or simultaneously with step a) of initialization of the system preceding the start of the test itself.

In certain embodiments of the method, the introduction of one or more data relating to the compound to be tested, in particular the type of activity sought for said compound or the type of chemical structure of said compound, make it possible to select among previous performance those whose objective was to test compounds sharing characteristics (structure and / or activity) common with the test compound. The use of the results of these previous execution instances then makes it possible to form a matrix MATSTAT used for the loading of the means (070) of Operational Planning and the means (020) for storing the values of metrics of the relations between the marker, at the same time. step a1) as already detailed in the description of the self learning property of the invention.

More specifically, when it is desired, for example, to test the cytotoxicity activity of a given compound, it is possible to use, in step a 1), the data stored in a MATSTAT matrix formed from the results of instances prior art for relevant markers to be tested for cytotoxicity to define the metric values contained in the storage means (020) and the initial priorities of the seed markers contained in the means (070). It is recalled that, in this case, the data contained in the matrix MATSTAT used were calculated during previous instances of execution of cytotoxicity tests, (i) with compounds whose cytotoxicity was already known at the time of said previous instances or (ii) with compounds that have been determined to be cyotoxic compounds in said prior instances, or (iii) with the types (i) and (ii) of compounds hereinbefore.

An illustration of such an embodiment of the method according to the invention is presented in Example 2. Thus, in Example 2, the method of the invention was used to test the cytotoxicity of the compound Paraquat, using, to load the Operational Planning means (070) with a set of potentially appropriate Gi marker data and the means (020) with metric values for potentially appropriate marker relationships, the results of execution instances Prior methods of the method with 14 compounds known or determined to be cytotoxic, said results being assembled in a matrix MATSTAT, in a form exploitable by the method. In these embodiments of the method of the invention, it is also possible to load the operational planning means (070) and the storage means (020) in step a) with a series of markers chosen on the basis of the chemical structure of the test compound. In these specific embodiments of the method, the system initiation step a) may (i) include a structure / activity relationship analysis step based on the structural data of the test compound or (ii) be preceded such a step of analyzing structure / activity relationships. In these embodiments, the step of analyzing structure-activity relationships between (i) on the one hand, the structure data of the test compound and (ii) on the other hand, the structure data of compounds already tested according to the method:

(1) allows to select one or more compounds already tested as constituting relevant bases of comparison with the test compound, then to form an MATSTAT matrix with the results obtained by the previous execution instances for these compounds, and (2) to determine the initial identity identity relative to the markers Gi, from the MATSTAT matrix previously generated. The data of said markers Gi thus selected are then loaded into the means (070) of Operational Planning and the means (020) for storing the metric values of the relations between markers, in step a1) of the method according to the invention as has already been detailed in the description of the self learning property of the invention.

Thus, according to certain aspects of the method of the invention, step a) comprises a step a) (iii-1), which preferably precedes step a) (iii), step a) (iii-1 ) consisting of a priority rank assignment step for at least a part of the Nm markers Gi whose data are stored in the means (010) and (020), said step a) (iii-1) being selected from l one of the following steps: (1) a step of assigning a priority rank to each marker Gi, said priority rank being calculated according to the degree of relevance of said marker Gi with respect to the type of effect cell disturbance sought for the current execution instance of the method; (2) a step of assigning a priority rank of each marker Gi, said priority rank being calculated according to the degree of relevance of said marker Gi with respect to the chemical structure of the substance S tested in the the current execution instance of the method.

As already indicated, the relevance of each Gi (i) marker to a type of cell perturbation effect or (ii) to the chemical structure of the test compound, for the assignment of a rank of priority to said marker Gi is calculated from the data already contained in MATSTAT matrices generated during previous instances of execution of the method, for example:

(i) prior instances of performing the method for testing a particular type of cellular disturbance effect, such as oncogenicity, inflammatory activity, ability to induce cellular apoptosis, cytotoxicity, etc. ; or

(ii) prior instances of execution of the method for testing a compound having a specific type of chemical structure, close to the chemical structure of the test compound in the instance running the process. The similarities of chemical structure between two compounds, respectively (a) a compound whose test data are included in a MATSTAT matrix previously generated and (b) the test compound, are preferably calculated according to a QSAR type analysis.

The degree of relevance of a given marker Gi with respect to the test to be performed, for assigning a priority rank for said marker Gi, can be calculated by any means, since this calculation makes it possible to assign a priority rank for said marker Gi. For example, for prioritization based on chemical structure comparisons, the degree of relevance is provided by the result of the QSAR analysis calculation.

Thus, in some of its embodiments of the method, step a) (iii-1) above consists of a step of assigning a priority rank of each marker Gi, said priority rank being calculated at from the results of a QSAR analysis between the chemical structure of the substance S tested and the chemical structure of compounds tested during previous execution instances of the process.

Typically, a QSAR analysis comprises the following steps: (1) generating and storing in a suitable storage means, by the memory of a computer, a set of data characteristic of the structure of a substance (S1) to be tested; (2) comparing said set of data generated in step (1) above with a plurality of data sets characteristic of the structure of a plurality of substances (S2, S3, ..., Sn), each set of data being characteristic of the structure of a given substance, among S2, S3, ..., Sn, said plurality of data sets having been previously generated;

(3) classifying the substances (S2, S3, ..., Sn) according to the degree of similarity of structure of each of said substances with the substance (S1) tested;

(4) select the substances with the greatest degree of structural similarity with the substance S1 tested;

(5) determining, for the substances selected in step (4), Gi markers whose presence and / or level of expression have been modified, and selecting said Gi markers;

(6) using said markers Gi selected in step (6) to initialize the system, in step a) of the method.

The structure / activity relation data sets of the substances (S2, S3, ..., Sn) above can result from: - test results obtained during the realization of previous instances of execution of the process of the invention with each of said substances S2, S3, ..., Sn; or

structure / activity relation data already known in the literature for each of said substances S2, S3,. According to the invention, the above data sets for each of the substances S2, S3,..., Sn may be included in matrices of the MATSTAT type.

As already indicated, the priority rank information, generated for at least a portion of the Nm markers Gi, are loaded in the means (070) of Operational Planning.

An illustration of such an embodiment of the method of the invention is presented in Example 3. Example 3 describes the results of the implementation of the method in the form of a cytotoxicity evaluation test. of a candidate compound to be tested, Rotenone. A preliminary analysis of structure-activity relationship by QSAR (Quantitative Structure-Activity Relationship) determined that the Rotenone was statistically close to several compounds, respectively Abamectin, Carbaryl and Fenazaquine. Abamectin, Carbaryl and Fenazaquine consist of reference substances which have already been tested for their neurotoxicity with the process of the invention. The results obtained for Abamectin, Carbaryl and Fenazaquine make it possible to calculate a corresponding MATSTAT matrix. Based on the identity data, the priority rank of the Gi markers, and the metric relationship between markers contained in the MATSTAT matrices generated for the neurotoxicity of the compounds Abamectin, Carbaryl and Fenazaquine, the markers Gi potentially relevant to the Rotenone compound to be tested, then we load the means (070) of Operational Planning and the means (020) for storing the metric values of the relationships between markers, in step a1) of the method according to the invention as it was already been detailed in the description of the self learning property of the invention.

The results obtained show that, thanks to the prior selection of the relevant Gi markers, complete or quasi-complete information concerning the neurotoxic activity of the candidate compound Rotenone is obtained after only 23 cycles of execution of the steps b) to e). of the method (87% of the relevant informative markers tested) or after only 40 cycles of steps b) to e) of the method (100% of the relevant informative markers tested).

Thus, carrying out step a1) of the method with a selection of markers whose initial priority rank and the metric of the relations between markers is determined on the basis of the data contained in previously generated MATSTAT matrices (i) for compounds having the physiological effect that is to be determined for the candidate compound, and (ii) for compounds having a structure close to the candidate compound, in particular those also having said physiological effect (structure-function relationship analysis), allows of considerably reducing the number of execution cycles of steps b) to e) of the method which are necessary to generate the results making it possible to classify the candidate compound, for example among the neurotoxic compounds or among the non-neurotoxic compounds. Of course, in the execution instance of the method with the new candidate compound, a new MATSTAT corresponding matrix is generated, the data of which can subsequently be used as references for the selection of relevant markers Gi, in step a1) a subsequent instance of execution of the process. Thus, the performance of the process of the invention increases with the increasing number of test results already achieved, which made it possible to generate MATSTAT reference matrices.

Thus, overall, the self-learning characteristics of the method according to the invention, some embodiments of which are illustrated above, entail a considerable time saving, given the reduced number of execution cycles of the steps b). to e) which is necessary, and also entails a reduced cost of implementation.

Also, according to some embodiments of the method according to the invention, to carry out the test of the physiological effect of a candidate compound, several distinct selections of a batch of relevant Gi markers may be available, for example a batch of markers. Gi relevant for a cytotoxic effect by apoptosis, or a batch of markers Gi relevant for a cytotoxic effect by oxidative stress. By way of illustration, for the test of a candidate compound for a given physiological effect, several distinct selections of a batch of relevant Gi markers may be available, for example a batch of Gi markers relevant for a hepatotoxicity effect, or a batch of Gi markers relevant for neurotoxicity effect. Consequently, for a candidate compound to be tested for a given physiological effect, for example of cytotoxicity, several instances The method according to the invention can be implemented successively, that is to say in series, or simultaneously, that is to say in parallel.

In another aspect, the test results for a candidate compound, which are retrieved and analyzed successively at each cycle of steps b) to e), in a given execution instance of the method, may allow:

(i) determining whether the terminating step f) should be performed early, before performing a test for all initially selected Gi markers; and

(ii) deciding, for said candidate compound, the realization of one or more other instances of execution of the method, with distinct selections of markers Gi, where appropriate one or more distinct selections more relevant than the selection of markers Gi that was performed for the first instance of execution of the process.

