Method for defining acceptability values of spectroscopy or spectrophotometry spectra for validation of one or more test batches of product

Abstract

To provide validation of natural matrices for therapeutic use on humans, animals and plants on biophysical bases as an alternative to validation through chemically definable substances derived from the matrices by isolation and / or synthesis processes, and also as an alternative to products comprising natural matrices validated on the basis of their traditional use.SOLUTION: The present invention relates to a new method for defining acceptability values or acceptability cutoffs for the compliance validation of batches of products comprising or consisting of one or more natural matrices, the products having confirmed therapeutic or beneficial effects. The present invention also relates to a new process for the compliance validation of one or more batches of the products.SELECTED DRAWING: None

Description

Technical Field

[0001] The present invention relates to a new batch control method for products containing or consisting of mixtures of natural or vegetable matrices, wherein the products are characterized by the fact that one or more of the matrices themselves exhibit characteristic emerging properties that are different from those represented by the sum of the properties of their individual components.

Background Art

[0002] In particular, in the context of health and safety issues, the historical concept of patenting for the public good has its origins over many centuries. The underlying principle is that while a patent provides the inventor with a temporary monopoly on their invention, the ultimate goal is to serve the greater benefit of society.

[0003] In modern times, this historical concept is reflected in the various legal regulations and policies that govern patents. The inventor emphasizes the understanding that while the inventor deserves recognition and protection for their contribution, society as a whole should ultimately benefit from these technological innovations, particularly in areas important for public health and safety.

[0004] In other words, the humanitarian basis of the patent system lies in its goal of striking a balance between promoting technological innovation and ensuring that the benefits of that innovation are shared for the improvement of society as a whole. In particular, the patent system should ensure the sharing of knowledge and the promotion of progress within the above scope.

[0005] In particular, the patent system can play an important role in addressing humanitarian and global challenges. For example, it can encourage the development of sustainable pharmaceuticals, environmentally sustainable technologies, and solutions to pressing problems such as clean energy and water scarcity.

[0006] From the beginning of the 16th century to the present, especially in the fields of medicine and beneficial products, it has been possible to standardize and thus validate only artifacts manufactured by chemically definable chemical methods.

[0007] This path has proven to be highly reductionist and of great value, enabling the eradication of many diseases in the past five centuries, but now facing its limits, which stem from the foreign nature of chemical substances and the life methods.

[0008] Regarding the development of new sustainable pharmaceuticals, it is now also confirmed that artificial (especially chemically synthesized) therapeutic products have harmful effects on biodiversity and the natural immune system.

[0009] It is well known that synthetic APIs can enter the ecosystem through various routes, mainly through the discharge of pharmaceutical waste from manufacturing plants and the improper disposal of unused or expired drugs. This can lead to the bioaccumulation of artificial and persistent substances in aquatic and terrestrial organisms, disrupt the food chain, and pose a threat to biodiversity.

[0010] Studies have shown harmful effects on aquatic organisms, such as changes in behavior, reproduction, and even mortality, as a result of exposure to synthetic APIs. (Boxall, A.B. et 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, R.H. (2015). Tysklind, M. and Larsson, D.G.J. (2015). Predicted critical environmental concentrations for 500 pharmaceuticals. Regulatory Toxicology and Pharmacology, 73(1), 607 - 616.)

[0011] Many synthetic APIs are designed to be biologically active and particularly stable, and as a result, it is well known that they may prevent their natural degradation methods. As a result, these molecules can persist in the environment for long periods and may accumulate in soil and water. This reduction in biodegradability raises concerns regarding long-term environmental impacts and the potential for 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, concerns are growing about the potential impact of synthetic APIs on the immune systems of humans and animals. Some pharmaceuticals have been found to directly or indirectly interfere with immune function, leading to changes in immune responses or increased susceptibility to infection, which can have significant implications 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, E.J., & Baldwin, L.A. (2003). Toxicology rethinks its central belief. Nature, 421(6924), 691 - 692].

[0013] In conclusion, while synthetic APIs have undoubtedly contributed to healthcare progress, their environmental and health impacts should be carefully considered. Efforts to develop more environmentally friendly pharmaceuticals, improve waste management, and monitor environmental pollution are important steps in reducing these concerns.

[0014] In addition, natural molecules within natural matrices, while chemically similar to their synthetic counterparts when isolated, may have different fingerprints with respect to their synthetic analogs due to completely different synthetic routes regarding primary metabolites, reactants, reaction temperatures, energy sources, catalysts, etc., and it should be noted that this may potentially affect their physicochemical behavior and reactivity, and thus their biological activity.

[0015] According to the traditional paradigm, from the perspective 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), which is notably identified in essential oils such as those essentially derived from Ocimum basilicum and Artemisia dracunculus, is known in the art for its potential aromatic and pharmaceutical uses. The molecular constitution and related energy states of estragole have been the subject of intense scientific scrutiny depending on its origin. The traditional view assumes uniform molecular attributes, but closer examination suggests subtle differences.

[0016] Considering this premise, estragole should ideally match in its intrinsic physicochemical attributes whether procured from plant sources by distillation or synthesized in the laboratory.

[0017] However, differentiating the production route is of utmost importance. In the plant matrix, the biosynthesis of estragole is orchestrated by a series of enzymatic reactions that start from primary metabolites and end with this specific secondary metabolite. Each of these enzymatic conversions is known in the art to act within different energy landscapes and potentially impart unique energy states to the molecule.

[0018] Conversely, the laboratory synthesis of estragole is governed by chemical reactions that are manipulated by different precursors and conditions (e.g., temperatures not compatible with plant life). The energy mechanics of such synthetic routes, governed by the thermodynamics and kinetics inherent to the reactions, are likely to deviate from the plant-mediated enzymatic route.

[0019] Furthermore, it is clear that the isotope abundances resulting from two different pathways (natural and synthetic) are unlikely to be the same. Even slight variations in isotope abundances are known to have a tangible impact on 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]. Considering the possible isotope differences between plant sources and synthetic reagents, the estragole molecules obtained are likely to have differential energy imprints and biological activities. In light of the above, it is reasonable to assume that molecules that are chemically similar but from natural and synthetic origins may have distinct energy fingerprints that potentially affect their physicochemical properties, reactivity, and thus their biological activities. Indeed, differences between the activities of synthetic estragole and natural estragole have been reported in the art (Suzanne M. F. 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] Furthermore, synthetic molecules (intended as molecules obtained by manufacturing carried out by humans through chemical synthesis laboratories / industrial methods) are designed to provide a desired interaction with a specific given target molecule, and this design does not take into account all the interactions that the molecule may have and will have within the natural matrix, environment, and the entire receptive network of the organisms in which they are used. On the other hand, natural biosynthetic molecules produced in a natural non-artificial environment exist in epigenetically determined competitions whose explanations are inaccessible when conventional deterministic chemical approaches are used, and they have essentially all the essential characteristics in order to perform their functions. Applying quantum biology can provide a possible decoding of the natural matrix and biosynthetic molecules.

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

[0022] As a result, research in the field of life sciences has come to the conviction that it should target substances that can be chemically validated using data such as the amount of individual substances at the molecular level and that can generate very powerful and effective artificial products using linear kinetics. This direction has also now become clear that it has harmful effects on biodiversity and the natural immune system.

[0023] In particular, it is one of the major difficulties for technology that products derived from natural sources, which are prepared by humans but consist mainly or solely of components derived from natural raw (starting) sources, i.e., 100% of non-artificial substances, cannot be standardized, which has opened the door to the current API-based pharmacological approach to ensure batch-to-batch validation of products derived from natural sources intended for medical or beneficial use.

[0024] As an example, natural matrices such as plant matrices are complex systems characterized by a number of molecular components belonging to different phytochemical classes that already interact with each other within the plant to determine the biology of the plant. This interaction continues during the processing stage, and different processing techniques affect the post-treatment interaction of the components. These compounds can interact at functional and structural levels. The supramolecular aggregates that result in both structural and functional networks, as well as their chemo-physical and structural properties, are dynamic interactions that can be regulated by environmental conditions, and as expected, these interactions affect the reactivity of the individual components, resulting in so-called "matrix effects" that give rise to properties typical of a distinct entity represented by the matrix, different from the sum of the properties of its single molecular components. Such properties are defined as "emerging properties". This phenomenon has been particularly described for organisms that have the driving force to self-assemble and self-organize to form supramolecular complexes and is the cause [Jean-Marie Lehn Toward complex matter: Supramolecular chemistry and self-organization. PNAS, 2002, 99(8) 4763-4768 https: / / doi.org / 10.1073 / pnas.072065599This inherent complexity results from the fact that the individual molecules within the natural matrix cannot be considered to be contained within isolated and fixed packages, as non-covalent and dynamic interactions continuously occur between them. Such interactions are both intra- and intermolecular, occurring both between molecules of the same type and between molecules belonging to different chemical classes. This introduces the need to consider that the ability of the natural matrix to exert therapeutic activity in the human body depends not only on the qualitative-quantitative composition of the matrix, which itself tends to be variable, but also on the existence 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 regard, it is clear that the classical validation of therapeutic products based on the structure-activity relationship (SAR), which is the most relevant relationship in the classical pharmacological activity between a pharmaceutical active ingredient (API) and the receptor targeted by that API, considered to be at the single-molecule level, is unlikely to be respected across different batches of the same natural matrix.

[0026] These considerations would seem to strongly distinguish the study of the interactions between self-assembled natural matrices, endowed with complexity at the molecular and supramolecular levels, and living systems from the interactions that would be established by the API and its target receptor cell structures. In fact, the latter is clearly defined by the elaborate deterministic criteria of a key-lock mechanism, by fixing the interaction between the API and its specific target, in particular, also in structural terms defined by both quantitative and qualitative methods. This concept is very broad from a conceptual perspective, leading to the possibility of controlling the reproducibility of the biological activity of the API by controlling the reproducibility of its molecular structure alone based on its structure-activity relationship (SAR). This clearly does not apply to natural matrices or products containing them due to the above characteristics.

[0027] Therefore, it seems necessary to pay attention to the fundamental differences between natural self-assembling matrices and APIs. - The first ones are biotic for humans and the environment, characterized by physiological interconnectivity with the recipient's biological system at the molecular level, and are in fact inappropriately described and characterized by the use of deterministic tools such as the key-lock model, precisely because of their complexity. - The latter, which are foreign bodies for humans and the environment, instead feature the clear possibility of describing their interactions with the recipient's biological system according to completely deterministic criteria, typically summarized by the "key and lock" model.

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

[0029] The network established between all the components of the matrix that gives rise to the "matrix effect" makes it impossible to identify a single marker representing the network, since a single component cannot convey all the properties specific to the matrix alone and thus does not reflect the interaction between the matrix and the target organism.

[0030] The matrix effect confers specific unique properties on the matrix itself or a mixture of matrices, resulting in a new and different matrix called an emerging property that cannot be replicated by any of the properties of the components taken individually. This fully reflects the fact that such properties cannot be accurately studied by the deterministic chemical methods commonly used in classical pharmacochemistry, and as such, it is only fully applicable 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 occurring within the matrix, as shown below. · The presence of a large number of components, · The inability to re-derive the properties of the matrix as the sum of the properties of single substances · The impossibility of describing the interaction between the matrix and the receiving organism according to the key-lock paradigm (model) that is the basis of SAR.

[0032] Currently, humans are increasingly recognizing that most responses to problems lie within nature itself, and the need to develop techniques and methods that enable understanding of natural complex entities such as supramolecular networks like natural matrices and thus to standardize them in some way. These entities are the only ones that are physiologically compatible with everything that forms their production. Therefore, it is necessary to shift from an environmental reductionist-based validation to a probabilistic approach triggered by the latest evolution of scientific thinking, and thus ultimately to oppose linear dynamics to circular dynamics. Therefore, deterministic chemical methods are not appropriate for investigating and monitoring the properties and quality of matrices. An approach is needed to evaluate the interactions within complex systems in order to enable the identification of characteristics related to the reproducibility of the therapeutic properties of matrices, if necessary.

[0033] Therefore, it is necessary to turn to an approach inspired by systems theory.

[0034] The study of such characteristics has not been achievable so far and requires tools such as "omics" science, among which transcriptomics and metabolomics can be identified as extremely important.

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

[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). The Ph.I.M MOA is a mode of action characterized by the key-lock model in which the selected API acts on its target receptor in accordance with the rules of SAR. Therefore, products containing or consisting of complex systems such as natural matrices can comply with the Regulation. In particular, this provision also indicates that products that modify pathological or physiological states or processes through non-Ph-IM mechanisms of action are MDs.

[0037] Therefore, this Regulation raises a two-fold problem to be solved. On the one hand, MDs made of materials of natural origin such as plant matrices need to undergo quality control validation in order to be available for treatment. On the other hand, it is necessary to demonstrate that the therapeutic effect of such products is achieved by non-Ph-IM mechanisms of action.

[0038] The current validation of products for therapeutic use is only applicable to products acting by Ph-IM mechanisms of action, based only on the reproducibility of their chemical composition.

[0039] While taking into account the complexity of the natural matrix, current standard techniques are based on the validation of products containing or consisting of a natural matrix for use in treating pathological conditions at the chemical level of the API (i.e., products falling within the definition of MD under EU regulations). This is in marked contrast to the intimate nature of such products for all the reasons stated above. Therefore, in the art, there is a need to develop validation procedures that are based on the verification of such complexity and are not limited to the evaluation of the reproducibility of such products based solely on their molecular composition. Furthermore, current standard techniques do not provide a method for evaluating the mechanism of action of such products.

[0040] Currently, there is a strong desire to find alternatives to traditional pharmacology, while 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] By providing a method for validating the quality of products containing or consisting of a natural matrix that is not based solely on the chemical composition of the natural matrix, it becomes possible to use products of natural origin in therapy, which have a cyclic dynamic rather than a linear dynamic natural matrix, i.e., they act on the overall physiological state that changes depending on the pathological condition rather than a single change. This leads to the development of new research areas and the possibility of using the entire network (such as the natural matrix) in treatment, where the network operates on the network represented by the treated subject receiving it, i.e., it is cyclic dynamic rather than a single compound and acts on a single point of the receiving network, i.e., it is linear dynamic.

