A method for defining the tolerances of spectroscopy spectra or spectroscopy intensity spectra for the validation of one or more test batches of a product

Abstract

It provides for the validation of natural matrices for biophysical-based therapeutic use in humans, animals and plants as an alternative to validation via chemically definable substances obtained from said matrices by isolation and / or synthesis methods and as an alternative to products containing natural matrices that have been validated based on traditional uses. The present invention relates to a new method for evaluating the tolerance range or acceptability cut-off for the compliance validation of a batch of a product comprising or consisting of one or more natural matrices, said product having a confirmed therapeutic or beneficial effect. The present invention also relates to a new method for the compliance validation of one or more batches of said product.

Description

[Technical field]

[0001] The present invention relates to a new batch control method for products comprising or consisting of a mixture of natural or vegetable matrices, said products being characterized by the fact that one or more of the matrices themselves exhibit characteristic emerging properties different from those exhibited by the sum of the properties of their individual components. [Background technology]

[0002] The historical concept of patents being granted for the public benefit, particularly in matters of health and safety, has its origins centuries ago. The underlying principle is that while a patent provides an inventor with a temporary monopoly on his invention, the ultimate purpose is to serve the greater good of society.

[0003] In modern times, this historical concept is reflected in the various legal provisions and policies governing patents, which emphasize the understanding that inventors deserve recognition and protection for their contributions, but that society as a whole should ultimately benefit from these technological innovations, especially in areas critical to public health and safety.

[0004] In other words, the humanitarian basis of the patent system lies in its goal of striking a balance between encouraging innovation and ensuring that the benefits of that innovation are shared for the overall betterment of society. In particular, the patent system should ensure the sharing of knowledge and the promotion of progress in the above areas.

[0005] In particular, the patent system can play a key role in addressing humanitarian and global challenges, for example by encouraging the development of sustainable medicines, environmentally sustainable technologies and solutions to pressing problems such as clean energy and water scarcity.

[0006] From the beginning of the 16th century until today, especially in the field of medical and beneficial products, it has been possible to standardize and therefore validate only artificial substances produced by chemically definable chemical methods.

[0007] This pathway, highly reductionist, has proven to be of great value, making it possible to eradicate many diseases over the past five centuries, but is now facing its limitations, which stem from the exogenous nature of chemicals to the ways of life.

[0008] With regard to the development of new sustainable medicines, it is now also recognized that man-made (especially chemically synthesized) therapeutic products have detrimental effects on biodiversity and the innate immune system.

[0009] It is well known that synthetic APIs can enter ecosystems through various pathways, mainly through the discharge of drug waste from manufacturing plants and improper disposal of unused or expired drugs, which can lead to bioaccumulation of artificial and poorly biodegradable substances in aquatic and terrestrial organisms, disrupting the food chain and threatening biodiversity.

[0010] Studies have shown adverse effects on aquatic organisms, such as changes in behavior, reproduction, and even mortality, as a result of exposure to synthetic APIs. (Boxall,ABet al(2012).Pharmaceuticals and personal care products in the environment:what are the big questions?.Environmental health perspectives,120(9),1221-1229;Fick,J.,&Lindberg,RH(2015).Tysklind,M.and Larsson,DGJ(2015).Predicted critical environmental concentrations for 500 pharmaceuticals.Regulatory Toxicology and Pharmacology,73(1),607-616.)

[0011] It is well known that many synthetic APIs are designed to be biologically active and particularly stable, which may hinder their natural degradation processes. As a result, these molecules may persist in the environment for long periods of time and accumulate in soil and water. This reduced biodegradability raises concerns about long-term environmental impacts and the possibility of bioaccumulation in organisms [Kasprzyk-Hordern, B., et al(2008).The removal of pharmaceuticals, personal care products, endocrine disruptors and illicit drugs during wastewater treatment and its impact on the quality of receiving waters.Water research,43(2),363-380;Verlicchi P.,et al(2012).Occurrence of pharmaceutical compounds in urban wastewater:Removal,mass load and environmental risk after a secondary treatment-A review.Science of the total environment,429,123-155].

[0012] Furthermore, there is growing concern about the potential impact of synthetic APIs on the immune system of humans and animals. Some medicines have been found to directly or indirectly interfere with immune function, leading to altered immune responses or increased susceptibility to infection. This can have significant consequences for both individual health and population-level immunity [Vos T.et al(2016).Global,regional,and national incidence,prevalence,and years lived with disability for 310 diseases and injuries,1990-2015:a systematic analysis for the Global Burden of Disease Study 2015.The Lancet,388(10053),1545-1602;Calabrese,EJ,&Baldwin,LA(2003).Toxicology rethinks its central belief.Nature,421(6924),691-692].

[0013] In conclusion, synthetic APIs have undoubtedly contributed to advances in healthcare, but their environmental and health impacts should be carefully considered. Efforts to develop greener pharmaceuticals, improve waste management, and monitor environmental pollution are important steps to mitigate these concerns.

[0014] In addition, it must be noted that natural molecules in natural matrices, although chemically similar to their synthetic counterparts when isolated and obtained, may have different fingerprints with respect to their synthetic analogues due to completely different synthetic routes in terms of primary metabolites, reactants, reaction temperatures, energy sources, catalysts, etc., potentially affecting their physicochemical behavior and reactivity and therefore their biological activity.

[0015] According to the traditional paradigm, in terms of chemical structure, the identity of a molecule is embedded in its atomic composition and its geometric arrangement. As an example, estragole (1-allyl-4-methoxybenzene), prominently identified in essential oils such as those derived essentially from Ocimum basilicum and Artemisia dracunculus, is known in the art for its potential aromatic and medicinal uses. The molecular makeup and associated energy states of estragole, depending on its origin, have been the subject of intense scientific scrutiny. While the traditional perspective assumes uniform molecular attributes, closer scrutiny suggests subtle differences.

[0016] Given this premise, estragole, whether procured from plant sources by distillation or synthesized in the laboratory, should ideally be identical in its inherent physicochemical attributes.

[0017] However, it is of utmost importance to distinguish the production pathways. In the plant matrix, the biosynthesis of estragole is orchestrated by a series of enzymatic reactions that start with a primary metabolite and end with this specific secondary metabolite. It is known in the art that each of these enzymatic transformations operates within a different energy landscape, potentially conferring a unique energy state to the molecule.

[0018] Conversely, laboratory synthesis of estragole would depend on chemical reactions engineered with different precursors and conditions (e.g., temperatures incompatible with plant life). The energy dynamics of such synthetic pathways, governed by the intrinsic thermodynamics and kinetics of the reactions, are likely to deviate from plant-mediated enzymatic pathways.

[0019] Moreover, it is clear that the isotopic abundances resulting from the two different routes (natural and synthetic) are unlikely to be the same either. It is known that the isotopic abundances, even when slightly varied, have a tangible effect on the vibrational frequencies, bond strengths, and consequently the energy state of the molecule itself [Bigeleisen, J. (1996). Nuclear spin conversion in polyatomic molecules. Journal of Chemical Physics, 105 (18), 8121-8129]. Given the possible isotopic differences between plant sources and synthetic reagents, the resulting estragole molecules are likely to have differential energy imprints and biological activities. In light of the above, although chemically similar, it is reasonably possible that molecules from natural and synthetic origins have distinct energy fingerprints that potentially affect their physicochemical properties, reactivity, and therefore their biological activity. Indeed, differences between the activity of synthetic and natural estragole have been reported in the art (Suzanne MF et al. "Basil extract inhibits the sulfotransferase mediated formation of DNA adducts of the procarcinogen 1'-hydroxyestragole by rat and human liver S9 homogenates and in HepG2 human hepatoma cells" Food and Chemical Toxicology, 2008, 46(6)2296-2302, https: / / doi.org / 10.1016 / j.fct.2008.03.010.).

[0020] Moreover, synthetic molecules (intended as molecules obtained by manufacturing carried out by humans through chemical synthesis laboratory / industrial methods) are designed to provide a desired interaction with a particular given target molecule, and the design does not take into account all the interactions that the molecule may and will have in the natural matrix, in the environment, and in the entire receptor network of the organism in which they are used. On the other hand, natural biosynthetic molecules produced in natural, non-artificial environments have essentially all the essential features to exist and exert their function in an epigenetically determined competition whose explanation is inaccessible when traditional deterministic chemical approaches are used. Quantum biology can be applied to provide a possible deciphering of natural matrices and biosynthetic molecules.

[0021] Products obtained from natural sources have been used for thousands of years to prevent and cure human diseases. In this context, numerous studies have been limited to characterizing their chemical composition and single molecule activity at the single molecule level, while the spontaneous assembly, interaction and supramolecular organization of all components in said natural products have not been fully investigated and therefore not understood. From the development of modern chemistry, a reductionist approach focused on the isolation of single molecules from natural products and the subsequent artificial synthesis of molecules of therapeutic interest, the aim has been to develop selected active ingredients that act on a given target according to the key-lock paradigm.

[0022] This has led to the conviction that research in the field of life sciences should be directed towards substances that can be chemically validated using data such as the amounts of individual substances at the molecular level, and that use linear kinetics to generate highly potent and effective artificial products, a direction that is now also proving to have detrimental effects on biodiversity and the innate immune system.

[0023] In particular, the inability to standardize products derived from natural sources, including products prepared by humans but consisting mainly or exclusively of components derived from natural raw (starting) sources, i.e. consisting of 100% non-artificial substances, has been one of the major challenges for the technology, thereby opening the door to the current API-based pharmacological approach to ensure batch-to-batch validation of products derived from natural sources intended for medicinal or beneficial uses.

[0024] Natural matrices, such as plant matrices, for example, are complex systems characterized by a large number of molecular components belonging to different phytochemical classes that already interact with each other in the plant to determine the plant's biology. This interaction continues during the processing stage, with different processing techniques influencing the post-processing interactions of the components. These compounds can interact at functional and structural levels. The supramolecular aggregates resulting in both structural and functional networks, as well as their chemical-physical and structural properties, are dynamic interactions that can be modulated by environmental conditions, and as can be expected, these interactions affect the reactivity of the individual components, resulting in properties typical of the separate entities represented by the matrix, different from the sum of the properties of its single molecular components, by so-called "matrix effects". Such properties are defined as "emerging properties". This phenomenon has been described and attributed in particular to organisms that have the driving force to self-assemble and self-organize to form supramolecular complexes [Jean-Marie Lehn Toward complex matter: Supramolecular chemistry and self-organization.PNAS,2002,99(8)4763-4768 https: / / doi.org / 10.1073 / pnas.072065599]. This inherent complexity leads to the fact that individual molecules in natural matrices cannot be considered as contained in isolated and fixed packages, since mutual non-covalent and dynamic interactions occur continuously between them. Such interactions are intra- and inter-molecular, occurring both between molecules of the same type as well as between molecules belonging to different chemical classes. This introduces the need to consider that the ability of natural matrices to exert therapeutic activity on the human body depends not only on the qualitative-quantitative composition of the matrix, which tends to be variable in itself, but also on the presence of such interactions between the same and different molecules, including small molecules as well as more complex ones such as proteins, polysaccharides, lipids, RNA, etc.

[0025] In this context, it is clear that the classical validation of therapeutic products based on the structure-activity pharmacological relationship (SAR), which is the most relevant relationship in classical pharmacological activity between an active pharmaceutical ingredient (API) and the receptor targeted by said API, considered at the level of a single molecule, is unlikely to be respected across different batches of the same natural matrix.

[0026] These considerations seem to distinguish to a great extent the study of interactions between self-assembled natural matrices endowed with complexity at the molecular and supramolecular level and biological systems from interactions that would be established by APIs and their target receptor cellular structures. In fact, the latter are well defined by the elaborate deterministic criteria of a key-lock mechanism, in particular by fixing the interaction between an API and its specific target also in structural terms defined in both quantitative and qualitative ways. This concept is so widespread from a conceptual point of view that it leads to the possibility of controlling the reproducibility of the biological activity of an API solely by controlling the reproducibility of its molecular structure based on its structure-activity relationship (SAR). This is obviously not applicable to natural matrices or products containing them, due to the above mentioned characteristics.

[0027] It therefore appears necessary to keep in mind the fundamental differences between natural self-assembling matrices and APIs. - The first ones are eubiotic towards humans and the environment, characterized by a physiological interconnection with the recipient's biological systems at the molecular level and, precisely due to their complexity, clearly inadequately described and characterized by the use of deterministic tools such as the key-lock model. -The latter, xenobiotics with respect to humans and the environment, are instead characterized by the clear possibility of describing their interaction with the recipient biological system according to fully deterministic criteria, typically summarized by the “key and lock” model.

[0028] Therefore, knowledge of the identity and amount of each and every molecule in a natural matrix is ​​not sufficient to predict the dynamic and kinetic properties and therapeutic efficacy of the matrix itself. When a selected single molecule such as an API is considered, the opposite occurs: the SAR, pharmacodynamic and pharmacokinetic properties are essentially related to the chemical identity of the active ingredient and the pharmacodynamic inertia of the excipients. For this reason, the standard concepts of pharmacodynamics and pharmacokinetics only make sense when referring to a single molecule (active ingredient) or its representatives (functional markers).

[0029] The network established between all the components of the matrix resulting in a "matrix effect" makes it impossible to identify a single marker representing the network, since no single component can transmit all the properties inherent to the matrix on its own, and therefore no single component reflects the interaction between the matrix and the target organism.

[0030] Matrix effects give rise to new and different matrices, called emerging properties, which confer certain intrinsic properties of the matrix itself or of a mixture of matrices and cannot be replicated to any of the properties of the components taken alone. This perfectly reflects the impossibility of studying such properties precisely by the deterministic chemical methods commonly used in classical pharmacological chemistry, which, as mentioned above, are only adequately suited to single active ingredients and excipients in the pharmaceutical environment.

[0031] Rather, the dynamic and kinetic behavior of the matrix is ​​the result of a dynamic network of interactions taking place within the matrix, as follows: The presence of many components, · The inability to reconvert the properties of the matrix into the sum of the properties of a single material · The impossibility of describing the interaction between the matrix and the receptor organism according to the key-lock paradigm (model) that is the basis of SAR.

[0032] Now, man is realizing that the answer to most of the problems lies in nature itself, and that it is necessary to develop techniques and methods that allow to understand and therefore in some way standardize the natural complex entities that self-organize supramolecular networks such as natural matrices. These entities are the only ones that are physiologically compatible with everything that forms the production. It is therefore necessary to move from environmental reductionist-based validation to a stochastic approach inspired by the latest evolutions of scientific thinking, thus finally opposing linear kinetics to cyclic kinetics. Therefore, deterministic chemical methods are not adequate to investigate and monitor the properties and quality of the matrices. An approach is needed to evaluate the interactions within the complex systems in order to allow the identification of features related to the reproducibility of the therapeutic properties of the matrices, if necessary.

[0033] There is therefore a need to turn to approaches inspired by systems theory.

[0034] The study of such properties has been hitherto unattainable and requires tools such as "omics" sciences, among which transcriptomics and metabolomics can be identified as crucial.

[0035] With regard to products containing or consisting of natural matrices with therapeutic activity, it is hereby recalled that the Medical Devices (MD) EU Regulation 2017 / 745 (Regulation) was officially published in Europe on 5 May 2017 [European Pharmacopoeia and Council Regulation (EU) 2017 / 745 of 5 April 2017 on medical devices, amending Directive 2001 / 83 / EC, Regulation (EC) No 178 / 2002 and Regulation (EC) No 1223 / 2009 and Council Directives 90 / 385 / EEC and 93 / 42 / EEC], introducing a completely new management regime for all aspects of the life cycle of MDs.

[0036] The term medical device according to this regulation includes products that achieve a therapeutic effect but do not have a pharmacological, immunological or metabolic (Ph.IM) mode of action (MOA). Ph.IM MOA is a mode of action characterized by a key-lock model in which the selected API acts on its target receptor according to the SAR regulation. Thus, products that contain or consist of complex systems such as natural matrices may comply with the regulation. Notably, this provision also indicates that products that modify a pathological or physiological condition or process via a non-Ph-IM mechanism of action are MDs.

[0037] The Regulation therefore poses a double problem to be solved: on the one hand, MDs made from materials of natural origin, such as plant matrices, need to undergo quality control validation in order to be usable for treatments, and on the other hand, it needs to be demonstrated that the therapeutic effect of the product is achieved by a non-Ph-IM mechanism of action.

[0038] The current validation of products for therapeutic use is based solely on the reproducibility of their chemical composition and is only applicable to products acting via a Ph-IM mode of action.

[0039] Although taking into account the complexity of natural matrices, the current standard techniques are based on the validation of products that contain or consist of natural matrices for use in treating pathological conditions (i.e. products that fall under the definition of MD according to EU regulations) at the chemical level with respect to the API. This is in stark contrast to the intimate nature of such products for all the reasons mentioned above. Therefore, there is a need in the art to develop validation procedures that are based on the confirmation of said complexity and are not limited to the evaluation of the reproducibility of such products based uniquely on their molecular composition. Moreover, the current standard techniques do not provide a method for the evaluation of the mechanism of action of said products.

[0040] Currently, there is a strong desire to find alternatives to traditional pharmacology, but at the same time there is a need to ensure the validation and standardization of products containing or consisting of one or more natural matrices used for therapeutic purposes.

[0041] Providing a method for validating the quality of a product that contains or consists of a natural matrix that is not based solely on the chemical composition of the natural matrix allows the use of products of natural origin in therapy, having a natural matrix that is cyclically dynamic rather than linearly dynamic, i.e. acting on the entire physiological state altered by the pathological condition rather than on a single change. This opens up a new field of research and provides the possibility of using whole networks (such as natural matrices) in therapy, which operate on the network represented by the receiving treatment subject, i.e. cyclically dynamic rather than on a single compound, and acting on a single point of the receiving network, i.e. linearly dynamic.

[0042] The present invention solves the first problem summarized in the paragraph above. Summary of the Invention

[0043] The present invention provides a new method for defining spectroscopic or spectrophotometric analytical acceptability ranges or cut-offs for the validation of one or more batches of a product comprising or consisting of one or more natural matrices for use in the treatment of a pathological condition, comprising a step in which said acceptance ranges or cut-offs are calculated based on a gold standard of said product having a confirmed therapeutic effect in the treatment of said pathological condition, and on the spectroscopic or spectrophotometric spectra of one or more different batches of said product, said spectra being defined as acceptable or not acceptable for one or more hallmarks of said pathological condition, and based on a selected biological activity exerted in at least one cell-based assay by said gold standard and said one or more different batches, rather than merely on their chemical composition.

[0044] In other words, a tolerance zone or acceptability cutoff is defined based on the deviation of the spectra from the mean spectrum derived therefrom.