This other aspect of the invention relates to situations in which the results of tests obtained with the initial selection of markers Gi, are uninformative and where it is therefore necessary to perform other instances of execution of the method with other potentially more relevant selections of Gi markers. This type of situation is conventionally encountered when an execution instance of the method is started while few MATSTAT matrices, or no MATSTAT matrix, relevant for the test to be performed, are stored in the system. This is typically the situation in which, for the test of a given physiological effect of a candidate compound, no reference MATSTAT matrix exists and where the markers Gi are selected arbitrarily, or are selected on the basis of of a priority rank affected solely by prior public knowledge of each of the markers Gi, which have not yet been experimentally tested with the method of the invention. According to this same aspect, the additional instances of execution of the method for testing said effect of said candidate compound can be started and executed simultaneously, successively, or in a time-shifted manner. The possibility of running in parallel manner a plurality of execution instances of the method of the invention has been described previously in the present description.

Still according to this particular aspect of implementation of the method according to the invention, the results of the tests performed during a given execution instance can alone constitute a set of information sufficient to characterize the candidate compound, for example concerning its possible cytotoxicity properties. Also, all of the information necessary to characterize said candidate compound may consist of the results of several execution instances, among the plurality of execution instances of the method which are finally performed with said candidate compound. In still other cases, all of the information necessary to characterize said candidate compound consists of the results of all the execution instances finally performed with said candidate compound. As indicated above, each of the execution instances can be performed for all the Gi markers initially selected for this execution instance, or for only a part of the Gi markers initially selected in case of early termination of this instance.

Finally, again according to this same aspect of the method of the invention, where a plurality of execution instances of the method is carried out for the determination of a given physiological effect of a candidate compound to be tested, the data of a matrix MATSTAT generated during the execution of a given instance of the method becomes a reference matrix on the basis of which a distinct selection of markers Gi can be made to start another execution instance, included in the plurality of instances execution above. Thus, an instance E1 generates results that can then be used to select the markers Gi to be tested during an instance E2 of a plurality of execution instances E of the method. In certain cases, it is the set of results generated by the realization of the plurality E of instances (E1, E2, ..., En) which makes it possible to characterize the candidate compound, from the point of view of the effect physiological whose determination is sought.

It is therefore understood that, according to this particular aspect of the method, the nature and the sequence of the different execution instances of the method subsequent to the first instance of execution (E1) is not necessarily determined in advance, at the when the execution instance E1 starts. The nature and sequence of the instances of execution subsequent to the first instance (E1) can be determined, in part or in whole, on the basis of the test results generated during the execution of the first instance E1.

In some cases, the successive determination of sets of markers Gi used in each instance of the plurality of execution instances of the method, in particular according to the results generated by already performed instances included in the final plurality of execution instances , can be represented in the form of a results tree, said results tree itself being able to be indexed in an additional information storage means of the system of the invention. The constituent data of this result tree, when stored in a suitable storage means of the system according to the invention, can be used later in a subsequent execution of the method, and contribute for example to selecting sets of markers. Gi for each instance of a plurality of subsequent execution instances of the method, for example for testing another candidate compound, for an identical physiological effect. In addition, a result tree that is generated as a result of the successive choices of a set of markers Gi for the execution of each instances included in the plurality of execution instances of the method, for example in the case where each instance is performed, for a given candidate compound, for a combination of parameters (i) of markers Gi to be tested, (ii) of concentration (C) of said candidate compound, (ii) time of exposure (T) of the cells to said candidate compound and (iv) cell identity (CELL) tested in the presence of said candidate compound, can be represented in a vector form . The parameters (trajectories) of the constitutive vectors of the result tree can be defined according to one or more of the following vectors: (i) the vector of the results of all Gi markers for a given concentration (C) of the candidate compound and a given exposure time (T) of the cells to said candidate compound

(trajectory in the marker space);

(ii) the vector of the results of a marker Gi for a given concentration (C) of the candidate compound, for all the durations of exposure (T1, T2, ..., Tn) of the cells to said candidate compound (trajectory in the space of concentrations); (iii) the vector of the results of a marker Gi for all the concentrations (C1, C2, ..., Cn) of the candidate compound, for a given duration of exposure (T) of the cells to said candidate compound (trajectory in the space of the exposure times); (iv) the vector of the results of a marker Gi for all the concentrations (C1, C2, ..., Cn) of the candidate compound and all the exposure times (T1, T2, ..., Tn) of the cells to said candidate compound, for a given type of cell (CELL), for example for a given cell line (trajectory in space of cell lines)

Thus, in some embodiments of the method, a plurality of vectors (a plurality of trajectories) can be generated for evaluating a single candidate compound. These vectors (trajectories) can be compared with each other in order to determine various comparison parameters, in particular among the following illustrative comparison parameters:

(i) the determination of the overall evolution of the set of Gi markers tested (comparison between the trajectories in the marker space);

(ii) determining the evolution of a Gi marker for a plurality of concentrations of the candidate compound, as a function of the duration of exposure of the cells to said candidate compound (comparison of trajectories in the marker space, for a marker Gi given);

(iii) determining the evolution of each Gi marker as a function of the concentrations of the candidate compound, for a given exposure time of the cells to said candidate compound (analysis of the synchronization of the cellular response as a function of the concentration of the candidate compound , by comparison between the trajectories in the space of the exposure times, for different Gi markers);

(iv) determining the evolution of each Gi marker as a function of the duration of exposure of the cells to said candidate compound, for a given concentration of said candidate compound (analysis of the synchronization of the cellular response as a function of the exposure durations of the cells to said candidate compound, by comparison between the trajectories in the space of the exposure times, for distinct Gi markers); Deregulation space

The results obtained because of the implementation of a plurality of execution instances of the general method according to the invention make it possible to generate three-dimensional matrices whose data delimit a "deregulation space". For example, a plurality of execution instances of the general method according to the invention makes it possible to obtain data, for each marker Gi tested, concerning the effect of a candidate substance S on the level of expression of said marker Gi , as a function of, respectively: (i) the concentration value of substance S over the set of cells tested (first dimension);

(ii) the duration of exposure of the set of cells tested to the candidate substance S (second dimension); and

(iii) the type of cell set exposed to said candidate substance S (third dimension).

This "Deregulation Space" delimits a space from which it is possible to determine, in particular, the following information for the Gi marker considered:

the space in which said substance (S) induces an effect on the level of expression of the marker Gi;

the space in which the effect induced by S is reversible, this space consisting of a subspace of the first space above;

the space in which the effect induced by S is irreversible, this space also consisting of a subspace of the first space above. The knowledge, for each marker Gi, of the corresponding deregulation space for a given substance S consists of an additional tool, provided by the method of the invention, making it possible to summarize the relevant information relating to the activity of said substance. S candidate (cytotoxicity, pharmacological activity, etc.), which can be very useful, especially for the regulatory approval phase of said substance S tested.

System according to the invention

The present invention also provides a system for determining the state of at least one set of prokaryotic or eukaryotic cells by determining the state of a set of biological markers contained or expressed by said cells, said system comprising:

1) means (010) data storage comprising a set of data characterizing a number _M of N biomarkers Gi;

2) means (020) for storing data characterizing a metric relationship R _M between two biological markers Gi among the N _M biological markers listed in the means (010), said means (020) comprising, for each data item of relation between two biological markers:

an identification reference of a first biological marker G1 included in the means (010);

an identification reference of a second biological marker G2 included in the means (010); a METRIC value (RM) defining the metric relation RM between the first and the second marker;

3) means (060-G) consisting of a set of Resource Units, comprising a number NU _R of Resource Units (061), each Resource Unit (061) having the function of transmitting at least one parameter of a state of a biological marker Gi, contained or expressed by a culture of C cells, to a state parameter evaluation means (300), each Resource Unit (061) comprising:

means (0611) for identifying said Resource Unit (061);

means (0612) for indicating the operating state of said Resource Unit (061) at a given instant;

means (0613) for determining at least one state parameter of a biological marker Gi, contained or expressed by a C cell culture; means (0614) for transmitting a signal between said Resource Unit (061) and the state parameter evaluation means (300);

4) means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a culture of C cells, said means (050) comprising:

means (051) for storing data relating to at least one or more biological markers selected from the group of N _M biological markers listed in the means (010), and to storage of relevance data, said means (051) comprising, for each of the biological markers listed in this one:

an identification reference of a first biological marker included in the means (010);

an identification reference of a second biological marker included in the means (010);

a METRIC value (RM) defining the metric relation RM between the first and the second marker; and

a value P (Gi) defining a relevance of said first marker in a test carried out for a determined marker Gi and for a determined set of cells, said value P (Gi) being calculated by means (400) of analysis;

means (052) for storing test results produced by one or more Resource Units (061) included in a means (060) consisting of a subset of the means (060-G), said means (052) of storage comprising a set of test result data, each test result data comprising:

an identification reference of a biological marker included in the means (010) and a state parameter of which is determined by means of a Resource Unit (061) included in the means (060); an order value specifying the test rank of said biological marker;

at least one state parameter value defining the result of the test carried out with said biological marker by said Resource Unit (061).

5) evaluation means (300) for performing tests and storing test results performed by one or more Resource Units (061) included in the means (060), said means (300) comprising: - means for storing at least one state parameter of a biological marker Gi, said state parameter being generated by a Resource Unit (061);

means for transmitting and receiving a signal between said means (300) and the Resource Units (061) included in the means (060);

means for transmitting a signal between said means (300) and the control means (100);

means for transmitting a signal from said means (300) to means (400) for analyzing the test results. 6) means (030) for storing a calculation function of a value P (Gi) defining the relevance of a biological marker Gi listed in the means (010);

7) an analysis means (400) for calculating the P (Gi) value defining the relevance of a biological marker Gi listed in the means (010), for a given cell culture C, using the function stored in means (030) with at least one state parameter defining the result of the test performed with said biological marker Gi by a Resource Unit (061), said state parameter being supplied to means (400) by the means (300). ), said means (400) comprising means for receiving a signal transmitted by the means (300); 8) Operational Planning means (070) including:

a set of test execution priority data for the biological markers Gi, said means (070) comprising, for each biological marker Gi: an identification reference of said biological marker Gi; and

a PRIORITY value defining the priority rank of said biological marker Gi;

signal transmission means between said means (070) and the control means (100); means for initial configuration of the priority data for each marker; the priority data being positive or zero values;

9) System initialization means (200), comprising:

means for transmitting a signal between said means (200) and the control means (100);

means for transmitting a signal between said means (200) and the means (010) comprising a set of data characterizing a number N _M of biological markers Gi;

means for transmitting a signal between said means (200) and the data storage means (020) characterizing a metric relationship R _M between two biological markers Gi.

means for transmitting a signal between said means (200) and means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a C cell culture.

means for transmitting a signal between said means (200) and the means (070) comprising a set of data characterizing the initial priorities of the Nm biological markers Gi.

