Biophysical-based verification of natural matrices for therapeutic use in humans, animals and plants

Abstract

The present invention relates to a novel method for defining the acceptable values of a spectroscopy or spectrophotometric spectrum for batch conformity verification by spectroscopic or spectrophotometric analysis of therapeutic or beneficial products, said products comprising or consisting of one or more natural matrices. The invention also relates to a novel method for the compliance verification of one or more batches of said product.

Description

Technical Field

[0001] The present invention relates to a novel method for defining the acceptability values of spectroscopic or spectrophotometric spectra for batch conformity verification by spectroscopic or spectrophotometric analysis of therapeutic or beneficial products, the products comprising or consisting of one or more natural matrices. The products comprising or consisting of one or more natural matrices are characterized in that the one or more matrices themselves exhibit unique emergent properties, i.e. properties that are different from the properties represented by the sum of the properties of their individual components. The invention also relates to a novel method for conformity verification of one or more batches of said products (batch conformity control in industrial production processes of products).

[0002] The present invention relates to a new batch control method for products comprising or consisting of a mixture of natural or plant matrices, said products being characterized in that one or more matrices themselves exhibit unique emergent properties that are different from the properties represented by the sum of the properties of their individual components. Background Art

[0003] The historical concept of granting patents in the public interest, particularly in health and safety matters, has its roots going back centuries. The rationale behind this is that while patents provide inventors with a temporary monopoly on their creations, the ultimate goal is to serve the greater good of society.

[0004] In modern times, this historical concept is reflected in the various laws and policies governing patents. It emphasizes the understanding that while inventors' contributions must be recognized and protected, society as a whole should ultimately benefit from these innovations, especially in areas critical to public health and safety.

[0005] In other words, the humanitarian basis of the patent system lies in its goal of striking a balance between promoting innovation and ensuring that the fruits of innovation are shared for the benefit of society as a whole. In particular, the patent system should ensure the sharing of knowledge and promote progress in the areas mentioned above.

[0006] In particular, the patent system can play a vital role in addressing humanitarian and global challenges. For example, it can incentivize the development of sustainable medicines, environmentally sustainable technologies, and solutions to pressing problems such as clean energy and water scarcity.

[0007] From the beginning of the 16th century until today, especially in the field of medicinal and beneficial products, standardization has been possible, so that only artificial substances produced by chemically definable alchemical processes can be verified.

[0008] This path, although very reductionist, has proven to be of great value, enabling the eradication of many diseases over the past five centuries, but is now encountering its limitations, which stem from the irrelevant nature of chemicals to life processes.

[0009] With regard to the development of new sustainable medicines, it is now also established that man-made (especially chemically synthesized) therapeutic products are having a detrimental impact on biodiversity and the innate immune system.

[0010] It is well known that synthetic APIs can enter ecosystems through multiple pathways, primarily through the discharge of pharmaceutical waste from manufacturing plants and the inappropriate disposal of unused or expired drugs. This can lead to the bioaccumulation of artificial and poorly biodegradable substances in aquatic and terrestrial organisms, potentially disrupting food chains and threatening biodiversity.

[0011] Studies have shown that exposure to synthetic APIs can cause adverse effects on aquatic organisms, such as altered behavior, reproduction, and even death. (Boxall, AB 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, RH (2015). Tysklind, M. and Larsson, DGJ (2015). Predicted critical environmental concentrations for 500 pharmaceuticals. Regulatory Toxicology and Pharmacology, 73(1), 607-616.)

[0012] It is well known that many synthetic APIs are designed to be biologically active and particularly stable, which may hinder their natural degradation process. As a result, these molecules will persist in the environment for a long time and may accumulate in soil and water. This reduction in biodegradability has caused concerns about 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].

[0013] In addition, there is growing concern about the potential effects of synthetic APIs on the immune systems of humans and animals. Some drugs have been found to interfere directly or indirectly with immune activity, leading to altered immune responses or increased susceptibility to infection. This may have a significant impact on individual health and population-level immunity [Vos T. et al. (2016). Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet, 388 (10053), 1545-1602; Calabrese, EJ, & Baldwin, LA (2003). Toxicology rethinks its central belief. Nature, 421 (6924), 691-692].