[0042] The present invention solves the first problem summarized in the above paragraph. SUMMARY OF THE INVENTION

[0043] The present invention provides a new method for defining acceptability ranges or cut-offs for spectroscopic or spectrophotometric analysis for the validation of one or more batches of a product for use in the treatment of a pathological condition, said product comprising or consisting of one or more natural matrices, said acceptability ranges or cut-offs comprising steps calculated based on a gold standard of said product having a therapeutic effect confirmed in the treatment of said pathological condition, and on spectroscopic or spectrophotometric spectra of one or more different batches of said product, said spectra being defined as acceptable or unacceptable based on one or more hallmarks of said pathological condition and 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 on their mere chemical composition.

[0044] In other words, the acceptability ranges or cut-offs are defined based on the deviation of the spectrum from the average spectrum obtained therefrom.

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

[0046] As disclosed above, due to the complex interactions within the natural matrix or matrix and the fact that therapeutic or beneficial (for health) products containing or consisting of such a matrix cannot have therapeutic or beneficial effects attributed to a specific API, there is a clear need in the art for not only best practices and standardization throughout the entire process of preparing a product containing or consisting of a natural matrix, but also for a batch control model for such products that is not based on the identification, quantification, and evaluation of the individual chemical entities contained within the matrix or matrices, since the therapeutic or beneficial emerging properties cannot be attributed to merely the sum of the properties of the individual components of the matrix or matrices. Therefore, this control model should take into account the entire system and enable batch evaluation within the context of the interactions between all components. This different evaluation method is necessary because the properties (emerging properties) of a product containing or consisting of one or two or more natural matrices, particularly a plant matrix, an animal matrix, or a mixture thereof, result precisely from the interconnectedness between all the components of the natural matrix present in such a product. This means that, as explained above, in contrast to classical pharmaceutical products whose activity is defined by a specific API, it is not possible to attribute the emerging properties typical of a natural matrix 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 within it, but also from the supramolecular interconnections between such components, including the way in which the component self-assembles at the supramolecular level, resulting in a network of interactions between all the components of the matrix. In other words, in a product containing or consisting of a natural matrix, there is no "active ingredient" responsible for the therapeutic characteristics of the product, or "excipient" responsible for not interfering with the characteristics of the active ingredient, as in a typical pharmaceutical product, but rather there are multiple interconnected and interacting components that are all responsible for the emerging properties of the matrix. "Emergent" is the term most frequently used to explain the observed integrated characteristics of a system.

[0047] The interaction between the natural matrix and the recipient organism, for example the human body, i.e., the interaction between the donor network (the matrix or natural material according to the present specification) and the recipient network (the body of the subject to which the product is administered, e.g., the human body), is also characteristic. Such interactions result in the modification of numerous interconnected biological pathways in a manner specific to each biological matrix. In contrast to specific APIs, the effects of therapeutic products comprising or consisting of one or more natural matrices are broad, encompassing a very large number of aspects of physiology, and as a result, the products do not modify a single function contributing to the pathological condition, but rather affect the overall pathological condition. The modification of the overall pathological condition is the result of a number of biological components constituting or comprising a natural material consisting of one or more natural matrices (i.e., the product), which act in concert (i.e., emerging properties or matrix effects) through both functional and structural interactions.

[0048] As described above, natural molecules within the natural matrix are chemically similar to their synthetic counterparts when isolated, but due to their completely different synthetic routes with respect to primary metabolites, reactants, reaction temperatures, energy sources, catalysts, etc., they may have different fingerprints with respect to their synthetic analogs, and it is also recalled herein that this may potentially affect their physicochemical behavior and reactivity, and thus their biological activity.

[0049] For the reasons given above, a preferred standardized eubiotic protocol is used for the production of natural matrices, particularly plant matrices and the final products validated by the methods of the present invention. The eubiotic protocol preferably starts from agricultural production and extends to the final conversion of raw materials designed to maintain the basic natural program rules that have enabled the interconnection between all components, organic and inorganic, of organisms over millions of years.

[0050] The Applicant's research disclosed in this specification demonstrates that the classical approach used for standard pharmaceutical products (i.e., qualitative - quantitative characterization of the matrix) is not applicable to products that provide therapeutic and / or health benefits when the product contains or consists of complex natural systems (i.e., natural matrices). As is known in the art, one of the main problems related to the validation of therapeutic products containing or consisting of one or more natural matrices is that, for example, a natural matrix extracted from a given plant is never completely identical, from a molecular component perspective, to the "same" natural matrix extracted in the same way from the same species or even from diverse other plants.

[0051] Due to the nature of natural matrices, in contrast to the classical quality control acceptance parameters used for classical pharmaceutical products based on specific API rules, a certain degree of variability in the qualitative - quantitative composition of products containing or consisting of natural matrices must be tolerated as an expression of the most intimate nature of such entities and their mode of action on the recipient organism. The problem, however, is to specify how to evaluate such an acceptable degree of variability.

[0052] This application provides a new and reliable method for evaluating the tolerance range or tolerance cut - off of spectroscopic or spectrophotometric methods suitable for quality methods of products containing or consisting of complex natural systems. The tolerance range or tolerance cut - off has a therapeutic or health effect based on the biological activity of such types of products 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 qualitative-quantitative differences between natural matrices obtained from different members of the same source (even via the same production procedure), different molecular entities in the matrices appear to act functionally and structurally in an overlapping manner with each other. This redundancy results in a clear maintenance of the biological activity exerted by products containing or consisting of natural matrices, even when the qualitative-quantitative composition of different batches of the product is not considered acceptable using the classical batch control protocols required by laws designed to regulate deterministically acting APIs. Without being bound by theory, the observed maintenance of biological activity is likely due to the fact that, as described above, the emerging properties of the natural matrix result from a matrix network that acts as an entity with characteristic properties and cannot be attributed to each single molecule as if it were isolated.

[0054] Accordingly, the inventors have discovered that different batches of products containing or consisting of complex natural systems result in non-compliance with common standard quality control validation techniques based on their qualitative-quantitative compositions, yet surprisingly result in the determination of equivalent biological effects that are maintained, i.e., they provide their desired biological activity despite their different compositions.

[0055] Thus, instead of basing the identification and evaluation of selected individual chemical entities on quality control acceptance ranges or acceptance cut-offs for a therapeutic product comprising or consisting of one or more natural matrices, and / or instead of performing a statistical pre-clearing of spectroscopic data to reject classically accepted outliers for APIs, the Applicant has developed a new method for evaluating quality control parameters based on the analysis of selected parameters representing its biological effect, i.e., for validating different batches of the product based on highly important characteristics of a medical device composed of a natural matrix. The evaluation of the acceptance ranges or acceptance cut-offs and validation methods provided herein is sufficient for the quality control of biological materials having therapeutic activity as defined by Regulation 2017 / 745, and reflects the product compliance to GSPR 1 of Annex I of that Regulation, specifically in the first line which lists the following: "The device must achieve the performance intended by its manufacturer and must be designed and manufactured so that during normal conditions of use the device is suitable for its intended purpose."

[0056] Accordingly, the present invention provides a method for defining an acceptance range or acceptance cut-off for spectroscopic analysis or spectrophotometric analysis for quality validation of one or more batches of a product for use in treating a pathological condition comprising or consisting of one or more natural matrices, the acceptance range or acceptance cut-off comprising the step of being calculated based on a gold standard having a therapeutic effect confirmed in the treatment of the pathological condition and on the spectroscopic or spectrophotometric spectra of one or more batches of the product, the spectra being defined as allowed or not allowed based on the biological activity exerted by the gold standard and the one or more batches of the product on one or more hallmarks of the pathological condition in at least one cell-based assay.

[0057] The present invention further provides a method for evaluating the gold standard of a product for use in the treatment of a pathological condition, comprising one or more natural matrices defined in the claims, between different batches. The present 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, wherein the product comprises one or more natural matrices, a. performing 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 said spectroscopic or spectrophotometric analysis.

[0058] The term As used in this application, "natural matrix" refers to a material consisting of a network represented by a wide number of components / constituents directly obtained (e.g., extracted) from members of the natural world or their naturally occurring parts (i.e., from natural raw materials) without any special treatment or synthetic modification. "Without any special treatment or synthetic modification" means that it is processed only by manual, mechanical or gravitational means, such as dissolution in water or other naturally occurring solvents such as 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 is intended to be extracted from air by any means, provided that the "natural matrix" excludes the said member of the natural world or its natural part itself. In other words, a natural matrix or a mixture of natural matrices is a material obtained from entities that are naturally self - assembling and are processed while maintaining their natural biophysical properties that determine physiological interactions with other organisms such as human organisms. Their emerging properties can be expressed by contributing to the physiological actions activated in each specific situation and to the rebalancing of the metabolic methods or states of the recipient organism and / or some organs or tissues. According to the present invention, the natural matrix can be derived from materials obtained from any source in the living world, i.e., Monera, Protista, Fungi, Plantae and Animalia. Thus, this term includes plant natural matrices, animal natural matrices, fungal natural matrices, protist (archaea or bacteria) natural matrices, Monera natural matrices. The natural matrix can also include natural inorganic materials such as minerals extracted from natural raw materials. The synonym of natural matrix or one or more natural matrices in this specification is the "natural material" defined below.

[0059] Examples of naturally occurring parts of organisms can be represented, for example, by 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. A plant natural matrix or a natural matrix obtained from a plant, An animal natural matrix or a natural matrix obtained from an animal, A fungal natural matrix or a natural matrix obtained from a fungus, A protist natural matrix or a natural matrix obtained from a protist, A monera natural matrix or a natural matrix obtained from a monera, Or a plant material and / or extract, an extract from an animal tissue or organ, a fungus and / or a fungal extract, or a mixture thereof. Furthermore, the natural matrix may contain minerals or components obtained from minerals.

[0061] Plant is synonymous with herb.

[0062] For example, in the context of a product containing or consisting of plant-derived materials (obtained from plants) such as herb supplements, the natural matrix includes the original, intentionally unmodified, preferably unmodified components that are naturally present in the raw material (e.g., extract of the source material), and thus includes various organic and inorganic components found in the above-mentioned kingdoms.

[0063] The term "natural" matrix emphasizes the retention of the integrity and complexity of the network of components rather than the isolation, purification, or extraction of specific molecules or molecular classes by extensive processing or chemical modification.

[0064] Due to the supramolecular self-assembly of the components of the natural matrix, the entire matrix behaves as a complex network that does not interact with a single target molecule but rather interacts with the network of recipients (also organized as a network) in the receiving organism. Thus, the interacting natural matrix - receiving organism is the result of the interaction between a network (i.e., the matrix) and a network (i.e., the organism to which the matrix is administered), rather than the result of point-to-point interactions as in the case of a typical pharmaceutical API.

[0065] The term "natural matrix" can also be replaced in any part of the specification and claims by a complex natural system.

[0066] In this specification and the claims, the term "natural matrix" cannot be construed as a "natural product"; rather, a natural matrix is a product obtained from a natural organism and processed (e.g., extracted) therefrom by a technique that does not substantially alter the biological structure and supramolecular interconnectivity among the components within the matrix.

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

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

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

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

[0071] Holism: The concept of emergent properties emphasizes the overall perspective by 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 a complex natural system(s)") is a product comprising or consisting of one or more natural matrices as also defined herein as "natural material", i.e., "a material obtained / manufactured / processed from natural raw materials or members of the natural world" (see below).

[0073] In any part of the specification and claims, "a product comprising or consisting of one or more natural matrices" can be replaced with "a product comprising or consisting of one or more plant matrices" or "a product comprising or consisting of a composite natural system", "natural material or material of natural origin".

[0074] Furthermore, the term "a product comprising or consisting of one or more natural matrices" according to the present specification can be an intermediate, or the final formulation for the intended use (e.g., a re-suspended dried product), or, particularly when the formulation for the intended use is in liquid form, this term can define a dry form or a lyophilized form or a concentrated form thereof to which water is added by the user or a 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. Further, if a single natural matrix is present in or consists of the product, the natural matrix is obtained (e.g., extracted) from the organisms defined above by technical means. If a mixture of natural matrices is included in or consists of the product, the mixture is a mixture of selected natural matrices manufactured by humans, and such a mixture cannot be found in any of the natural products from which each matrix contained therein is derived. Thus, when a product comprises or consists of a plurality of natural matrices, the natural matrices are combined by humans, and the resulting product is endowed with new emerging properties.

[0076] According to the present specification, the expression "biological functions associated with a pathological condition" refers to a set of biological functions related to the distance / deviation from homeostasis that can or cannot reach the onset, progression, and exacerbation of a pathological condition. Thus, the expression "modification of biological functions associated with a pathological condition" refers to the regulation or change from the normal (healthy) physiological state of biological functions (e.g., activities or methods) in an organism (preferably a human) directly related to the change / disorder of homeostasis to a pathological condition or disease. In other words, it describes a specific adjustment or deviation from the healthy physiological state of a series of biological functions that occur as a result of, or simultaneously with, the onset, progression, and exacerbation of a pathological condition or disease.

[0077] As an example, in the case of diabetes, the biological functions related to glucose metabolism, insulin production, and regulation are directly related to the pathological condition of diabetes and are thus modified to be related to the pathological condition or state of diabetes according to the present specification.

[0078] According to the present specification, synthesis has the meaning conventionally accepted in chemistry.

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

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

[0081] The term "eubiotics" as used herein has the meaning of "innate to the living world" (i.e., plants, animals, fungi, protists, kingdom Monera). This term is derived from the Greek word "eu," which means good or well, and "bio," which means life. In this specification, the Greek concept of "eu" is intended to mean "innate to" / "belonging to" the living world, and thus maintains the integrity and complexity of their interactions. This term is opposed to "xenobiotic." The term "xenobiotic" is derived from the Greek word "xenos," which means foreign, and "bios," which means life. It refers to substances and materials that are "foreign to the living world" in the sense that they are foreign to the natural nutrition / metabolism of living organisms.

[0082] Generally, eubiotic drugs or treatments or supplements are designed to support and promote a healthy balance within the biological system without introducing substances or materials that cause imbalance within the biological system. This can include drugs aimed at positively influencing the microbiota, promoting a healthy immune response, or enhancing overall well-being, for example, by promoting a physiological state. Since synthetic products are a cause of imbalance to physiological methods, eubiotic drugs can only be natural.