10) control means (100) comprising: means for transmitting a signal between said means (100) and each Resource Unit (061); means for transmitting a signal between said means (100) and the operational scheduling means (070);

means for transmitting a signal between said means (100) and the means (300) for analyzing the test results; means for transmitting a signal between said means (100) and the data storage means (050);

means for controlling the operation of the Resource Units (061).

Advantageously, the method of the invention is realized using a system including one or more computer (s). Thus, advantageously, the system as defined above includes at least one computer, which includes the following internal and external components.

The internal components of said computer system include a processor element, for example a microprocessor, which is interconnected with a main memory element. For example, the computer system may consist of a Pentium ^® type processor, such as a Pentium ^® microprocessor marketed by the Intel Corporation (USA), which has a clock speed of 3.20 GHz said microprocessor being connected to a main memory of 256 MB or larger.

External components include mass storage means, such as one or more hard disks, that have a storage capacity of at least 40 GB. The external components also include at least one display means, such as a printer or a computer screen. The external components also include at least one information input means in the system, such as a computer keyboard, a pointing device, a graphics palette, and so on.

The external components also include at least one interface device allowing the signals transmitted by the Resource Units (061) to be interpreted and processed by the microprocessor. Such an interface device generally consists of a device capable of converting a analog signal generated by the Resource Units (061) into a digital signal that can be processed by the microprocessor.

External components may be removed from the computer using any suitable communication mechanism including, but not limited to: computer network, data bus, fieldbus, serial link, etc. In the case where more than one computer is used, the computers may communicate through any available means of communication, including but not limited to: one or more local network (s), serial or parallel interface, extended network (internet) ), wired or wireless, telecom network, to allow a distributed and cooperative implementation of the process.

In the above system, the means (010), (020), (030), and (050) consist of data storage means which are preferentially included in the main memory of the computer system, more specifically in partitions of the central memory that are allocated by the microprocessor to these data storage means.

In the above system, the control means (100), the initialization means (200), the test evaluation means (300), the data analysis means (400) and the means (070) ) Operational Planning also include data storage means which are preferentially included in the main memory of the computer system. The data processing which is carried out by the means (300), (400) and (070), in particular the commands and the calculations, is preferentially carried out by the microprocessor.

In the case where several computers are used, the means (010), (020), (030) as well as the storage means used by the means (100), (200), (300), (400) and (070 ) can be distributed in the RAMs and / or storage of said computers. Still in this case, the data and instruction processing included in all the means presented in the invention can be carried out on a single computer, or on the contrary distributed over the set of computers by means of distributed algorithms.

The computer system also includes, loaded in its main memory or in the one or more mass storage means, one or more computer program elements. The computer program element or elements include the operating system that is responsible for managing the system according to the invention, including the coordination of the operation of the internal and external components of said system, and the execution of the elements of the system. program containing the specific instructions for the implementation of the method according to the invention. Thus, the computer program element (s) comprise sequences of instructions that enable the microprocessor to perform the data processing that is necessary to execute the method according to the invention. In addition, in order to facilitate the implementation and operation of the method, the system may use additional software tools such as, but not limited to, database software, interactive graphical interfaces, systems for archiving, in order to implement the set of means presented in the invention.

In some embodiments of a system according to the invention, which are particularly suitable for the implementation of the method including a step (a) (iii-1) of priority ranking for Gi markers based on a comparison of the chemical structure of a candidate compound to be tested, with respect to the chemical structure of compounds already tested and whose test data are included in already generated MATSTAT matrices, said system further comprises a means (1000) for comparing chemical structures. For example, the means (1000) may consist of a computer program comprising a series of instructions for performing a QSAR-type structure / activity comparison. A system according to the invention also comprises one or more Resource Units (061) which are connected to the computer system described above, such as for example one or more microarrays or one or more protein chips. In a particular embodiment of the method defined above, designated (I), the resource units (061) comprise at least one cell culture disruption means (CELL), placing it in the presence of a arbitrary substance S under conditions of concentration C1 and exposure time T1 set by the user, the system for evaluating the substance-induced disturbance S in said C1 concentration conditions and T1 exposure time on the cellular culture.

By "disturbance" is meant according to the invention a variation of the value of a state parameter of at least one marker Gi, with respect to the value possessed by said state parameter in a set of reference cells. for example in the absence of said arbitrary substance.

Alternatively, in one embodiment of the process defined above, designated (II), the cell culture (CELL) is previously disturbed by an arbitrary substance S under C1 concentration conditions and T1 exposure time given set by the user, said cell culture enabling the evaluation of said substance S-induced disturbance in said C1 concentration conditions and T1 exposure time on the cell culture. In some embodiments of the invention described above, the general method of determining the state of a set of cells may be applied to test the effect of a substance (S) on a set of cells, for example on a given cell line, or on a plurality of cell sets, for example on a plurality of distinct cell lines. In these particular embodiments of the invention, for which the determination of the state of a set of cells is performed for (i) a plurality of cell sets (CELL1, CELL2, ..., CELLn), optionally (ii) a plurality of concentrations (C1, C2, ..., Cn) of a substance (S), optionally (iii) a plurality of exposure times

(T1, T2, ..., Tn) cells to said substance (S) and optionally (iv) a plurality of substances (S1, S2, ..., Sn) to be tested, it is possible to use a plurality of determining the state of at least one set of prokaryotic or eukaryotic cells as defined above, especially in the case where the test is performed by simultaneously performing a plurality of execution instances of the general process of the invention, each execution instance of the general method being performed for a specific combination of (i) set of prokaryotic or eukaryotic cells, (ii) concentration of substance (S), (iii) duration of exposure of the cells to the substance (S) and (iv) substance (S).

Thus, the present invention also relates to a device for testing the effect of a substance (S) on a set (CELL) of prokaryotic or eukaryotic cells, said device comprising a plurality of systems (Sys1, Sys2, ... , Sys2) according to the invention, each of said systems according to the invention being adapted to determine the state of a set of prokaryotic or eukaryotic cells for a combination of at least two of the following parameters:

(i) a set (CELL) of prokaryotic or eukaryotic cells; (ii) a determined concentration (C) of a substance (S) to be tested;

(iii) a determined duration of exposure (T) of the cells to a substance (S) to be tested; and

(iv) a substance (S) determined.

Preferably, the device defined above constitutes a means of comparative evaluations based on multiple evaluations, characterized in that said evaluations are carried out by N systems (Sys1 ... SysN) such as those noted (I) or (II) above, each system Sys (i), 1 <= i <= N evaluating a cell culture (CELL) disturbed by a substance S under conditions of concentration C1 (i) and exposure time T1 (i) data set by the user and specific to the system Sys (i), and at least one of the systems, which may be designated SysRef, evaluating a culture of undisturbed reference cells, in order to obtain by comparison the results obtained for each of the systems (Sys1, Sys2, ..., Sysn) an estimate of the perturbation induced by said substance S according to the concentrations C1 (i) ( 1 <= i <= N) used as well as the exposure times T1 (i) (K = K = N).

Alternatively, in a particular embodiment of the above process, designated (III), the resource units (061) comprise at least one means for generating, from the cell culture (CELL), a culture of CELLtesti cells obtained by putting an arbitrary amount of CELL in the presence of an arbitrary substance S1 under C1 concentration conditions and exposure time T1 set by the user, and at least one means for generating, from cell culture (CELL), a cell culture CELLtest2 obtained by putting an arbitrary amount of CELL in the presence of an arbitrary substance S2 under concentration conditions C2 and exposure time T2 set by the user, then perform an evaluation in parallel, for a marker Gi contained in (051), cell cultures CELLtesti and CELLtest2 thus disturbed, thus allowing the Resource Unit to generate one or more state parameters for the marker Gi relating to the difference in behavior, relative to Gi, between the cell culture (CELL) perturbed with S1 according to C1 and T1 and the cell culture (CELL) perturbed with S2 according to C2 and T2. By extension, from the above immediately, in a particular mode of implementation of the method, the Resource Units such as described in the designated system (III) can generate one or more state parameters for a marker Gi contained in (051) relating to the difference in behavior, relative to Gi, between the cell culture (CELL) perturbed with S1 according to C1 and T1 and undisturbed cell culture (CELL).

Thus, according to some embodiments of a system or device of the invention, as defined in the present description, said system or device may also be characterized in that the Resource Units (061 ) comprise at least one means for generating, from a starting cell culture (CELL), a CELLtesti cell culture obtained by placing an arbitrary amount of CELL in the presence of an arbitrary substance S1 under concentration conditions C1 and exposure time T1 data set by the user, in order to perform a parallel evaluation, for a marker Gi contained in (051), cell cultures CELLtesti and CELL undisturbed allowing the unit of resource to produce one or more state parameters for the marker Gi relating to the difference in behavior, relative to Gi, between the cell culture (CELL) disturbed with S1 according to C1 and T1 and the cell ulture (CELL) undisturbed. Means for generating, from a starting cell culture, cultures of cells exposed to specific environmental conditions are known per se in the state of the art. These means may notably consist of programmable laboratory automatons, which are commonly marketed.