[0045] The products that can be validated with the method of the invention, despite the fact that they contain or consist of natural matrices and thus are obtained from natural products, are preferably prepared according to good manufacturing practices and therefore standardized procedures, in order to empirically obtain a high degree of uniformity between batches in advance.

[0046] As disclosed above, due to the complex interactions within natural matrices or matrices and the inability to attribute therapeutic or beneficial (health) effects to specific APIs with therapeutic or beneficial products that contain or consist of said matrices, there is a clear need in the art for best practices and standardization throughout the entire process of preparation of eubiotic products that contain or consist of natural matrices, as well as for batch control models of said products that are not based on the identification, quantification and evaluation of the individual chemical entities contained in said matrices or matrices, since the therapeutic or beneficial emerging properties cannot be attributed to the mere sum of the properties of the individual components of said matrices or matrices. This control model should therefore take into account the entire system and allows batch evaluation within the context of the interactions between all the components. This different evaluation method is necessary because the properties (emerging properties) of products that contain or consist of one or more natural matrices, in particular plant matrices, animal matrices or mixtures thereof, are due to the very interconnections between all the components of the natural matrices present in this type of product. This means that, in contrast to classical pharmaceutical products, whose activity is defined by a specific API, as explained above, it is not possible to attribute the emerging properties typical of natural matrices to the functional interactions of a single or a few components. In fact, the properties of a natural matrix arise not only from each single component therein, but also from the supramolecular interconnections between said components, including the way they self-assemble at the supramolecular level, resulting in a network of interactions between all the components of the matrix. In other words, in products that contain or consist of natural matrices, there is no "active ingredient" responsible for the therapeutic properties of the product, or "excipients" responsible for not interfering with the properties of the active ingredient, as in typical pharmaceutical products, but rather a multiplicity of interconnected and interacting components that are all responsible for the emerging properties of the matrix. "Emergent" is the term most frequently used to describe the observed integrated characteristics of the system.

[0047] Also characteristic is the interaction between the natural matrix and the recipient organism, e.g. the human body, i.e. the interaction between the donor network (matrix or natural material according to the present specification) and the recipient network (the subject's body to which the product is administered, e.g. the human body). Such interactions result in the modification of numerous interconnected biological pathways in a manner specific to each biological matrix. In contrast to a specific API, the effect of a therapeutic product that includes or consists of one or more natural matrices is broad and encompasses many aspects of physiology, so that the product does not modify a single function that contributes to the pathological condition, but rather affects the overall pathological condition. The modification of the overall pathological condition is the result of the numerous biological components that make up the natural material that includes or consists of one or more natural matrices (i.e. the product), acting in concert (i.e. emerging properties or matrix effects) by both functional and structural interactions.

[0048] As mentioned above, it is also envisaged herein that naturally occurring molecules in natural matrices, although chemically similar to their synthetic counterparts when isolated and obtained, may have different fingerprints with respect to their synthetic analogues due to completely different synthetic routes with respect to primary metabolites, reactants, reaction temperatures, energy sources, catalysts etc., potentially affecting their physicochemical behaviour and reactivity and therefore their biological activity.

[0049] For the above reasons, preferred standardized eubiotic protocols are used for the production of natural matrices, especially plant matrices, and the final products validated with the method of the present invention, preferably starting from the agricultural production and up to the final transformation of the raw materials, designed to maintain the basic natural program rules that have allowed the interconnection between all the components of living organisms, organic and inorganic, over millions of years.

[0050] Applicant's work disclosed herein demonstrates that classical approaches used for standard pharmaceutical products (i.e., qualitative-quantitative characterization of the matrix) are not applicable to products providing therapeutic and / or health benefits when the products contain or consist of complex natural systems (i.e., natural matrices). As is known in the art, one of the main problems associated with the validation of therapeutic products that contain or consist of one or more natural matrices is that a natural matrix extracted, for example, from a given plant is never completely identical, in terms of molecular composition, to the "same" natural matrix extracted in the same way from another plant of the same species or even variety.

[0051] Due to the nature of the natural matrices, in contrast to the classical quality control acceptance parameters used for classical pharmaceutical products based on specific API regulations, some degree of variability in the qualitative-quantitative composition of products containing or consisting of natural matrices must be tolerated as a manifestation of the most proximate nature of such entities and their mode of action on the recipient organism, but the question is to identify how to assess said acceptable degree of variability.

[0052] The present application provides a new and reliable method for evaluating the tolerance range or cut-off of a spectroscopic or spectrophotometric method suitable for quality methods of products containing or consisting of complex natural systems, the tolerance range or cut-off having a therapeutic or health effect based on the biological activity of the product type against the hallmarks of a given pathological condition, rather than on the qualitative-quantitative analysis of specific chemicals in the product.

[0053] The inventors have surprisingly found that, despite the qualitative-quantitative differences between natural matrices obtained from different members of the same source (even through the same production procedure), the different molecular entities in said matrices appear to functionally and structurally act redundantly with each other. This redundancy results in a clear maintenance of the biological activity exerted by products that contain or consist of natural matrices, even when the qualitative-quantitative composition of different batches of said products is not considered acceptable currently using classical batch control protocols required by legislation designed to regulate deterministically acting APIs. Without wishing to be bound by theory, the observed maintenance of biological activity is likely due to the fact that the emerging properties of natural matrices, as described above, are due to the matrix network acting as a whole entity with characteristic properties and cannot be attributed to each single molecule as if it were isolated.

[0054] Thus, the inventors have discovered that different batches of products comprising or consisting of complex natural systems, following common standard quality control validation techniques based on their qualitative-quantitative composition, result in poor compliance with the determination of their desired biological activity despite their different composition, surprisingly maintaining comparable biological effects.

[0055] Therefore, for therapeutic products that contain or consist of one or more natural matrices, instead of basing the quality control tolerance zones or acceptability cut-offs on the identification and evaluation of selected individual chemical entities and / or instead of performing statistical pre-clearing of spectroscopic data to discard outliers classically accepted for APIs, the Applicant has developed a new method for validating different batches of said product based on the evaluation of quality control parameters based on the analysis of selected parameters representative of their biological effect, i.e. a crucial feature of medical devices composed of natural matrices. The evaluation of the tolerance zones or acceptability cut-offs and validation method provided herein is sufficient for the quality control of biological materials with therapeutic activity as defined by Regulation 2017 / 745 and reflects the product conformity to GSPR 1 of Annex I of said Regulation, specifically in the first line which lists: "The device must achieve the performance intended by its manufacturer and must be designed and manufactured in such a way that during normal conditions of use the device is suitable for its intended purpose."

[0056] The present invention therefore provides a method for defining a spectroscopic or spectrophotometric analytical acceptance zone or acceptability cut-off for the quality validation of one or more batches of a product for use in the treatment of a pathological condition comprising or consisting of one or more natural matrices, the acceptance zone or acceptability cut-off comprising a step of calculating said acceptance zone or acceptability cut-off based on a gold standard having a confirmed therapeutic effect in the treatment of said pathological condition and a spectroscopic or spectrophotometric spectrum of said one or more batches of said product, said spectrum being defined as acceptable or not acceptable based on the biological activity exerted by said gold standard and said one or more batches of said product for one or more hallmarks of said pathological condition in at least one cell-based assay.

[0057] The invention further provides a method for evaluating, between different batches, a gold standard of a product for use in the treatment of a pathological condition, comprising one or more natural matrices as defined in the claims. The invention also provides a method for the validation (i.e. quality control compliance) of one or more batches of a product for the treatment of a pathological condition, the product comprising one or more natural matrices, a. performing a spectroscopic or spectrophotometric analysis of each batch; b. validating each batch, wherein the parameters obtained are within the ranges or cut-offs specified according to the method of the present invention for that spectroscopic or spectrophotometric analysis.

[0058] term "Natural matrix" in the present application refers to a material consisting of a network represented by a wide number of components / constituents that are obtained (e.g., extracted) directly from a member of the natural world or its naturally occurring parts (i.e., from natural raw materials) without any special processing or synthetic modification, where "without any special processing or synthetic modification" is intended to mean processed only by manual, mechanical or gravitational means, for example by dissolution in water or other naturally occurring solvents such as water, water-alcohol solutions, by flotation, by extraction with water or other naturally occurring solvents, by steam distillation, or by heating only to remove water or any other naturally occurring solvent, or extracted from air by any means, provided that "natural matrix" excludes the member of the natural world or its naturally occurring parts themselves. In other words, a natural matrix or mixture of natural matrices is a material obtained from entities that naturally self-assemble and are processed while maintaining their natural biophysical properties that determine their physiological interactions with other organisms, such as human organisms. Their emerging properties may be expressed by contributing to a rebalancing of the metabolic processes or states of the recipient organism and / or some organs or tissues, with physiological actions activated in each specific situation. According to the invention, the natural matrix may originate from materials obtained from any source of the kingdoms of life, namely Monera, Protist, Fungi, Planta and Animalia. Thus, the term encompasses plant natural matrices, animal natural matrices, fungal natural matrices, protist (archaea or bacteria) natural matrices, Monera natural matrices. The natural matrix may also include natural inorganic materials such as minerals extracted from natural raw materials. A synonym for natural matrix or one or more natural matrices in this specification is "natural material" as defined below.

[0059] Examples of naturally occurring parts of an organism may be represented by, for example, roots, leaves, bark, fruits, flowers, plants or sections thereof, organs, tissues.

[0060] In any part of the description the general term natural matrix can be replaced by the following: Plant natural matrices or natural matrices obtained from plants, Animal natural matrices or natural matrices derived from animals, Fungal natural matrices or natural matrices obtained from fungi, Protist natural matrices or natural matrices obtained from protists, Monera natural matrix or natural matrix obtained from Monera, or plant material and / or extracts, extracts from animal tissues or organs, fungi and / or fungal extracts, or mixtures thereof. Additionally, the natural matrix may contain minerals or components derived from minerals.

[0061] Plant is synonymous with herb.

[0062] For example, in the context of a product that includes or consists of a material of botanical origin (obtained from a plant), such as an herbal supplement, the natural matrix includes some of the original, unintentionally altered, preferably unaltered, components naturally present in the raw material (e.g., an extract of the source material), and thus includes the various organic and inorganic components found in the kingdoms mentioned above.

[0063] The term "native" matrix emphasizes that the integrity and complexity of the network of components / ingredients is preserved as in the original natural source, rather than isolating, purifying or extracting specific molecules or classes of molecules through extensive processing or chemical modification.

[0064] Due to the supramolecular self-assembly of the components / ingredients of the natural matrix, the entire matrix behaves as a complex network that does not interact with a single target molecule, but with a network of recipients (also organized as a network) in the recipient organism. Thus, the interaction of the natural matrix recipient organism is not the result of point-to-point interactions, as with typical pharmaceutical APIs, but rather the result of network-to-network (i.e., the matrix) interactions with the organism (i.e., the organism to which the matrix is ​​administered).

[0065] The term natural matrix may also be replaced with complex natural system in any part of the specification and claims.

[0066] In this specification and claims, the term natural matrix cannot be construed as a "natural product," but rather, a natural matrix is ​​a product obtained from a naturally occurring organism and processed (e.g., extracted) therefrom by techniques that do not substantially alter the biological structure and supramolecular interconnections between components within the matrix.

[0067] Emerging Properties According to the present specification and the art, this term defines properties of a natural matrix or material according to the present specification, i.e. properties that are not merely represented by the sum of the properties of each isolated component / ingredients of said matrix / material, but by the intermolecular interactions between all components / ingredients of said matrix / material that are the result of supramolecular self-assembly of said components / ingredients within the matrix / material itself.

[0068] Thus, "emerging properties" refer to the technical effects, such as therapeutic or homeostatic-adjuvant properties (i.e., beneficial effects), that the interactions and relationships between components / ingredients of a natural matrix have on a recipient biological system. Emerging properties are not immediately evident or predictable based solely on the individual properties of each component / ingredients of the matrix. Instead, they "emerge" when all components / ingredients of the matrix network interact with each other and with the recipient biological system network in a dynamic and complex way. Emerging properties have been widely discussed in the art in various scientific and systems-oriented fields, including physics, chemistry, biology, and complex systems theory.

[0069] Important points regarding emerging properties include: Complexity of the system: Emerging properties are associated with systems that exhibit a certain level of complexity. In simple systems, interactions between components / ingredients are limited and properties are more easily deducible from the properties of the individual components. However, in complex systems, interactions between components and their supramolecular organization can give rise to novel and unexpected features.

[0070] Nonlinearity: Emerging properties often result from nonlinear interactions, where the relationship between cause and effect is not proportional.

[0071] Holism: The concept of emerging properties emphasizes a holistic perspective, recognizing that the whole system is greater than the sum of its parts.

[0072] A product comprising or consisting of one or more natural matrices according to the present invention (also known as a "product comprising or consisting of complex natural system(s)") is a product comprising or consisting of one or more natural matrices, also defined herein as "natural materials", i.e. "materials obtained / manufactured / processed from natural raw materials or members of the natural world" (see below).

[0073] In any part of the description and claims, the term "product comprising or consisting of one or more natural matrices" may be substituted with "product comprising or consisting of one or more plant matrices" or "product comprising or consisting of a complex natural system" or "natural material or material of natural origin".

[0074] Furthermore, the term "product comprising or consisting of one or more natural matrices" according to the present specification may be an intermediate, or a final formulation for the intended use (e.g. a resuspended dry product), or, particularly when the formulation for the intended use is in liquid form, the term may define a dry or lyophilized form or a concentrated form thereof to which water is added by the user or physician to prepare the formulation for administration.

[0075] The "product comprising or consisting of one or more natural matrices" in the specification and claims cannot be intended to be a natural product per se. Moreover, when a single natural matrix is ​​present in or consists of the product, the natural matrix is ​​obtained (e.g. extracted) by technical means from an organism as defined above. When a mixture of natural matrices is present in or consists of the product, the mixture is a mixture of selected natural matrices produced by humans, which cannot be found as such in any of the natural products from which each matrix contained therein originates. Thus, when a product comprises or consists of multiple natural matrices, the natural matrices have been combined by humans, endowing the resulting product with new emerging properties.

[0076] According to this specification, the expression "biological functions associated with a pathological condition" refers to a set of biological functions that are related to the distance / deviation from homeostasis that may or may not be reached by the onset, progression, or deterioration of a pathological condition. Thus, the expression "alteration of biological functions associated with a pathological condition" refers to the regulation or change of biological functions (e.g., activities or methods) in an organism (preferably human) from a normal (healthy) physiological state to a pathological condition or disease that is directly related to the change / disturbance of homeostasis. In other words, it describes a specific adjustment or deviation of a set of biological functions from a healthy physiological state that occurs as a result of or occurs simultaneously with the onset, progression, or deterioration of a pathological condition or disease.

[0077] By way of example, in the case of diabetes, biological functions related to glucose metabolism, insulin production and control are directly related to the diabetic pathology and thus are altered in a manner associated with the diabetic pathology or condition according to the present invention.

[0078] According to this specification, synthesis has its conventionally accepted meaning in chemistry.

[0079] Traditionally, in chemistry, the term "synthetic" refers to the origin or source of a material or substance. Synthetic substances or materials are produced by humans by artificial synthesis, i.e., by laboratory chemical reactions that usually react simpler chemicals to produce more complex chemicals via methods that often use different pathways, temperature conditions, pressure conditions, energy sources and / or catalysts than those used by living organisms.

[0080] Examples: Synthetic substances or materials include plastics, drugs, and many industrial chemicals. For example, nylon is a synthetic polymer made by chemical synthesis, and aspirin is a synthetic drug made by a specific chemical reaction.

[0081] The term "eubiotics" as used herein has the meaning "native to the living kingdom" (i.e. plants, animals, fungi, protists, Monera). The term is derived from the Greek "eu," meaning good or good, and "bio," meaning life. As used herein, the Greek concept of "eu" is intended to mean "native" / "belonging" to the living kingdom, thus preserving the integrity and complexity of their interactions. This term is opposed to "xenobiotic." The term "xenobiotic" is derived from the Greek words "xenos," meaning foreign, and "bios," meaning life. It refers to substances and materials "foreign to the living kingdom," in the sense of being foreign to the natural nutrition / metabolism of an organism.

[0082] In general, eubiotic drugs or treatments or supplements are designed to support and promote healthy balance in a biological system without introducing substances or materials that cause imbalances in that biological system. This may include drugs aimed at positively influencing the microbiome, promoting a healthy immune response, or enhancing overall well-being, for example, by promoting physiological conditions. Eubiotic drugs may only be natural, since synthetic products are a cause of imbalance to physiological processes.

[0083] In agriculture, eubiotics usually refer to practices that enhance soil health and promote a balanced ecosystem for crops. This may include the use of organic fertilizers, crop rotation, and other sustainable farming practices.

[0084] In microbiology, eubiotics generally refers to the study of microorganisms that contribute positively to environmental health, including understanding the role of beneficial bacteria in various ecosystems.

[0085] Overall, the general underlying concept of the term eubiotics is the promotion of a state of health, balance, and harmony within a living system, whether it be an animal's digestive system, the human microbiota, or an ecosystem.

[0086] In vitro cell-based assay herein has the meaning conventionally used in the art, and in particular it refers to a cell-based assay for evaluating cellular behavior and response to injury or stimuli in the context of a disease or pathological or pre-pathological condition, and is intended as an experimental technique used to evaluate how a particular disease or pathological or pre-pathological condition affects the behavior, function, or properties of selected cultured cells. This type of assay is designed to study the biological response of cells in a controlled environment, often within a petri dish or well plate.

[0087] Cell-based: This term indicates that the assay involves living cells. These cells can be from humans, animals, or cell lines that mimic a particular tissue or organ.

[0088] Assay: An assay is a set of tests or procedures performed in a laboratory setting to measure or analyze a particular property or function of biological material. In this case, the assay focuses on cells.

[0089] Disease or pathological condition / pre-pathological condition: In the context of disease or pathological condition / pre-pathological condition, the cell-based assay is specifically designed to simulate or mimic the conditions associated with the disease or pathological condition. In particular, the cell-based assay can be used to evaluate the therapeutic, adjuvant and / or beneficial effects of different compounds or products in vitro. This may include exposing the cells to factors known to be associated with the disease or pathological condition, exposing the cells to potential treatments or auxiliary products that help restore physiological conditions, or using cells that have been genetically modified to have features specific to the disease or pathological condition.

[0090] A healthy physiological state refers to the state of an organism's body, organ, device, system or body region and its internal processes when they are functioning optimally within normal parameters for that individual, i.e. the state in which homeostasis tends to prevail. In the context of biological functions known to contribute to the hallmarks of a given disease or pathological condition, a healthy physiological state refers to a state in which the various biological functions in question are operating optimally within normal (healthy) parameters. This state is characterized by the absence of significant abnormal cellular or molecular processes associated with the particular disease under consideration.