[0083] In agriculture, typically, a biotic is associated with practices that enhance soil health and promote a balanced ecosystem for crops. This can include the use of organic fertilizers, crop rotation, and other sustainable farming methods.

[0084] In microbiology, a biotic generally refers to the study of microorganisms that positively contribute to the health of the environment. This includes understanding the role of beneficial bacteria in various ecosystems.

[0085] Overall, the general underlying concept in the term biotic is the promotion of a state of health, balance, and harmony within a biological system, whether it be the digestive system of an animal, the human microbiome, or an ecosystem.

[0086] The in vitro cell-based assays herein have the meaning conventionally used in the art, and in particular, it refers to a cell-based assay for evaluating cell behavior and response to injury or stimulation in the context of a disease or a pathological or pre-pathological condition, and is intended as an experimental technique used to evaluate how a selected cultured cell's behavior, function, or characteristics are affected by a particular disease or pathological or pre-pathological condition. This type of assay is often designed to study the biological responses of cells in a controlled environment within a Petri dish or well plate.

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

[0088] Assay: An assay is a series of tests or procedures conducted in a laboratory environment to measure or analyze a specific property or function of a biological material. In this case, the assay focuses on cells.

[0089] Disease or pathological condition / pre-pathological condition: In the context of a disease or pathological condition / pre-pathological condition, cell-based assays are specifically designed to simulate or mimic conditions associated with the disease or pathological condition. In particular, cell-based assays can be used to evaluate in vitro the therapeutic, adjuvant, and / or beneficial effects of different compounds or products. This can include exposing cells to factors known to be associated with the disease or pathological condition, exposing cells to potential treatments or adjunct products that assist in restoring physiological states, or using cells genetically modified to have characteristics specific to the disease or pathological condition.

[0090] A healthy physiological state refers to the state of an organism's body, organs, devices, systems, or body regions, and their internal processes when they are functioning optimally within the normal parameters of that individual, i.e., the state where homeostasis tends to prevail. A healthy physiological state refers to the state in which these various biological functions are operating optimally within normal (healthy) parameters in the context of biological functions known to contribute to the hallmarks of a given disease or pathological condition. This state is characterized by the absence of significant abnormal cellular or molecular processes related to the specific disease under consideration.

[0091] This term takes into account the prominent hallmarks of a particular disease, which are the distinctive features or characteristics typically observed in individuals affected by that disease. These hallmarks can include specific cellular behaviors, molecular pathways, or physiological responses that play important roles in the onset or progression of the disease.

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

[0093] Therefore, a healthy physiological state also indicates the direction of regulation of biological functions, which is a known hallmark of pathological states in homeostasis, i.e., the direction of homeostasis of the regulation of a set of biological functions resulting from a particular system, region, device, or organ of a healthy subject, prior to the onset of the pathological state.

[0094] The 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, a prominent hallmark of a disease is an indicator that can show the progression or control of a given disease or pathological state. These hallmarks (also called "key indicators") are typically a set of characteristics or patterns that a physician monitors over time to track the progression or regression of a particular disease. In summary, the hallmarks of a disease are defining features or characteristics whose modification indicates a given medical state 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, synapse and neuronal network (dysfunction), (abnormal) proteostasis, cytoskeleton (abnormalities), (altered) energy homeostasis, DNA and RNA (defects), inflammation (increase), and neuronal cell death (increase). In cancer research, prominent hallmarks of cancer are a set of specific characteristics commonly found in cancer cells. These hallmarks include (sustained) proliferative signaling, (evasion) of growth suppressors, (resistance to) cell death, (enablement of) replicative immortality, (induction of) angiogenesis, and (activation of) invasion and metastasis.

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

[0096] As used herein, the expression "natural material" refers to a material consisting of one or more natural matrices, provided that the material(s) are not found as such in nature but are 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, via preparation methods aimed at maintaining the integrity of the network within the natural raw material source from which the natural material is prepared. As used herein, "natural material" is considered synonymous with one or more natural matrices. Thus, a natural material according to the present specification can be a product such as a product having a therapeutic effect consisting of or comprising only different natural matrices selectively assembled (not assembled in such a combination in nature) to provide a given therapeutic effect, thereby forming an "interactome network", and administration thereof to its target (i.e., the receiving living network) exhibits an emerging property that provides a therapeutic or homeostatic regulatory effect, i.e., an effect beneficial to the health of the target.

[0097] "Having a therapeutic effect": As used herein, a product having a therapeutic effect, 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 alleviation, mitigation or reduction of at least one clinical symptom, and / or provides a delay in the progression of the condition, or (fully or partially) restores a healthy physiological state in the area affected by the pathological condition.

[0098] Having a beneficial effect as used herein includes products where administration to a healthy subject or a subject that is healthy but not in homeostasis, or administration to an in vitro cell assay representing a sufficiently healthy state, results in restoration of homeostasis or in vitro or in vivo evidence of an adjuvant at the time of administration in the cell assay or in the intended system / area / device / organ of the recipient.

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

[0100] Having a "beneficial / health / health-beneficial" effect according to the present specification encompasses products where administration to a non-constant healthy subject or a healthy subject, or administration to an in vitro cell assay representing a sufficiently healthy state, results in in vitro or in vivo evidence of restoration of constancy or adjuvantization at the time of administration in the cell assay or the system / region / device / organ of the intended recipient.

[0101] The term "product having (identified) 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, and the emerging properties of said product provide the therapeutic effects defined below in this glossary.

[0102] This term can be replaced, in any part of the specification and claims, with "product having therapeutic activity comprising or consisting of a complex natural system", "formulation having therapeutic properties comprising (or consisting of) a complex natural system" or "composition having therapeutic properties comprising (or consisting of) a complex natural system" or "mixture having therapeutic properties comprising (or consisting of) a complex natural system", and the term "uncomplicated natural system" can be replaced with "one or more natural matrices" or "natural material".

[0103] The definition applies, with the necessary modifications, to the term "product beneficial for beneficial / health / health properties, comprising one or more natural matrices".

[0104] According to the present specification, the term homeostasis has the meaning conventionally accepted in the art and thus refers to the physiological processes by which the living body 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 state of the organism remains within the optimal range for survival and proper physiological functions (a healthy physiological state). Homeostasis is achieved by organisms through the regulation of a series of biological functions and processes aimed at maintaining a healthy physiological state.

[0105] Products that assist homeostasis processes are products that regulate biological functions in the direction of a healthy physiological state, and thus are suitable for healthy individuals, support the homeostasis mechanisms that contribute to a healthy physiological state, and can be used by healthy individuals to assist in the regulation of homeostasis of biological functions related to the hallmarks of a given pathological state.

[0106] A medical device (also known as an MD) is, according to the present specification, a product as defined above according to the definition in Article 2(1)(a) to (c) of EU Regulation 2017 / 745, and since it is necessarily used for treatment purposes, "medical device" means any... [omitted]... material that a manufacturer intends to be used alone or in combination for one or more of the following specific medical purposes in humans... - treatment or alleviation of a disease, - treatment, alleviation, or compensation for an injury or disability, - modification of a physiological or pathological process or condition, ... omitted... It does not achieve its main intended action by pharmacological, immunological, or metabolic means within or in the human body, but its function can be assisted by such means.

[0107] The "performance" of a medical device means the ability of the medical device, as defined in this specification, to achieve its intended purpose as stated by the manufacturer; The "clinical performance" of a medical device means the ability of the medical device, as defined in this specification, to achieve its intended purpose as claimed by the manufacturer, arising from any direct or indirect medical effect resulting from its technical or functional characteristics, including diagnostic characteristics, such that when used as intended by the manufacturer, it provides a clinical benefit to the patient; The "clinical benefit" of a medical device means a positive impact of the device, as defined in this specification, on an individual's health, or a positive impact on patient management or public health, as represented in terms of meaningful measurable patient-related clinical outcomes (s), including diagnosis-related results (s).

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

[0109] Under section 201(h)(1) of the Federal Food, Drug, and Cosmetic Act, a device is: An instrument, apparatus, implement, machine, contrivance, implant, in vitro reagent, or other similar or related article, including a component part or accessory thereof, (A) Recognized in an official national formulary, or the United States Pharmacopeia, or any supplement thereto, (B) Intended for use in the diagnosis of disease or other conditions in humans or other animals, or in the cure, mitigation, treatment, or prevention of disease, or (C) It is intended to affect the structure or any function of the body of humans or other animals, and does not achieve its main intended purpose by chemical action in or on the body of humans or other animals, and does not depend on being metabolized for the achievement of its main intended purpose. The term "device" does not include software functions excluded according to item (o) of Section 520.

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

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

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

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

[0114] The terms "treating", "treatment" or "to treat" (and their grammatical variations) mean that the severity of the condition of the subject is reduced, at least in part improved or ameliorated, and / or some alleviation, mitigation or reduction of at least one clinical symptom is achieved, and / or the progression of the disease or disorder is delayed.

[0115] Legend of batches: Figures 2-7 and 12: Product Arte-Gx in lyophilized form (see detailed composition of the product of 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 Dry 21E1640 Figure 9 Gold Standard of Product B Figure 11 Gold Standard of Product C (see detailed composition of the product of Example 1).

Brief Description of the Drawings

[0116]

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Mode for Carrying Out the Invention

[0117] The present invention provides a tolerance range or tolerance cut-off of spectroscopy or spectrophotometry based on the measured value of the modification of a specific biological activity associated with a therapeutic effect or beneficial effect, enabling a constant balance of a slight imbalance in a physiological-pathological situation or an organism such as a human organism, and providing a method and approach for batch-to-batch validation of products comprising or consisting of a natural matrix of 100% user biotic entities that exhibit therapeutic or beneficial activity. Therefore, the applicant provides a new standard technology that enables standardizing products of this type and thus enables compliance with a regulatory framework that provides an executable space for the innovative use of such products in treatment. Over the past few decades, the applicant has pursued an interdisciplinary research path that has led to the development of user biotic protocols for agricultural production and methods of converting raw materials (starting materials) in order to maintain the basic natural program rules that have enabled the millions of years of interconnection between all components of organic and inorganic organisms along with scientific innovation.

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

[0119] This is particularly interesting 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 formulation APIs. The main problem with this type of product is ensuring product compliance with the claimed therapeutic / beneficial effect, despite the important therapeutic / beneficial effect exerted when there is no reproducible and accurate method for batch - to - batch validation. This is because, precisely due to their origin (nature), they exhibit variability inherent in their qualitative - quantitative composition and cannot be correctly evaluated by classical validation methods based solely on qualitative - quantitative composition. So far, in practice, it has not been possible to take into account this and bring products containing or consisting of one or more natural matrices into a regulatory framework that enables high - level innovation. This problem is solved by the present invention.

[0120] Since the techniques and methods of the present invention are designed for products containing or consisting of natural matrices, it is preferable that the manufacture of these products be carried out with the entire manufacturing process standardized in both agriculture and the manufacturing method.

[0121] The inventors demonstrate that an approach judged based on criteria designed for the control of a single API acting through a deterministic key-lock mechanism due to the presence of a clear SAR, based only on a reproducibility assay by classical targeted metabolomics, for example the qualitative - quantitative analysis of the chemical class of a product having a therapeutic effect or of a specific chemical compound, is 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 the chemical substance classes of different batches of the same product, if considered as the only reference parameter for evaluating the quality of the batch according to the reference applied to the API, show that the quantitative variability of the individual chemical substance classes of the substances present in these different batches leads to the a priori hypothesis that these batches have different biological activities (see the second table and Figure 5 of 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, despite their variable qualitative - quantitative chemical composition, the batches have the same biological activity, probably due to the presence of redundancy between single components at both the structural and functional levels, an elastic behavior.

[0122] Therefore, 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 make it possible to accurately estimate the activity profile when the product contains or consists of one or more natural matrices. Thus, the data provided herein demonstrate that, in contrast to API - based pharmaceutical products, the qualitative - quantitative analysis of the individual components of a therapeutic product containing or consisting of one or more natural matrices (i.e., providing a therapeutic effect based on network - to - network interactions) is therefore not suitable for evaluating the correct compliance batches for such products, especially when carried out as a method for assessing the reproducibility of non - SAR - based entities.

[0123] In fact, considering exactly that nature of the natural matrix, the quantitatively variable chemical profiles between batches would prompt the validator to consider different batches of a product containing or consisting of one or more natural matrices as "different materials" with respect to a given gold standard of that product, and thus to discard said batches. Conversely, the results provided herein by the inventors demonstrate that qualitatively - quantitatively different batches of a given product exert the same relevant reaction for their intended therapeutic use. This is another demonstration that the biological activity of the 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 matrix's activity does not exclusively depend on the reproducibility of the identity and amount of the molecular components that constitute it.

[0124] The results obtained by the inventors demonstrate that both structural and functional redundancy mechanisms that impart a certain resilience to the matrix exist within the natural matrix, and that the matrix itself should not be recognized as a collection of molecules acting independently of each other that remain unchanged under the influence of SAR, which is considered a common cause when they are studied individually.

[0125] As shown herein (see examples and figures), different batches of a test product containing or consisting of one or more natural matrices have been confirmed to have different qualitative - quantitative compositions from each other and different from the gold standard of the product, and yet can retain the ability to mediate the same therapeutic or beneficial activity despite having different quantitative compositions at the molecular level.

[0126] Accordingly, the inventors have developed a new method for defining an acceptance range or acceptance cut-off for 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 comprises or consists of one or more natural matrices; the further method is a method for the validation of different batches of a product comprising or consisting of one or more natural matrices and is not based on the preservation of the selected intrinsic properties (regulation of the selected biological characteristics) of the matrix, nor on the preservation of molecular components. The method of the invention makes it possible to identify a validation acceptance range or acceptance 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] This specification discloses, by way of example, experimental data relating to a model product of this specification designated as Arte-GX, consisting essentially of a plant-derived natural matrix, for use in the treatment of osteoarthritis (disclosed in International Publication No. 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 recognized 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 therapeutic products comprising or consisting 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 pathological conditions, the matrix being obtained from plant biological material that has been appropriately processed and formulated to obtain the final natural material (as defined in the glossary), which is capable of modifying the pathological situation at the time of administration 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, hundreds of components derived from the crude raw plant parts establish multiple combinations of molecular and supramolecular interactions among themselves and with the target tissue, characteristic of materials of natural biological origin, and thus do not lose their ability to maintain therapeutic emerging properties.