Preferably, the device defined in a general manner above, constitutes a means of comparative evaluations noted ScompCT based on multiple evaluations, each evaluation corresponding to an execution instance of the general method of the invention, and to quantify the the impact of a set of N concentration conditions and exposure time (Ci ₁ Ti), 1 <= i <= N in the disturbance of a culture of cells (CELL) by a substance S, with respect to a reference concentration and exposure time condition (Cref.Tref) for the same substance S, ScompCT comprising:

a system Sys1 as defined by the preceding notation (I), (II) or (III) using a set of Gset markers stored in the means (051), allowing the evaluation of a cell culture (CELL) disturbed by the substance S under concentration and exposure time conditions (Cref.Tref) so that a reference evaluation E of the perturbation induced by said substance S and a chronology T concerning the sequence of the tests are obtained; markers of Gset carried out as part of evaluation E on the one hand, and

a system Sys2 as defined by the preceding designations (I), (II) or (III) using the markers of Gset stored in (051); the means (070) initially containing the initial priorities of the markers present in Gset so that the initial priorities reproduce an overall order of the markers of Gset identical to that induced by the chronological order T obtained by Sys1 for the markers of Gset; the means (020) of Sys2 being loaded with a null metric, so that the scheduling inherent in the timeline T is reproduced by Sys2 during the evaluation of said cell culture

(CELL) perturbed by the substance S under conditions of concentration and exposure time chosen in (Ci ₁ Ti), 1 <= i <= N.

The ScompCT benchmarking system implements the Sys1 system once and then as many times as necessary.

Sys2 to measure the impact of concentration variations and exposure time (Ci ₁ Ti), 1 <= <i <= N with respect to (Cref.Tref) on the cell culture induced perturbation (CELL) by the substance S by comparison between the reference assessment E and the evaluations obtained by the occurrences of Sys2. The invention also relates to a device for comparative evaluations using a set of Gset markers for quantifying the impact of a set of N concentration and exposure time conditions (Ci ₁ Ti), 1 <= i <= N in the disturbance of a cell culture (CELL) by a substance S, with respect to a concentration and reference exposure time conditon (Cref.Tref) (Cref being possibly equal to 0) for the same substance S, characterized in that it comprises:

at least N systems (Sys1, Sys2, ... SysN) as defined above, each system Sys (i), 1 <= i <= N using the set of markers Gset, to evaluate the cell culture (CELL ) disturbed by S under conditions of concentration Ci and exposure time Ti data set by the user and specific to the system Sys (i), - at least one system SysRef as defined above and using the set of markers Gset to evaluate S-perturbed cell culture (CELL) with concentration conditions (Cref.Tref); knowing that if Cref = 0, then SysRef evaluates undisturbed cell culture (CELL). The device of comparative evaluations makes it possible to obtain by comparison the results obtained for each of the systems an estimate of the disturbance induced by said substance S according to the concentrations C (i) (1 <= i <= N) and Cref thus used. that the exposure times T (i) (K = K = N) and Tref. Alternatively, the device defined in a general way above, constitutes a device of comparative evaluations noted ScompSub based on multiple evaluations and to quantify the impact, for a Cref concentration concentration and a given exposure time Tref, perturbations induced by a set of N substances Sub1 ... SubN with respect to a reference substance Sref, ScompSub comprising: a system Sys1 as defined by the preceding notation (I), (II) or (III) using a set of Gset marker stored in (051), allowing the evaluation of a cell culture (CELL) disturbed by the substance Sref under conditions of concentration and time of exposure (Cref.Tref) so that a reference evaluation E of the perturbation induced by said substance Sref is obtained, as well as a chronology T concerning the sequence of the tests of the markers of Gset carried out as part of the evaluation E on the one hand, and - a system Sys2 as defined by the previous notation (I), (II) or (III) using the markers of Gset stored in (051); the means (070) initially containing the initial priorities of the markers present in Gset so that the initial priorities reproduce an overall order of the markers of Gset identical to that induced by the chronological order T obtained by Sys1 for the markers of Gset; the means (020) of Sys2 being loaded with zero metric, so that the scheduling inherent in the T timeline is reproduced by Sys2 during the evaluation of said cell culture (CELL) perturbed by a substance selected in (Sub (i)), 1 <= i <= N, under the concentration and exposure time conditions (Cref.Tref),

The ScomSub comparative evaluation system uses the Sys1 system only once and then as many times as necessary the Sys2 system to measure the impact of substance variations (Sub (i)), 1 <= <i <= N with respect to Sref, condition of concentration and fixed exposure time (Cref.Tref) on the cell culture (CELL) by comparison between the reference evaluation E and the evaluations obtained by the occurrences of Sys2.

Thus, the invention also relates to a device for comparative evaluations using a set of Gset markers making it possible to quantify the impact for a concentration condition Cref and a time of exposure given Tref, perturbations induced by a set of N substance Sub (i), 1 <= i <= N, with respect to a reference substance Sref possibly indefinite, characterized in that it comprises:

at least N systems (Sys1 ... SysN) as defined above, each system Sys (i), 1 <= i <= N using the set of markers

Gset and assessing cell culture (CELL) disturbed by Sub substance (i) under Cref concentration conditions and Tref exposure time,

at least one SysRef system as defined above using the set of Gset markers and evaluating the cell culture

(CELL) perturbed by Sref with concentration conditions (Cref.Tref); knowing that if Sref is undefined, then SysRef evaluates the undisturbed C-cell culture.

The device for comparative evaluations makes it possible to obtain, by comparison, the results obtained for each of the systems an estimate of the disturbance induced by said substances Sub (i),

1 <= i <= N and Sref according to the Cref concentration and the exposure time Tref.

The invention also relates to a device for comparative evaluations of the above type using a set of markers Gset, a reference evaluation system SysRef and N evaluation systems Sys (i), 1 <= i <= N, characterized in that:

- the SysRef reference evaluation system is executed first, so that a reference evaluation E and a chronology T concerning the test sequence of the Gset markers carried out as part of the evaluation E are obtained. on the one hand, and

for each evaluation system Sys (i) the means (070) is initially configured with initial priorities for the markers present in Gset so that the initial priorities reproduce an overall order of the markers of Gset identical to that induced by the order chronological T obtained by SysRef for markers of Gset; the means (020) of Sys (i) being loaded with a null metric, so that the scheduling inherent in the timeline T is reproduced by Sys (i) during its execution. In certain particular embodiments, a system or device (plurality of systems) according to the invention is characterized in that it comprises a set of markers M, the device comprising means allowing the user to specify a value of ACCEPT ACCEPT real positive or null may or may not be adjusted in time, so that said system or said device can separate at any time from the evaluation, the set of markers not yet tested in two subsets:

the subset of the SIGNIFICANT markers, defined as the set of markers G of M for which the priority at this instant, established in the means (070), is numerically greater than the value ACCEPT, and

the subset of the NON-SIGNIFICANT markers, defined as the set of markers G of M for which the priority at this instant established in the means (070) is numerically smaller than the value ACCEPT.

Most preferably, a system noted (I), (II) or (III) above takes into account the results of a set of N evaluations {EL..EN}, each evaluation i (1 <i ≤N) being obtained by means of an Si system; the Si system comprising: - a cell culture (CELLi) disturbed by a substance SUBi,

a set of markers Gi, producing the evaluation Ei comprising all the data contained in the means (050) of Si, said system making it possible to define, for a subset M of UNION markers (Gi), (1 < i≤N), UNION representing the set union, a weighting POND_M of the markers of M, the weight of each marker G of M in POND_M taking into account the values RELEVANCE (G), Result (G) and Iter (G) obtained in the means (051) and (052) evaluations Ei (1 <i≤N) in which G participated, the weight of each marker G of M in POND_M accounting for the global relevance of the marker G in the N evaluations {E1 ... EN}. Preferably, the system defined immediately above comprises a set of markers M containing markers Gi which have or have not taken part in one or more previous evaluations, so that the weighting POND_M of all or some of the markers of M can be established by the according to the description given immediately above, the weighting information obtained making it possible to establish the initial priority data of the markers of M in the means (070) of said system, said initial priority of each marker Gi of M being proportional to the weight of the marker Gi in the POND M weighting. Alternatively, the system defined above comprises a set of markers M containing Gi markers that have or have not taken part in one or more previous evaluations, so that the weighting POND_M of all or part of markers of M can be established, the weighting information obtained making it possible to establish the Initial metric data of the relationships between markers of M in the means (020) of said system, the metric value between any two markers Gi and Gj of M being obtained by comparing the weights of the markers Gi and Gj obtained in POND_M.

The invention thus also relates to a self-learning system, determining, by successive evaluations, the priority markers as well as the marker metric data for an arbitrary set M of Gi markers according to the methods presented immediately above.

The system defined generally above may include means for the user to specify a positive or zero scalable real ACCEPT acceptance value, whether or not be adjusted in time, so that said system can separate at any time from the evaluation, the set of markers M not yet tested in two subsets, respectively:

the subset of the SIGNIFICANT markers, defined as the set of markers G of M for which the priority at this instant, established in the means (070), is numerically greater than the value ACCEPT, and

the subset of the NON-SIGNIFICANT markers, defined as the set of markers G of M for which the priority at this instant established in the means (070) is numerically smaller than the value ACCEPT.

Another object of the invention is a Cluster Monitor (1000) method for dynamically assigning resource unit between multiple evaluation systems, characterized in that said Cluster Monitor controls the dynamic sharing of a set R of a number RU (t) of resource units (061) similar, the number RU (t) may or may not vary in time by addition and withdrawal of resource units, between a number N (t) of systems P (i) (1 i i N N (t)) as defined immediately above (N (t) may or may not vary in time), the resource units (061) each carrying out an evaluation of independent or not, assessments are conducted in parallel and competitively on the R-set, the dynamic assignment system overseeing dynamic sharing to ensure that at each moment each of the N (t) assessment processes has, in relative terms, a sufficient number of resource units in order to meet its immediate needs, the dynamic assignment system using a real FRACTION parameter such as O≤FRACTION≤I, the value of FRACTION being arbitrarily set by the user and may or may not vary over time; so that at each instant T each evaluation process P (i) (1≤i≤N (T)) is assigned by the system a minimum number of resource units MIN (i) (T) = FRACTION * RU (T) / N (T); added with a resource unit variable number DYN (i) (T) which directly depends on the number SG (i) (T) of markers present in the subset of the SIGNIFYING markers present in the evaluation process P ( i) at time T, calculated according to the following formula:

DYN (I) (T) = (1-FRACTION) * RU (T) * SG (i) (T) / (ΣSGG) (T), 1≤j≤N (T)) with the following rule:

if the number of markers of the process PQ), 1 <j≤N (T) is zero at time T, then SGQ) (T) = 1, - Σ representing the addition operator,

then, the dynamic assignment system assigns at each instant T a number MIN (i) (T) + DYN (i) (T) to the evaluation process P (i) (1 <i≤N (T)) .