[0091] The term takes into account the salient hallmarks of a particular disease, which are distinctive features or characteristics typically observed in individuals afflicted with a particular disease. These hallmarks may include specific cellular behaviors, molecular pathways, or physiological responses that play a key role in the development or progression of the disease.

[0092] In summary, a healthy physiological state in the context of a particular disease or pathological condition is one in which biological functions associated with known hallmarks of that disease or pathological condition are regulated in a direction consistent with a non-disease (non-pathological) state, in other words, in the opposite direction to the disease (pathological) state.

[0093] Therefore, a healthy physiological state also exhibits the direction of regulation of biological functions that are known hallmarks of pathological states in homeostasis, i.e., prior to the onset of the pathological state, in other words the homeostatic direction of regulation of a set of biological functions attributable to a particular system, region, apparatus or organ in a healthy subject.

[0094] Hallmarks of a disease or pathological or medical condition according to this specification have the meaning conventionally used in the art. According to standard techniques, hallmarks of a disease are indicators that can indicate the progression or control of a given disease or pathological condition. These hallmarks (also called "key indicators") are typically a set of features or patterns that physicians monitor over time to track the progression or regression of a particular disease. In summary, hallmarks of a disease are defining features or characteristics whose modification is indicative of a given medical condition and aids in its identification, diagnosis, monitoring and understanding. As an example, for neurodegenerative diseases (NDDs), at least the following eight hallmarks of NDDs are known in the art: (pathological protein) aggregation, synapses and neuronal networks (dysfunction), (abnormal) proteostasis, cytoskeleton (abnormal), (altered) energy homeostasis, DNA and RNA (deficiency), inflammation (increase), and neuronal cell death (increase). In cancer research, hallmarks of cancer are a set of distinctive characteristics commonly found in cancer cells. These hallmarks include (sustaining) proliferative signaling, (evading) growth inhibitors, (resistant) cell death, (enabling) replicative immortalization, (inducing) angiogenesis, and (activating) invasion and metastasis.

[0095] The hallmarks of disease, their biomarkers, the biological functions associated with the hallmarks, etc., are a framework for studying a disease or pathological or medical condition using an integrative / holistic approach.

[0096] The expression "natural material" according to the present specification refers to a material consisting of one or more natural matrices, with the proviso that the material(s) is not found in nature per se, but is the result of technical human intervention (e.g. extraction methods, filtration, etc., detailed). These materials are typically obtained from plants, animals, fungi or microorganisms, and minerals, through preparation methods that aim to maintain the integrity of the network within the natural source from which the natural material is prepared. In the present specification, "natural material" is considered as a synonym for one or more natural matrices. Thus, a natural material according to the present specification can be a product, such as a product with a therapeutic effect, consisting only of or including different natural matrices selectively assembled (not combined in such a combination in nature) to produce a given therapeutic effect, thereby forming an "interactor network", the administration of which to a subject (i.e. the receiving living network) exhibits emerging properties that provide a therapeutic or homeostatic regulatory effect, i.e. a beneficial effect on the health of the subject.

[0097] "Therapeutically effective": According to the present specification, a therapeutically effective product is one which, when administered to a subject suffering from a pathological condition, reduces the severity of the subject's condition (i.e., the severity is at least partially reduced or alleviated) and / or provides some relief, alleviation or reduction of at least one clinical symptom and / or provides a delay in the progression of the condition, or restores (fully or partially) a healthy physiological state in the area affected by the pathological condition.

[0098] Having a beneficial effect according to the present specification includes products whose administration to a healthy subject or a healthy but not homeostatic subject, or to an in vitro cell assay representative of a sufficiently healthy state, results in in vitro or in vivo evidence of restoration of homeostasis or adjuvant effect upon administration in the cell assay or recipient system / area / device / organ of interest of the subject.

[0099] The terms "prevent", "preventing" and "prevention of" (and grammatical variations thereof) refer to a reduction and / or delay in the onset and / or progression of a disease, disorder and / or clinical symptom(s) in a subject, and / or a reduction in the severity of the onset and / or progression of a disease, disorder and / or clinical symptom(s) in a subject, compared to what would occur in the absence of the method of the present invention. Prevention can be complete, e.g., the total absence of a disease, disorder and / or clinical symptom(s). Prevention can also be partial, such that the onset and / or the severity of the onset and / or progression of a disease, disorder and / or clinical symptom in a subject is less than would occur in the absence of a composition according to the present invention.

[0100] Having a "beneficial / health / health beneficial" effect according to this specification encompasses products whose administration to a non-homeostatic healthy subject or to a healthy subject, or to an in vitro cellular assay representative of a fully healthy state, results in in vitro or in vivo evidence of restoration of or adjuvanting of homeostasis upon administration in said cellular assay or in the intended recipient system / area / device / organ.

[0101] The term "product having (confirmed) therapeutic properties comprising one or more natural matrices" or "product for treating a pathological condition comprising one or more natural matrices" according to the present invention is a product as defined above, the emerging properties of which provide a therapeutic effect as defined below in the glossary.

[0102] This term may be replaced in any part of the specification and claims with "a therapeutically active product comprising or consisting of a complex natural system", "a formulation comprising (or consisting of) a complex natural system" or "a composition comprising (or consisting of) a complex natural system" or "a mixture comprising (or consisting of) a complex natural system" and the term "unrefined natural system" may be replaced with "one or more natural matrices" or "natural material".

[0103] The definition applies mutatis mutandis to the term "products having beneficial / healthy / health properties comprising one or more natural matrices".

[0104] According to this specification, the term homeostasis has its conventional meaning in the art and thus refers to the physiological way in which an organism maintains a stable internal environment despite external changes. This stability is important for the proper functioning of cells, tissues and organs. The purpose of homeostasis is to ensure that the internal conditions of an organism remain within the optimal range for survival and proper physiological function (healthy physiological state). Homeostasis is achieved by an organism through the regulation of a set of biological functions and processes aimed at maintaining a healthy physiological state.

[0105] A product that aids in the homeostatic process is a product that regulates biological functions in the direction of a healthy physiological state and is therefore suitable for healthy individuals and can be used by healthy individuals to support homeostatic mechanisms that contribute to a healthy physiological state and to aid in the homeostatic regulation of biological functions associated with the hallmarks of a given pathological condition.

[0106] A medical device (also MD) is, according to this specification, a product as defined above according to the definition in Article 2(1) points 1 to 3 of EU Regulation 2017 / 745, which is necessarily used for treatment purposes, therefore "medical device" means any ... [omitted]... material intended by the manufacturer to be used by humans, alone or in combination, for one or more of the following specific medical purposes: - Treating or alleviating a disease, - Treatment, mitigation, or compensation for injury or disability; -modification of physiological or pathological processes or conditions, ...omission... It does not achieve its primary intended action by pharmacological, immunological or metabolic means in or within the human body, although its function may be assisted by such means.

[0107] "Performance" of a medical device means the ability of a medical device, as defined herein, to achieve its intended purpose as stated by the manufacturer; "Clinical performance" of a medical device means the ability of a medical device, as defined herein, to achieve its intended purpose as claimed by the manufacturer, resulting from any direct or indirect medical effect derived from its technical or functional characteristics, including diagnostic properties, thereby providing a clinical benefit to the patient when used as intended by the manufacturer; "Clinical benefit" of a medical device means the positive impact of the device, as defined herein, on an individual's health, or the positive impact on patient management or public health, expressed in terms of meaningful, measurable, patient-relevant clinical outcome(s), including diagnostic related outcome(s).

[0108] Additionally, if a composition (e.g., an invention such as a product having therapeutic properties that includes one or more natural matrices) is intended to have a medical purpose, such as the diagnosis, treatment, mitigation, or prevention of disease, or to affect the structure or function of the body, and meets the criteria outlined in the definition, it may be classified as a medical device by the U.S. FDA.

[0109] Pursuant to section 201(h)(1) of the Food, Drug, and Cosmetic Act, a device is: Any instrument, apparatus, device, machine, contrivance, implant, in vitro reagent, or other similar or related article, including any component parts or accessories thereof, (A) recognized in the official National Pharmacopoeia or the United States Pharmacopoeia, or any supplement thereto; (B) intended for use in the diagnosis of disease or other condition in humans or other animals, or in the cure, mitigation, treatment, or prevention of disease; or (C) is intended to affect the structure or any function of the body of a human or other animal, does not achieve its primary intended purpose by chemical action in or on the body of a human or other animal, and does not depend on being metabolized for the achievement of its primary intended purpose. The term "device" does not include software features excluded pursuant to section 520(o).

[0110] The classification of medical devices within risk classes is typically based on factors such as the intended use, instructions for use, and the risks associated with the device.

[0111] A product believed to have a confirmed therapeutic effect according to the present invention means that there exists a gold standard for products that exhibit the desired therapeutic effect at least in vitro, e.g. in a laboratory setting using cells, organoids, tissues, and / or in vivo in animal models or clinical trials.

[0112] The expression having a confirmed beneficial / healthy / beneficial effect according to the present invention means that it is a product for which there is a gold standard of products that show the desired effect of restoring homeostasis / adjuvanting at least in vitro on animal models, e.g. in a laboratory environment using cells, organoids, tissues and / or in vivo cells, organoids, tissues.

[0113] As used herein, a subject "in need thereof" refers to a subject who can benefit from the therapeutic and / or prophylactic effects of a therapeutic composition. Such a subject can be diagnosed with a disease or disorder, a subject suspected of having or developing a disorder, and / or a subject determined to be at high risk of having or developing a disease or disorder.

[0114] The terms "treat," "treating," or "treatment of" (and grammatical variations thereof) mean that the severity of the subject's condition is reduced, at least partially ameliorated or improved, and / or some alleviation, alleviation, or reduction of at least one clinical symptom is achieved, and / or the progression of the disease or disorder is slowed.

[0115] Batch Legend: Figures 2-7 and 12: Product Arte-Gx in lyophilized form (see detailed composition of the product in Example 1): Batch 20B1955 or L20B1955 Gold Standard Batch 20B0596 or L20B0596 Batch 20I1297 or L20I1297 Batch 21E1640 or L21E1640 Batch 20J1770 or L20J1770 Batch Drying 21E1640 Figure 9 Gold standard for product B Figure 11 Gold standard for product C (See detailed product composition in Example 1). [Brief description of the drawings]

[0116] [Figure 1] Illustrative hallmarks of osteoarthritis including trends of hallmarks indicative of improvement in disease state (column 1), biological functions associated with each disease (column 2) and their regulation in pathological states (column 3), and the regulation of each of said biological functions indicative of a healthy physiological state (column 4); dark grey: upregulation, light grey: downregulation. [Diagram 2]Modulation of selected biological functions in chondrocyte-based assays in osteoarthritis: Column 1 is the hallmark including the tendency of the hallmark representing the improvement of the pathological condition, Column 2 is the biological function, Column 3 is the predicted modulation of the biological function in the pathological situation, Column 4 is the desired modulation of the biological function in the healthy physiological condition, Column 5 is the cell-based assay without therapeutic treatment representing the biological function modulation in the pathological situation, Column 6 is the modulation induced by the gold standard of the product tested. The cell-based assay shows that the gold standard modulates the selected function according to the healthy physiological condition. The numbers reported in each box represent the Z-score (sometimes referred to as "Z-score") calculated with the method of the invention representing the modulation of each biological function observed. [Diagram 3] Modulation of selected biological functions in chondrocyte-based assays representative of osteoarthritis: column 1 represents the hallmarks including the tendency of the hallmarks representing the improvement of the pathological condition, column 2 represents the biological function, column 3 represents the predicted modulation of the biological function in a pathological situation, column 4 represents the desired modulation of the biological function in a healthy physiological condition, column 5 represents the biological function modulation in a pathological situation, cell-based assay without therapeutic treatment, column 6 represents the modulation induced by the reference drug (triamcinolone acetonide), column 7 represents the modulation induced by the gold standard of the test product, columns 8-11 represent the modulation induced by four different batches of the test product. In particular, column 11 represents the modulation induced by an intentionally destabilized batch (DEST 21E1640) that shows weaker therapeutic activity. The cell-based assay shows that the gold standard and the additional batches similarly modulate the selected functions according to the healthy physiological condition. The numbers reported in each box represent the calculated Z-score values ​​representing the modulation of each biological function observed. [Figure 4]Figure 4 corresponds to Figure 3 plus column 12 showing a control analysis of the modulation induced by a non-destabilized batch (21E1640) validated as complying with the method of the invention. The cell-based assay shows that the gold standard and the additional batch similarly modulate the selected functions according to the healthy physiological state, thus confirming the compliance of the batch validated with the method of the invention. The numbers reported in each box represent the calculated Z-score value, which represents the modulation of each biological function observed. As shown in the table below, for each modulated biological function, a reference Z-score value was calculated according to the invention, taking into account the gold standard Z-score value (column 8 of Figure 4) and the drug Z-score value (column 9 of Figure 4) selecting the Z-score value associated with the weakest performance as the reference Z-score value (column 13 of Figure 4): [Table 1] Since the therapeutic effect is confirmed for both the product as well as the drug, if both the reference drug and the gold standard provide modulation of a selected biological function in the same direction of a healthy physiological state, it is correct to accept the weakest performance Z-score as the reference cut-off for that modulation. [Diagram 5] Targeted metabolomics of Arte Gx main chemical classes of 5 batches (including the gold standard). This figure clearly shows that each tested batch differs from each other and from the gold standard in qualitative-quantitative composition. When compared with the testing of selected biological activities of the same batches in cell-based assays (Figures 3 and 4), the qualitative-quantitative analysis of different batches of products for use in the treatment of pathological conditions shows that products containing or consisting of one or more natural matrices cannot be accurately estimated in their activity profile. [Figure 6a] NIR spectra of the gold standard and three different positive batches selected in iv) in the wavelength range of interest. [Figure 6b]NIR average spectra of the four batches of 6a. NIR spectrum of negative batch 21E1640 Dest. [Figure 6c] NIR average spectra of four batches of 6a and two empirically undesirable spectra (undesirable A Centella asiatica extract, undesirable B Echinacea extract). [Figure 6d] NIR average spectra of the four batches of 6a and the NIR spectrum of the unassessed batch 21E1640 (not destabilized). [Figure 7] Figure 1 shows the ROS scavenging activity of the four validated batches, including the gold standard of Arte-Gx. The amount of ROS detected in the sample treated with AAPH was considered as the maximum release of ROS (100%), and the amount of ROS detected in the other samples was calculated as a percentage of the maximum release induced by AAPH. One-way ANOVA and Dunnett's post-hoc test were applied. Only values ​​able to return p<0.05 were considered significant (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). Statistical significance of all samples vs. untreated cells. The figure demonstrates that the validated batches indeed induce ROS scavenging activity as desired for the intended therapeutic use. [Figure 8a] Illustration of salient hallmarks of Mild Cognitive Impairment (MCI) (column 1), the biological functions associated with each disease (column 2) and their regulation in the pathological state (expressed as an alteration of the healthy physiological state) (column 3), and the regulation of each of said biological functions representative of the healthy physiological state (column 4); dark grey: upregulation, light grey: downregulation. [Figure 8b] Illustration of salient hallmarks of Mild Cognitive Impairment (MCI) (column 1), the biological functions associated with each disease (column 2) and their regulation in the pathological state (expressed as an alteration of the healthy physiological state) (column 3), and the regulation of each of said biological functions representative of the healthy physiological state (column 4); dark grey: upregulation, light grey: downregulation. [Figure 9a]Modulation of selected biological functions in a human neuronal cell-based assay (cells SH-SY5Y): column 1 is the hallmark, column 2 is the biological function, column 3 is the predicted modulation of the biological function in a pathological situation, column 4 is the desired modulation of the biological function in a healthy physiological state, column 5 is the modulation induced by the gold standard of the tested product B. The cell-based assay shows that the gold standard modulates the selected function according to the healthy physiological state. The numbers reported in each box represent the Z-score calculated with the method of the invention, which represents the modulation of each biological function observed. The test product B used is described in Example 1. [Figure 9b] Modulation of selected biological functions in a human neuronal cell-based assay (cells SH-SY5Y): column 1 is the hallmark, column 2 is the biological function, column 3 is the predicted modulation of the biological function in a pathological situation, column 4 is the desired modulation of the biological function in a healthy physiological state, column 5 is the modulation induced by the gold standard of the tested product B. The cell-based assay shows that the gold standard modulates the selected function according to the healthy physiological state. The numbers reported in each box represent the Z-score calculated with the method of the invention, which represents the modulation of each biological function observed. The test product B used is described in Example 1. [Figure 10a] Example of hallmarks for osteoporosis (OP) including trends of hallmarks representing improvement of the disease state (column 1), biological functions associated with each disease (column 2) and their regulation in the pathological state (expressed as a change in the healthy physiological state) (column 3), and the regulation of each of said biological functions representing the healthy physiological state (column 4); dark grey: upregulation, light grey: downregulation. [Figure 10b] Example of hallmarks for osteoporosis (OP) including trends of hallmarks representing improvement of the disease state (column 1), biological functions associated with each disease (column 2) and their regulation in the pathological state (expressed as a change in the healthy physiological state) (column 3), and the regulation of each of said biological functions representing the healthy physiological state (column 4); dark grey: upregulation, light grey: downregulation. [Figure 11a]Modulation of selected biological functions in an adipose-derived mesenchymal stem cell line (hADMSC) capable of differentiating into osteoblasts and mineralizing the extracellular matrix (ECM): column 1 is the hallmark, column 2 is the biological function, column 3 is the predicted modulation of the biological function in a pathological situation, column 4 is the desired modulation of the biological function in a healthy physiological state, column 5 is the modulation induced by the gold standard of the tested product C. The cell-based assay shows that the gold standard modulates the selected function according to the healthy physiological state. The numbers reported in each box represent the Z-score calculated with the method of the invention, which represents the modulation of each biological function observed. The test product C used is described in Example 1. [Figure 11b] Modulation of selected biological functions in an adipose-derived mesenchymal stem cell line (hADMSC) capable of differentiating into osteoblasts and mineralizing the extracellular matrix (ECM): column 1 is the hallmark, column 2 is the biological function, column 3 is the predicted modulation of the biological function in a pathological situation, column 4 is the desired modulation of the biological function in a healthy physiological state, column 5 is the modulation induced by the gold standard of the tested product C. The cell-based assay shows that the gold standard modulates the selected function according to the healthy physiological state. The numbers reported in each box represent the Z-score calculated with the method of the invention, which represents the modulation of each biological function observed. The test product C used is described in Example 1. [Figure 12] Biological functions of the four validated batches, including the gold standard Arte-Gx: modulation of oxidative stress (hallmark inflammation). Ascorbic acid is used as a positive control and injury with AAPH as a negative control representing the pathological situation. As is evident from the figure, the use of different markers to monitor the modulation of biological functions causally related to the pathological hallmarks of osteoarthritis (OA) is also suitable to validate the batches as alternatives to transcriptomic markers. [Figure 13]Biophysical characterization of total RNA of biological plant material. Figure 13 shows the electropherogram of the production intermediate of Arte GX, i.e. Centella Asiatica and Echinacea aqueous co-extract, in the proportions shown in Example 1, before ultrafiltration, panel "A" shows the size distribution of total RNA and panel "B" shows the RNA size distribution between 4 nt and 150 nt. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0117] The present invention provides approaches and methods for batch-to-batch validation of products that comprise or consist of natural matrices, such as products that consist of 100% eubiotic entities and exert a therapeutic or beneficial activity, by providing spectroscopic or spectrophotometric tolerance ranges or tolerance cut-offs based on measurements of modifications of specific biological activities that are associated with a therapeutic or beneficial effect, allowing a homeostatic rebalancing of slight imbalances in physiological-pathological situations or in organisms, such as the human organism. The applicant therefore provides new standard techniques that allow this type of product to be standardized and thus to comply with a regulatory framework to give a viable space for innovative use of said products in treatment. In the past decades, the applicant pursued a multidisciplinary research path that led to the development of eubiotic protocols for agricultural production and methods of transformation of raw materials (starting materials), in order to maintain, together with scientific innovations, the fundamental natural program rules that allowed millions of years of interconnection between all the components of living organisms, organic and inorganic.