[0014] In summary, while synthetic APIs have undoubtedly contributed to advances in healthcare, their environmental and health impacts should be carefully considered. Efforts to develop greener medicines, improve waste management, and monitor environmental pollution are key steps in mitigating these issues.

[0015] Furthermore, it must be noted that natural molecules in natural matrices, although chemically similar to their synthetic counterparts if considered individually, may have fingerprints that are different from their synthetic analogs due to completely different synthetic pathways in terms of primary metabolites, reactants, reaction temperatures, energy sources, catalysts, etc., which may affect their physicochemical behavior and reactivity, and thus their biological functions.

[0016] 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. For example, estragol (1-allyl-4-methoxybenzene), identified in nature primarily in essential oils such as those derived from basil (Ocimum basilicum) and tarragon (Artemisia dracunculus), is known in the art for its potential aromatic properties and medicinal applications. The molecular makeup and associated energy profile of estragol, depending on its source, have been the subject of intense scientific scrutiny. While traditional views assume that the molecular properties are consistent, closer scrutiny reveals that subtle differences exist.

[0017] Given this premise, estragole, whether obtained from plant sources by distillation or synthesized within the laboratory context, should ideally be consistent with its inherent physicochemical properties.

[0018] However, it is crucial to distinguish the production pathways. In plant matrices, the biosynthesis of estragole is orchestrated through a series of enzymatic reactions starting from primary metabolites and terminating in this specific secondary metabolite. It is known in the art that each of these enzymatic transformations occurs in a different energy environment, potentially conferring a unique energy state on the molecule.

[0019] In contrast, laboratory synthesis of estragole relies on chemical reactions controlled by different precursors and conditions, such as temperatures incompatible with plant life. The energy dynamics of this synthetic pathway are governed by the intrinsic thermodynamics and kinetics of the reactions and likely deviate from the plant-mediated enzymatic pathway.

[0020] Furthermore, it is clear that the isotopic abundances produced by the two different pathways (natural and synthetic) are unlikely to be the same. It is known that even slight changes in isotopic abundance can have a significant impact on vibrational frequencies, bond strengths, and, inevitably, 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 isotopic differences between plant sources and synthetic reagents, the resulting estragole molecules may have different energy signatures and biological activities. In view of the above, although the chemical properties are similar, molecules of natural and synthetic origin are likely to have different energy fingerprints, which may affect their physicochemical properties, reactivity, and thus their biological functions. In fact, differences between the activities of synthetic and natural estragole have been reported in the art (Suzanne MF et al. “Basil extract inhibits the sulfotransferase mediated formation of DNA adducts of the procarcinogen 1′-hydroxyestragole by rat and human liver S9 homogenates and in HepG2 human hepatoma cells” Food and Chemical Toxicology, 2008, 46(6)2296-2302, https: / / doi.org / 10.1016 / j.fct.2008.03.010.).

[0021] Furthermore, synthetic molecules (molecules intended to be produced by humans through chemical synthesis laboratory / industrial processes) are designed to provide the desired interaction with a specific given target molecule, without taking into account all the interactions that the molecule may and will have within its natural matrix, with the environment and with the entire receiving network of the organism in which it will be used. On the other hand, natural biosynthetic molecules produced in a natural, non-artificial environment will inherently carry all the basic characteristics of existence and perform their functions in a competition of epigenetic determinations, the description of which is unattainable when using traditional deterministic chemical methods. Applied quantum biology can provide a possible deciphering of the natural matrix and biosynthetic molecules.

[0022] For thousands of years, products derived from natural sources have been used to prevent and cure human diseases. However, many studies have been limited to characterizing their chemical composition and single-molecule activity at the single-molecule level, while the spontaneous assembly, interactions, and supramolecular organization of all components of these natural products have not been fully investigated and understood. Since the development of modern chemistry, a reductionist approach has focused on isolating single molecules from natural products and subsequently synthesizing them artificially to produce therapeutic molecules, with the goal of developing selected active principles that act on a given target according to a key-lock paradigm.