Alternatively, the Cluster Monitor (1000) constituting a dynamic resource unit assignment system oversees the dynamic sharing of a set R of a number RU (t) of resource units (061) similar, the number RU (t) may or may not vary in time by addition and withdrawal of resource units, between a number N (t), N (t) may or may not vary over time, P (i) systems (1 ≤ i≤N (t)) being as defined immediately above (N (t) may or may not vary over time), each independently evaluating whether or not the evaluations are carried out in parallel and concurrently on the set R, each process P (i) (1 <i≤N (t)) using a set of a number C (i) of arbitrary markers, the dynamic assignment system supervising the dynamic sharing so as to guarantee that at each moment each of the N (t) evaluation processes has, in a relative manner, a sufficient number of Resource Units in order to meet its immediate needs, the dynamic assignment system using a real FRACTION parameter such as O≤FRACTION≤I, the value of FRACTION being arbitrarily set by the user and may or may not vary over time; so that at each moment T each evaluation process P (i) (1≤i≤N (T)) is assigned by the system a minimum number of resource units MIN (i) (T) = FRACTION ^* RU (T) ^* C (i) / (ΣCG), 1 <j N N (T)), Σ representing the addition operator; added a variable number DYN (i) (T) of Resource Units which depends directly on the number SG (i) (T) of markers present in the subset of the SIGNIFYING markers present in the evaluation process Pi to instant T, calculated according to the following formula:

DYN (i) (T) = (1-FRACTION) * RU (T) * SG (i) (T) * C (i) / (ΣCG) * SGG) (T), 1 <j≤N (T) )), with the following rule:

if the number of significant markers of the process Pj (1 <j≤N (T)) is zero at time T, then SGQ) (T) = 1,

- Σ representing the addition operator, - then, the dynamic assignment system assigns at each moment T MIN (i) (T) + DYN (i) (T) to the evaluation process P (i) (1) <i≤n (T)).

The present invention is further illustrated, but not limited to, the following examples.

EXAMPLES

Example 1: Description of an embodiment of a system according to the invention.

It is desired to carry out the evaluation of the toxicity of a collection of pesticides (15) by toxicogenomic analysis of the impact of these pesticides on neuronal cells, according to 4 modes of exposure of the cells to the substances:

Expo11 = product concentration C1 = IC50, Exposure time T1 =

24. Expo12 = product concentration C1 = IC50, exposure time T2 =

48h. Expo21 = product concentration C2 = IC50 / 10, exposure time T1

= 24h.

Expo22 = product concentration C2 = IC50 / 10, exposure time T2

= 48h. For this purpose, 51 gene-type biological markers are used in a system according to the present invention. The pesticides tested are: Abamectin, Aldicarb, Aldrin, Carbaryl, Chlorpyriphos, Dicofol,

Fenazaquin, Fipronil, Heptachlor, Lindan, Methoxychlor, Paraquat,

Permethrin, Phosmet, Rotenone. The 51 genes used are also known to induce various pathological responses, classified in our example in 6 distinct families:

Stress, DNA damage, Cell cycle, Neurotoxicity,

Hormonal Response and Conformational Impairment (Proteins). We are therefore interested in the impact of pesticides on these 6 gene families. The genes used, 51 in number, are classified in these 6 families described below.

The system according to the invention consists of a computer of the type

PC executing the means described in the invention, the PC being connected by a serial link to a single resource unit RU 1. RU 1 contains:

DNA chips made specifically to test the level of expression of the 51 genes at the level of the cells under study, each chip being configured for only one gene in our case, each chip making it possible to perform for each gene a number redundant measure (16) to stabilize expression levels by averaging the results. The spots on the chips are numbered sp1 to sp 16.

A device D1 making it possible to select one of the precharacterized DNA chips for a given gene and to put it in the presence of 2 biological samples E1 and E2, so that E1 is assigned to the spots sp1 to sp8, E2 is assigned to sp9 spots sp16.

A device D2 making it possible to introduce a cell culture C into the resource unit. - A device D3 for introducing a substance S into the resource unit.

A communication means C1 with the PC allowing the PC to specify a gene G, a concentration Co and an exposure time T, and a configuration signal of the resource unit with G ₁ C and T,

A means of communication C2 with the PC enabling the PC to request the execution of a test after a configuration,

A communication means C3 enabling the resource unit to transmit to the PC the result RES of a test; a communication means C4 with the PC enabling the PC to request the resetting of the resource unit;

An automated device D4 making it possible, on a C1 configuration signal from the PC, to take a sample of the cell culture C, to put it in the presence of the substance S under the conditions of concentration Co and exposure T specified in the configuration .

An automated device D5 making it possible, on the execution signal of the test C2, to take a sample E1 of the cell culture C (unexposed) and a sample E2 of the cell culture C exposed to the substance by the device previously described in the conditions specified in the configuration, then using the device D1 to select a DNA chip corresponding to the gene specified during the configuration, and to put the samples E1 and E2 thus obtained in the presence of said DNA chip according to the modalities described in the device D1, A device D6 allowing a reading of the DNA chip being tested by the device D5, making it possible to calculate an expression value of the gene for the cell culture C impacted by the substance S under the configuration conditions, the calculation of the value being done by dividing the average of the values obtained for the spots sp9 to sp16 by the average of the values obtained for the spots sp1 to spδ, the device D6 using C3 to transmit this result value to the PC,

A device D7 making it possible to clean the internal components of the resource unit on reception of the signal C4. The resource unit therefore offers testing possibilities which are a priori independent of the markers, or even the cell culture and the substance to be tested.

The PC may, within the scope of the invention, request the configuration of the resource unit for a given gene, under conditions of concentration and precise exposure time of an arbitrary cell culture to an arbitrary substance.

The result of a test, RES, transmitted by the resource unit to the PC, is a raw numeric value which indicates the level of expression of the gene designated in the configuration, for the cell exposed to the substance under the conditions of concentration. and exposure times designated at the configuration versus the level of expression of the same gene in a cell of the same nature not exposed to the substance. Thus, a result with the value 2 indicates that the gene is 2 times more expressed for the exposed cell than for the unexposed cell, a result of 0.5 indicates that the gene is 2 times less expressed for the exposed cell than for the non-exposed cell. exposed etc ..

The descriptions of the 51 genes are initially placed in the medium (010). Table 1:

IDENTITY AND CLASSIFICATION OF THE 51 GENES PRESENT IN (010)

Table 1 (continued):

IDENTITY AND CLASSIFICATION OF THE 51 GENES PRESENT IN (010)

Example 2 Description of a Mode of Implementation of the Method According to the Invention

Having defined in Example 1 the evaluation environment, as well as its objectives, different modes are now presented. method of use according to the invention, in which the behavior of the system is influenced at the initialization of each step (evaluation of each of the pesticides) by the configuration of the means (020) and (070).

Each pesticide is evaluated by an instance of the process. Before each evaluation, the means (010) contains the description of the markers. Each evaluation concerns one of 15 substances under specific concentration and exposure time conditions.

The order of evaluation of the substances is as follows: Abamectin, Aldicarb, Aldrin, Carbaryl, Chlorpyrifos, Dicofol, Fenazaquin, Fipronil, Heptachlor, Lindan, Methoxychlor, Permethrin, Phosmet, Rotenone, Paraquat.

For each substance, the conditions Expo11, Expo12, Expo21, Expo22 are tested, which generally requires 15 * 4 = 60 full evaluations. The 3 strategies presented below are purely illustrative and in no way limit the invention to their sole use.

1 / Random marker selection strategy:

To implement this strategy, we load in the PC the average

(030) with a PNUL relevance model, defined by: regardless of the result of a test from RU 1 for a G gene under specific exposure conditions, PNUL (G) = 0.

Whatever the metric used in the means (020), whatever the seed counters initially specified in the means (070), PNUL makes it possible to test the seed markers at the beginning of the evaluation, then adopts a selection mode. random for other markers.

2 / Marker selection strategy by class: This strategy consists in trying to test, as a priority, the markers of one of the 6 classes with a level of expression relevant to the evaluation. The relevant level of expression is such that the substance triggers, for specific exposure conditions, at least a factor 2 gene expression in more or less in the exposed cell compared to the unexposed cell. We also try to impose on the system a random start, so that it randomly tests markers until it chooses one of a certain class that provides relevant results: in this case, it is desired that the system preferentially study the other markers of the class before continuing its random exploration to a second relevant class, and so on until the markers are exhausted.

To implement this strategy, we load in the PC a means (070) initialized with zero priority values for all the markers (no seed markers), a metric model in the model (020) defined by a numeric function MET_CLASS :

Whatever (Gi, Gj) in all 51 markers, if Gi and Gj belong to the same class, MET-CLASS (Gi, Gj) = 1;

MET_CLASS (Gi, Gj) = 0 otherwise.

MET_CLASS defines the values of the 51 * 50/2 relations between pairs of markers.