[0118] In accordance with the teachings of the present invention, it is now possible to evaluate precise parameters for validating batch-to-batch compliance of products having emerging properties that result in physiological therapeutic or beneficial activity, where the product comprises or consists of one or more natural matrices.

[0119] This is of particular interest for all products for therapeutic / beneficial use that are not based on excipients, such as products that contain or consist of one or more natural matrices, in addition to classical pharmacological formulations APIs. The main problem for this type of product is to ensure the compliance of the product with the claimed therapeutic / beneficial effect, despite the important therapeutic / beneficial effect exerted in the absence of reproducible and accurate methods for batch-to-batch validation, which, due to their very origin (nature), show an inherent variability in their qualitative-quantitative composition and cannot be properly evaluated by classical validation methods based on a mere qualitative-quantitative composition. Up until now, it has in practice not been possible to take this into account and bring products that contain or consist of one or more natural matrices into a regulatory framework that allows for a high degree of innovation. This problem is solved by the present invention.

[0120] Since the techniques and methods of the present invention are designed for products that contain or consist of natural matrices, the production of these products is preferably carried out with standardization of the entire production process, both in agricultural and manufacturing methods.

[0121] The inventors demonstrate that classical targeted metabolomic reproducibility assays, such as those based only on the qualitative-quantitative analysis of a chemical class or specific chemical compounds of a therapeutic product, judged on the basis of criteria designed for the control of a single API acting via a deterministic key-lock mechanism due to the presence of a distinct SAR, are not suitable for quality control when the product contains or consists of one or more natural matrices. Indeed, when faced with the selected biological activity of each batch, the results obtained by the inventors from the analysis of chemical classes of different batches of the same product show that the quantitative variation of the individual chemical classes of substances present in the different batches, when considered as the only reference parameter for assessing the quality of the batch according to the reference applied to the API, leads to the a priori assumption that these batches have different biological activities (see the second table and Figure 5 in Example 3.1). In contrast, the experiments carried out by the inventors (see Example 3.1, in particular Figures 3, 4 and 5) demonstrate that the batches, despite their variable qualitative-quantitative chemical composition, have the same biological activity, an elastic behavior probably due to the presence of redundancy between the single components at both the structural and functional levels.

[0122] Thus, the experiments carried out by the inventors (see in particular Figures 3, 4 and 5) show that, when considered alone, the qualitative-quantitative analysis of different batches of a product for use in the treatment of a pathological condition does not allow to accurately estimate the activity profile when the product comprises or consists of one or more natural matrices. The data provided herein therefore demonstrate that, in contrast to API-based pharmaceutical products, the qualitative-quantitative analysis of the individual components of a therapeutic product that comprises or consists of one or more natural matrices (i.e. providing a therapeutic effect based on network interactions) is therefore not suitable to assess the correct batch compliance for a batch of said product, especially when carried out as a method to assess the reproducibility of non-SAR-based entities.

[0123] Indeed, considering the very nature of natural matrices, quantitatively variable chemical profiles between batches would prompt validators to consider various batches of a product that contains or consists of one or more natural matrices as "different materials" with respect to a given gold standard of said product and therefore discard said batches, but on the contrary, the results provided by the inventors herein demonstrate that qualitatively-quantitatively different batches of a given product exert the same relevant responses for their intended therapeutic use. This is another demonstration that the biological activity of a complex matrix cannot be traced back to the sum of the activities of each single molecule within the matrix itself, and that the reproducibility of the activity of a matrix does not exclusively depend on the reproducibility of the identities and amounts of the molecular components that compose it.

[0124] The results obtained by the inventors demonstrate that both structural and functional redundant mechanisms exist within the natural matrix that confer a particular resilience to the matrix, and that the matrix itself should not be perceived as a collection of molecules acting independently of each other that, when studied individually, remain invariably under the influence of a common cause SAR.

[0125] As shown herein (see examples and figures), different batches of test products comprising or consisting of one or more natural matrices have been identified as differing in their qualitative-quantitative composition from each other and from the gold standard of said products, and may retain the ability to mediate the same therapeutic or beneficial activity despite the different quantitative composition at the molecular level.

[0126] The inventors have therefore developed a new method for defining the acceptance zone or acceptability cut-off of a spectroscopic or spectrophotometric analysis suitable for the validation of one or more batches of a product for use in the treatment of a pathological condition, the product comprising or consisting of one or more natural matrices; a further method is a method for the validation of different batches of a product comprising or consisting of one or more natural matrices, based on the preservation of selected intrinsic properties of the matrix (modulation of selected biological characteristics) and not on the preservation of molecular components. The method of the invention allows to identify the validation acceptance zone or acceptability cut-off based on the evaluation of selected parameters that effectively correlate with the maintenance of the desired overall biological activity, as demonstrated herein.

[0127] The present specification discloses experimental data by way of example for a model product herein designated Arte-GX (see examples for product composition), consisting essentially of a plant-derived natural matrix, for use in the treatment of osteoarthritis (disclosed in WO 2018 / 138678). Faced with the problem of meeting the regulatory requirements for putting the above-mentioned product into treatment, the inventors tested classical validation methods and realized that the classical validation methods (qualitative-quantitative chemical composition) are not suitable for accurately assessing the therapeutic effect of the product (compare Figures 3, 4 and 5). That is, the inventors developed the techniques and methods disclosed herein and found results consistent with those reported herein for other different products with therapeutic effect that contain or consist of one or more natural matrices.

[0128] All products tested consist of or contain a natural matrix and are intended for use in the treatment of a pathological condition, the matrix being derived from plant biomaterials that have been appropriately processed and formulated to obtain a final natural material (as defined in the glossary) that, upon administration, is capable of modifying the pathological situation and promoting the restoration of a healthy physiological state. For all products tested, a gold standard with a confirmed therapeutic effect was available. A detailed description of the products tested is provided in the Examples section.

[0129] In the products tested, the hundreds of components derived from the crude raw plant parts are not deprived of the ability to maintain their therapeutic emerging properties, since they establish multiple combinations of molecular and supramolecular interactions among themselves and with the target tissues, characteristic of materials of natural biological origin.

[0130] In particular, the products tested by the applicant are prepared according to a eubiotic protocol selected and standardized by the applicant through more than 40 years of experience, starting from the preparation of the soil to the production of the final product, empirically making the final product as homogeneous as possible and thus increasing efficiency in terms of the yield of useful batches. The eubiotic protocol developed by the applicant is interpreted as providing a 100% natural final product, as opposed to synthetic or partially synthetic products (i.e. products not containing a single component obtained by artificial chemical synthesis), in which each component is produced under eubiotic conditions, in order to standardize each step leading to the desired final product as much as possible in relation to the eubiotics of each step. By comparing, or rather integrating, the reductionist approach described above with those of systems theory and quantum biology, it is possible to develop a fully eubiotic standardized production method involving the integration of interdisciplinary techniques and research in several different fields, from the agricultural field to the omics and mathematical science fields. Preferably, according to the present invention, test products comprising or consisting of one or more natural matrices are free of chemically synthesized molecules and free of natural matrices with which they are in contact and which may have internalized chemically synthetic molecules, thereby making it possible to provide natural matrices and final products consisting of 100% natural components.

[0131] The present invention relates to a method for defining the acceptance range or the acceptance cut-off of a spectroscopic or spectrophotometric analysis for the validation of one or more batches of a product intended for use in the treatment of a pathological condition, comprising or consisting of one or more natural matrices, the method comprising: calculating said tolerance zone or acceptability cutoff on the spectroscopic or spectrophotometric spectra of one or more batches of said product and a gold standard having a confirmed therapeutic effect in treating said pathological condition, said spectra being defined as acceptable or unacceptable based on biological activity exerted in at least one cell-based assay by said gold standard and one or more batches on one or more hallmarks of said pathological condition.

[0132] Depending on the pathological condition of interest, the hallmarks may be one or more, preferably more hallmarks are selected, but for example in the case of cancer, the skilled artisan is well aware that the more relevant hallmark is the proliferation of cancer cells, and therefore the selected cell-based assay is in this case an assay validating the viability of the neoplastic cells or tumor mass upon administration of the product of interest. Furthermore, according to the present invention, it is preferred to use a single cell-based assay, but two or more cell-based assays can also be used, and in a non-limiting example, additional cell-based assays can be performed if different cell-based assays are considered more appropriate for the analysis of different hallmarks.

[0133] The main difference between the product validation procedure of the present invention and standard techniques is based on the demonstration that the qualitative-quantitative characterization of products containing or consisting of one or more natural matrices, although beneficial, is not suitable to evaluate the real efficacy of these types of products due to the dynamic interactions of all its components resulting in new emerging properties, and therefore the validation procedure must be performed on a different basis than that of classical API-based therapeutic products. Indeed, as also shown by the data provided in the examples and figures of the present application, the qualitative-quantitative validation in the case of products containing or consisting of natural matrices is not sufficient and suitable to ensure the therapeutic efficacy of the product.

[0134] The applicant has developed new approaches and methods to base the validation procedure on the definition of validation parameters that are truly representative of the therapeutic effectiveness of the product.

[0135] However, additional metabolomic analyses may still be desirable for manufacturers, for example to assess the toxicological profile of the product.

[0136] Depending on the pathological condition of interest, the hallmarks may be one or more, and preferably more hallmarks are selected if available, but in the case of e.g. cancer, the skilled artisan will be well aware that the most relevant hallmark is the proliferation of cancer cells, and therefore the skilled artisan will be able to limit the method of the invention to this single hallmark, and the selected cell-based assay will in this case be an assay validating the viability of the neoplastic cells or tumor mass upon administration of the product of interest.

[0137] In one embodiment of the invention, the method comprises the steps of: i) a. retrieving a list of hallmarks for the pathological condition from standard techniques; b. identifying for each of said hallmarks a set of alterations in biological functions detectable in said pathological condition, determining the modulation of each of said functions associated with a desired therapeutic effect, and thereby designing a pattern of modulation of each of said functions that is indicative of a healthy physiological state; c. identifying for each of said biological functions markers and their regulation patterns that are responsible for the detectable alteration in said pathological condition, and for each of said markers, establishing a regulation pattern opposite to that identified as indicative of said healthy physiological condition; ii) i) analyzing the expression pattern of each of the markers identified in c. induced by the gold standard of said product in a suitable in vitro cell-based assay, determining the qualitative-quantitative regulation of each of said markers induced by said gold standard with respect to the control of a pathophysiological condition of said in vitro cell-based assay, calculating a gold standard Z-score value of the regulation of each of said biological functions induced by said gold standard, and selecting each of said gold standard Z-score values ​​as a reference cut-off Z-score value indicative of said desired therapeutic effect; iii) analyzing the pattern of regulation of the markers identified in i)c. induced by further different batches of the product in the in vitro cell-based assay and determining the qualitative-quantitative regulation of each of the markers induced by each of the batches, thereby calculating a Z-score value of the regulation of each of the biological functions induced by each of the batches; iv) comparing the Z-score values ​​of each of the modulations of the biological functions induced by each of the batches calculated in iii) with the corresponding cut-off Z-score values ​​of each of the modulations of the biological functions provided in ii), and selecting at least three positive batches in which each Z-score value of each of the modulations of the biological functions calculated in iii) complies with the corresponding reference cut-off Z-score value, and at least one negative batch in which at least one Z-score value of each of the modulations of the biological functions calculated in iii) does not comply with the corresponding reference cut-off Z-score value. v) performing spectroscopic or spectrophotometric analysis of the gold standard and the batch selected in iv); vi) defining as acceptable the variation spectroscopy or spectrophotometric range obtained by considering each result obtained in v) as acceptable for each positive batch and as unacceptable for each negative batch, thereby providing said acceptable spectroscopy or spectrophotometric range or cut-off.

[0138] When the same hallmark may be related to a biological function that can be monitored by different biological markers, the skilled person may decide to carry out one or more assays to monitor said function. In the exemplary sections and figures, the definition of the tolerance zone with different markers is provided, and the results show that in each case, despite the different markers for analyzing the regulation of the selected biological function, the results are consistent and the resulting cutoffs are the same when the same spectroscopic technique is used.

[0139] The skilled artisan will be able to select the more appropriate marker depending on the selected hallmark of the pathological condition of interest.

[0140] Such markers can be, by way of example, gene expression patterns, ROS, oxidative stress, cell viability, and the like.

[0141] In a preferred, but non-limiting embodiment of the present invention, the method comprises the steps of: i) a. retrieving a list of hallmarks for the pathological condition from standard techniques; b. identifying for each of said hallmarks a set of alterations in biological functions detectable in said pathological condition, determining the modulation of each of said functions associated with a desired therapeutic effect, and thereby designing a pattern of modulation of each of said functions that is indicative of a healthy physiological state; c. identifying for each of said biological functions the genes and their expression patterns that are responsible for the detectable alteration in said pathological state, and for each of said genes, establishing an expression pattern opposite to the expression pattern identified as indicative of said healthy physiological state; ii) i) analyzing the expression pattern of each of the genes identified in c. induced by the gold standard of said product in a suitable in vitro cell-based assay, determining the qualitative-quantitative regulation of the expression of each of said genes induced by said gold standard with respect to the pathophysiological state control of said in vitro cell-based assay, calculating a gold standard Z-score value of the regulation of each of said biological functions induced by said gold standard, and selecting each of said gold standard Z-score values ​​as a reference cut-off Z-score indicative of said desired therapeutic effect; iii) analyzing the expression patterns of the genes identified in i)c. induced by further different batches of the product in the in vitro cell-based assay and determining the qualitative-quantitative modulation of the expression pattern of each of the genes induced by each of the batches, thereby calculating a Z-score value of the modulation of each of the biological functions induced by each of the batches; iv) comparing the Z-score values ​​of each of the modulations of the biological functions induced by each of the batches calculated in iii) with the corresponding reference cut-off Z-score values, and selecting at least three positive batches in which each Z-score value calculator of iii) complies with the corresponding reference cut-off Z-score value, and at least one negative batch in which at least one Z-score value calculated in iii) does not comply with the corresponding reference cut-off Z-score value. v) performing spectroscopic or spectrophotometric analysis of the gold standard and the batch selected in iv); vi) defining a variation spectroscopic or spectrophotometric range obtained by considering each of the results obtained in v) as acceptable for each positive batch and as unacceptable for each negative batch, thereby providing said acceptable spectroscopic or spectrophotometric range or cut-off.

[0142] According to the present invention, the product subjected to the batch-to-batch validation method of the present invention and provided with an appropriate tolerance range or tolerance cut-off value together with the method of the present invention is a product comprising or consisting of one or more natural matrices for use in the treatment of a pathological condition, i.e. a product having a therapeutic effect that has been validated at least preclinically in vitro on cells and / or tissues and / or organoids and / or animal models, and is therefore expected to reduce the severity of the subject's condition (i.e. at least partially improve or ameliorate the severity) and / or provide some relief, alleviation or reduction of at least one clinical symptom of the condition and / or delay the progression of the condition, when administered to a patient suffering from a given pathological condition. The subject treated according to the present invention may be an animal, including a human (hence the product is for human or veterinary use), or a plant.

[0143] The approach and method provided in the present invention are in fact methods that can be implemented in the production chain with the aim of validating a batch of a given therapeutic product that contains or consists of a natural matrix.

[0144] As already mentioned above, the product is a product which comprises or consists of one or more natural matrices, i.e. complex natural systems, non-limiting examples of which are represented by one or more of the following: chopped or crushed plant parts, plant extracts, processed plant parts, fractions of plant extracts, for example fractions of plant extracts obtained by filtration through semi-permeable membranes (microfiltration, ultrafiltration, nanofiltration) or by treatment with adsorbent resins, microorganisms, honey, propolis, silk, wax, plant resins, plant gums, plant exudates, plant oils, plant essential oils, animal tissue lysates, plant or animal fluids.

[0145] Preferably the microorganism is an inactivated microorganism, such as a Tyndall treated organism.

[0146] In the most preferred embodiment, the therapeutic product is a product consisting of 100% natural components intended as components not obtainable by humans through chemical synthesis reactions, therefore, when the product contains one or more natural matrices, it may also contain minerals, any other organic or inorganic materials generally found in nature. Preferably, the products subject to the techniques and methods of the present invention are products that are obtained or can be obtained according to a standardized protocol, more preferably through a eubiotic standardized protocol. Even if a standardized protocol is not available, the skilled person can minimize the differences between batches of the same product by using starting materials or intermediate materials or pools of natural matrices for each natural matrix contained in the product. In this way, the inherent variability of natural matrices derived from different samples of the same type of source (e.g. the same plant of different cultivars) can be reduced by said pooling.

[0147] According to the present invention, the product may be a food supplement, a dietary supplement, a medical device, a medicine.

[0148] In one embodiment, the product is a medical device as defined in Article 2(1) points 1 to 3 of EU Regulation 2017 / 745, the medical purpose being the treatment or mitigation of a disease or the modification of a pathological process or condition.

[0149] Article 2(1) points 1 to 3 of EU Regulation 2017 / 745 states: For the purposes of these Regulations, the following definitions apply: (1) ``Medical device'' means any [...] material or other article intended by its manufacturer to be used in humans, either alone or in combination, for one or more of the following specific medical purposes: -diagnosis, prevention, monitoring, prediction, prognosis, treatment or mitigation of disease; -diagnosis, monitoring, treatment, mitigation, or compensation for injury or disability; - the investigation, replacement or modification of anatomical structures or physiological or pathological processes or conditions; [...] It does not achieve its primary intended action by pharmacological, immunological or metabolic means at or within the human body, although its function may be assisted by such means. The product may be a product classified by the FDA as a medical device.