[0130] In particular, the products tested by the Applicant were prepared according to a user biotic protocol selected and standardized by the Applicant through more than 40 years of experience, starting from soil preparation to the manufacture of the final product, empirically making the final product as homogeneous as possible and thus enhancing efficiency with respect to the yield of effective batches. The user biotic protocol developed by the Applicant is interpreted as providing a 100% natural final product, as opposed to synthetic or semi-synthetic products (i.e., products that do not contain single components obtained by artificial chemical synthesis) in which each component is manufactured under user biotic conditions, in order to standardize as much as possible each step leading to the desired final product in relation to the user biotics of each step. By comparing or rather integrating the reductionist approach described above with that of systems theory and quantum biology, it is possible to develop a fully user biotic standardized production method involving the integration of intersectoral technologies and research in several different fields, from agriculture to omics and mathematical sciences. Preferably, according to the present invention, a test product comprising or consisting of one or more natural matrices does not contain chemically synthesized molecules, is in contact with, and does not contain a natural matrix that may have incorporated chemically synthesized molecules, thereby making it possible to provide a natural matrix and a final product consisting of 100% natural components.

[0131] The present invention aims at a method for defining an acceptance range or an acceptance cut-off for spectroscopic or spectrophotometric analysis for the 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, comprising calculating an acceptance range or an acceptance cut-off on the spectroscopic or spectrophotometric spectrum of one or more batches of said product and a gold standard having a therapeutic effect confirmed in the treatment of said pathological condition, said spectrum being defined as acceptable or unacceptable based on the biological activity exerted in at least one cell-based assay by one or more batches on one or more hallmarks of said gold standard and said pathological condition.

[0132] Depending on the disease state of interest, there can be one or more hallmarks, preferably more hallmarks are selected. For example, in the case of cancer, those skilled in the art are well aware that a more relevant hallmark is the proliferation of cancer cells. Thus, the selected cell-based assay is, in this case, an assay that validates the viability of neoplastic cells or tumor masses upon administration of the product of interest. Furthermore, according to the present invention, it is preferred to use a single cell-based assay, although two or more cell-based assays can also be used. In non-limiting examples, additional cell-based assays can also 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 that, although beneficial, the qualitative-quantitative characterization of products containing or consisting of one or more natural matrices is not suitable for evaluating the actual effectiveness of these types of products due to the dynamic interactions of all their components that bring about new emerging properties. Thus, the validation procedure must be carried out based on the demonstration that it is different from that of classical API-based therapeutic products. In fact, as also shown by the examples and data provided in this application, the qualitative-quantitative validation in the case of products containing or consisting of natural matrices is not sufficient and not suitable to ensure the therapeutic effectiveness of the product.

[0134] The applicant has developed new approaches and methods based on a validation procedure based on the definition of validation parameters that truly represent the therapeutic effectiveness of the product.

[0135] By the way, for example, when additional metabolomics analysis is still desirable for the manufacturer to evaluate the toxicological profile of the product.

[0136] Depending on the disease state of interest, there can be one or more hallmarks, and preferably more hallmarks are selected if available. For example, in the case of cancer, one of ordinary skill in the art is well aware that the most relevant hallmark is the proliferation of cancer cells. Thus, one of ordinary skill in the art can limit the method of the present invention to this single hallmark, and the selected cell-based assay is, in this case, an assay that validates the viability of neoplastic cells or tumor masses upon administration of the product of interest.

[0137] In one embodiment of the present invention, the method comprises the following steps: i) a. Searching a list of hallmarks of the disease state from standard techniques; b. Identifying a set of modifications of biological functions detectable in the disease state for each of the hallmarks, determining the regulation of each of the functions associated with the desired therapeutic effect, and thereby designing a regulation pattern for each of the functions representing a healthy physiological state; c. Identifying markers and their regulation patterns that are the cause of the modifications detectable in the disease state for each of the biological functions, and setting a regulation pattern opposite to that specified as the regulation pattern indicating the healthy physiological state for each of the markers; ii) Analyzing the expression pattern of each of the markers identified in i)c. induced by the gold standard of the product in an appropriate in vitro cell-based assay, determining the qualitative-quantitative regulation of each of the markers induced by the gold standard with respect to the pathophysiological state control of the in vitro cell-based assay, calculating the gold standard Z-score value of the regulation of each of the biological functions induced by the gold standard, and selecting each of the gold standard Z-score values as a reference cut-off Z-score value indicating the desired therapeutic effect. iii) Analyze in the in vitro cell-based assay the regulation patterns of the markers specified in i) c. induced by further different batches of the product, determine the qualitative-quantitative regulation of each of the markers induced by each of the batches, and thereby calculate the Z-score value of the regulation of each of the biological functions induced by each of the batches. iv) Compare the Z-score value of the regulation of each of the biological functions induced by each of the batches calculated in iii) with the corresponding cut-off Z-score value of the regulation of each of the biological functions provided in ii), and select at least three positive batches in which each Z-score value of the regulation of each of the biological functions calculated in iii) conforms to the corresponding reference cut-off Z-score value, and at least one negative batch in which at least one Z-score value of the regulation of each of the biological functions calculated in iii) does not conform to the corresponding reference cut-off Z-score value. v) Perform spectroscopic or spectrophotometric analysis of the gold standard and the batches selected in iv). vi) Define as acceptable the range of variable spectroscopy or spectrophotometry obtained by considering each result obtained in v) to be acceptable for each positive batch and unacceptable for each negative batch, and thereby provide the acceptable spectroscopy or spectrophotometry range or cut-off.

[0138] When the same hallmark can be associated with biological functions monitored by different biological markers, one of ordinary skill in the art can determine to perform one or more assays to monitor the function. In the exemplary sections and figures, definitions of tolerance ranges with different markers are provided, and the results are consistent in each case, indicating that regardless of the different markers used to analyze the regulation of the selected biological function, the resulting cut-off is the same when the same spectroscopic technique is used.

[0139] One skilled in the art can select a more appropriate marker according to the selected hallmark of the target pathological condition.

[0140] The marker can be, by way of example, gene expression patterns, ROS, oxidative stress, cell viability, etc.

[0141] Although not limited, in a preferred embodiment of the present invention, the method includes the following steps: i) a. Searching a list of hallmarks of the pathological condition from standard techniques; b. Identifying a set of modifications of biological functions detectable in the pathological condition for each of the hallmarks, determining the regulation of each of the functions associated with the desired therapeutic effect, and thereby designing a regulation pattern for each of the functions representing a healthy physiological state; c. Identifying the genes and their expression patterns that are the cause of the modifications detectable in the pathological condition for each of the biological functions, and for each of the genes, setting an expression pattern opposite to the expression pattern identified as the expression pattern indicating the healthy physiological state; ii) Analyzing the expression pattern of each of the genes identified in i)c. induced by the gold standard of the product in an appropriate in vitro cell-based assay, determining the qualitative-quantitative regulation of the expression of each of the genes induced by the gold standard with respect to the pathophysiological state control of the in vitro cell-based assay, calculating the gold standard Z-score value for the regulation of each of the biological functions induced by the gold standard, and selecting each of the gold standard Z-score values as a reference cut-off Z-score indicating the desired therapeutic effect. iii) Analyze in the in vitro cell-based assay the expression patterns of the genes identified in i) c. induced by further different batches of the product, determine the qualitative-quantitative regulation of each of the expression patterns of each of the genes induced by each of the batches, and thereby calculate the Z-score value of the regulation of each of the biological functions induced by each of the batches. iv) Compare the Z-score value of the regulation of each of the biological functions induced by each of the batches calculated in iii) with the corresponding reference cut-off Z-score value, and select at least 3 positive batches in which each Z-score value calculator in iii) conforms to the corresponding reference cut-off Z-score value, and at least 1 negative batch in which at least 1 Z-score value calculated in iii) does not conform to the corresponding reference cut-off Z-score value. v) Perform spectroscopic or spectrophotometric analysis of the gold standard and the batches selected in iv). vi) Define the range of variable spectroscopy or spectrophotometry obtained by considering each of the results obtained in v) to be acceptable for each positive batch and unacceptable for each negative batch, and thereby provide the acceptable spectroscopy or spectrophotometry range or cut-off.

[0142] According to the present invention, a product to be 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 containing or consisting of one or more natural matrices for use in the treatment of a pathological condition, that is, a product having at least a pre - clinically validated therapeutic effect in vitro on cells and / or tissues and / or organoids and / or animal models, and thus, when administered to a patient suffering from a given pathological condition, is expected to reduce the severity of the condition of the subject (i.e., the severity is at least partially improved or ameliorated), and / or provide some alleviation, mitigation or reduction of at least one clinical symptom of the condition, and / or delay the progression of the condition. The subject to be treated according to the present invention may be an animal including a human (thus, the product is for human or veterinary use), or a plant.

[0143] The techniques and methods provided by the present invention are, in fact, methods that can be implemented for the purpose of validating batches of a given therapeutic product containing or consisting of a natural matrix in the production chain.

[0144] As already mentioned above, the product is a product containing or consisting of one or more natural matrices, that is, a product containing or consisting of a complex natural system. Non - limiting examples of such natural matrices include cut or ground plant parts, plant extracts, processed plant parts, fractions of plant extracts, for example, fractions of plant extracts obtained by filtration through a semi - permeable membrane (microfiltration, ultrafiltration, nanofiltration), or by treatment with an adsorbent resin, microorganism, honey, propolis, silk, wax, plant resin, plant gum, plant exudate, vegetable oil, essential oil, animal tissue lysate, or one or more of the fractions of plant extracts such as those obtained by treatment with a plant or animal fluid.

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

[0146] In the most preferred embodiment, the therapeutic product is a product consisting of 100% natural ingredients intended as ingredients not obtainable by humans through chemical synthesis reactions. Thus, if the product contains one or more natural matrices, it can also include minerals and any other organic or inorganic materials generally found in nature. Preferably, the products subject to the methods and processes of the present invention are products that can be obtained or are obtainable according to a standardized protocol, more preferably through a standardized protocol for nutraceuticals. Even when a standardized protocol is not available, one skilled in the art can minimize the differences between batches of the same product by using starting materials or intermediate materials or a pool 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 cultivated varieties) can be reduced by such pooling.

[0147] According to the present invention, the product can be a dietary supplement, a nutritional supplement, a medical device, or a medicine.

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

[0149] Article 2(1)(a) to (c) of EU Regulation 2017 / 745 states the following: For the purposes of this Regulation, the following definitions apply: (1) "Medical device" means any... material or other article intended by the manufacturer to be used alone or in combination for humans for one or more of the following specific medical purposes: - Diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, - Diagnosis, monitoring, treatment, alleviation or compensation for an injury or physical impairment, - Investigation, replacement or modification of an anatomical structure or a physiological or pathological method or condition, [...] This does not achieve its main intended action by pharmacological, immunological or metabolic means in or on the human body, but its function can be assisted by such means. The product may be a product classified as a medical device by the FDA.

[0150] Under section 201(h)(1) of the Federal Food, Drug, and Cosmetic Act, a device is: An instrument, apparatus, implement, machine, contrivance, implant, in vitro reagent, or other similar or related article, including a component part or accessory, (A) recognized in the official National Formulary, or the United States Pharmacopeia, or any supplement to them, (B) intended for use in the diagnosis of disease or other conditions in humans or other animals, or in the cure, mitigation, treatment, or prevention of disease, or (C) intended to affect the structure or any function of the body of humans or other animals and which does not achieve its principal intended purpose by chemical action within or on the body of humans or other animals and which is not dependent upon being metabolized for the achievement of its principal intended purpose. The term "device" does not include software functions excluded in accordance with section 520(o).

[0151] Since the method of the present invention is preferably carried out on the dry form of the product of interest, if the final product intended for use is in solution, suspension or other liquid form, the method can be carried out on the lyophilized product before its rehydration.

[0152] In its final form for administration, the product can be in the form of powder, granules, tablets, syrups, solutions, suspensions, hard or soft gelatin, capsules, sprays, creams, etc.

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

[0154] This includes, but is not limited to, cancers of major interest such as head and neck cancer, melanoma, breast cancer, bladder and osteosarcoma.

[0155] Pathological conditions as well as hallmarks of specific diseases are well-known in the art. A person skilled in the art can readily search in the scientific literature for hallmarks of the pathological condition of interest and the biological functions that are the cause of said hallmarks. It is obvious that a person skilled in the art selects the biological functions underlying a given hallmark in view of the specific pathological condition of interest.

[0156] As an example, a person skilled in the art can use different standard technical information sources to investigate the pathological state of the art of the disease of interest.

[0157] A person skilled in the art wishing to define the hallmarks of the disease of interest can search for the desired information from the scientific literature. Non-limiting examples of sources that can be used are, for example, 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 a person skilled in the art can select said functions from what is 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 present invention, preferably at least two, at least three or four or more of said functions are selected.

[0159] If one wishes to use specific software available for facilitating the execution of certain steps of the method of the present invention, such as finding the biological functions underlying the hallmarks of diseases, one of ordinary skill in the art may wish to adapt the definitions and the retrieved hallmarks to better examine the software used. By way of example, if the software used is Qiagen IPA (IPA version 94302991 Qiagen), information found in the aforementioned resources can be used, if necessary, to redefine the hallmark in order to examine IPA. When using IPA to quickly identify the biological functions underlying the hallmarks of diseases, the following procedure can be followed.

[0160] One can write the hallmarks one by one into the "Disease and Function" query box, and then the search is initiated.

[0161] The resulting resume table enables one of ordinary skill in the art to filter out diseases / functions arising from multiple evidences. By way of example, the source of the relationship can be the Ingenuity Knowledge Base, including curations from journal articles, OMIM, JAX, and ClinicalTrials.gov.

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

[0163] Examples of known hallmarks related to pathological conditions are shown in FIGS. 1-4, FIGS. 8-12.

[0164] By way of mere example, prominent hallmarks of OA known in the art include proliferation (skeletal and muscular development and function, such as joint dysfunction and joint cavity); inflammation; anatomical damage. Further by way of example, the appropriate biological functions underlying the above hallmarks of OA can include: Proliferation: Biological functions of interest are the development and function of the skeletal and muscular systems, such as the formation of joint dysfunction and joint cavity, joint dysfunction, joint cavity, and cartilage tissue. Inflammation: Biological functions of interest are inflammatory diseases, inflammation and nociception, joint inflammation. Protection from anatomical damage: Biological functions of interest are biological damage and abnormalities, such as joint inflammation and swelling, difficulty in moving the joint: osteoarthritis.