Finally, we initialize the means (030) with a relevance model PERT_CLASS:

Regardless of the RES result of a test from RU1 for a G gene under specific exposure conditions, PERT_CLASS (G) = 0 if 0.5 <RES <2; PERT_CLASS (G) = RES if 2 <= RES; PERT_CLASS (G) = 1 / RES otherwise. 3 / Self learning strategy:

The purpose of this strategy is to allow the system to automatically use a number of tests performed in the past to conduct an assessment probabilistically leading to test the markers presenting the most relevant results for the evaluation. The relevant level of expression is such that the substance triggers, for specific exposure conditions, at least a factor 2 gene expression in more or less in the exposed cell compared to the unexposed cell. To do this, a collection of results already obtained for a set of substances is used, and a statistical analysis of these results is carried out. For each result, we count the genes that presented relevant results, and each time these genes presented a relevant result, counted the other genes that had relevant results. This statistical accounting is performed for the collection of previous results obtained for various substances and exposure conditions. Statistical analysis leads in this case to a symmetric matrix 51 * 51 MATSTAT, which can be formed by the system without intervention of the user.

We impose on the system a number Ns of seed markers. The system then chooses the markers G1 ... GNs such that the values on the diagonal of MATSTAT are the Ns highest values (so that MATSTAT (G 1, G1)> = MATSTAT (G2, G2)> =

...> = MATSTAT (GNs, GNs)), and assigns priority values to G1 ... GNs in (070) large enough not to be competing with the first evaluations. Thus, in our case, the system assigns in (070) the priority value 1000 * MATSTAT (Gi ₁ Gi) to the markers Gi (1 <= i <= Ns), and the priority velocity 0 to the other markers. In addition, the system uses the metric values present in the MATSTAT matrix by applying a metric model MET_STAT configured in (020): Whatever (Gi, Gj) in all 51 markers, MET_STAT (Gi, Gj ) = MATSTAT (Gi ₁ Gj)

Finally, the relevance model loaded in (030) is the PERT_STAT model:

Regardless of the RES result of a test from RU1 for a G gene under specific exposure conditions, PERT_STAT (G) = 0 if 0.5 <RES <2; PERT_STAT (G) = 1 otherwise.

The results of the three types of strategies conducted by the process according to the invention are presented below. However, in order not to overload the presentation, the results for a single substance are presented: Paraquat.

The following results are derived from 3 evaluations each using a different strategy, the target cells being neuronal cells, the mode of exposure being Expol 1.

1 / Results of the random strategy The results are presented in Figure 8.

Whenever a test result returned a RES value less than or equal to 0.5, or greater than or equal to 2 for a given marker, this marker is counted in a counter ("nb.of Expressed Markers" in Figure 8). ). We trace the evolution of this counter over time, represented by the number of tests performed in sequence by RU 1.

In addition, we retrace the chronological sequence of the markers tested, from the data present in (052) at the end of the evaluation. This sequence should be read as proceeding from left to right. For each marker tested, if the test returned a RES value less than or equal to 0.5, or greater than or equal to 2, it is indicated by a cross. The results are shown in FIG. 8. As a consequence of the random strategy introduced into the system according to the modalities presented above, the chronological order presented in FIG. 8 is random.

2 / Results of the Class Mark Selection Strategy The results are shown in Figure 9.

Whenever a test result returned a RES value less than or equal to 0.5, or greater than or equal to 2 for a given marker, the markers are counted in a counter ("nb.of Expressed Markers" in the graph figure 9 ). We trace the evolution of this counter over time, represented by the number of tests performed in sequence by RU 1.

In addition, we retrace the chronological sequence of the markers tested, from the data present in (052) at the end of the evaluation. This sequence should be read from left to right. For each marker tested, if the test returned a RES value less than or equal to 0.5, or greater than or equal to 2, it is indicated by a cross. The results are shown in Figure 9.

Under the influence of the class marker selection strategy introduced into the system according to the modalities presented above, the system first randomly tested a HORMONE RESPONSE class marker (CYP19A1), which did not provide any results. relevant. Still randomly, the system selected a marker of the STRESS (SOD1) class with no more success, then a marker of the DNA DAMAGE class (CDKN 1A) for which a relevant result was found. Because of the strategy implemented, the system has therefore explored all of the DNA DAMAGE genes, and then spread over a random selection of the A2M marker (MISCONFORMATION). The relevant result of A2M led the system to explore all the genes of MISCONFORMATION, etc ...

This mode can be easily supplemented by the use of seed markers from each of the gene classes so that the evaluation can be statistically oriented towards the most relevant classes in priority, without the need for an analysis of previous results.

3 / Results of the self-learning strategy

The self-learning strategy was configured according to the modalities described above based on the results obtained for the 14 substances Abamectin, Aldicarb, Aldrin, Carbaryl,

Chlorpyriphos, Dicofol, Fenazaquin, Fipronil, Heptachlor, Lindan,

Methoxychlor, Permethrin, Phosmet, Rotenone, each tested according to the 4 exposure modes Expo11, Expo12, Expo21, Expo22. The matrix

MATSTAT 51 by 51 obtained is not presented for reasons of readability. In the Paraquat evaluation presented here, the number of Ns seed marker deduced by the system was set at 5. *

The results are shown in Figure 10.

Whenever a test result returned a RES value less than or equal to 0.5, or greater than or equal to 2 for a given marker, this marker is counted in a counter ("nb.of

Expressed Markers "in the graph figure 10). We trace the evolution of this counter over time, represented by the number of tests performed in sequence by RU 1.

In addition, we retrace the chronological sequence of the markers tested, from the data present in (052) at the end of the evaluation.

This sequence should be read as proceeding from left to right right. For each marker tested, if the test returned a RES value less than or equal to 0.5, or greater than or equal to 2, it is indicated by a cross. The results are shown in Figure 10.

As can be seen from the results presented in Figure 10, the system has benefited from statistics on previous assessments of the other 14 substances (pesticides) to optimize the likelihood of selecting relevant markers in priority. The seed markers enabled the initiation of the process, then the statistical metrics and relevance models took over to enable exploration of the relevant markers in an advantageous manner. This mode, although statistical, can therefore allow a premature interruption of the test sequence by the user, thus saving time and substantial means. By way of comparison, for the evaluation of Paraquat on neuronal cells in the Expo11 exposure mode, the self-learning strategy presented here as an example provides 15 relevant markers in 22 RU1 executions. , while in the case of the random strategy example, 35 executions of RU 1 are required to obtain the same result. 4 / Raw results of the Paraquat evaluation

The results presented in Table 2 below indicate the values obtained in (052) for the evaluation of Paraquat according to the 4 modes Expo11, Expo12, Expo21, Expo22 made elsewhere. The missing data are irrelevant for the evaluation (between 0.5 and 2 strictly).

EXAMPLE 3 Implementation of the Method of the Invention with a Structure-Activity Relationship Analysis Step (QSAR) Prior to the Selection of Gi Markers in Process Step a) The cytotoxicity properties of the method were tested. candidate compound

Rotenone, with the process of the invention. The method was carried out by performing a prior step of QSAR (Quantitative Structure Activity Relationship) analysis, comparing Rotenone to each of the 14 pesticide compounds already tested in Example 2 above. . By QSAR analysis, three pesticide compounds were selected as compounds closest to Rotenone, respectively Abamectin, Carbaryl and Fenzaquin. In particular, these last three compounds have structural characteristics in common with Rotenone, such as the absence of chlorine atom, phosphate and sulfur. These three pesticidal compounds were therefore selected as reference compounds, for the selection of the identity and order of Gi markers to be tested for Rotenone, on the basis of the 51 Gi markers described in Example 1. therefore the results obtained previously for the 51 markers during independent evaluations of the impact of the 3 substances Abamectin, Carbaryl and Fenazaquin on the neuronal cells for the Expo11, Expo12, Expo21 and Expo22 exposures to form a self-learning MATSTAT matrix. previously described. Assays were performed by exposure of a SH-SY5Y neuronal cell line with an IC50 / 10 concentration of Rotenone and a 24 hour rotenone cell exposure time.

For all the other conditions, the process is carried out as described in Example 2. In step a), the system is imposed with a number Ns = 5 of seed markers. The system then chooses the markers G1 ... GNs such that the values on the diagonal of MATSTAT are the Ns highest values (so that MATSTAT (G 1, G1)> = MATSTAT (G2, G2)> = .. .> = MATSTAT (GNs, GNs)), and assigns priority values to G1 ... GNs in (070) large enough not to be competing with the first evaluations. So, in In our case, the system assigns in (070) the priority value 1000 *

MATSTAT (Gi ₁ Gi) to the markers Gi (1 <= i <= Ns), and the priority value 0 to the other markers.

In addition, the system uses the metric values present in the MATSTAT matrix by applying a metric model

MET_QSAR configured in (020):

Whatever (Gi, Gj) in all 51 markers,

MET_QSAR (Gi ₁ Gj) = MATSTAT (Gi ₁ Gj)

Finally, the relevance model loaded in (030) is the PERT_QSAR model:

Whatever the RES result of a test from RU1 for a G gene under specific exposure conditions,

PERT_ QSAR (G) = 0 if 0.5 <RES <2;

PERT_ QSAR (G) = 1 otherwise. The formulas and structures of the compounds that were compared, respectively Rotenone (Formula (I)), Abamectin (Formula (M)),

Carbaryl (Formula (IM)) and Fenzaquin (Formula (IV)). Formulas (I) to

(IV) are described below.

Each of the execution instances of the method corresponds to the exposure of the cells with a determined concentration of Rotenone. Each run cycle (unit test) of an instance The data of the method corresponds to the test of a marker Gi, and more specifically, to the expression test of a given gene (Gi marker).

At the end of the set of execution instances of the various cycles of the process, the results generated by the different tests were analyzed according to: (i) the number of informative marker genes Gi, that is to say which are under-expressed or overexpressed, relative to cells cultured in the absence of the candidate compound, as a function of (ii) the number of successive cycles of execution of the method.

The results are shown in Figure 11. Each time a test result has returned a value RES less than or equal to 0.5, or greater than or equal to 2 for a given marker, this marker is counted in a counter (on the ordinate in the graph of Figure 11). We trace the evolution of this counter over time, represented by the number of tests performed in sequence by RU 1.

In addition, we retrace the chronological sequence of the markers tested, from the data present in (052) at the end of the evaluation. This sequence should be read from left to right. For each marker tested, if the test returned a RES value less than or equal to 0.5, or greater than or equal to 2, it is indicated by a cross. The results are shown in Figure 11.