[0150] Pursuant to section 201(h)(1) of the Food, Drug, and Cosmetic Act, a device is: Any instrument, apparatus, device, machine, contrivance, implant, in vitro reagent, or other similar or related article, including any component parts or accessories thereof, (A) recognized in the official National Pharmacopoeia or the United States Pharmacopoeia, or any supplement thereto; (B) intended for use in the diagnosis of disease or other condition in humans or other animals, or in the cure, mitigation, treatment, or prevention of disease; or (C) is intended to affect the structure or any function of the body of a human or other animal, does not achieve its primary intended purpose by chemical action in or on the body of a human or other animal, and does not depend on being metabolized for the achievement of its primary intended purpose. The term "device" does not include software features excluded pursuant to section 520(o).

[0151] The method of the present invention is preferably performed on a dried form of the desired product, therefore, if the final product intended for use is a solution, suspension or other liquid form, the method may be performed on the lyophilized product prior to its rehydration.

[0152] In its final form for administration, the product may be in the form of a powder, granules, tablets, syrup, solution, suspension, hard or soft gelatin, capsule, spray, cream, or the like.

[0153] According to the present invention, a pathological condition is a specific disease or pathological condition. Non-limiting examples of pathological conditions include mild cognitive impairment (MCI), osteoporosis (OP) (including postmenopausal or perimenopausal osteoporosis (PMO)), osteoarthritis (OA), and cancer.

[0154] Cancers of primary interest include, but are not limited to, head and neck cancer, melanoma, breast, bladder and osteosarcoma.

[0155] Hallmarks of pathological conditions and specific diseases are well known in the art. A person skilled in the art can easily search for hallmarks of a pathological condition of interest as well as the biological functions responsible for said hallmarks in the scientific literature. It is clear that a person skilled in the art will select the biological functions underlying a given hallmark taking into account the particular pathological condition of interest.

[0156] By way of example, one skilled in the art can research the pathological state-of-the-art of a disease of interest using different standard technical sources.

[0157] Those skilled in the art who wish to define the hallmarks of a disease of interest can retrieve the desired information from the scientific literature. By way of example, non-limiting examples of sources that can be used include Robbins & Cotran Pathologic Basis of Disease (Robbins Pathology) 10th Edition; https: / / calgaryguide.ucalgary.ca / ;Biomedical literature from PubMed Central( https: / / pubmed.ncbi.nlm.nih.gov / ) etc.

[0158] For each of said hallmarks, several biological functions underlying them are also known in the art and the skilled person can select said functions from those disclosed in the art. If more biological functions are ascribed in the art to a given hallmark of a given pathology in the method of the invention, preferably at least two, at least three or more of said functions are selected.

[0159] If one wishes to use certain software available to easily perform certain steps of the method of the present invention, such as finding the biological functions underlying disease hallmarks, one skilled in the art may wish to adapt their definitions to accommodate the hallmarks retrieved in order to better explore the software used. As an example, if the software used is Qiagen IPA (IPA version 94302991 Qiagen), one may use the information found in the aforementioned resources, if necessary, to redefine the hallmarks in question to explore IPA. When using IPA to quickly identify the biological functions underlying disease hallmarks, the following procedure may be followed.

[0160] Hallmarks can be written one by one in the "Diseases and Functions" query box, and then the search will be initiated.

[0161] The resulting resumé table allows one of skill in the art to filter diseases / functions arising from a body of evidence. By way of example, the source of the relationships can be the Ingenuity Knowledge Base, which includes journal articles, OMIM, JAX, and curation from ClinicalTrials.gov.

[0162] Thus, the tool can associate with each biological function a predetermined number of genes whose modulation can affect the control of the biological function itself.

[0163] Examples of known hallmarks associated with pathological conditions are shown in Figures 1-4 and 8-12.

[0164] By way of example only, prominent hallmarks of OA known in the art include proliferation (development and function of the skeletal and muscular systems, e.g., joint dysfunction and joint space); inflammation; and anatomical damage. By way of further example, pertinent biological functions underlying the above hallmarks of OA may include: Growth: Biological functions of interest are the development and function of the skeletal and muscular systems, for example joint dysfunction and joint cavities, joint dysfunction, joint cavities and formation of cartilage tissue. Inflammation: Biological functions of interest are inflammatory diseases, inflammation and nociception, inflammation of the joints. Protection from anatomical damage: Biological functions of interest are biological damage and abnormalities, such as inflammation and swelling of joints, difficulty in moving joints: osteoarthritis.

[0165] Possible standard technical keywords for defining the functions are shown in Figs. 1 to 4.

[0166] Further by way of example, known hallmarks of MCI may include cognition (impaired), activation and survival (neurons, decreased), myelination and branching (decreased), inflammation (increased), skeletal and muscular system function (decreased).

[0167] Cognitive: The biological function of interest is cognition and learning; Activation and viability: The biological function of interest is development, neuronal differentiation, proliferation of neuronal cells; Myelination and Branching: The biological functions of interest are neuronal branching, neuronal sprouting; Inflammation: The biological function of interest is a chronic inflammatory disorder; Skeletal and muscular system functions: The biological functions of interest are muscle cell proliferation and muscle necrosis.

[0168] Possible standard technical keywords for defining the functions are shown in Figs.

[0169] Further by way of example, known hallmarks of OPs, including PMOs, may include mineralization, inflammation (increased), bone adipose tissue (increased), bone remodeling, osteoporosis, osteoblast differentiation (decreased).

[0170] Mineralization: The biological function of interest is mineralization of bone cell lines and osteoblasts, the formation of bone; Inflammation: The biological function of interest is inflammation of adipose, connective and white adipose tissue; Bone-adipose tissue: biological functions of interest are weight gain, transdifferentiation and adipocyte differentiation; Bone remodeling: The biological functions of interest are bone remodeling and resorption; Osteoporosis: The biological function of interest is osteoporosis itself; Osteoblast differentiation: The biological functions of interest are activation of alkaline phosphatase, osteocyte differentiation, and osteoblast differentiation.

[0171] Possible keywords linked to this function are shown in FIGS.

[0172] For each of these hallmarks, their underlying biological functions are known in the art.

[0173] For each of the biological functions, the modulation causally related to the pathological condition is also known in the art, and therefore the opposite modulation can be considered as the modulation concomitant with the desired therapeutic effect, so that a panel can be designed showing the desired modulation pattern for each of the functions, which panel represents the modulation tendency of the function in a healthy physiological state (see Figures 1-4, 8-11). Modulation in this specification contemplates the up- or down-regulation of a given function. Up-regulation refers to the modification of the activity, expression of a particular gene, protein, cellular pathway or cellular component that results in the enhancement of a given biological function. Down-regulation is the opposite of up-regulation. It involves the modification of the activity, expression of a gene, protein, cellular pathway or cellular component that results in the reduction of a given biological function.

[0174] Non-limiting examples of the modulation of biological functions causally related to pathological conditions (OA, MCI and OP, including PMO) leading to pathological conditions are shown in Figures 1-4 and 8-12.

[0175] Conversely, a healthy physiological state, referred to a pathology of interest, can therefore be designed as a counter regulation of each selected biological function. By way of example, but not limitation, the regulation leading to a healthy physiological state is shown in Figures 1-4 and 8-12 for OA, MCI and OP, particularly PMO.

[0176] If a regulation pattern resulting in a healthy physiological state is observed for each or most of the biological functions causally related to a given disease hallmark upon treatment with a given product, the product can be identified as a product with a desired therapeutic effect. Thus, a product that induces the regulation of the biological functions causally related to a given pathological condition hallmark in a direction toward a healthy physiological state can be identified as a product with a desired therapeutic effect for the overall pathological condition. If only some of the biological functions causally related to a disease hallmark match the physiological standard values ​​defined above, the product has only a partial therapeutic effect that does not meet the overall healthy physiological state.

[0177] If gene expression is selected as marker, the genes responsible for the modification of each biological function causally related to each selected hallmark of a pathological condition and their respective expression patterns can be retrieved by the skilled artisan from standard techniques, a task that can be facilitated by using ad-hoc bioinformatics tools. The same Qiagen IPA mentioned above is suitable for the rapid culling of said information from the scientific literature, since it is an aggregator of scientific literature that allows to retrieve information on genes / proteins and to build networks that predict the behavior of biological systems according to gene expression states.

[0178] The pathophysiological features (hallmarks) available in standard techniques for a given pathological condition are used to query the IPAs via the "IPA Bioprofiler" tool and can also be used as keywords to add additional keywords related to the hallmarks.

[0179] The use of the "IPA Bioprofiler" allows one skilled in the art to identify expressed genes that are causally related to each of the identified biological functions and the specific molecular pathways that support them. Information regarding the measured gene expression data induced by each batch (for example, fold change cutoffs ≦-2 and ≧+2 and p-value ≦0.05 according to the manufacturer's instructions) was then superimposed onto the resulting network to define the affected genes and the regulation of the associated biological functions.

[0180] Once the most relevant genes and their expression patterns that are responsible for the detectable alterations in the pathological state of interest for each selected biological function have been identified, for each of the genes, the expression pattern opposite to the identified expression pattern is set as the expression pattern indicative of the healthy physiological state of that biological function.

[0181] As mentioned above, the modulation of biological activity is divided into down- or up-modulation depending on the relevant gene regulation. Based on the literature, the resulting expected calculated impact on the relevant biological function can be determined by the "IPA Molecular Activity Predictor" tool (MAP) and resumed in a heatmap visualization using a color code that can be easily converted to a numerical value by the user.

[0182] Step ii) of the method of the present invention comprises ii) analyzing the modulation of each of the markers identified in i)c. induced by the gold standard of the product in the in vitro cell-based assay, determining the qualitative-quantitative modulation of each of the markers induced by the gold standard, and calculating a Z-score value of the modulation of each of the biological functions induced by the gold standard, thereby providing a gold standard cut-off Z-score value of the modulation of each of the biological functions indicative of the desired therapeutic effect.

[0183] In vitro cell-based assays are well-known laboratory techniques that involve the use of isolated cells to study biological processes or to test the effects of drugs, chemicals or other substances.

[0184] According to the invention, cell culture models such as monolayer cultures or three-dimensional (3D) stems can be used. Where appropriate, depending on the disease of interest (e.g., cancer), disease-specific cell lines can be used, and proliferation assays can also be used.

[0185] Suitable in vitro cell-based assays are, for example, assays designed to mimic a disease due to the nature of the cells used or by inducing a disease phenotype in cells treated with a specific compound, i.e., a "disease model assay" or "disease-in-a-dish" model.

[0186] Selection of cell type: A cell line or primary cell relevant to the disease being modeled is selected. As an example, when studying OA, a suitable and recognized cell-based assay is using chondrocytes, which are an art-recognized disease model for OA when treated with IL1B. Further by way of example, when studying neurodegenerative diseases, neuronal cell lines such as SH-SY5Y can be selected as primary neurons, or primary cells that can be "injured" by a given compound to induce the desired phenotype can be used.

[0187] For the study of osteoporosis, and in particular PMO, a suitable cell-based assay can be prepared by using a human adipose-derived mesenchymal stem cell line (hADMSC) capable of differentiating into osteoblasts and mineralizing the extracellular matrix (ECM), as described in the Examples.

[0188] For cancer research, viability tests can be performed in appropriate (depending on the cancer of interest) cell-based assays.

[0189] For example, if ROS scavenging activity is the selected biological function, a suitable cell-based assay can be performed using a human fibroblast (HuDe) cell line injured with a ROS generator (e.g., AAPH 2,2'-azobis-2-methyl-propanimidamide, dihydrochloride), as known in the art.

[0190] For cell-based assays where a pathological condition must be induced by injury, the assay cells can also be directly tested with the product of interest to validate that modulation of the selected biological function has the same propensity for modulation as would be expected to result in a healthy physiological state. This is particularly useful for evaluating the beneficial (homeostatic adjuvanting) effects of the product.

[0191] Cell-based assays preferably include appropriate controls, such as untreated cells, vehicle-treated cells, and cells treated with a compound known not to affect the disease phenotype. These controls help distinguish the specific effects of test compounds.

[0192] If the markers and their regulation patterns correspond to genes and their expression patterns that are responsible for the detectable alteration in a pathological state for each of the selected biological functions, transcriptomics analysis can be performed on a suitable in vitro cell-based assay representative of the pathological state of interest to identify the genes and their expression patterns that are responsible for the detectable alteration in a pathological state for each of the selected biological functions. If the disease phenotype is caused by administration of a particular agent to cultured cells, the alteration that is representative of the pathological state is the modified cells versus the unmodified cells, and the alteration induced by the gold standard is the modified cells versus the unmodified cells plus the gold standard.

[0193] Transcriptome analysis can be performed using any suitable technique known in the art, including next generation sequencing and gene expression microarrays, and the transcriptome expression profile can be evaluated in basal cells as opposed to cells treated to mimic a pathological condition to identify significantly differentially expressed genes and their expression patterns. According to the methods of the present invention, the expression patterns of significantly differentially expressed genes in cells that represent a disease phenotype versus cells prior to the injury that induces the disease phenotype are evaluated, with the opposite expression pattern being considered to represent a healthy physiological state.

[0194] If gene expression is the selected marker, for each biological function identified in i)b, the genes and their expression patterns that are responsible for the detectable alteration in the pathological condition for each of said biological functions can be identified from standard techniques using appropriate tools.

[0195] By way of example, one skilled in the art can derive this information using any suitable approach, including the use of software specifically designed for this scope, such as Ingenuity Pathway Analysis (IPA version 94302991 Qiagen).

[0196] Interpretation of high-throughput gene expression data is greatly facilitated by taking into account prior biological knowledge. This can be done using statistical gene set enrichment methods, where differentially expressed genes are intersected with gene sets related to specific biological functions or pathways (Abatangelo, L. et al. (2009) Comparative study of gene set enrichment methods. BMC Bioinform., 10, 275). Another recent approach involves the application of causal networks that integrate previously observed causal relationships reported in the literature (Chindelevitch, L. et al. (2012a) Causal reasoning on biological networks: interpreting transcriptional changes. Bioinformatics, 28, 1114-1121; Felciano, RM et al. (2013) Predictive systems biology approach to broad-spectrum, host-directed drug target discovery in infectious diseases. Pac. Symp. Biocomput., 2013, 17-28; Kumar, R. et al. (2010) Causal reasoning identifies mechanisms of sensitivity for a novel AKT kinase inhibitor, GSK690693. BMC Genom., 11, 419; Martin, F. et al. (2012) Assessment of network perturbation amplitudes by applying high-throughput data to causal networks. BMC Syst.Biol.,6,54;Pollard,J.Jr.et al.(2005)A computational model to define the molecular causes of type 2 diabetes mellitus.Diabetes Technol.Ther.,7,323-336).Although still relying on statistics, it is more powerful than gene set enrichment because it leverages knowledge of the direction of effects rather than just associations.

[0197] In a preferred embodiment, the skilled artisan can follow the protocols described in the publication "Causal analysis approaches in Ingenuity Pathway Analysis provides and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base" by Kramer et al, Bioinformatics vol 30 no 4 2014, pages 523-530 or in the manufacturer's instructions (IPA version 94302991 Qiagen). The methods and algorithms disclosed in this paper allow the skilled artisan to predict downstream effects on biological functions and diseases.

[0198] In this paper, the authors describe the causal analysis approach implemented in Ingenuity Pathway Analysis (IPA), with a particular focus on the details of the underlying algorithms and their application to several real-world use cases. In particular, points i)b. and i)c. can be easily implemented by those skilled in the art by using Ingenuity Pathway Analysis (IPA version 94302991 Qiagen), a well-known pathway analysis application among the life science research community that has been cited in tens of thousands of papers, allowing understanding the causal relationships between diseases, genes and networks of upstream regulators.

[0199] Once the desired modulation of a biological function has been defined (i.e., representative of a healthy physiological state) and the desired modulation of a relevant marker (e.g., ROS scavenging activity, genes, etc.) has been identified for the pathological condition of interest according to point i) of the method, an analysis of the selected marker modulation (e.g., in case of gene expression, transcriptome analysis) in the same in vitro cell-based assay representative of the pathological condition is performed upon treatment of the cells to determine the gold standard of the therapeutic product under test. As already revealed previously, the gold standard has a previously evaluated therapeutic or beneficial effect. The qualitative-quantitative modulation of the marker (e.g., expression of the gene of interest) induced by the gold standard is determined and the Z-score value of each modulation of the selected biological function is calculated, which is then used as the gold standard Z-score cut-off value of each modulation of said biological function that indicates said desired therapeutic effect.

[0200] The gold standard for a tested product is a batch of the product of interest whose therapeutic or beneficial effect has been evaluated in vitro or in vivo, preclinically or clinically, as described above. In either case, it is a batch of the product of interest whose therapeutic or beneficial efficacy has been previously validated.

[0201] According to the method of the present invention, the gold standard Z-score value of the modulation of each biological function obtained from the analysis performed in ii) is considered as the reference Z-score value representing the desired therapeutic or beneficial effect. As an example, if the desired modulation of the biological activity is upregulation, the cut-off Z-score value will be equal to or greater than the gold standard (reference) Z-score value, and if the desired modulation of the biological activity is downregulation, the cut-off Z-score value will be equal to or less than the gold standard (reference) Z-score value. The reference Z-score value can also be adjusted when the cell-based assay is performed with one or more reference drugs (i.e. drugs known in the art that are indicated for the treatment of the pathological condition of interest), as described below. The drugs are expected to modulate at least some of the selected biological functions in the desired direction, but due to their different modes of action (SAR), the drugs are expected to modulate only some of the selected biological functions in the desired direction. Therefore, as described in more detail below, the adjustment of the reference Z-score value, also taking into account the drug Z-score value, is only performed for those biological functions that are modulated by the test drug in the same direction as in the healthy physiological state.

[0202] The Z-score values ​​of steps ii) and iii) are calculated to represent the direction and magnitude of regulation for each biological function exerted by a given batch of products. In the case of transcriptomics, the aforementioned Z-score values ​​can be easily obtained by those skilled in the art using Qiagen's core analysis IPA version 94302991 according to the manufacturer's instructions.

[0203] If the core analysis does not provide sufficient relevant information, an alternative approach can be adopted. An example of an alternative approach is provided below (overlay analysis). Step iii) of the method of the invention comprises: iii) analyzing the pattern of regulation of the markers identified in i)c. induced by further different batches of the product in the in vitro cell-based assay and determining the qualitative-quantitative regulation of each of the markers induced by each of the batches, thereby calculating a Z-score value of the regulation of each of the biological functions induced by each of the batches.