[0165] Keywords of standard techniques that can define the function are shown in FIGS. 1 to 4.

[0166] Furthermore, as an example, known hallmarks of MCI may include cognition (disorder), activation and viability (neurons, decrease), myelination and branching (decrease), inflammation (increase), skeletal and muscle system function (decrease).

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

[0168] Keywords of standard techniques that can define the function are shown in FIGS. 8 and 9.

[0169] Furthermore, as an example, known hallmarks of OP including PMO may include calcification, inflammation (increase), bone adipose tissue (increase), bone remodeling, osteoporosis, osteoblast differentiation (decrease).

[0170] Calcification: Biological functions of interest are the calcification of osteocyte cell lines and osteoblasts, bone formation; Inflammation: The biological functions of interest are inflammation in adipose, connective, and white adipose tissue; Bone adipose tissue: The 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 the function are shown in FIGS. 9 and 10.

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

[0173] For each of these biological functions, the regulations causally related to the pathological state are also known in the art. Thus, the opposite regulations can be considered as regulations associated with the desired therapeutic effect. As a result, a panel showing the desired regulation pattern for each of these functions can be designed, and the panel represents the regulation tendency of the function in a healthy physiological state (see FIGS. 1-4, 8-11). The regulations in this specification are intended to upregulate or downregulate a given function. Upregulation refers to the modification of the activity and expression of a specific gene, protein, cell pathway, or cell component that results in the enhancement of a given biological function. Downregulation is the opposite of upregulation. It involves the modification of the activity and expression of a gene, protein, cell pathway, or cell component that results in the decrease of a given biological function.

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

[0175] Conversely, therefore, the healthy physiological states referred to the target lesions can be designed as the inverse regulation of each selected biological function. By way of example but not limited thereto, for OA, MCI and OP, especially PMO, the regulations leading to the healthy physiological states are shown in FIGS. 1 to 4 and FIGS. 8 to 12.

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

[0177] When gene expression is selected as a marker, the genes that are the cause of the modification of each biological function causally related to each selected hallmark of the pathological state and the expression pattern of each of these genes can be retrieved by those skilled in the art from standard techniques, and this task can be facilitated by using ad hoc bioinformatics tools. The same Qiagen IPA mentioned above is a scientific literature aggregator that enables searching for information on genes / proteins and constructing a network for predicting the behavior of biological systems according to the gene expression state, and is thus suitable for the rapid screening of such information from scientific literature.

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

[0179] The use of the "IPA Bioprofiler" enables those skilled in the art to identify the expressed genes causally related to each of the specified biological functions and the specific molecular pathways that support them. Next, in order to define the regulation of the genes affected and the related biological functions, information regarding the measured gene expression data induced by each batch (e.g., fold change cut-off ≤ -2 and ≥ +2 and p-value ≤ 0.05 according to the manufacturer's instructions) was overlaid on the obtained network.

[0180] Once the most relevant genes and their expression patterns that are the cause of the detectable modifications in the target pathological state for each of the selected biological functions are identified, for each of these genes, an expression pattern opposite to the identified expression pattern is set as the expression pattern indicating the healthy physiological state of the biological function.

[0181] As described above, the regulation of biological activity is divided into downregulation or upregulation according to the related gene regulation. Based on the literature, the expected calculated effects resulting from the related biological functions can be determined by the "IPA Molecular Activity Predictor" tool (MAP) and can be resumed in a heatmap visualization using color codes that can be easily converted to numerical values by the user.

[0182] Step ii) of the method of the present invention is ii) analyzing the regulation 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 regulation of each of the markers induced by the gold standard, calculating the Z-score value of the regulation of each of the biological functions induced by the gold standard, thereby providing the gold standard cut-off Z-score value of the regulation of each of the biological functions indicating the desired therapeutic effect.

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

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

[0185] Suitable in vitro cell-based assays are assays designed, for example, to mimic a disease resulting from the nature of the cells used or to induce 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 related to the disease being modeled is selected. As an example, when studying OA, a suitable and recognized cell-based assay is one using chondrocytes, which are a disease model of OA recognized in the art, treated with IL1B. As a further example, when studying a neurodegenerative disease, a neuronal cell line such as SH-SY5Y, or primary neurons can be selected, or primary cells that can induce the desired phenotype by "injury" with a given compound can be used.

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

[0188] For the study of cancer, a viability test can be performed using a suitable cell-based assay (depending on the cancer of interest).

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

[0190] In the case of a cell-based assay where a diseased condition must be induced by the injury, in order to validate that the modulation of the selected biological function has the same trend as the modulation expected to result in a healthy physiological state, the assay cells can also be directly tested with the product of interest. This is particularly useful for evaluating the beneficial (homeostasis-adjuvant) effect of the product.

[0191] The cell-based assay preferably includes appropriate control groups, such as untreated cells, vehicle-treated cells, and cells treated with a compound known not to affect the disease phenotype. These controls help to distinguish the specific effects of the test compound.

[0192] If the marker and its regulatory pattern correspond to the gene and its expression pattern that are the cause of the detectable modification in the diseased state for each of the selected biological functions, a transcriptomics analysis is performed on an appropriate in vitro cell-based assay representing the diseased state of interest, and the gene and its expression pattern that are the cause of the detectable modification in the diseased state for each of the selected biological functions can be identified. When the disease phenotype is caused by the administration of a specific agent to cultured cells, the modification representing the diseased state is the unmodified cells versus the modified cells, and the modification induced by the gold standard is the modified cells + gold standard versus the unmodified cells.

[0193] Transcriptome analysis can be performed using any suitable technique known in the art, including next-generation sequencing and gene expression microarrays, to evaluate the transcriptome expression profile in basal cells, as opposed to cells that have been treated to mimic a diseased state, and to identify genes that are significantly differentially expressed and their expression patterns. According to the method of the present invention, when the expression pattern of genes that are significantly differentially expressed in cells representing a disease phenotype versus cells before injury that induces the disease phenotype is evaluated, the opposite expression pattern is considered to represent a healthy physiological state.

[0194] When gene expression is the selected marker, for each biological function identified in i)b, the genes and their expression patterns that are the cause of the detectable modifications in each of the biological functions in the diseased state can be identified from standard techniques using appropriate tools.

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

[0196] The 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 intersect 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, R. M. 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).Still relying on statistics, but this is more powerful than gene set enrichment as it utilizes knowledge about the direction of the effect rather than just an association.

[0197] In a preferred embodiment, one of ordinary skill in the art can follow the protocol described in the publication of Kramer et al, Bioinformatics vol 30 no 4 2014, pages 523 - 530 "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" or the manufacturer's instructions for (IPA version 94302991 Qiagen). The methods and algorithms disclosed in this paper enable one of ordinary skill in the art 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 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 readily performed by one of ordinary skill in the art by using Ingenuity Pathway Analysis (IPA version 94302991 Qiagen), a well-known pathway analysis utility among the life sciences research community that is cited in tens of thousands of papers enabling an understanding of the causal relationships between diseases, genes, and networks of upstream regulators.

[0199] A desired regulation of a biological function is defined (i.e., representing a healthy physiological state), and when a desired regulation of a relevant marker (e.g., ROS scavenging activity, gene, etc.) is identified for a target pathological state according to point i) of the method, an analysis of the selected marker regulation (e.g., in the case of gene expression, transcriptome analysis) in the same in vitro cell-based assay representing the pathological state is performed at the time of cell treatment, and the gold standard of the therapeutic product under test is carried out. As has been previously clarified, the gold standard has a previously evaluated therapeutic effect or beneficial effect. Determine the qualitative-quantitative regulation of the marker (e.g., expression of the target gene) induced by the gold standard, calculate the Z-score value for each regulation of the selected biological function, and subsequently use it as the gold standard Z-score cut-off value for each regulation of the biological function showing the desired therapeutic effect.

[0200] The gold standard of the product tested is, as described above, a batch of the product of interest whose therapeutic effect or beneficial effect has been evaluated in vitro or in vivo, preclinically or clinically. 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 regulation of each biological function obtained from the analysis performed in ii) is regarded as the reference Z-score value representing the desired therapeutic effect or beneficial effect. As an example, when the desired regulation of biological activity is upregulation, the cut-off Z-score value is equal to or higher than the gold standard (reference) Z-score value, and when the desired regulation of biological activity is downregulation, the cut-off Z-score value is equal to or lower than the gold standard (reference) Z-score value. The reference Z-score value can also be adjusted when performing the cell-based assay with one or more reference drugs (i.e., drugs known in the art indicated for the treatment of the disease state of interest), as described below. These drugs are expected to regulate at least a part of the selected biological function in a desired trend, but due to their different mechanisms of action (SAR), these drugs are expected to regulate only a part of the selected biological function in a desired trend. Therefore, as will be described in more detail below, the adjustment of the reference Z-score value considering the drug Z-score value is performed only for the biological function regulated by the test drug in the same direction as the healthy physiological state.

[0202] The Z-score values of steps ii) and iii) are calculated to represent the directionality and magnitude of the regulation for each biological function exerted by a given batch of the product. In the case of transcriptomics, those skilled in the art can use the IPA version 94302991 core analysis of Qiagen to easily obtain the aforementioned Z-score values 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 method is provided below (overlay analysis). Step iii) of the method of the present invention is iii) Analyze in the in vitro cell-based assay the regulation patterns of the markers specified in i) c. induced by further different batches of the product, determine the qualitative-quantitative regulation of each of the markers induced by each of the batches, and thereby calculate the Z-score value of the regulation of each of the biological functions induced by each of the batches.

[0204] Step iii) is carried out as step ii) using different batches of the product of interest. Since it is desirable to have at least 3 batches in compliance and 1 batch not in compliance with the gold standard Z-score cut-off, those skilled in the art will analyze at least 4 further batches of the product of interest.

[0205] Step iv) of the method is iv) Compare the Z-score value of the regulation of each of the biological functions induced by each of the batches calculated in iii) with the corresponding reference cut-off Z-score provided in ii), and select at least 3 positive batches in which each Z-score value of the regulation of each of the biological functions is in compliance with the corresponding reference cut-off Z-score value, and at least 1 negative batch in which at least 1 Z-score value of the regulation of each of the biological functions calculated in iii) is not in compliance with the corresponding reference cut-off Z-score value.

[0206] The batches of iii) considered to be in compliance are batches in which each Z-score value obtained from the analysis of the expression pattern specified in i) c. is above the reference cut-off Z-score value when the desired regulation of biological activity is up-regulation, and below the reference cut-off Z-score value when the desired regulation of biological activity is 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 acceptable reference for the final evaluation of the range or cut-off of the permissive spectrometry or spectrophotometry.

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

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

[0209] Since conventional drugs are expected to regulate only some of the biological functions selected for their mechanism of action (SAR) in the desired direction, only the Z-score values related to the functions regulated in the same direction of a healthy physiological state are considered.

[0210] As is known to those skilled in the art, reference drugs for treating a disease state may be known a priori to provide a therapeutic effect only against one or a few hallmarks of the disease. In this case, the information integrated into the method of the present invention relates only to the hallmarks of interest and the related biological functions.

[0211] In non-limiting embodiments of the present invention, steps i) to iv) can be carried out as follows using the IPA version 94302991 Qiagen: i) a. - c. Definition of the pathophysiological state of the standard techniques of the disease for examining IPA and the pathophysiological hallmarks of the disease The standard techniques of the pathophysiology of the disease of interest are investigated 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 is used to identify the hallmarks for examining IPA by the following procedure: · Each hallmark is written one by one into the "Disease and Function" query box and the search is initiated. · The resulting resumption list makes it possible to filter diseases / functions arising from many evidences. The sources of relationships are the Ingenuity Knowledge Base, including curations from journal articles, OMIM, JAX, and ClinicalTrials.gov. · The in-silico models are limited to genes and mRNAs.

[0212] Thus, the tool can associate each biological function with 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. An in vitro cell-based assay is performed by treating cells having a disease phenotype with different batches of the product of interest, reference drugs, etc., regardless of whether a given compound is a gold standard.

[0214] Transcriptome raw data analysis The whole transcriptome expression profile is evaluated in an in vitro cell model representing the disease of control cells and model cells. According to the manufacturer's instructions, the Human Clariom(™) S Pico Assay HT (Applied Biosystems, ThermoFisher Scientific) can be used with the GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific). 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 multi-chip analysis (SST-RMA) analysis algorithm, and provides a list of differentially expressed genes (Limma Bioconductor package). At this stage, the user can obtain a list of differentially expressed genes (DEGs) identified based on the relevant control experimental conditions, in this case, the fold change in expression relative to those that reproduce the pathological situation in vitro.

[0215] The transcription modification profile thus obtained is 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)]. By using IPA, the user can estimate how and to what extent the regulation of gene expression in a cell line (cell-based assay) affects the biological functions related to the disease of interest.

[0216] IPA pre-analysis filtering of the transcription profile (context 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 diseased state. Typically (e.g., according to the manufacturer's instructions), the fold change threshold is set to include values of ≤ -2 and ≥ +2, with statistical significance indicated by a p-value of ≤ 0.05. However, those skilled in the art have the flexibility to adjust the cut-off based on their expertise, taking into account successful implementation of a negative control (a sample representing the diseased situation) or a reference standard that can completely or partially cancel out the diseased situation.

[0217] Possible methodological approaches for extracting biological significance from a list of gene expression profile alterations via IPA can be of two types: "core analysis" and "overlay analysis of in silico models of pathophysiological states" (abbreviated as overlay analysis).

[0218] Therefore, at this stage of the procedure, one can proceed with two different alternative options.

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

[0220] By initiating "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. Subsequently, a network of the network eligible molecules is algorithmically generated based on their connectivity.

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

[0222] It is the responsibility of the skilled operator to carefully select the biological functions 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] Subsequently, the associated Z-score values are used to indicate the directionality and magnitude of regulation of each biological function.