The results show that the number of informative markers Gi reaches a plateau after only 40 cycles of execution of the method, that is to say after only 40 markers Gi (out of 51) tested.

The results of Figure 11 also show that 80% of informative Gi markers were tested after only 23 run cycles of the method, i.e. after only 23 Gi markers (out of 51) tested, thus allowing a substance classification process to characterize Rotenone before all 51 markers are tested (which may result in an interruption if premature evaluation by the user if the results are considered sufficient).

Table 2

Table 2 (continued)

Claims

A method for determining the state of at least one set of prokaryotic or eukaryotic cells by determining the state of a set of biological markers contained or expressed by said cells, said method being implemented with a system for determining the state of at least one set of prokaryotic or eukaryotic cells, said system comprising:

1) data storage means (010) comprising a data set characterizing an N _M number of biological markers

Gi;

2) means (020) for storing data characterizing a metric relationship R _M between two biological markers Gi among the N _M biological markers listed in the means (010), said means (020) comprising, for each data item of relation between two biological markers:

an identification reference of a first biological marker G1 included in the means (010);

an identification reference of a second biological marker G2 included in the means (010);

a METRIC value (R _M ) defining the metric relation R _M between the first and the second marker;

3) means (060-G) consisting of a set of Resource Units, comprising a number NU _R of Resource Units (061), each Resource Unit (061) having the function of transmitting at least one parameter of state of a biological marker Gi, contained or expressed by a culture of C cells, to a state parameter evaluation means (300), each Resource Unit (061) comprising: - a means (0611) of identification of said Resource Unit

(061); means (0612) for indicating the operating state of said Resource Unit (061) at a given instant;

means (0613) for determining at least one state parameter of a biological marker Gi, contained or expressed by a C cell culture;

means (0614) for transmitting a signal between said Resource Unit (061) and the state parameter evaluation means (300);

4) means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a culture of C cells, said means (050) comprising:

means (051) for storing data relating to at least one or more biological markers selected from the group of N _M biological markers listed in the means (010), and to storage of relevance data, said means (051) comprising, for each of the biological markers listed in this one:

an identification reference of a first biological marker included in the means (010);

an identification reference of a second biological marker included in the means (010);

a METRIC value (R _M ) defining the metric relation R _M between the first and the second marker; and

a value P (Gi) defining a relevance of said first marker in a test carried out for a determined marker Gi and for a determined set of cells, said value P (Gi) being calculated by means (400) of analysis;

means (052) for storing test results produced by one or more Resource Units (061) included in a means (060) consisting of a subset of the means (060-G), said means (052) of storage comprising a set of test result data, each test result data comprising: an identification reference of a biological marker included in the means (010) and a state parameter of which is determined by means of a Resource Unit (061) included in the means (060); an order value specifying the test rank of said biological marker;

at least one state parameter value defining the result of the test carried out with said biological marker by said Resource Unit (061). 5) evaluation means (300) for performing tests and storing test results performed by one or more Resource Units (061) included in the means (060), said means (300) comprising:

means for storing at least one state parameter of a biological marker Gi, said state parameter being generated by a

Resource Unit (061);

means for transmitting and receiving a signal between said means (300) and the Resource Units (061) included in the means (060); means for transmitting a signal between said means (300) and the control means (100);

means for transmitting a signal from said means (300) to means (400) for analyzing the test results.

6) means (030) for storing a calculation function of a value P (Gi) defining the relevance of a biological marker Gi listed in the means (010);

7) an analysis means (400) for calculating the P (Gi) value defining the relevance of a biological marker Gi listed in the means (010), for a given cell culture C, using the function stored in means (030) with at least one state parameter defining the result of the test performed with said marker a resource unit (061), said state parameter being supplied to the means (400) by the means (300), said means (400) comprising means for receiving a signal transmitted by the means (300). ); 8) Operational Planning means (070) including:

a set of test execution priority data for the biological markers Gi, said means (070) comprising, for each biological marker Gi:

an identification reference of said biological marker Gi; and a PRIORITY value defining the priority rank of said biological marker Gi;

signal transmission means between said means (070) and the control means (100);

means for initial configuration of the priority data for each marker; the priority data being positive or zero values; 9) System initialization means (200), comprising:

means for transmitting a signal between said means (200) and the control means (100); means for transmitting a signal between said means (200) and the means (010) comprising a set of data characterizing a number N _M of biological markers Gi;

- means for transmitting a signal between said means (200) and the means (020) for storing data characterizing a metric relation R _M between two biological markers Gi.

means for transmitting a signal between said means (200) and means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a C cell culture. means for transmitting a signal between said means (200) and the means (070) comprising a set of data characterizing the initial priorities of the Nm biological markers Gi.

10) control means (100) comprising: means for transmitting a signal between said means (100) and each Resource Unit (061);

means for transmitting a signal between said means (100) and the operational scheduling means (070);

means for transmitting a signal between said means (100) and the means (300) for analyzing the test results;

means for transmitting a signal between said means (100) and the data storage means (050);

means for controlling the operation of the Resource Units (061), said method comprising the following steps: a) initializing the system in a step during which the control means (100) performs the following commands: a1)

(i) loading in the storage means (051) the data contained in the means (010) and (020);

(ii) loading in the means (030) the information and instructions concerning the function of calculating the values of relevance used for the markers Gi contained in the means (051); (iii) loading in the means (070) the initial priority information for at least a portion of the biological markers Gi selected from the Nm biological markers; and

a2) select from a set (060-G) of units of

Resource (061), a set (060) of Resource Units (061) capable of performing a state test for at least part of the biological markers Gi referenced in step a1) in the means (051) and (070), and then initializing each of the Resource Units (061) of the means (060). ); b) starting the system in a step in which the control means (100) performs the following commands: b1) selecting the marker Gi listed in the means (070) having the highest PRIORITY priority value, and then delete the data of said marker Gi from the content of the means (070); b2) adding, in the storage means (052), data associated with said selected marker Gi, respectively:

the identification reference of said biological marker Gi included in the means (051), and an order value specifying the test rank of said biological marker Gi. b3) selecting a Resource Unit (061) capable of performing a status test of said biological marker Gi and transmitting by means (300) a command to execute a state test of said selected marker Gi, said test being executed by the said Unit

Resource (061) after configuration of it with the marker

Gi, said resource unit being thereby assigned a "Blocked" status value; c) Retrieve the results of the tests performed in step b) starting the system, according to the following steps: d) load the state parameter (s) generated by each selected Resource Unit (061) at the end of the step b) in the storage means included in the evaluation means (300); c2) transmitting the one or more state parameters loaded in step d) to the storage means (052) and to the analysis means (400); d) Analyzing the results of the tests recovered in step c), according to the following steps: d1) calculating, for each biological marker Gi for which at least one state parameter has been transmitted by means of analysis (400), the P (Gi) value defining the relevance of said biological marker Gi, by using the function stored in the means (030) with said state parameter defining the result of the test carried out with said biological marker Gi by a Resource Unit (061) ; d2) propagating the value P (Gi) calculated in step d1) for said biological marker Gi to the storage means (051), the propagation of assigning to each data of relationship between the markers Gj not yet tested and Gi a propagation value: PROPAGATION (Gj ₁ Gi) = P (Gi) in the storage means (051); d3) resetting the Resource Unit (061) used for said biological marker Gi by assigning to said Resource Unit the "Free" status value. e) Update the marker data contained in the system, according to the following steps: e1) Re-sort the order of the Gi markers not yet tested listed in the storage means (051), assigning each marker Gi not yet tested a command value, said command value consisting of a weight value Pi being a function of the value of the result of the following equation (1):

Pi = ΣMETRIC (Gi, Gk) * PROPAGATON (Gi, Gk); 1 <= k = N, in which:

- Σ is the operator "sum"

N is the number of markers present in the means (051); - METRIC (Gi ₁ Gk) is the value of the metric relationship between the marker Gi and the marker Gk contained in the means (051), loaded in step a1) - (i);

- PROPAGATION (Gi ₁ Gk) is the parameter defining the value propagated in step d2) during the test of the marker Gk if it has already been tested; PROPAGATION (Gi ₁ Gk) = O if Gk has not been tested yet; and e2) update the data of the Planning medium (070)

Operational with the new classification induced by the weight values obtained in step e1) for each Gi marker not yet tested. the cycles of steps b) to e) being repeated until the first occurrence of one of the following conditions f): f) termination conditions: (i) interruption of the system by the user;

(ii) the value of a generated state parameter for a marker Gi by a Resource Unit (061) has been predefined as a system shutdown condition;

(iii) the steps a) to e) of the method have been executed for all the markers Gi listed in the means (051) of storage, it being understood that all the state parameters contained in the means (052) of storage at the end of step f) constitutes the state of the prokaryotic or eukaryotic cell culture or cultures which is determined by the method, and it being understood that at the end of step f), the storage means ( 052) contains the information concerning the chronological order in which the markers were tested by the method.

2. Method according to claim 1, characterized in that the biological markers Gi comprise a marker or a combination of markers chosen from the following markers: the presence or absence of a nucleic acid in the genome of the cells tested, including the presence or absence of a polynucleotide encoding a protein, or the presence or absence of a polynucleotide regulating the expression of a gene;

the presence or absence of polymorphic sites in the sequence of a genomic nucleic acid of the tested cells;

the presence or absence of a specific allele in a polymorphic site contained in a genomic nucleic acid of the cells tested;

the presence or absence of a transcription product of a gene contained in the genome of the cells tested, including a messenger RNA (mRNA) or a complementary DNA (cDNA);

the presence or absence of a small RNAi-type interfering RNA, a small RNAsi-like interfering RNA, an RNAmi-type interfering microRNA, a small RNAsno-type nucleolar RNA, and a small RNA nuclear RNA sn;

the level of transcription of a gene contained in the genome of the cells tested; the presence or absence of a protein encoded by the genome of the cells tested, or the presence or absence of a protein encoded by an organism hosted in the cells tested, for example a viral or fungal organism;

the level of translation of a protein encoded by the genome of the cells tested, or the level of translation of a protein encoded by an organism hosted in the cells tested;

the intracellular or extracellular quantity of a protein encoded by the genome of the cells tested, or the intracellular or extracellular quantity of a protein encoded by an organism hosted in the cells tested; - the presence or absence or the quantity of any other detectable cellular metabolite, including transcription factors, epigenetic control factors, hormones, enzyme cofactors, intracellular receptor cofactors or extra-cellular, lipids, fatty acids, polysaccharides, vitamins or trace elements.