[0204] Step iii) is performed as step ii) with different batches of the product of interest. Since at least three batches that comply and one batch that does not comply with the gold standard Z-score cutoff are desired, the skilled artisan will analyze at least four additional batches of the product of interest.

[0205] Step iv) of the method comprises: iv) comparing the Z-score values ​​of each of the adjustments of the biological functions induced by each of the batches calculated in iii) with the corresponding reference cut-off Z-scores provided in ii), and selecting at least three positive batches in which each Z-score value of each of the adjustments of the biological functions complies with the corresponding reference cut-off Z-score value, and at least one negative batch in which at least one Z-score value of each of the adjustments of the biological functions calculated in iii) does not comply with the corresponding reference cut-off Z-score value.

[0206] Batches iii) considered compliant are those in which each Z-score value obtained from the analysis of the expression patterns identified in i)c. is equal to or greater than the reference cut-off Z-score value if the desired modulation of the biological activity is an up-regulation, or equal to or less than the reference cut-off Z-score value if the desired modulation of the biological activity is a down-regulation; conversely, if at least one Z-score value calculated in iii) does not meet the above requirements, the batch is considered non-compliant and can be used as an acceptability reference for the final assessment of the acceptability spectroscopy or spectrophotometric range or cut-off.

[0207] In a preferred embodiment of the invention, additional different batches of the product of interest can be analyzed. In particular, if a batch X of the product of interest is not within the tolerance zone or acceptability cut-off defined in the method of the invention in the method of batch-to-batch validation of the invention, step iii) can be performed for said batch and if it complies with the reference Z-score cut-off defined in ii), batch X is considered to be compliant and the tolerance zone or acceptability cut-off obtained in the method of the invention can be adjusted by taking into account the compliant batch X in the subsequent steps iv), v) and vi).

[0208] Furthermore, if desired, step ii) of the above method may further comprise: analyzing the expression patterns of the markers identified in i)c. induced by one or more reference drugs for treating the pathological condition in the in vitro cell-based assay; determining the qualitative-quantitative regulation of the expression of each marker induced by each drug; and calculating a drug Z-score value of each regulation of the biological functions induced by each of the drugs. For each biological function also modified by the one or more drugs toward a healthy physiological state, the reference Z-score value may be adjusted by comparing the drug Z-score value with a gold standard Z-score value and selecting the Z-score value associated with the weakest performance as a reference cut-off Z-score value.

[0209] Because conventional drugs are expected to modulate in the desired direction only a portion of the biological functions selected for their mechanism of action (SAR), only Z-score values ​​associated with functions that are modulated in the same direction in a healthy physiological state are considered.

[0210] As known to those skilled in the art, a reference drug for treating a pathological condition may be known a priori to provide a therapeutic effect only on one or a few hallmarks of the disease, in which case the information integrated in the method of the present invention relates only to the hallmarks and associated biological functions of interest.

[0211] In a non-limiting embodiment of the invention, steps i)-iv) can be carried out using IPA version 94302991 Qiagen as follows: i) a.~c. Definition of patho-physiological state of disease and pathophysiological hallmarks of disease for standard techniques of examination of IPA The pathophysiology of the disease of interest is investigated using standard techniques using different specific sources: -Robbins&Cotran Pathologic Basis of Disease(Robbins Pathology) 10th Edition -https: / / calgaryguide.ucalgary.ca / -Biomedical literature from PubMed Central(https: / / pubmed.ncbi.nlm.nih.gov / ) The information found in the aforementioned resources can be used to identify hallmarks for IPA by following these steps: · Hallmarks are written one by one in the “Disease and Function” query box and the search is initiated. The resulting resume table allows filtering diseases / functions arising from a body of evidence. Sources of interest are the Ingenuity Knowledge Base, which includes journal articles, OMIM, JAX, and curation from ClinicalTrials.gov. In silico models are limited to genes and mRNAs.

[0212] Thus, the tool can associate with each biological function a predetermined number of genes whose regulation can affect the regulation of the biological function itself.

[0213] ii) and iii) The following applies to any step of the method of the invention of any embodiment described herein, in which an in vitro cell-based assay is performed by treating cells having a disease phenotype with a given compound, whether it is a gold standard or not, different batches of a product of interest, a reference drug, etc.

[0214] Transcriptome raw data analysis Whole transcriptome expression profiles are evaluated in in vitro cell models representing control and model cell disease. The Human Clariom™ S Pico Assay HT (Applied Biosystems, ThermoFisher Scientific) can be used on a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific) according to the manufacturer's instructions. CEL intensity files can be generated by the Affymetrix GeneChip Command Console software (AGCC, ThermoFisher Scientific). Data analysis can be performed using the Transcriptomic Analysis Console software (TAC, ThermoFisher Scientific), which provides quality control analysis, performs normalization and summarization based on the Signal Space Transformation-Robust Multichip Analysis (SST-RMA) analysis algorithm, and provides a list of differentially expressed genes (Limma Bioconductor package). This step allows the user to obtain a list of differentially expressed genes (DEGs) identified based on expression fold change relative to a relevant control experimental condition, in this case one that recapitulates the pathological situation in vitro.

[0215] The transcriptional modification profiles thus obtained are subjected to functional pathway enrichment analysis. One commercially available tool that can be used is Ingenuity Pathway Analysis (IPA version 94302991, Qiagen) [Kramer et al. (2014)]. The use of IPA allows users to estimate how and to what extent the modulation of gene expression in cellular systems (cell-based assays) affects biological functions relevant to the pathology of interest.

[0216] IPA pre-analysis filtering of transcriptional profiles (contextual data analysis) In preparation for subsequent analysis, the transcriptome profile undergoes a filtering method to identify relevant genes and their corresponding measurements. This filtering aims to select only genes that are significantly perturbed, as indicated by their fold change compared to the pathological condition. Typically (e.g., according to the manufacturer's instructions), the fold change threshold is set to encompass values ​​of ≦-2 and ≧+2, with statistical significance indicated by a p-value of ≦0.05. However, the skilled artisan has the flexibility to adjust the cutoff based on expert knowledge, taking into account the successful implementation of negative controls (samples representative of a pathological condition) or reference standards known to be able to fully or partially negate a pathological condition.

[0217] Possible methodological approaches to extract biological significance from the list of alterations in gene expression profiles via IPA can be of two types: “core analysis” and “overlay analysis of in silico models of pathophysiological conditions” (abbreviated as overlay analysis).

[0218] Thus, at this stage in the procedure, one can proceed via two different alternative options.

[0219] Core Analysis The list of differentially expressed genes (DEGs) after the gold standard or any other product batch / reference drug or other administration and the corresponding data measurements (fold change relative to the pathological state) identified in the different experimental conditions are uploaded into the application. The available identifiers are mapped to the corresponding entities in the QIAGEN knowledge base.

[0220] By initiating a "core analysis," significantly perturbed DEGs, called network-eligible molecules, are overlaid onto a global molecular network developed from information contained in the QIAGEN knowledge base. A network of network-eligible molecules is then algorithmically generated based on their connectivity.

[0221] The core analysis provides a comprehensive list of approximately the top 500 biological functions derived from the generated network. The associated biological function-genes are always supported by annotations corresponding to scientific peer-reviewed publications that demonstrate the calculated directionality and magnitude of regulation of the biological function through the automated association of Z-score [Kramer et al. (2014)]. In essence, this value represents a statistical metric that evaluates the similarity between the observed pattern of differentially expressed genes (DEGs) and the expected pattern based on the existing literature for a given annotation.

[0222] It is the responsibility of the skilled operator to carefully select the biological functions that are relevant to the particular pathology under investigation. The selection of biological functions is structured based on the identified hallmarks of the pathology of interest.

[0223] The associated Z-score values ​​are then used to indicate the direction and magnitude of regulation of each biological function.

[0224] Overlay analysis If the core analysis does not yield sufficient relevant information, an alternative approach, called "overlay analysis", can be adopted. This analysis focuses on biological functions identified by an "in silico model of the pathophysiological state". The selection of biological functions is structured based on the identified hallmarks of the pathology of interest.

[0225] An "overlay analysis" is constructed by establishing the relationship between the pattern of differentially expressed genes and the selected biological function using the following procedure (always supported by corresponding annotations in scientific peer-reviewed publications demonstrating the directionality and magnitude of regulation of the biological function): □ Import a set of selected biological functions from an in silico model of a pathophysiological state into a new sheet called "my pathway". □ Using the "build tool" and "nurture tool", we identify differentially expressed genes (DEGs) that belong to the transcriptome profile under investigation and are associated with the regulation of the biological functions selected in the previous step. □ Regulation of the identified DEGs is represented using green (indicating downregulation) and red (indicating upregulation) colors. □ To determine the predicted calculated impact of such experimentally observed modulation of gene expression on biological function activity, the "Overlay" and "Molecular Activity Predictor" tools (MAP) are used. The "Predict" function is run within the MAP tool to calculate the predicted resulting modulation of biological function, thus establishing a color coding: - Orange: Increased activity - Blue: decreased activity -White: unattainable / unpredictable

[0226] Since the "Overlay Analysis" does not directly calculate a Z-score for each biological function, but rather provides results in terms of a color indicating the direction of modification and an intensity of the color signal proportional to the magnitude of regulation of interest, it is necessary to convert the intensity of the regulation signal (graphed in the "My Pathways" tab) into a numerical value. This is achieved by converting the color intensity obtained for each biological function into a Z-score.

[0227] One possible tool that can be used for this purpose is the "IPAmap_Parser" app, a webport app of Pipeline Pilot, which aims to assign scores, called Z-scores, to genes and biological functions based on their coloring within biological pathways generated by QIAGEN's Ingenuity Pathway Analysis software. A key step of the algorithm is the conversion from the RGB color model to the LAB model (https: / / www.xrite.com / it-it / blog / lab-color-space, posted by Tim Mouw in October 2018), a colorimetric coding that allows recording not only the RGB composition but also the intensity of the color. This conversion is performed within the Pipeline Pilot "component" using a procedure written using R software based on specific features of the color space package (https: / / cran.r-project.org / web / packages / colorspace / index.html, for details see Zeileis et al 2020 journal of statistical software, doi:10.18637 / jss.v 096.i 01).

[0228] The Z-score allows for an objective comparison of the effects of different treatments.

[0229] When the above protocol is performed using a gold standard and optionally one or more reference drugs, the Z-score value obtained for each biological function modulation disclosed above is considered as a reference cut-off Z-score value for the desired modulation of that function, and thus, when the desired modulation is up-regulation, the cut-off Z-score value corresponds to equal to or greater than the reference Z-score value obtained according to the present specification, and when the desired modulation is down-regulation, the cut-off Z-score value corresponds to equal to or less than the reference Z-score value obtained according to the present specification.

[0230] If one or more reference drugs are also tested in the selected in vitro cell-based assay, the adjusted Z-score values ​​observed for the biological functions known to be adjusted by said reference drugs can be taken into account to establish the cut-off Z-score value to be used in the compliance reference, i.e. iv).

[0231] A reference drug is a drug recommended by clinical guidelines for treating the lesion or hallmark of interest.

[0232] If the reference drug modulates one or more biological functions associated with the hallmark of the pathological condition of interest, it is also tested in an in vitro cell-based assay, and both the Z-scores obtained with the gold standard and the reference drug are considered to be valid for said one or more biological functions, and thus the value associated with the weakest performance is assumed to identify the lower limit of compliance for each of said one or more biological functions and is considered as the cut-off Z-score referred to in point iv).

[0233] Step v) of the method comprises: v) performing spectroscopic or spectrophotometric analysis of the gold standard and the batch selected in iv); Non-limiting examples of spectroscopic analyses according to the present invention are near infrared spectroscopy (NIR), Fourier transform infrared (FTIR), Raman spectroscopy, spectrophotometry such as UV-VIS (UV-visible), fluorescence spectroscopy, light scattering.

[0234] In a preferred embodiment of the present invention, the spectroscopic analysis is carried out by NIR. Indeed, as the skilled person knows, NIR spectroscopy is a vibrational spectroscopy technique that provides qualitative information about the chemical species present in the analyzed material along with information about its physical state. To carry out a NIR analysis means to expose a material to light of different wavelengths and to measure the vibration of the material at each wavelength. The vibrations detected depend on the composition and the interactions between the components, which affect the vibrational ability of each component placed in the matrix. This analysis produces a vibrational footprint that is unique to the material.

[0235] The analysis of the NIR fingerprint allows the reconstruction of a chemical-physical profile characteristic of the molecular composition of each analyzed sample, influenced by its chemical environment. Indeed, the molecules in the sample can form bonds between them, especially hydrogen bonds, both inter- and intra-molecular. This leads to a change in the vibrational frequency, both stretching and bending, of the hydrogen atoms, resulting in a shift in vibrational frequency for single isolated molecules. For this reason, NIR spectroscopy can be an excellent means to characterize complex matrices. This technique is therefore particularly suitable for the analysis of natural matrices, since it provides a fingerprint of the entire matrix network and the interactions between the components of the matrix.

[0236] An example of a NIR spectral profile is shown in Figure 6.

[0237] Step vi) of the method comprises: vi) defining as acceptable a range of variation spectroscopy or spectrophotometry obtained by considering each result obtained in v) as acceptable, thereby providing said acceptable spectroscopy or spectrophotometry range.

[0238] The ranges obtained depend on the spectroscopic or spectrophotometric technique used and the product being tested.

[0239] Regardless of the spectroscopic or spectrophotometric technique used, the common feature is that each batch and gold standard selected in iv) is empirically established as a valid and acceptable product for their assessed effect on the selected biological function.

[0240] When using NIR, the acceptability cut-offs obtained with the methods of the invention are suitable for use in NIR suitability testing of batch-to-batch compliance (i.e. validation of batches for manufacturing).

[0241] Clearly, suitability testing must be performed using the same spectroscopic or spectrophotometric techniques that are used to assess the tolerance zone or tolerance cutoff.

[0242] To define the acceptability cutoff, obtain full NIR spectra of all samples and the gold standard selected in iv), align and normalize the spectra (standard normal variation), thus defining the wavelength (λ) region of interest in the spectrum, and generate an average spectrum of the spectra of all compliant (positive) samples + the gold standard.

[0243] The average spectrum obtained is Reference Spectra It becomes.

[0244] In performing NIR suitability testing of pharmaceutical API-based products, pre-processing involves the definition of the λ region of interest, as described above (SNV), and the maximum suitability index value is typically used in suitability testing and is conventionally imposed as 3.5, which means that the maximum value of standard deviation allowed for a pharmaceutical product at any point in the spectrum is typically 3.5.

[0245] Since in the method disclosed herein the tolerance range or acceptability cut-off is not based on the quality quantitative analysis of specific chemicals in the product but on the regulatory activity exerted by the product on the selected biological function, the Maximum Conformity Index (MCI) values ​​traditionally imposed in the quality control of classical APIs related to the qualitative-quantitative chemical composition cannot be considered empirically acceptable, and therefore values ​​are assigned based on the spectra of the batches selected in iv) and the gold standard.

[0246] Furthermore, Sum 2 (derived from CI but also taking into account the NIR spectrum of one or more undesired samples) is more suitable for inhomogeneous samples and is preferably used as the acceptability parameter according to the present invention.

[0247] In this embodiment of the invention, the CI (fit index) limit to which the suitability test is pre-processed corresponds to the maximum value of the CI MAX (also defined herein as the CI limit) defined by the spectra of the batch selected in iv) and the gold standard.

[0248] Therefore, according to the present invention, the acceptance range or acceptability cut-off of the spectroscopic or spectrophotometric analysis is defined based on the regulatory activity for each selected biological function exerted by the gold standard in said regulation and by batches of products conforming to the gold standard.

[0249] Thus, for NIR spectroscopy, the CI limit, i.e., the acceptability cutoff, is calculated according to the following formula: CI=(A 参照,i -A サンプル,i ) / s 参照,i During the ceremony, A 参照,i = average absorbance at a given wavelength (i) of the reference (average spectrum) A サンプル,i = absorbance at a given wavelength (i) of the test sample s 参照,i= standard deviation at a given wavelength (i) of the reference (average spectrum)

[0250] As mentioned above, for suitability tests involving heterogeneous samples, the Sum 2 parameter is more appropriate. Sum 2 = (sum of all CIs > CI limit - CI limit) / (sum of number of points in the spectrum with CI > CI limit)

[0251] The selection of appropriate parameters in suitability testing depends on the user's specific control issues, which can be easily addressed by one skilled in the art; for products that contain or consist of one or more natural matrices, i.e. highly heterogeneous samples, Sum 2 is an appropriate parameter.

[0252] In one embodiment of the present invention, the Sum 2 parameter is selected to determine the acceptability cutoff for the suitability test.

[0253] Depending on the spectroscopic or spectrophotometric method used, the tolerance range or acceptability cut-off is calculated, mutatis mutandis, by defining the tolerance values ​​obtained from the batch and the gold standard selected in iv) in the same ratios as used for NIR spectroscopy.

[0254] According to the present invention, when carrying out a method for compliance validation method (suitability testing) of one or more batches of a product comprising a complex natural system for treating a pathological condition, the batch may produce a non-compliant result in a first analysis.

[0255] It may then be of interest to validate whether non-compliance results are due to effective non-compliance of the batch with the desired modulation of biological function (i.e., therapeutic effect) or due to tolerability parameters that can be expanded and thus adjustments of said parameters can be made.

[0256] According to the method of the invention, step iii) can be repeated for said batches and, if the Z-score values ​​of each of said adjustments of said biological functions comply with the corresponding cut-off Z-score values, the tolerance zone or acceptability cut-off is corrected by defining the previously obtained non-compliant batch as compliant (recalculating the tolerance zone or acceptability cut-off).

[0257] The higher the number of compliant batches identified in step iv), the more accurate the tolerance zone or acceptability cut-off obtained with the method of the invention.

[0258] Thus, in one embodiment, according to the method of the invention, iii) is carried out on one or more additional different batches of the product of the method (e.g. one or more batches obtained in a first screening with unacceptable spectroscopy or spectrophotometry or simply additional batches in order to increase the number of acceptable batches according to step iv), one or more additional batches whose Z-score value for the modulation of each of said biological functions complies with the corresponding cut-off Z-score value, are subjected to the same spectroscopic or spectrophotometric analysis as carried out in v), and the acceptance zone or acceptability cut-off defined in vi) is recalculated by defining each of said batches as acceptable as well.

[0259] Additionally, the method may also, in any of the embodiments disclosed herein, further comprise: vii) performing spectroscopic or spectrophotometric analysis of one or more empirically undesirable batches of said product to validate that said one or more undesirable batches are not within the tolerance range or acceptability cut-off defined in iv) and are not negative (i.e. where a batch results within the tolerance range of the cut-off defined in iv); viii) defining a new, narrower variational spectroscopy or spectrophotometric range or cut-off, obtained by considering each result obtained in vii) as unacceptable.