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

[0225] "Overlay analysis" is constructed by using the following procedure to establish the relationship between the pattern of differentially expressed genes and the selected biological functions (always supported by annotations corresponding to scientific peer-reviewed publications demonstrating the direction and magnitude of the regulation of biological functions): □ Import a set of biological functions selected from an in-silico model of pathophysiological states into a new sheet called "my pathway". □ Use "construction tools" and "cultivation tools" to identify differentially expressed genes (DEGs) belonging to the transcriptome profile under investigation and related to the regulation of the biological functions selected in the previous step. □ The regulation of the identified DEGs is represented using green (indicating downregulation) and red (indicating upregulation). □ "Overlay" and "molecular activity predictor" tools (MAP) are used to determine the expected calculated impact of such experimentally observed regulation of gene expression on biological function activity. Activate the "prediction" function within the MAP tool to calculate the expected regulation resulting from the biological function. In this way, color coding is established: - Orange: increased activity - Blue: decreased activity - White: impossible to achieve / impossible to predict

[0226] Instead of directly calculating the Z-score for each biological function, "overlay analysis" provides results regarding the color indicating the direction of modification and the intensity of the color signal proportional to the magnitude of the regulation of interest. Therefore, it is necessary to convert the intensity of the regulatory signal (plotted as a graph in the "My Pathway" 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 web port app of Pipeline Pilot, which aims to assign a score called Z-score to genes and biological functions based on the coloring within biological pathways generated by QIAGEN's Ingenuity Pathway Analysis software. An important step in 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), which is a colorimetric encoding that can record not only the RGB components but also the intensity of the color. This conversion is performed within the Pipeline Pilot "component" using procedures described using R software based on specific features of the colorspace package (https: / / cran.r-project.org / web / packages / colorspace / index.html, see Zeileis et al 2020 journal of statistical software, doi:10.18637 / jss.v 096.i 01 for details).

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

[0229] When the above protocol is carried out using a gold standard and optionally one or more reference drugs, the Z-score values obtained for each of the biological function modulations disclosed above are considered as reference cut-off Z-score values for the desired modulation of the function. Thus, if the desired modulation is up-regulation, the cut-off Z-score value corresponds to being equal to or greater than the reference Z-score value obtained according to this specification, and if the desired modulation is down-regulation, the cut-off Z-score value corresponds to being equal to or less than the reference Z-score value obtained according to this specification.

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

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

[0232] When the reference drug modulates one or more biological functions associated with the hallmark of the disease state of interest, it is also tested in an in vitro cell-based assay, and both the Z-scores obtained using the gold standard and the reference drug are considered valid for the one or more biological functions. Thus, it is assumed that the value associated with the weakest performance identifies the lower limit of compliance for each of the 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 is v) performing a spectroscopic or spectrophotometric analysis of the batch selected in the gold standard and iv) Non-limiting examples of spectroscopic analysis 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 methods.

[0234] In a preferred embodiment of the present invention, the spectroscopic analysis is carried out by NIR. In fact, as is known to those skilled in the art, NIR spectroscopy is a vibrational spectroscopic technique that provides qualitative information on the chemical species present in the analyzed material together with information on its physical state. Performing NIR analysis means irradiating the material with light of different wavelengths and measuring the vibrations of the material at each wavelength. The detected vibrations depend on the composition and the interactions between the components, which affect the vibrational ability of each component arranged within the matrix. This analysis generates a vibrational fingerprint characteristic of the material.

[0235] Analysis of the NIR fingerprint enables the reconstruction of a chemo-physical profile characteristic of the molecular composition of each analyzed sample, which is affected by the chemical environment. In fact, the molecules within the sample can form bonds, particularly hydrogen bonds, both intermolecularly and intramolecularly. This results in changes in the vibrational frequencies of both the stretching and bending of the hydrogen atoms, leading to a shift in the vibrational frequencies for a single isolated molecule. For this reason, NIR spectroscopy can be an excellent means of characterizing complex matrices. Thus, this technique is particularly suitable for the analysis of natural matrices, as it provides a fingerprint of the entire matrix network and the interactions between the components of the matrix.

[0236] An example of an NIR spectral profile is shown in FIG. 6.

[0237] Step vi) of the method is vi) defining as acceptable the range of the variance spectroscopy or spectrophotometry obtained by considering as acceptable each result obtained in v), thereby providing the acceptable range of the spectroscopy or spectrophotometry.

[0238] The range obtained depends on the spectroscopy or spectrophotometry technique used and the product being tested.

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

[0240] When using NIR, the acceptability cut-off obtained by the method of the present invention is suitable for use in the NIR compliance test for batch-to-batch compliance (i.e., validation of batches for manufacture).

[0241] It is clear that the compliance test must be performed using the same spectroscopic or spectrophotometric technique as that used for the evaluation of the tolerance range or acceptability cut-off.

[0242] To define the acceptability cut-off, obtain the complete NIR spectra of all samples and gold standards selected in iv), align and normalize the spectra (standard normal variate), thus define the target wavelength (λ) region of the spectra, and generate the average spectrum of the spectra of all compliant (positive) samples + gold standards.

[0243] The average spectrum obtained is Reference spectrum throughout the procedure.

[0244] In the execution of the NIR compliance test for pharmaceutical API-based products, the pretreatment includes the definition of the target λ region as described above (SNV), and the maximum compliance index value is commonly used in the compliance test and has conventionally been set as 3.5, which means that the maximum value of the standard deviation allowed for the pharmaceutical product at any point in the spectrum is usually 3.5.

[0245] In the method disclosed in this specification, the acceptance range or acceptance cut-off is not based on the quality quantification analysis of a specific chemical substance in the product, but rather on the regulatory activity exerted by the product on a selected biological function. Therefore, the maximum compatibility index (MCI) value conventionally imposed in the quality control of classical APIs related to qualitative-quantitative chemical composition cannot be considered empirically acceptable. Thus, the value is assigned based on the spectrum of the batch selected in (iv) and the gold standard.

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

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

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

[0249] Therefore, in the case of NIR spectroscopy, the CI limit, i.e., the acceptance cut-off, is calculated according to the following formula. CI=(A 参照,i -A サンプル,i ) / s 参照,i Wherein, A 参照,i = average absorbance (average spectrum) at a given wavelength (i) of the reference 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 described above, in the compatibility test related to heterogeneous samples, the Sum 2 parameter is more suitable. Sum 2 = (Total of all CIs > CI limit - CI limit) / (Total number of points within the spectrum having CI > CI limit)

[0251] The selection of appropriate parameters in the compatibility test depends on user-specific control issues that can be easily addressed by those skilled in the art. In the case of products containing one or more natural matrices, i.e., extremely heterogeneous samples, Sum 2 is the appropriate parameter.

[0252] In one embodiment of the present invention, the Sum 2 parameter is selected to determine the acceptance cut-off of the compatibility test.

[0253] Depending on the spectroscopy or spectrophotometry used, the acceptance range or acceptance cut-off is calculated by making the necessary changes and defining the acceptance values obtained from the batches and gold standards selected in iv) at the same ratio as used for NIR spectroscopy.

[0254] According to the present invention, when performing a method for the compliance validation method (compatibility test) of one or more batches of a product containing a complex natural system for treating a pathological condition, the batch may result in non-compliant results in the first analysis.

[0255] In that case, it may be of concern to validate whether the non-compliance result is due to an effective non-compliance of the batch due to the desired regulation of biological function (i.e., therapeutic effect), or can be extended, and thus due to an acceptable parameter that allows adjustment of the parameter.

[0256] According to the method of the present invention, step iii) can be repeated for the batch, and when the Z-score value of each regulation of the biological function conforms to the corresponding cut-off Z-score value, the tolerance range or tolerance cut-off is corrected (recalculate the tolerance range or tolerance cut-off) by defining the previously obtained non-conforming batch as conforming.

[0257] The highest is the number of conforming batches identified in step iv), and the tolerance range or tolerance cut-off obtained by the method of the present invention becomes more accurate.

[0258] Thus, in one embodiment, according to the method of the present invention, iii) one or more additional different batches of the product of the method (for example, to increase the number of acceptable batches according to step iv), unacceptable spectroscopy or spectrophotometry or one or more batches obtained by the first screening with simply additional batches) are carried out, and one or more additional batches in which the Z-score value of each regulation of the biological function conforms to the corresponding cut-off Z-score value are subjected to the same spectroscopic analysis or spectrophotometric analysis as carried out in v), and the tolerance range or tolerance cut-off defined in vi) is recalculated by defining each of the batches as acceptable as well.

[0259] Furthermore, the method also, in any of the embodiments disclosed herein, vii) a step of performing spectroscopic analysis or spectrophotometric analysis of one or more empirically undesirable batches of the product, wherein the one or more undesirable batches are within the tolerance range or tolerance cut-off defined in iv) and do not result in a negative (i.e., a batch within the tolerance range of the cut-off defined in iv)) to validate, viii) further includes a step of defining a new, narrower variable spectroscopy or spectrophotometry 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 compounding errors expected from the manufacturing chain such as lack of ingredients are excluded in advance from the tolerance range or the tolerance cut-off.

[0261] The present invention also relates to a method for evaluating the gold standard of a product for use in the treatment of a pathological condition, comprising one or more natural matrices, and comprising the following steps: i) d. searching from standard techniques for a list of hallmarks of the pathological condition and one or more reference drugs for treating the pathological condition; e. identifying, for each of the hallmarks, a set of modifications of biological functions detectable in the pathological condition, determining for each of the functions the regulation associated with the desired therapeutic effect, thereby designing a regulation pattern for each of the functions representing a healthy physiological state; f. identifying, for each of the biological functions, the markers that are the cause of the modifications detectable in the pathological condition and their regulation patterns, and for each of the markers, setting a regulation pattern opposite to that identified as the regulation pattern indicating the healthy physiological state; ii’) analyzing, in the in vitro cell-based assay, the regulation pattern of each of the markers identified in i) c. induced by the one or more reference drugs, determining the qualitative-quantitative regulation of the expression of each of the genes induced by the one or more drugs with respect to the control of the pathophysiological state of the in vitro cell-based assay, and calculating the Z-score value of the regulation of each of the biological functions induced by the one or more drugs that provides the reference cut-off Z-score value for the regulation of each of the biological functions indicating the desired therapeutic effect; iii’) Analyze the regulatory patterns of the markers specified in i’) c. induced by two or more different batches of the product in the in vitro cell-based assay, determine the qualitative-quantitative regulation of the expression patterns of each of the genes induced by each of the batches, and thereby calculate the Z-score value of the regulation of each of the biological functions induced by each of the batches. iv’) Compare the Z-score value of the regulation of each of the biological functions induced by each of the batches calculated in iii’) with the corresponding reference cut-off Z-score value, and select as the gold standard the batch that provides the best performance Z-score value for each Z-score value of the regulation of each of the biological functions with respect to the corresponding reference cut-off Z-score value.

[0262] Steps i’) a to c are carried out, with the necessary modifications, as steps a’) a to c described above and in the examples.

[0263] Also, steps ii’), iii’) and iv’) are carried out, with the necessary modifications, as steps ii), iii) and iv) of the method described above and in the examples.

[0264] The markers and their regulatory patterns described above for the method of defining the tolerance range or tolerance cut-off for spectroscopic or spectrophotometric analysis for the validation of one or more batches of a product are applied, with the necessary modifications, to the method for defining the gold standard. Thus, in one embodiment, the markers are genes and their regulation is their expression patterns.

[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, the product comprising one or more natural matrices (defined above), and the following a. Performing a spectroscopic or spectrophotometric (as defined above) analysis of each batch of interest b. validating each batch whose acquired spectrum meets the tolerance range or permissive cut-off identified according to the method described above and in claims 1-10 using the same spectroscopic technique as that used to define the tolerance range of the cut-off.

[0266] Considering the fact that the method of the present invention provides reliable parameters for batch-to-batch validation for compliance of products containing or consisting of one or more natural matrices, those skilled in the art will recognize that the tolerance range or permissive cut-off is a process calculated from the gold standard spectroscopic or spectrophotometric spectrum of the product, where the gold standard has a confirmed homeostatic adjuvant effect in maintaining the healthy physiological state of the system, organ or device, and the product of one or more different batches, and the spectrum is defined as acceptable based on the biological activity exerted by the one or more different batches of the product on the gold standard and one or more biological functions underlying the healthy physiological state in a cell-based assay. It will be readily understood that the method of the present invention can be applied, with the necessary modifications, to define the tolerance range or permissive cut-off for spectroscopic or spectrophotometric analysis for the validation of one or more batches of products that adjuvant the homeostasis of a target system, organ or device containing or consisting of one or more natural matrices.

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

[0268] In any part of the specification and claims, the term "comprising" can be replaced with "consisting of".

[0269] The following examples do not limit the present invention.

[0270] Example 1. Composition of the test product Arte GX (Figs. 2 - 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 dried extract 1% w / w Royal jelly lyophilized product 1% w / w Blueberry dried extract 0.29% w / w Concentrated blueberry juice 5% w / w Concentrated apple juice 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 dried extract 0.05% w / w Equisetum arvense dried aqueous extract 1.37% w / w Malpighia emarginata dried extract 1.50% w / w Sugarcane fine powder 48.95% w / w

[0271] 2. In vitro cell assay representing osteoarthritis An in vitro cell model [1-3] that can reproduce the characteristics of osteoarthritis was established by exposing primary human chondrocytes (HC, Cell Application INC 402K-05) to IL1B [5 ng / ml] for 6 hours and then to five different batches of "Arte-GX" [1.4 mg / ml] for 24 hours: □ Batch 20B1955 (Gold Standard) □ Batch 20I1279 □ Batch 20J1770 □ Batch 20B0596 □ Immediately consecutive, aliquots of the batch that induced destabilization of batch 21E1640 and the product called batch DEST 21E1640 in this specification were also analyzed (see Figures 3 and 4).

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

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

Table 2

[0274] 2.1.2. Gene expression analysis At the end of the above treatment period, the cells were washed with 100 μl of PBS, lysed, and recovered 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 the cell lysates using the QIAsymphony RNA kit (Qiagen) equipped with a QIAsymphony SP instrument (Qiagen).