3. Method according to one of claims 1 and 2, characterized in that the Resource Units (061) selected in step a2) may comprise microarrays and / or protein chips.

4. Method according to one of claims 1 to 3, characterized in that the set of cells tested consists of a cell culture of a given type CELL incubated for a period T with a final concentration C of a substance S .

5. Method according to one of claims 1 to 4, characterized in that in step ai) is assigned a value PROPAGATION zero (equal to zero) for all the values P (Gi) contained in the means (051) storage.

6. Method according to one of claims 1 to 5, characterized in that, in step b) of the life cycle of the method, a single Resource Unit (061) can be selected a plurality of times, according to its availability and according to its ability to perform the controlled test for a given Gi marker.

7. Method according to one of claims 1 to 6, characterized in that at the end of step c), the means (052) contains at least one state parameter value, for each of the markers Gi listed in said means (052).

8. Method according to one of claims 1 to 7, characterized in that in step d), the relevance value P (Gi) for a marker Gi is calculated according to the following conditions: (i) given a set of C cells; and

(ii) given the execution of a Resource Unit "Ressourceldi" configured with a marker G1 and the sample derived from C; (iii) then: - Relevance (G1) = 0 if the execution of the Resource Unit

"Ressourceldi" does not generate any significant result, in the context of the state test of the set of cells that is the subject of the execution of the process - Otherwise, Relevance (G1)> 0

9. Method according to one of claims 1 to 8, characterized in that it further comprises a step a) (iii-1) consisting of a step of priority ranking for at least a portion of the Nm markers Gi whose data are stored in the means (010) and (020), said step a) (iii-1) being chosen from one of the following steps:

(1) a step of assigning a priority rank to each marker Gi, said priority rank being calculated according to the degree of relevance of said marker Gi with respect to the type of cell perturbation effect sought for the current execution instance of the method;

(2) a step of assigning a priority rank of each marker Gi, said priority rank being calculated according to the degree of relevance of said marker Gi with respect to the chemical structure of the substance S tested in the the current execution instance of the method.

10. Method according to claim 9, characterized in that step a) (iii- 1) consists of a step of assigning a priority rank of each marker Gi, said priority rank being calculated from the results QSAR analysis between the chemical structure of the substance S tested and the chemical structure of compounds tested during previous execution instances of the process.

A method for simultaneously determining the state of a plurality of sets of prokaryotic or eukaryotic cells by means of determining the state of a set of biological markers contained or expressed by the cells of each set of cells, said process comprising the following steps:

1) performing, for each set of cells of the plurality of sets of cells, a method according to one of claims 1 to 10;

2) recover, for each set of cells, all the state parameters contained in the storage means (052) at the end of step f) of the method according to one of claims 1 to 10 executed with said set of cells, the set of recovered data constituting the state of the plurality of set of cells determined by the method.

A method for testing the effect of a substance (S) on a set (CELL) of prokaryotic or eukaryotic cells comprising the steps of: a) determining a number of combinations of (i) concentration of said substance (S) and (ii) the duration of exposure of the set (CELL) of cells to said substance (S), to perform the test; b) perform as many instances of execution of the method according to one of claims 1 to 10 as combinations determined in step a); c) determining the effect of the substance (S) on the whole (CELL) of prokaryotic or eukaryotic cells, said effect being determined from the totality of the state parameters of the markers Gi contained in the storage means (052 ) after completion, in step b), of the last execution of the method according to one of claims 1 to 11.

A method for testing the effect of a substance (S) on a plurality of sets (CELL) of prokaryotic or eukaryotic cells comprising the steps of: a) determining a number of combinations of (i) sets of cells contained in said plurality of sets of cells, (ii) concentration of said substance (S) and (iii) duration of exposure of the cells to said substance (S), to perform the test; b) performing as many instances of execution of the method according to one of claims 1 to 11 as combinations determined in step a); c) determining the effect of the substance (S) on the plurality of sets (CELL1, CELL2, ..., CELLn) of prokaryotic or eukaryotic cells, said effect being determined from all the state parameters of the markers Gi contained in the storage means (052) after completion, in step b), of the last execution instance of the method according to one of claims 1 to 11.

A system for determining the state of at least one set of prokaryotic or eukaryotic cells by determining the state of a set of biological markers contained or expressed by said cells, said system comprising:

1) means (010) data storage comprising a set of data characterizing a number _M of N biomarkers Gi; 2) means (020) for storing data characterizing a metric relationship R _M between two biological markers Gi among the N _M biological markers listed in the means (010), said means (020) comprising, for each data item of relation between two biological markers:

an identification reference of a first biological marker G1 included in the means (010);

an identification reference of a second biological marker G2 included in the means (010); a METRIC value (RM) defining the metric relation RM between the first and the second marker;

3) means (060-G) consisting of a set of Resource Units, including a number N _UR of Resource Units (061), each Resource Unit (061) having the function of transmitting at least one parameter of a state of a biological marker Gi, contained or expressed by a culture of C cells, to a state parameter evaluation means (300), each Resource Unit (061) comprising:

means (0611) for identifying said Resource Unit (061);

means (0612) for indicating the operating state of said Resource Unit (061) at a given instant;

means (0613) for determining at least one state parameter of a biological marker Gi, contained or expressed by a C cell culture;

means (0614) for transmitting a signal between said Resource Unit (061) and the state parameter evaluation means (300);

4) means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a culture of C cells, said means (050) comprising: means (051) for storing data relating to at least one or more biological markers selected from the group of N _M biological markers listed in the means (010), and to storage of relevance data, said means (051) comprising, for each of the biological markers listed in this one:

an identification reference of a first biological marker included in the means (010);

an identification reference of a second biological marker included in the means (010); a METRIC value (RM) defining the metric relation RM between the first and the second marker; and

a value P (Gi) defining a relevance of said first marker in a test carried out for a determined marker Gi and for a determined set of cells, said value P (Gi) being calculated by means (400) of analysis;

means (052) for storing test results produced by one or more Resource Units (061) included in a means (060) consisting of a subset of the means (060-G), said means (052) of storage comprising a set of test result data, each test result data comprising:

an identification reference of a biological marker included in the means (010) and a state parameter of which is determined by means of a Resource Unit (061) included in the means (060); an order value specifying the test rank of said biological marker;

at least one state parameter value defining the result of the test carried out with said biological marker by said Resource Unit (061). 5) evaluation means (300) for performing tests and storing test results performed by one or more units of Resources (061) included in the means (060), said means (300) comprising:

means for storing at least one state parameter of a biological marker Gi, said state parameter being generated by a Resource Unit (061);

means for transmitting and receiving a signal between said means (300) and the Resource Units (061) included in the means (060);

means for transmitting a signal between said means (300) and the control means (100);

means for transmitting a signal from said means (300) to means (400) for analyzing the test results.

6) means (030) for storing a calculation function of a value P (Gi) defining the relevance of a biological marker Gi listed in the means (010);

7) an analysis means (400) for calculating the P (Gi) value defining the relevance of a biological marker Gi listed in the means (010), for a given cell culture C, using the function stored in means (030) with at least one state parameter defining the result of the test performed with said biological marker Gi by a Resource Unit (061), said state parameter being supplied to means (400) by the means (300). ), said means (400) comprising means for receiving a signal transmitted by the means (300); 8) Operational Planning means (070) including:

a set of test execution priority data for the biological markers Gi, said means (070) comprising, for each biological marker Gi:

an identification reference of said biological marker Gi; and a PRIORITY value defining the priority rank of said biological marker Gi; signal transmission means between said means (070) and the control means (100);

means for initial configuration of the priority data for each marker; the priority data being positive or zero values;

9) System initialization means (200), comprising:

means for transmitting a signal between said means (200) and the control means (100);

means for transmitting a signal between said means (200) and the means (010) comprising a set of data characterizing a number N _M of biological markers Gi;

- means for transmitting a signal between said means (200) and the means (020) for storing data characterizing a metric relation R _M between two biological markers Gi. means for transmitting a signal between said means (200) and means (050) for storing data of state parameters of biological markers Gi, contained or expressed by a C cell culture.

means for transmitting a signal between said means (200) and the means (070) comprising a set of data characterizing the initial priorities of the Nm biological markers Gi.

10) control means (100) comprising:

means for transmitting a signal between said means (100) and each Resource Unit (061); means for transmitting a signal between said means (100) and the operational scheduling means (070);

means for transmitting a signal between said means (100) and the means (300) for analyzing the test results;

means for transmitting a signal between said means (100) and the data storage means (050); means for controlling the operation of the Resource Units (061).

A system for determining the state of at least one set of prokaryotic or eukaryotic cells according to claim 14, characterized in that the resource units (061) comprise at least one means for disrupting cell culture (CELL), by placing it in the presence of an arbitrary substance S under given concentration and exposure time conditions set by the user, the system for evaluating the substance-induced disturbance S under said concentration and reaction time conditions. exposure on cell culture.

A device for testing the effect of a substance (S) on a set (CELL) of prokaryotic or eukaryotic cells, said device comprising a plurality of systems according to one of claims 14 and 15, each of said systems according to the invention being adapted to determine the state of a set of prokaryotic or eukaryotic cells for a combination of at least two of the following parameters: (i) a determined set of prokaryotic or eukaryotic cells;

(ii) a determined concentration of a substance (S) to be tested;

(iii) a determined duration of exposure of cells to a substance

(S) to be tested; and

(iv) a substance (S) determined.