[0260] The addition of the above steps may be desired by the product manufacturer to ensure that batches that may result from expected formulation errors from the manufacturing chain, such as missing ingredients, are pre-existing and excluded from the acceptance range or acceptability cutoff.

[0261] The present invention also relates to a method for evaluating a gold standard product for use in treating a pathological condition, comprising one or more natural matrices, the method comprising the steps of: i) d. retrieving from standard techniques a list of hallmarks for the pathological condition and one or more reference drugs for treating said pathological condition; e. identifying for each of said hallmarks a set of alterations in biological functions detectable in said pathological condition, determining the modulation of each of said functions associated with a desired therapeutic effect, and thereby designing a pattern of modulation of each of said functions that is indicative of a healthy physiological state; f. identifying for each of said biological functions markers and their regulation patterns that are responsible for the detectable alteration in said pathological condition, and for each of said markers, establishing a regulation pattern opposite to that identified as indicative of said healthy physiological condition; ii') analyzing the regulation pattern of each of the markers identified in i)c. induced by the one or more reference drugs in the in vitro cell-based assay, determining a qualitative-quantitative regulation of expression of each of the genes induced by the one or more drugs with respect to controlling the pathophysiological condition in the in vitro cell-based assay, and calculating a Z-score value of the regulation of each of the biological functions induced by the one or more drugs providing a reference cut-off Z-score value of the regulation of each of the biological functions indicative of the desired therapeutic effect; iii') analyzing the regulation patterns of the markers identified in i') c. induced by two or more different batches of the product in the in vitro cell-based assay and determining the qualitative-quantitative regulation of the expression pattern of each of the genes induced by each of the batches, thereby calculating a Z-score value of the regulation of each of the biological functions induced by each of the batches; iv') Comparing the Z-score values ​​of each of the adjustments of the biological functions induced by each of the batches calculated in iii') with the corresponding reference cut-off Z-score values, and selecting as the gold standard the batch in which each Z-score value of each of the adjustments of the biological functions provides the best performance Z-score value with respect to the corresponding reference cut-off Z-score value.

[0262] Steps i') a-c are carried out mutatis mutandis as steps a') a-c described above and in the Examples.

[0263] Also steps ii'), iii') and iv') are carried out mutatis mutandis as steps ii), iii) and iv) of the methods described above and in the Examples.

[0264] The markers and their regulation patterns described above for the method for defining the acceptance range or acceptance cut-off of a spectroscopic or spectrophotometric analysis for the validation of one or more batches of a product apply mutatis mutandis to the method for defining a gold standard. Thus, in one embodiment, the markers are genes and their regulation is their expression pattern.

[0265] Finally, the present invention provides a method for the compliance validation (i.e. quality control, compliance) of one or more batches of a product for the treatment of a pathological condition, said product comprising one or more natural matrices (as defined above) and comprising: a. performing a spectroscopic or spectrophotometric (as defined above) analysis of each batch of interest b. validating as compliant each batch whose acquired spectrum meets the acceptance range or acceptability cut-off identified according to the methods described above and in claims 1-10, using the same spectroscopic analysis technique as used to define the acceptance range for that cut-off.

[0266] Given the fact that the method of the present invention provides reliable parameters for use in the batch-to-batch validation of compliance of a product comprising or consisting of one or more natural matrices, one skilled in the art will readily understand that the method of the present invention, comprising the steps of: said tolerance zone or acceptability cut-off being calculated on a spectroscopic or spectrophotometric spectrum of a gold standard of said product, said gold standard having a confirmed homeostatic adjuvant effect in the maintenance of a healthy physiological state of said system, organ or device, and of one or more different batches of said product, said spectrum being defined as acceptable based on said gold standard and the biological activity exerted in a cell-based assay by said one or more different batches of said product for one or more biological functions underlying said healthy physiological state, may be applied mutatis mutandis to define a spectroscopic or spectrophotometric analytical acceptance zone or acceptability cut-off for the validation of one or more batches of a product adjuvanting the homeostasis of a system, organ or device of interest comprising or consisting of one or more natural matrices.

[0267] In this case, the desired adjuvantization of homeostasis in a particular system, region, device or organ can be assessed by carrying out points 1a-c of the above method, thereby evaluating the healthy physiological state of a given system, region, device or organ and using a gold standard of product that modulates selected biological functions in the same trend of the healthy physiological state.

[0268] Wherever possible in the specification and claims, the term "comprising" may be replaced with "consisting of."

[0269] The following examples are not intended to limit the invention.

[0270] example 1. Composition of the test product Arte GX (Figures 2 to 6) Centella Asiatica Dried Leaves 90% w / w Echinacea purpurea dried flowers 10% w / w Co-extraction in water Product B (Fig. 10) Melissa officinalis leaf dry extract 1% w / w Royal jelly lyophilized 1% w / w Blueberry dry extract 0.29% w / w Concentrated blueberry juice 5% w / w Apple juice concentrate 47% w / w Clarified lemon juice 0.5% w / w Honey 35% w / w Deionized water 6% w / w Malpighia emarginata juice 1% w / w Sambucus nigrum juice 2% w / w Product C Coral Calcium Powder 19.35% w / w Eggshell calcium powder 19.35% w / w Coral Calcium Citrate Powder 9.40% w / w Champignon mushroom dry extract 0.05% w / w Equisetum arvense dry aqueous extract 1.37% w / w Malpighia emarginata dry extract 1.50% w / w Sugarcane fines 48.95% w / w

[0271] 2. In Vitro Cellular Assays Representing Osteoarthritis An in vitro cell model [1-3] capable of recapitulating the characteristics of osteoarthritis was established by exposing primary human chondrocytes (HC, Cell Application INC 402K-05) to IL1B [5ng / ml] for 6 hours, followed by 24 hours to five different batches of "Arte-GX" [1.4mg / ml]: □ Batch 20B1955 (Gold Standard) □ Batch 20I1279 □ Batch 20J1770 □ Batch 20B0596 At successive moments, batch 21E1640 was also analyzed, as well as an aliquot of that batch that had been treated to induce destabilization of the product, referred to herein as batch DEST 21E1640 (see Figures 3 and 4).

[0272] Fresh IL1B [5 ng / ml] was also added to the medium each time one of the batch solutions was added.

[0273] 2.1.1. Time schedule for chondrocyte experiments The time schedule used in the experimental setup is as follows: [Table 2]

[0274] Gene expression analysis At the end of the treatment period, cells were washed with 100 μl of PBS, lysed, and collected in RLT buffer (Qiagen, 1053393) supplemented with β-mercaptoethanol (Sigma, M3148) and DX reagent (Qiagen, 19088) for gene expression analysis experiments. Total RNA was extracted from cell lysates using the QIAsymphony RNA kit (Qiagen) with a QIAsymphony SP instrument (Qiagen).

[0275] RNA quality and quantity were determined by A230, A260, A280 and A320 measurements on a Varioskan™ LUX multimode microplate reader (Thermo Scientific™). RNA integrity was confirmed using the 2100 expert_Eukaryote Total RNA Nano Kit (Agilent). Whole transcriptome expression profiles were assessed using the Human Clariom™ S Pico Assay HT (Applied Biosystems, ThermoFisher Scientific) on a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific) according to the manufacturer's instructions. Briefly, 6ng of total RNA was used to generate cDNA, and then the fragmented and labeled cDNA was hybridized to a Human Clariom S 96 array plate at 45°C for 17 hours. Arrays were washed, stained, and then scanned using a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific), and CEL Intensity files were generated by Affymetrix GeneChip Command Console software (AGCC, ThermoFisher Scientific).

[0276] Transcriptome data analysis Data analysis was performed using the Transcriptomic Analysis Console software (TAC, ThermoFisher Scientific), which provided quality control analysis, performed normalization and summarization based on the Signal Space Transformation-Robust Multichip Analysis (SST-RMA) analysis algorithm, and provided a list of differentially expressed genes (Limma Bioconductor package, p-value ≤ 0.05).

[0277] 2.1.4. Bioinformatic modelling of experimentally observed transcriptomic data For each study batch, Ingenuity Pathways Analysis (IPA) (QIAGEN\Inc., https: / / www.qiagenbioinformatics.com / products / ingenuitypathway-analysis) [4] was used to assess the modulation of gene expression associated with the desired effect.

[0278] IPA is an aggregator of scientific references that allows retrieval of information about genes / proteins and building networks that predict the behavior of biological systems according to their gene expression states.

[0279] The pathophysiological characteristics of the standard technique "osteoarthritic state" were reviewed with particular attention to the following areas of involvement: [Table 3]

[0280] This knowledge was used to explore IPA via the "IPA Bioprofiler" tool using the following keywords: osteoarthritis, arthropathy, cartilage formation, cartilage destruction, cartilage damage, connective tissue disorders, joint inflammation, immune cell trafficking, oxidative stress and hyaluronic acid.

[0281] The use of the "IPA Bioprofiler" made it possible to identify clusters of expressed genes that are causally related to each of the identified biological functions and the specific molecular pathways that support them. Information on the measured gene expression data (fold change cutoffs ≦-2 and ≧+2 and p-value ≦0.05) induced by each batch was then superimposed on the resulting network in order to define the affected genes and the regulation of the associated biological functions.

[0282] The regulation of expressed genes was shown in different intensities of blue (indicating down-modulation) or red (indicating up-modulation). Based on the literature, the resulting expected calculated impact on the relevant biological functions was determined by the "IPA Molecular Activity Predictor" tool (MAP) and resumed in a heatmap visualization.

[0283] The color and intensity were converted into a numerical value.

[0284] 2.1.5.Results The results of these tests provided a comparison of the performance and mechanism of action of five different batches of Arte GX. The analysis revealed that all batches were able to return reproducible biological effects, but it was also possible to identify batch-specific variations in the induced transcriptional patterns. Apparently, the induction of slightly different transcriptional patterns still results in the same desired regulation of biological functions. This is due to functional redundancy in the interactions between the product's components and the body, whereby, due to a multifocal mechanism of action, slightly different compositions induce the same effect (Figures 3 and 4).

[0285] Therefore, the five batches appear to have comparable biological output due to the conserved induction and repression patterns.

[0286] The different transcriptional patterns and relative biological effects of the different batches are intended as a hallmark of the inherent variability present in preparations composed of biological material. From the results summarized in Figure 4, it is clear that the observed transcriptional patterns of the five different batches induce highly reproducible biological effects, resulting in a general alteration of the pathological methodology and equivalence of the overall pathological situation of all batches reported in Figure 4.

[0287] 3.1. Targeted Metabolomics In order to understand whether the final matrix constituting "Arte GX" is characterized by matrix effects, a series of analyses were carried out on the batches reported above to characterize the product in different ways. A targeted metabolomic analysis was carried out, which allowed the identification of most of such molecular components, together with other analyses reported herein.

[0288] As mentioned above, the product consists of two plant matrices assembled to give a final new plant matrix. Several analytical techniques are used to identify and quantify compounds belonging to the main classes present in the plant. Metabolomic analysis does not contribute to understanding the dynamic changes within the components of the matrix, but it allows a "picture" of the composition at the moment the analysis is performed.

[0289] In the following analysis, individual components (plant metabolites) are specifically studied, hence the name of this analysis "targeted metabolomics". This analysis makes it possible to capture a frame on qualitative data by determining the chemical compounds present in the material, and quantitative data by defining the concentration of each compound in the material.

[0290] For ArteGX, a qualitative and quantitative characterization of as many primary and secondary metabolites as possible was performed using an “omic” approach, targeted metabolomic analysis, based on the use of multiple analytical methodologies.

[0291] The analytical methods used for the chemical characterization of each batch are described below. Based on the chemical nature of the classes of compounds present, the most appropriate analytical techniques have been adopted. Analysis by chromatographic methods combined with different detection techniques (e.g. GC and LC, each combined with a suitable detector) made it possible to identify and quantify, if necessary, the organic compounds. Inductively coupled plasma analysis using a single quadrupole mass spectrometer (ICP-MS) or an optical emission spectrometer (ICP-OES) made it possible to establish the levels of the elements present, while anions were determined by ion chromatography and a conductivity detector. Other gravimetric methods were used to determine the classes of substances not quantifiable by chromatographic methods.

[0292] The following table summarizes all the methods used. [Table 4]

[0293] The results summarized in the table below show considerable compositional variation for each batch, highlighting the impossibility of reproducing the properties of the matrix as the sum of its single components. The studies performed and reported herein (see cell-based assay results), together with the following data, demonstrate that the biological effects induced by the product cannot be reproduced by the sum of the effects induced by the single molecular components, but are the result of the interconnections and interactions between the components: matrix effects. This leads to the impossibility of formally defining the structure-activity relationship (SAR) according to the principles standardly applied for APIs. [Table 5-1] [Table 5-2] [Table 5-3] [Table 5-4] [Table 5-5] [Table 5-6] [Table 5-7] [Table 5-8]

[0294] The results show significant quantitative variations of the individual chemical classes in the five batches of co-extracts. These variations, when considered as reference parameters, lead to the empirical observation that these batches have different biological activities, eliminating those that do not compare to the gold standard. If the criteria applied are those valid for APIs acting via the key-lock paradigm, due to the presence of clear SAR. The analysis reported here argues against the fact that none of the single molecular components identified adheres to the criteria set for a single API, despite the biological activity being maintained across all the different batches evaluated, thus demonstrating that the matrix should not be considered as a compilation of APIs.

[0295] As noted above, biological activity is preserved from batch to batch.

[0296] Thus, Figure 5 shows that it is not representative and therefore incorrect to rely solely on the quantitative analysis of the individual components to estimate the reproducibility of the activity profile of a complex matrix. Indeed, considering the very nature of a complex matrix, qualitatively different chemical profiles that should be considered different from a chemical point of view instead provoke the same reaction in a biological system that is relevant for the intended application. This is not a surprising observation, but it is another proof that the biological activity of a complex matrix cannot be traced back to the sum of the activity of each single molecule in the matrix itself (i.e., from a chemical point of view). Thus, the activity of a matrix does not depend exclusively on the identity and amount of the molecules that make up the matrix.

[0297] This also highlights the fact that there are both structural and functional redundant mechanisms that give the matrix a particular resilience, i.e., the ability to mediate the same activity for quantitative compositions of different quality, as shown above. In other words, the study of the matrix from an exclusive molecular point of view is incorrect, since the identity of its individual components does not reflect its characteristics. This confirms the need for methods that can describe the intrinsic properties of the matrix, rather than looking only at its molecular components. These methods, as provided in the present invention, should monitor the preservation of parameters on which the maintenance of biological activity actually depends.

[0298] 3.2.Near infrared spectroscopy (NIR) Introduction To generate control charts and provide NIR acceptability cutoffs, four batches of ArteGX (including the gold standard) made on a prototype and industrial scale, selected as positive batches according to the method of the invention, steps i) to iv), were analyzed to form a library of good quality samples (training set). The batches used to build the training set were selected after passing suitability tests performed through the biological assays of the invention (see also the examples above).

[0299] A library was defined and a batch of Arte GX DEGR 21E1640 selected as a negative batch according to the method of the invention, steps i) to iv), was also analyzed.

[0300] Five batches were used to set the NIR tolerance parameters.

[0301] The acceptability parameters were defined and two formulations of insufficient quality defined above as test samples (R19L4299 and R19L4298) as well as an unknown ArteGX batch (21E1640) were analyzed using the same operating method. According to the results obtained after the analysis by suitability testing, the test samples are confirmed to be of good quality or not, depending on whether they pass or not the suitability tests carried out via biological assays to confirm or possibly correct the acceptability criteria identified by the control cards.

[0302] The objective of this pilot study was to construct a NIR spectral control map, defined a priori by the assessment of the suitability of the biological activity of the batches of which it is a part, as a fingerprint used to identify valid compliant batches of Arte GX from samples of insufficient biological and / or formulation quality.

[0303] Below is a list of the four batches used to create the NIR library and a list of the samples analyzed in the study. Lyophilize 4 batches of Arte GX (tab 1) for library construction □One low quality batch of Arte GX (low biological activity quality) □ 1 batch of Arte GX (Table 2 without corner brackets) freeze-dried as library test □ Two prescription quality defects (Table 2 without brackets) [Table 6] [Table 7]

[0304] 3.2.2.Equipment Bruker NIR Spectrometer, Model MPA (Multipurpose Analyser): ·Resolution: 16cm-1 Wavenumber reproducibility: better than 0.04 cm-1 Wavenumber accuracy: better than 0.1 cm-1 ·Photometry accuracy: 0.1%T Wavenumber range: 4000~12500cm-1 Background Scan: 64 Scans for sample acquisition: 64

[0305] 3.3.Statistical tests Compliance Testing Compliance testing is a simple method to test the deviation of a measured NIR spectrum within a certain range. To set these limits (acceptability cut-offs), it is necessary that samples of good and bad quality belong to at least one batch or manufacturing cycle of the final product, which is identified as the reference spectrum. According to the invention, the reference samples are identified by biological assays (cell-based assays) considered appropriate (steps i)-iv of the method of the invention) and are tested and studied by NIR to evaluate the minimum range of the specification, including the batch itself. According to the invention, this range is imposed as acceptable to recognize whether a batch of unknown conformity is compliant or not. The NIR spectra of these samples reflect the different variations of the samples that can achieve compliant and non-compliant performance in terms of biological activity and form a confidence band within the spectral range. To pass the NIR conformity test, the spectrum of the new sample must fall within this confidence band. First, the mean and standard deviation of the absorbance values ​​for each wavelength (i) must be calculated. The mean value + / - standard deviation determines the confidence band within the spectral range and defines how much variation is acceptable for the analyzed product across each spectral wavelength.

[0306] Secondly, it is necessary to check whether the spectrum of the sample to be tested is within a confidence band defined within the spectral range. The difference between this sample and the mean of the reference samples is calculated at each wavelength (i). This absolute deviation is then weighted by the corresponding standard deviation "s" of the respective wavelength, resulting in a relative deviation called the Conformity Index (CI). CI=(A 参照,i -A サンプル,i ) / s 参照,i A 参照,i = average absorbance at a given wavelength (i) of the reference (average spectrum) A サンプル,i = absorbance at a given wavelength (i) of the test sample s 参照,i = standard deviation at a given wavelength (i) of the reference (average spectrum)

[0307] In conformance testing, other parameters can be used to apply CI limits and evaluate the test against a reference library.

[0308] This parameter, called Sum 2, is represented by: Sum 2 = (sum of all CIs > CI limit - CI limit) / (sum of number of points in the spectrum with CI > CI limit)

[0309] The selection of appropriate parameters in suitability testing depends on the user's specific control issues, which can be easily addressed by one skilled in the art; for products that contain or consist of one or more natural matrices, i.e. highly heterogeneous samples, Sum 2 is an appropriate parameter.