[0275] The quality and quantity of RNA were determined by A230, A260, A280, and A320 measurements using a Varioskan (trademark) LUX multimode microplate reader (Thermo Scientific (trademark)). The integrity of RNA was confirmed using the 2100 expert_Eukaryote Total RNA Nano Kit (Agilent). The whole transcriptome expression profile was evaluated according to the manufacturer's instructions using the Human Clariom (trademark) S Pico Assay HT (Applied Biosystems, ThermoFisher Scientific) on a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific). Briefly, 6 ng 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. The array was washed, stained, and then scanned using a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific), and a CEL Intensity file was generated by Affymetrix GeneChip Command Console software (AGCC, ThermoFisher Scientific).

[0276] 2.1.3. Transcriptome Data Analysis Data analysis was performed using 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, p - value ≤ 0.05).

[0277] 2.1.4. Bioinformatics modeling of experimentally observed transcriptome data For each study batch, Ingenuity Pathways Analysis (IPA) (QIAGEN\Inc., https: / / www.qiagenbioinformatics.com / products / ingenuitypathway - analysis)[4] was used to evaluate the regulation of gene expression related to the effect of interest.

[0278] IPA is an aggregator of scientific references that enables the search for information on genes / proteins and the construction of networks that predict the behavior of biological systems according to their gene expression states.

[0279] The pathophysiological characteristics of the "osteoarthritic condition" of standard techniques were examined with particular attention to the following involved areas.

Table 3

[0280] This knowledge was used to interrogate IPA via the "IPA Bioprofiler" tool using the following keywords: osteoarthritis, arthrosis, cartilage tissue formation, cartilage tissue 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. Next, to define the regulation of the genes affected and the related biological functions, information on the measured gene expression data (fold change value cut-off ≤ -2 and ≥ +2 and p-value ≤ 0.05) induced by each batch was overlaid on the resulting network.

[0282] The regulation of the expressed genes was shown in different intensities of blue (indicating downregulation) or red (indicating upregulation). Based on the literature, the predicted calculated effects resulting as a consequence for the related biological functions were determined by the "IPA Molecular Activity Predictor" tool (MAP) and resumed in the heatmap visualization.

[0283] Its color and intensity were converted into numerical values.

[0284] 2.1.5. Results From the results of these tests, the comparative results of the performance and mechanism of action of five different batches of Arte GX were obtained. 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. Clearly, the induction of slightly different transcriptional patterns still results in the same desirable regulation of biological functions. This is due to functional redundancy in the interaction between the components of the product and the body, whereby different compositions induce the same effect through a multi-focal mechanism of action (Figures 3 and 4).

[0285] Therefore, since the induction and repression patterns are conserved, the five batches are considered to have equivalent biological outputs.

[0286] The different transcription patterns and relative biological effects of different batches are adopted as hallmarks of the inherent variability present in preparations composed of biological materials. From the results summarized in Figure 4, it is clear that the observed transcription patterns of five different batches induce highly reproducible biological effects and result in general modifications of the equivalence of the pathological methods and overall pathological conditions of all batches reported in Figure 4.

[0287] 3.1. Targeted metabolomics To understand whether the final matrix constituting "Arte GX" is characterized by matrix effects, a series of analyses were performed on the batches reported above to grasp the characteristics of the product in different aspects. Targeted metabolomics analysis, which can identify most of such molecular components, was performed together with the other analyses reported herein.

[0288] As described above, the product consists of two assembled plant matrices, resulting in a final new plant matrix. Several analytical techniques are used to identify and quantify the compounds belonging to the major classes present in the plant. Although metabolomics analysis does not contribute to grasping the dynamic changes within the components of the matrix, it enables a "picture" (visual cutout) of the composition at the moment the analysis is performed.

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

[0290] For ArteGX, based on the use of multiple analytical methodologies, an "omic" approach, targeted metabolomics analysis, was used to perform qualitative and quantitative characterization of as many primary and secondary metabolites as possible.

[0291] The analytical methods used for the chemical characterization evaluation of each batch are described below. Based on the chemical properties of the classes of compounds present, the most appropriate analytical techniques have been employed. Analysis by chromatography methods combined with different detection techniques (e.g., GC and LC combined with their respective appropriate detectors) made it possible to identify and quantify organic compounds as necessary. 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 classes of substances that could not be quantified by chromatography methods.

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

Table 4

[0293] The results summarized in the following table show significant compositional variations for each batch, highlighting that it is not possible to reproduce the properties of the matrix as the sum of its individual components. The studies conducted and reported herein (refer to the cell-based assay results), along with the following data, demonstrate that the biological effects induced by the product cannot be reproduced by the sum of the effects induced by single molecular components, but rather are the result of interconnections and interactions between components: the matrix effect. This leads to the fact that it is not possible to formally define a structure-activity relationship (SAR) according to the principles typically applied to 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 that significant quantitative variations in the individual chemical substance classes are found in five batches of co-extracts. These variations, when considered as reference parameters, lead to the empirical view that these batches have different biological activities and exclude batches that do not match the gold standard. This is the case when the applied criteria are effective for APIs acting via the key-lock paradigm due to the presence of an obvious SAR. The analysis reported here newly shows (argues) the fact that none of the identified single molecular components comply with 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 described above, the biological activity is conserved for each batch.

[0296] Therefore, Figure 5 shows that it is not typical and thus incorrect to rely solely on the quantitative analysis of individual components to estimate the reproducibility of the activity profiles of complex matrices. In fact, considering exactly the nature of the composite matrix, qualitatively different chemical profiles that should be considered different from a chemical perspective instead cause the same reactions related to the intended use in biological systems. This is not a surprising observation, but another proof that the biological activity of the composite matrix cannot be traced back to the sum of the activities of each single molecule within the matrix itself (i.e., from a chemical perspective). Therefore, the activity of the matrix does not exclusively depend on the identity and amount of the molecules constituting the matrix.

[0297] This also emphasizes the fact that both the structural and functional redundancy mechanisms that give a particular resilience to the matrix, i.e., as shown above, have the ability to mediate the same activity for quantitatively different compositions of different qualities. In other words, studying the matrix from the perspective of exclusive molecules is incorrect because the identity of its individual components does not reflect its characteristics. This confirms the need for methods that can explain the inherent properties of the matrix rather than just looking at its molecular components. These methods, as provided in the present invention, should monitor the preservation of the parameters on which the maintenance of biological activity actually depends.

[0298] 3.2. Near-infrared spectroscopy (NIR) 3.2.1. Introduction To create a reference chart and provide an NIR acceptance cut-off, four batches of ArteGX made at industrial scale (including the gold standard) and prototypes selected as positive batches according to steps i) - iv) of the method of the present invention were analyzed to form a library of good-quality samples (training set). The batches used to construct the training set were selected after passing the compatibility tests conducted through the biological assay of the present invention (see also the above example).

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

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

[0301] The acceptability parameters were defined and two poorly formulated products (R19L4299 and R19L4298) and an unknown ArteGX batch (21E1640) as defined above were analyzed as test samples using the same operating method. Depending on the results obtained after analysis by the compliance test, the test samples were confirmed to be of good quality or not according to whether they passed the compliance test performed via a biological assay to confirm or, in some cases, correct the acceptability criteria specified by the control card.

[0302] The aim of this test study was to construct a control map of the NIR spectrum, which was defined a priori by the assessment of the compliance of the biological activity of the batches that are part of it and is defined as a fingerprint used to identify effective compliance batches of Arte GX from samples of poor biological quality and / or formulation quality.

[0303] The following is a list of the four batches used to create the NIR library and a list of the samples analyzed as tests. □ Four batches of Arte GX for library construction (Table 1) lyophilized □ One low-quality batch of Arte GX (low biological activity quality) □ One batch of Arte GX as a library test (Table 2 without parentheses) lyophilized □ Two poorly formulated products ((Table 2 without parentheses)

Table 6

Table 7

[0304] 3.2.2. Machine Bruker NIR spectrometer, model MPA (multi-purpose analyzer): · Resolution: 16 cm-1 · Wavenumber reproducibility: better than 0.04 cm-1 · Wavenumber accuracy: better than 0.1 cm-1 · Photometric accuracy: 0.1%T · Wavenumber range: 4000~12500 cm-1 · Background scan: 64 · Scan for sample acquisition: 64

[0305] 3.3. Statistical test Compliance test The compliance test is a simple method for testing the deviation of the measured NIR spectrum within a specific range. In order to set these limits (acceptability cut-off), it is necessary that good and bad samples belong to at least one batch or manufacturing cycle of the final product specified as the reference spectrum. According to the present invention, the reference sample is identified by a biological assay (cell-based assay) considered appropriate (steps i) to iv) of the method of the present invention) and is tested and studied by NIR to evaluate the minimum range of specifications including the batch itself. According to the present invention, this range is imposed as acceptable to recognize whether batches of unknown compliance comply. The NIR spectra of these samples can achieve compliant and non-compliant performance with respect to biological activity and reflect different variations of samples that can form a confidence band within the spectral range. In order to pass the NIR compliance test, the spectrum of the new sample must fall within this confidence band. First, the mean and standard deviation of the absorbance values at 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 allowed for the product analyzed over each spectral wavelength.

[0306] Second, it is necessary to check whether the spectrum of the sample being tested is within the defined confidence band within the spectral range. The difference between this sample and the average of the reference samples is calculated at each wavelength (i). Next, this absolute deviation is weighted by the corresponding standard deviation "s" of each 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 = Mean absorbance (mean spectrum) at a given wavelength (i) of the reference 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 (mean spectrum)

[0307] In the conformity test, another parameter can be used to apply the limit of CI to evaluate the test against the reference library.

[0308] This parameter, called Sum 2, is represented as follows. Sum 2 = (Total of all CIs > CI limit - CI limit) / (Total number of points within the spectrum having CI > CI limit)

[0309] The selection of appropriate parameters in the conformity test depends on user-specific control issues that can be easily handled by those skilled in the art. In the case of products containing one or more natural matrices, i.e., extremely heterogeneous samples, Sum 2 is the appropriate parameter.

[0310] Therefore, in this case, the Sum 2 parameter was selected to determine the pass / fail cut-off for the conformity test.

[0311] 3.3.1 Sample Preparation Each sample was transferred to a sample holder suitable for NIR analysis of heterogeneous solids. Before analysis, it was confirmed that the bottom of the sample holder was completely covered.

[0312] 3.3.2 Sample Acquisition To ensure high reproducibility of the data, NIR spectra were acquired in reflection mode using a rotating sample holder suitable for the analysis of non-uniform solids as well as samples such as powders.

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

[0314] The samples reported in the previous tables (Tab 1 and Tab 2) were prepared and analyzed by NIR as described above.

[0315] 3.3.3. Data Pretreatment Pretreatment is a mathematical operation to extrapolate spectral features and reduce sources of variation.

[0316] For the development of the reprocessing method, a pretreatment method including the use of SNV normalization was selected, and the spectral region of 4200 - 9000 cm -1 was selected as the spectral region most relevant to the model.

[0317] OPUS software (Opus 8.5, Bruker) was used for the implementation of the fitness test.

[0318] By applying the pretreatment method, the following parameters in the OPUS fitness index method were set: a) Pretreatment: SNV; b) Region: 4200 - 9000 cm-1; c) Fitness test parameter: maximum fitness index value; Sum 2 3.3.4. Data Acquisition

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

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

[0321] SNV preprocessing was performed, and the region of 4200~9000 cm -1 was selected as the region for data reprocessing. The CI MAX threshold and Sum 2 value of the card batch are shown below:

Table 8

[0322] As described above, the maximum compatibility index value is assigned based on the maximum CI MAX value defined by training with compliance (conformity: positive) samples by cell-based assay. From the initial data (reported above), the CI limit was set to 1.5, and thus this value was used to calculate the Sum 2 of the training set and the test set.

[0323] To define the compatibility limit of Sum 2, the negative batch (i.e., steps i) to iv)) of the method of the present invention (biological data (cell-based assay) that does not comply (is not conforming)) DEST 21E160 was tested against the control chart. The following table shows the results regarding the CI and Sum 2 of each batch.

Table 9

[0324] Based on the Sum 2 value of batch DEG 21E1640 and its non-compliance with the cell-based assay, the threshold Sum 2 value for defining the batch as non-compliant is thus set to ≦1.2. When this tolerance cut-off is set according to the method of the present invention, new unknown batches of Arte GX and batches of known formulation non-compliance are tested to validate the reliability of the method of the present invention and its compliance with the quality control method according to the specification and claims.

Table 10

[0325] Thus, using the acceptance cut-off evaluated by the method of the present invention, the NIR assay showed that batch 21E1640 complied with the validation method of the present invention.

[0326] To confirm the validity of the validation method of the present invention, the regulation of the biological functions identified for the above product Arte GX was also performed for batch 21E1640, and the product showed results that were compliant in light of the reference Z-scores according to steps ii) to iv) of the method of the present invention.

[0327] Therefore, a technique and method have been identified that enable the definition of criteria for product acceptability. The product is a product comprising or consisting of one or more natural matrices, and the method and process are based on preserving a number of selected biological activities, without considering the notion of its composition at the molecular level.

[0328] 4. Radical scavenging activity As a further control for the effectiveness of the techniques and methods of the present invention, all of the above Arte GX batches were also tested for their radical scavenging activity, since this activity 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 due to scavenging activity.

[0330] Tests were performed on five different batches of Arte GX. The concentration was 1.4 mg / ml, and a dilution factor of 2.8 was applied for calculation to reflect 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 oxidation promoter 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 minutes for a total of 90 minutes) using a fluorometer (Varioskan Lux, Thermo-Scientific) and correlated quantitatively with the production of free radicals in the cells. To account for the number of cells at the end of the assay, all calculated fluorescence values were normalized with respect to the relevant cell viability measured by the MTT (tetrazolium salt, [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, Sigma Aldrich) assay performed according to the manufacturer's instructions. The degree of protection from ROS generation provided by the tested product was 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 area under the curve (AUC) of the fluorescence integration versus time plot calculated for AAPH (considered 100% ROS production).

[0332] 4.2. Results Figure 7 shows the equivalent radical scavenger activity of all five batches of Arte GX. All batches show an equally significant protective effect against fibroblasts.

[0333] The above data provides further qualitative assurance that the five batches are equivalent with respect to the induction of the same biological effects due to their influence on gene expression and radical scavenging activity.

[0334] The percentage (Z-score) was calculated as shown in Figure 12.

[0335] All batches complied with the Z-score values specified for the gold standard. Therefore, the NIR cut-off calculated as above also provided confirmation that the techniques and methods of the present invention using different markers to monitor the regulation of the selected biological functions are appropriate.

[0336] 4. Isotope Abundance 4.1. Introduction The analysis of isotope abundance is a method of describing substances from an atomic perspective. The isotope distribution characterizing the starting material can be affected by phenomena of different natures, which can lead to significant variations in the final product [ISPRA, Quaderni-Laboratorio 2 / 2018. ISBN 978-88-448-0873-0]. The isotope composition of a sample is equal to the ratio of the abundance of the heavy isotope form to the abundance of the light isotope form (e.g., the relationship 13C / 12C) and is expressed as the deviation per thousand from an internationally specified standard reference material. A positive value of δ indicates that the heavy isotope is enriched in the sample compared to the standard, and a negative value indicates a deficiency of the heavy isotope in the sample.

[0337] A significant difference in the isotope abundance ratio of a sample compared to a sample known to be of good quality can be explained by different intra- and intermolecular interactions between the phytochemical classes constituting the matrix. There is no need to consider the quantitative profiles of individual species and different chemical reaction kinetics. In the first case, this phenomenon is defined as the geometric isotope effect (GIE) and is due in particular to hydrogen bonding. 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 of both the intramolecular and intermolecular structures.

[0338] The isotope abundance also changes the kinetics of reactions known as kinetic isotope effects (KIEs). The effect can be either primary or secondary and depends on whether the isotope makes the reaction faster or slower than the way the isotope is incorporated into the product. Thus, it is clear that KIEs demonstrate the relationship between the abundance of a given isotope in a substance and its ability to interact with biological systems in a reproducible manner. Therefore, the analysis of isotope abundance can be considered a possible tool for monitoring product fitness from a physicochemical and potentially biological perspective.

[0339] As indicated by the change in the isotope abundance ratio in a batch, impurity incorporation and low product quality are considered. Considering samples representing different intermediates occurring during the manufacturing process may indicate that the isotopes with their desired native conformations are being lost overall.

[0340] In this regard, the acquisition of some good-quality batches of the product may lead to the generation of a reference library that can evaluate individual batches and validate isotope reproducibility within established ranges, along with established fitness validation techniques such as NIR.

[0341] Furthermore, 14C activity assessment can define the system as 100% natural. This is because 14C is an unstable isotope (half-life 5730 years), so petroleum derivatives have a very low presence of this unstable carbon isotope, but it accumulates easily in biological materials.

[0342] 4.1.1. Results and Discussion The analysis of isotope abundance was included in the development and validation of the NIR method and was thus performed on five batches constituting good-quality batches (20B0596, 20B1955, 20I1279, 20J1770, 21E1640), with batches 20B0596 and 20B1955 prepared from different batches of starting materials with respect to batches 20I1279, 20J1770, and 21E1640.

[0343] The samples were sent to the Chelab (Tentamus Company) Institute and tested for stable isotopes as follows: -δ18O: Method IRMS, UNIT ‰ V-SMOW. -δ13C: Method QMA-M-01, EA-IRMS, UNIT ‰V-PDB. The 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 above table include the percentage error according to the official method used) The measured values of the C14 activity of the Pmc samples correspond to the measured values of substances from pure bio-based carbon. There is no evidence of synthetic sources in the analyzed substances. Since the C14 activity values are not affected by the biological variability of the starting materials, they completely overlap between batches, thus identifying a high reproducibility of the manufacturing method according to the preservation of this parameter.

[0346] For two batches of co-extracts (20J1770 e 21E1640), a study test of the isotope abundances during different steps of the manufacturing method was carried out.

[0347] The results are reported in the following table showing the δ ratios of the major isotopes of the raw plant parts of the co-extract centella-echinacea.

Table 12

[0348] The evaluation of the isotope abundance of the material along the manufacturing process indicates that the manufacturing process does not change the abundance ratio. Therefore, this method has been demonstrated to preserve the natural biophysical properties of the starting material.

[0349] The analysis of the batches subjected to the study showed a substantial similarity of the values and further showed the maintenance of the ratios during the manufacturing process. This result was consistent with the aforementioned NIR results. Therefore, all batches were judged to be similar and merged without considering outliers for the similar spectra.

[0350] 5. RNA Evaluation in Manufacturing Intermediates The evaluation of the biophysical properties of biological plant materials includes the evaluation of biological materials in manufacturing intermediates.

[0351] "RIC 199 EL 0, extract_BLEND CENT_ECH EL, batch R 20 I 4716" corresponds to the manufacturing intermediate of Arte GX at the ratio shown in Example 1 before ultrafiltration, namely the water co-extract of Centella Asiatica and Echinacea. The presence of RNA has been evaluated both quantitatively and qualitatively. After homogenization using a QIAshredder column before proceeding with the kit extraction protocol, RNA was extracted using a plant matrix-specific kit (RNeasy PowerPlant kit). The size distribution of the obtained RNA was performed using a Bioanalyzer 2100 equipped with RNA 6000 Nano, RNA 6000 Pico, and small RNA kits.

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

[0353] Next, to quantitatively evaluate the total RNA extracted from the samples, nucleic acid digestion was performed using the New England Biolabs nucleoside digestion mix kit. The RNA concentration was 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, to a further extent, indicate both the structural complexity and functional complexity that should be considered in product management as additional information.

[0355] For the purposes of quick reference and comparison, the experimental protocols used for the three different products described in Example 1 are summarized and shown in the following table.

Table 14

Table 15-1

Table 15-2

[0356] 5. Conclusions In summary, the data reported in this specification enables the identification of acceptance parameters. These parameters serve as a key for judging to ensure the quality of the manufacturing method of products containing or consisting of one or more matrices of biological origin (natural matrices). Interestingly, the data shows that monitoring the reproducibility of the composition at the molecular level alone does not lead to a beneficial strategy. This is because the strategy ignores the important characteristics of the matrix that affect the ability to induce a reproducible effect when used to treat biological systems. It is speculated 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 the composite matrix, the biological activity of the product strongly depends on the characteristics that can be more appropriately monitored by analyzing the carefully selected biophysical properties of the matrix.

[0357] Furthermore, when using only the target metabolomics data without using other data, it can prevent the evaluation of the same product for its ability to induce a reproducible biological effect for different batches (see Figure 5 versus Figures 3 and 4). This is especially the case when judged according to the principles usually ensured for a single API. Applying only targeted metabolomics will wrongly recognize that the batches are unacceptably different from each other. In contrast, by applying techniques for monitoring the characteristics of the matrix that are distinct and derived from the network of interactions, and that are either different from or only partially common to the methods relying on single molecular components, as disclosed in the present application, the similarity between the different analyzed batches can be accurately identified sufficiently, and its consistency with the fact that they actually induce a reproducible and desirable biological effect is shown.

Claims

**Claim 1** A method for defining an acceptance range or an acceptance cut-off for spectroscopic analysis or spectrophotometric analysis for the validation of one or more batches of a product, wherein the product is a product for use in the treatment of a pathological condition comprising or consisting of one or more natural matrices, the method comprising calculating the acceptance range or the acceptance cut-off from spectroscopic spectra or spectrophotometric spectra of the product and of gold standards of one or more different batches of the product, the gold standards having been confirmed to have a therapeutic effect for the treatment of the pathological condition, wherein the definition of whether the spectra are acceptable or unacceptable is made based on biological activity against one or more hallmarks of the pathological condition exerted in at least one cell-based assay by the gold standards and the one or more different batches, method. **Claim 2** The method according to claim 1, comprising the following steps: i) a. Searching a list of hallmarks of the pathological condition from standard techniques; b. Identifying, for each of the hallmarks, a set of modifications of biological functions detectable in the pathological condition, determining the regulation of each of the functions associated with the desired therapeutic effect, and thereby designing a regulation pattern for each of the functions representing a healthy physiological state; c. Identifying markers and their regulation patterns that are the cause of the modifications detectable in the pathological condition for each of the biological functions, and setting, for each of the markers, a regulation pattern opposite to that identified as the regulation pattern representing the healthy physiological state; ii) In an appropriate in vitro cell-based assay, analyze the expression pattern of each of the markers induced by the gold standard of the product in i), c. Determine the qualitative-quantitative regulation of each of the markers induced by the gold standard with respect to the pathophysiological state control of the in vitro cell-based assay, calculate the gold standard Z-score value for each of the regulations of the biological functions induced by the gold standard, and select each of the gold standard Z-score values as a reference cut-off Z-score value indicating the desired therapeutic effect. iii) Analyze in the in vitro cell-based assay the regulation pattern of the markers identified in i), c. induced by further different batches of the product, determine the qualitative-quantitative regulation of each of the markers induced by each of the batches, thereby calculating the Z-score value for each of the regulations of the biological functions induced by each of the batches. iv) Compare the Z-score value for each of the regulations of the biological functions induced by each of the batches calculated in iii) with the corresponding reference cut-off Z-score value, and select at least three positive batches in which each Z-score value calculated in iii) conforms to (matches) 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 conform to the corresponding reference cut-off Z-score value. v) Perform spectroscopic or spectrophotometric analysis of the gold standard and the batches selected in iv). vi) Define the range of variable spectroscopy or spectrophotometry obtained by considering each of the results obtained in v) to be acceptable for each positive batch and unacceptable for each negative batch, thereby providing the acceptable spectroscopy or spectrophotometry range or cut-off.

3. Step ii) is In the in vitro cell-based assay, for one or more reference drugs for treating the disease state, i) the regulatory pattern of the markers identified in c. is analyzed, the qualitative-quantitative regulation of each of the markers induced by each drug is determined, and the drug Z-score value of the regulation of each of the biological functions induced by each of the drugs is calculated, for each biological function modified by the one or more drugs in the direction of the healthy physiological state, the drug Z-score value is compared with the gold standard Z-score value, selecting the Z-score value associated with the weakest performance as the reference cut-off Z-score value The method according to claim 2, further comprising.

4. The method according to claim 2 or 3, wherein the marker and its regulatory pattern correspond to the gene and its expression pattern that are the cause of the detectable modification in the diseased state for each of the biological functions.

5. The method according to any one of claims 1 to 4, wherein the product is in a dry form or a lyophilized form.

6. Step iii) is performed on one or more additional different batches of the product, the Z-score value of the regulation of each of the biological functions is subjected to the same spectroscopic analysis or spectrophotometric analysis as that performed in v), and the tolerance range or tolerance cut-off defined in vi) is recalculated by defining each of the batches as acceptable. The method according to any one of claims 2 to 5.

7. vii) Performing spectroscopic analysis or spectrophotometric analysis on one or more empirically undesirable batches of the product, and validating that the one or more undesirable batches are within the tolerance range or tolerance cut-off defined in vi) and do not become negative. viii) Defining a new, narrower range or cut-off of variable spectroscopy or spectrophotometry obtained by considering each result obtained in vii) as unacceptable. The method according to any one of claims 2 to 6, further comprising.

8. The method according to any one of claims 1 to 7, wherein the product comprises or consists of one or more of cut or ground plant parts, plant extracts, fractions of said extracts, such as fractions obtained by filtration through a semipermeable membrane (microfiltration, ultrafiltration, nanofiltration) or by treatment with an adsorbent resin, or microorganisms, honey, propolis, silk, wax, plant resin, plant gum, plant exudate, vegetable oil, essential oil, animal tissue lysate, plant or animal fluid.

9. The method according to any one of claims 1 to 8, wherein the product is a medical device as defined in Article 2(1), Characteristics 1 to 3 of EU Directive 2017 / 745 or as defined in FDA Section 201(h)(1) of the US Food, Drug, and Cosmetic Act.

10. The method according to any one of claims 1 to 9, wherein the pathological condition is one of osteoarthritis, mild cognitive impairment, postmenopausal osteoporosis, cancer.

11. The method according to any one of claims 1 to 10, wherein the spectroscopic analysis is selected from NIR, FTIR, Raman, and the spectrophotometric analysis is selected from ultraviolet-visible spectroscopy, fluorescence spectroscopy, light scattering method.

12. A method for evaluating the gold standard of a product for use in treating a pathological condition, the method comprising the following steps, wherein the product comprises or consists of one or more natural matrices: i') a. Searching for a list of hallmarks of the pathological condition and one or more reference drugs for treating the pathological condition from standard techniques; b. Identifying a set of modifications of biological functions detectable in the pathological condition for each of the hallmarks, determining the regulation of each of the functions associated with the desired therapeutic effect, and thereby designing a regulation pattern for each of the functions representing a healthy physiological state; c. Identifying markers that are the cause of the detectable modifications in the pathological condition for each of the biological functions and their regulation patterns, and setting a regulation pattern opposite to that specified as the regulation pattern representing the healthy physiological state for each of the markers; ii') Analyzing the regulatory pattern of each of the markers identified in i’) c. by the one or more reference drugs in the in vitro cell-based assay, determining the qualitative-quantitative regulation of each of the markers induced by the one or more drugs with respect to the control of the pathophysiological state of the in vitro cell-based assay, and calculating the Z-score value of the regulation of each of the biological functions indicating the desired therapeutic effect induced by the one or more drugs that provide the reference cut-off Z-score value for the regulation of each of the biological functions; iii’) Analyzing the regulatory pattern of the markers identified in i’) c. induced by two or more different batches of the product in the in vitro cell-based assay, determining the qualitative-quantitative regulation of each of the markers induced by each of the batches, and thereby calculating the Z-score value of the regulation of each of the biological functions induced by each of the batches; iv’) Comparing the Z-score value calculated in iii’) with the corresponding reference cut-off Z-score value, and selecting, as the gold standard, the batch that provides the best performance Z-score value for each Z-score value calculated in iii’) with respect to the corresponding reference cut-off Z-score value. **Claim 13** The method according to claim 12, wherein the marker and its regulatory pattern correspond to the gene and its expression pattern that are the cause of the detectable modification in the diseased state for each of the biological functions. **Claim 14** A method for compliance validation of one or more batches of a product for the treatment of a diseased state, wherein the product comprises a complex natural system, the method comprising the following steps: a. Performing spectroscopic analysis or spectrophotometric analysis on each batch; b. Validating, as compliant, each batch whose obtained spectrum meets the tolerance range or tolerance cut-off specified according to the method according to any one of claims 1 to 11 using the spectroscopic analysis or spectrophotometric analysis technique of step a. A method comprising.

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