[0310] Therefore, in this case, the Sum 2 parameter was chosen to determine the pass / fail cutoff for the suitability test.

[0311] 3.3.1 Sample preparation Each sample was transferred to a sample holder suitable for NIR analysis of heterogeneous solids, ensuring that the bottom of the sample holder was completely covered prior to analysis.

[0312] 3.3.2 Sample acquisition To ensure high reproducibility of the data, NIR spectra were acquired in reflectance mode using a rotating sample holder suitable for the analysis of heterogeneous solid and powder samples.

[0313] Quality control and background subtraction were performed before each acquisition.

[0314] Samples also reported in the previous tables (tabs 1 and 2) were prepared as described above and analyzed by NIR.

[0315] Data Preprocessing Preprocessing is a mathematical operation to extrapolate spectral features and reduce sources of variation.

[0316] For the development of the reprocessing method, a preprocessing method including the use of SNV normalization was selected as the 4200–9000 cm -1 This region of the spectrum was selected as the most relevant region of the spectrum for the model.

[0317] The compatibility tests were performed using OPUS software (Opus 8.5, Bruker).

[0318] By applying the pre-processing method, the following parameters in the OPUS suitability index method were set: a) Pretreatment: SNV; b) Area: 4200~9000cm-1; c) Conformance test parameters: Maximum conformance index value; Sum 2 Data Acquisition

[0319] The four batches shown in Tab I / 1 as well as the batch in Tab I / 2 were analyzed.

[0320] The four batches in Table I / 1 above were used as reference spectra in generating the compatibility index (CI) since they had the desired biological activity.

[0321] SNV normalization preprocessing was performed, and the 4200-9000 cm -1 The region was selected for data reprocessing. The CI MAX threshold and Sum 2 values ​​for the batch of cards are shown below: [Table 8]

[0322] As above, the maximum fitness index value is assigned based on the maximum CI MAX value defined by training consisting of compliant (fit: positive) samples from the cell-based assay. From the initial data (reported above), the CI limit was set to 1.5 and therefore this value was used to calculate the Sum 2 for the training and test sets.

[0323] To define the suitability limits for Sum 2, negative batches of the method of the present invention (i.e., non-compliant (not compatible) with biological data (cell-based assay) according to steps i) to iv) DEST 21E160 were tested against the control chart. The following table shows the results for CI and Sum 2 for each batch. [Table 9]

[0324] Based on the Sum2 value of batch DEG 21E1640 and its non-compliance with the cell-based assay, the threshold Sum2 value for defining a batch as non-compliant is therefore set at ≦1.2. Once this acceptability cutoff was set according to the method of the present invention, new unknown batches of Arte GX and known non-compliant batches were tested to validate the reliability of the method of the present invention and its suitability for the quality control method according to the specification and claims. [Table 10]

[0325] Thus, batch 21E1640 was compliant in the validation method of the present invention with the NIR assay using the acceptance cutoff evaluated in the method of the present invention.

[0326] To validate the validation method of the present invention, the modulation of the biological functions identified for the above-mentioned product Arte GX was also carried out for batch 21E1640, which showed a conformity with the reference Z-score according to steps ii) to iv) of the method of the present invention.

[0327] Thus, approaches and methods have been identified that make it possible to define criteria for the acceptability of a product, comprising or consisting of one or more natural matrices, and that are based on the preservation of a number of selected biological activities, without taking into account the notion of its composition at the molecular level.

[0328] 4. Radical scavenging activity As an additional control for the validity of the method and method of the present invention, all the above Arte GX batches were also tested for their radical scavenging activity, which is known to have a significant promoting effect on bone formation. Figure 12 summarizes the significant hallmarks and biological functions associated with this marker.

[0329] 4.1. Assay Method The assay uses the human fibroblast (HuDe) cell line, which is a model for testing the ability of products to have antioxidant activity through scavenger activity.

[0330] Five different batches of Arte GX were tested, with a concentration of 1.4 mg / ml, calculated by applying a dilution factor of 2.8 to reflect the product dilution in synovial fluid in an in vivo scenario.

[0331] The ROS scavenger activity test is based on the use of the reactive oxygen species (ROS) generator AAPH (2,2'-azobis-2-methyl-propanimidamide, dihydrochloride), which can simulate the appearance of exogenous pro-oxidant damage and thereby induce the production of endogenous ROS. The fluorescent probe 6-carboxy-2',7'-dichlorodihydrofluorescein diacetate (H2DCFDA, Life Technologies) was used as an indicator of the presence of ROS in cells. The fluorescence emission of H2DCFDA was measured at regular time intervals (every 10 min for a total of 90 min) using a fluorometer (Varioskan Lux, Thermo-Scientific) and quantitatively correlated with the production of free radicals in cells. To account for cell number at the end of the assay, all calculated fluorescence values ​​are normalized with respect to the associated cell viability measured by the MTT (tetrazolium salt, [3-(4,5-dimethylthiazol-2yl)-2,5-diphenyltetrazolium bromide, Sigma Aldrich) assay performed according to the manufacturer's instructions. The degree of protection from the generation of ROS offered by the tested products is compared to that obtained by protecting the cells with ascorbic acid (considered the benchmark of antioxidant molecules). The results are shown as a comparison of the integrated area under the fluorescence versus time curve (AUC) calculated for AAPH (considered 100% of ROS production).

[0332] 4.2.Results Figure 7 shows equivalent radical scavenging activity of all five batches of Arte GX. All batches show equally significant protective effect on fibroblast cells.

[0333] The above data provide further qualitative assurance that the five batches are equivalent with respect to induction of the same biological effect due to effects on gene expression as well as radical scavenging activity.

[0334] The percentages (Z-scores) were calculated as in FIG.

[0335] All batches complied with the Z-score values ​​specified for the gold standard, thus providing validation that the NIR cut-offs calculated as above are appropriate for the approach and method of the present invention using different markers for monitoring the regulation of selected biological functions.

[0336] 4.Isotope abundance (ABUNDANCE) Introduction The analysis of isotopic abundance is a method of describing a substance in terms of atoms. The isotopic distribution that characterizes the starting material can be affected by phenomena of different nature, which can result in significant variations in the final product [ISPRA, Quaderni-Laboratorio 2 / 2018. ISBN 978-88-448-0873-0]. The isotopic composition of a sample is equal to the ratio between the abundance of heavy isotope forms and the abundance of light isotope forms (for example, the relationship 13C / 12C) and is expressed as deviations per thousand parts from an internationally identified standard reference material. A positive value of δ indicates that the heavy isotope is enriched in the sample compared to the standard, while a negative value indicates that the heavy isotope is depleted in the sample.

[0337] The significant difference in the isotopic abundance of the sample compared to a sample known to be of good quality can be explained by different intra- and intermolecular interactions between the phytochemical classes that make up the matrix. There is no need to take into account the quantitative profiles and different chemical reaction kinetics of the individual species. In the first case, this phenomenon is defined as the geometric isotope effect (GIE) and is due in particular to hydrogen bonds. In fact, the length of the hydrogen bond with oxygen is smaller than the length of the hydrogen bond between deuterium and oxygen. This can involve different structural rearrangements, both intra- and intermolecular.

[0338] Isotope abundance also alters the kinetics of a reaction, known as the kinetic isotope effect (KIE). The effect can be either first order or second order, depending on whether the isotope alters the product reaction to make it faster or slower than the process of interest. It is therefore clear that the KIE establishes a link between the abundance of a given isotope in a substance and its ability to interact in a reproducible manner with biological systems. Therefore, the analysis of isotope abundance is a possible tool for monitoring the suitability of a product from a physicochemical and potentially biological point of view.

[0339] Changes in isotopic abundance in a batch can indicate impurities, poor product quality, etc. Considering samples representing different intermediates that arise during the manufacturing process may indicate a total loss of an isotope in its desired natural conformation.

[0340] In this context, the acquisition of several good quality batches of a product, together with established suitability validation techniques such as NIR, could lead to the generation of a reference library against which individual batches can be assessed and the isotopic reproducibility validated within established limits.

[0341] Furthermore, the 14C activity assessment allows the system to be defined as 100% natural, since 14C is an unstable isotope (half-life 5730 years) and therefore petroleum derivatives have a very low presence or absence of this unstable carbon isotope, but it easily accumulates in biological materials.

[0342] 4.1.1. Results and Discussion Isotope abundance analysis was performed on five batches that were included in the NIR method development and validation and therefore constituted the good quality batches (20B0596, 20B1955, 20I1279, 20J1770, 21E1640), with batches 20B0596, 20B1955 being prepared from different batches of starting material with respect to batches 20I1279, 20J1770, 21E1640.

[0343] Samples were sent to Chelab (a Tentamus Company) laboratory and tested for stable isotopes as follows: -δ18O: Method IRMS, UNIT‰ V-SMOW. -δ13C: Method QMA-M-01, EA-IRMS, UNIT‰V-PDB. C14-activity was also tested: -14C activity: Method ISO-16620-2;2015 (AMS), unit % modern carbon (pMC).

[0344] The results were as follows: [Table 11]

[0345] (The values ​​in the table above include percentage errors due to the formula method used) The measured C14 activity of the Pmc samples corresponds to that of material from pure bio-based carbon. There is no evidence of synthetic sources in the analyzed material. The C14 activity values ​​overlap perfectly between batches, as they are not affected by the biological variability of the starting material, thus identifying a high reproducibility of the production method according to the conservation of this parameter.

[0346] Two batches of co-extract (20J1770 e 21E1640) were tested to study the isotope abundance during different stages of production.

[0347] The results are described as reported in the table below showing the δ ratios of major isotopes of co-extracted Centella echinacea crude plant material plant parts. [Table 12]

[0348] Evaluation of the isotopic abundance of the material along the preparation process shows that the preparation process does not change the abundance ratio, thus demonstrating the fact that the process preserves the natural biophysical properties of the starting material.

[0349] Analysis of the batches studied showed substantial similarity in values ​​and furthermore maintenance of ratios during the manufacturing process. This result was in agreement with the NIR results mentioned above. Therefore, all batches were deemed similar and merged without considering outliers for similar spectra.

[0350] 5. RNA evaluation in manufacturing intermediates Biophysical characterization of biological plant material includes evaluation of the biological material in its manufacturing intermediate state.

[0351] "RIC 199 EL 0, extract_BLEND CENT_ECH EL, batch R 20 I 4716" corresponds to the production intermediate of Arte GX, i.e. Centella Asiatica and Echinacea aqueous co-extract, in the proportions shown in Example 1, before ultrafiltration. The presence of RNA has been assessed both quantitatively and qualitatively. RNA was extracted using a plant matrix specific kit (RNeasy PowerPlant kit) after homogenization using QIAshredder columns before proceeding with the kit extraction protocol. Size distribution of the obtained RNA was performed using a Bioanalyzer 2100 equipped with an RNA 6000 Nano, an RNA 6000 Pico and a small RNA kit.

[0352] In FIG. 13, electropherogram "A" shows the size distribution of total RNA, and electropherogram "B" shows the size distribution of RNA between 4 and 150 nt.

[0353] Nucleic acid digestion was then performed using the New England Biolabs Nucleoside Digestion Mix Kit to quantitatively assess the total RNA extracted from the samples. RNA concentrations were expressed as total nucleosides by UHPLC-qToF analysis. The following table reports the RNA expressed as total nucleosides. [Table 13]

[0354] These observations not only provide a method for validating the biological origin of the matrix, but also provide an additional degree of information, both structural and functional complexity, that should be taken into account in product management.

[0355] For purposes of quick reference and comparison, the experimental protocols used for the three different products described in Example 1 are summarized in the table below. [Table 14] [Table 15-1] [Table 15-2]

[0356] 5. Conclusion In summary, the data reported herein make it possible to identify acceptability parameters that are key to guarantee the quality of the manufacturing process of a product that contains or consists of one or more matrices of biological origin (natural matrices). Interestingly, the data show that monitoring the reproducibility of the composition at the molecular level alone does not lead to a profitable strategy, since it ignores important features of the matrix that affect its ability to induce reproducible effects when used to treat biological systems. The inference is that, due to the existence of redundant effects between molecular components at both the structural and functional levels, and the existence of a network of physical and functional interactions within a complex matrix, the biological activity of the product depends more strongly on features that are appropriately monitored than by analyzing carefully selected biophysical properties of the matrix.

[0357] Moreover, using only targeted metabolomics data, without other data, can hinder the evaluation of the ability of different batches of the same product to induce reproducible biological effects (see Figure 5 vs. Figures 3 and 4). This is especially true when judged according to the principles usually reserved for a single API. Applying targeted metabolomics alone would erroneously identify the batches as unacceptably different from each other. In contrast, applying techniques and methods that monitor matrix features that are explicit and derived from a network of interactions and therefore different or only partially common to methods that rely on single molecular components, as disclosed herein, allows a sufficiently accurate identification of similarities between the different analyzed batches, consistent with the fact that they do indeed induce reproducible desired biological effects.

Claims

1. 1. A method for defining tolerances of a spectroscopic or spectrophotometric spectrum for validation of one or more test batches of a product, comprising: The product is a product for the treatment of a pathological condition comprising one or more natural matrices, the method comprising the steps of: (a) performing at least one in vitro cell-based assay on a reference standard of said product and said one or more test batches of said product, wherein the reference standard is known to have a therapeutic effect for the treatment of said pathological condition, and wherein results from the cell-based assay are indicative of modulation of a biological activity associated with one or more hallmarks of said pathological condition; (b) quantifying as a Z-score the results from the cell-based assay for the modulation induced by each sample tested in each step (a); (c) defining as acceptable a Z-score of one or more test batches inducing modulation of each of the biological activities in the cell-based assay that is: (c-1) in the case where the regulation of the biological activity is up-regulation, the Z-score is equal to or greater than that of a reference standard; or (c-2) in the case where the regulation of the biological activity is down-regulated, the Z-score is equal to or less than that of a reference standard; and defining as unacceptable a Z-score of one or more test batches that induces a modulation of at least one of said biological activities in said cell-based assay that is smaller than the Z-score of a reference standard in case of up-regulation of said biological activity, or defining as unacceptable a Z-score of one or more test batches that induces a modulation of at least one of said biological activities in said cell-based assay that is larger than the Z-score of a reference standard in case of down-regulation of said biological activity; (c') comparing the Z-scores quantified for the one or more test batches in step (b) with the acceptable Z-scores defined in step (c) to select at least three acceptable test batches; (d) performing spectroscopic analysis or measurements on said reference standard and said at least three acceptable test batches; and (e) defining a spectroscopic or spectrophotometric spectral tolerance as the variability of the spectroscopic or spectrophotometric spectrum based on the spectroscopic or spectrophotometric spectra of the at least three acceptable test batches and the reference standard defined as acceptable based on Z-scores in step (c), wherein the variability is a range that encompasses the spectroscopic or spectrophotometric spectral values ​​of the at least three acceptable test batches.

2. 1. A method for defining tolerances of a spectroscopic or spectrophotometric spectrum for validation of one or more test batches of a product, comprising: The product is a product for the treatment of a pathological condition comprising one or more natural matrices, the method comprising the steps of: (a) performing at least one in vitro cell-based assay on a reference standard of said product, wherein the reference standard is known to have a therapeutic effect for the treatment of said pathological condition, and performing an in vitro cell-based assay on a reference drug for the treatment of said pathological condition; provided that the results from the cell-based assay are indicative of modulation of a biological activity associated with one or more hallmarks of said pathological condition; (b) performing at least one in vitro cell-based assay on said one or more test batches of said product; (c) quantifying as a Z-score the results from the cell-based assay for the modulation induced by each sample tested in each step (a) and (b); (d) defining as acceptable a Z-score of one or more test batches inducing modulation of each of the biological activities in the cell-based assay that is: (d-1) in the case where the regulation of the biological activity is up-regulation, the Z-score is equal to or greater than that of a reference standard; or (d-2) in the case where the regulation of the biological activity is down-regulated, the Z-score is equal to or less than that of a reference standard; and defining as unacceptable a Z-score of one or more test batches that induces a modulation of at least one of said biological activities in said cell-based assay that is smaller than the Z-score of a reference standard in case of up-regulation of said biological activity, or defining as unacceptable a Z-score of one or more test batches that induces a modulation of at least one of said biological activities in said cell-based assay that is larger than the Z-score of a reference standard in case of down-regulation of said biological activity; (d') comparing the Z-scores quantified for the one or more test batches in step (c) with the acceptable Z-scores defined in step (d) to select at least three acceptable test batches; (e) performing spectroscopic analysis or measurements on said reference standard and said at least three acceptable test batches; and (f) defining a tolerance value for the spectroscopy or spectrophotometric spectrum as the variability of the spectroscopy or spectrophotometric spectrum based on the spectroscopy or spectrophotometric spectra of the at least three acceptable test batches and the reference standard defined as acceptable based on Z-scores in step (d), wherein the variability is a range that encompasses the spectroscopy or spectrophotometric spectral values ​​of the at least three acceptable test batches.

3. 3. The method of claim 2, further comprising determining biomarkers and / or patterns of regulation of biomarkers in both healthy and pathological conditions associated with one or more hallmarks of the pathological condition treated with the product.

4. The method of claim 3, wherein the biomarkers and / or patterns of regulation of the biomarkers correspond to genes and their expression patterns detectable in the pathological condition for each result obtained from the cell-based assay.

5. The method of claim 1 , wherein the product is dried or freeze-dried.

6. performing a spectroscopic or spectrophotometric analysis on one or more known unacceptable batches of said product to confirm that said one or more unacceptable batches do not exhibit a spectrum within the acceptable range; The method of claim 1 further comprising:

7. 2. The method according to claim 1, wherein the product comprises or consists of one or more of the following: chopped or crushed plant parts, plant extracts, fractions of said extracts, such as fractions obtained by filtration on semi-permeable membranes (microfiltration, ultrafiltration, nanofiltration) or by treatment with adsorption resins, or microorganisms, honey, propolis, silk, wax, plant resins, plant gums, plant exudates, plant oils, plant essential oils, animal tissue lysates or plant or animal fluids.

8. 2. The method of claim 1, wherein the pathological condition is osteoarthritis, mild cognitive impairment, postmenopausal osteoporosis, or cancer.

9. 2. The method of claim 1, wherein the spectroscopic analysis is selected from NIR, FTIR, and RAMAN, and the spectrophotometric analysis is selected from UV-Vis spectroscopy, fluorescence spectroscopy, and light scattering.

10. 1. A method for compliance validation of a test batch of a product for use in the treatment of one or more pathological conditions, said product comprising one or more natural matrices, the method comprising the steps of: (a) performing a spectroscopic or spectrophotometric analysis of each test batch; (b) validating as compliant each batch whose resulting spectra meet the acceptance range or acceptability cutoff identified according to the method of claim 1; A method comprising:

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