[0023] This has led to the belief that the goal of research in the life sciences is to exploit data on individual substances at the molecular level, such as substances whose quantities can be verified chemically, to produce very robust and effective artificial products with linear dynamics. It is now becoming increasingly clear that this direction also has detrimental effects on biodiversity and the innate immune system.

[0024] The inability to standardize products derived from natural sources, particularly including products prepared by humans but consisting primarily or solely of ingredients derived from natural raw (starting) sources (i.e., consisting 100% of non-artificial substances), is one of the major difficulties of the technology and therefore opens the door for current API-based pharmacology approaches to ensure batch-to-batch validation of products derived from natural sources intended for medicinal or beneficial applications.

[0025] For example, natural matrices (e.g. plant matrices) are complex systems characterized by many molecular components belonging to different phytochemical classes, which interact in the plant to determine the biology of the plant. This interaction also continues during the processing stage, and different processing techniques affect the post-processing interactions of the components. These compounds can interact at the functional and structural levels. Supramolecular aggregates and their chemical, physical and structural characteristics that lead to structural and functional networks are dynamic interactions and can be regulated by environmental conditions, and as can be expected, these interactions affect the reactivity of the individual components and, through the so-called "matrix effect", lead to typical properties of the different entities represented by the matrix, which are different from the sum of the properties of its single molecular components. Such properties are defined as "emergent properties". This phenomenon has been described and specifically attributed to living matter, which has the power to self-assemble and self-organize to form supramolecular complex entities [Jean-Marie Lehn Toward complex matter: Supramolecular chemistry and self-organization. PNAS, 2002, 99 (8) 4763-4768 https: / / doi.org / 10.1073 / pnas.072065599]. This inherent complexity leads to the fact that the individual molecules within the natural matrix cannot be considered contained in an isolated and fixed package, since they are constantly undergoing mutual non-covalent and dynamic interactions. Such interactions are both intramolecular and intermolecular and occur between molecules of the same type as well as between molecules belonging to different chemical classes. This requires considering that the ability of the natural matrix to exert therapeutic activity in the human body depends not only on the qualitative and quantitative composition of the matrix (which itself is inherently prone to variation), but also on the presence of such interactions between identical and different molecules (including small molecules as well as more complex molecules such as proteins, polysaccharides, lipids, RNA, etc.).

[0026] In this context, classical validation of therapeutic products based on the pharmacological structure-activity relationship (SAR) (which is the most relevant relationship in classical pharmacological activity between an active pharmaceutical ingredient (API) and the receptor targeted by said API, considered at the single-molecule level) is unlikely to be adhered to in different batches of the same natural matrix.

[0027] These considerations appear to completely distinguish the study of interactions between self-assembling natural matrices and biological systems (replete with complexity at the molecular and supramolecular levels) derived from interactions that can be established through the structure of the API and its target receptor. Indeed, the latter are clearly defined by the precise, deterministic specification of a key-lock mechanism, which first and foremost defines the interaction between the API and its specific target in terms of structure, both quantitatively and qualitatively defined. From a conceptual perspective, this concept is so general that it translates into the possibility of controlling the reproducibility of the biological function of an API by controlling the reproducibility of its molecular structure alone, based on structure-activity relationships (SAR). Due to the aforementioned characteristics, this clearly does not apply to natural matrices or products containing them.

[0028] Therefore, it is necessary to note the fundamental differences between natural self-assembling matrices and APIs:

[0029] - the former is about the health of humans and the environment, which is characterized by physiological interconnections with the biological systems of the recipient at the molecular level and, precisely because of its complexity, is clearly inappropriate to describe and characterize by using deterministic tools such as the key-lock model;

[0030] -The latter is a xenobiology of humans and the environment, characterized by the explicit possibility of describing their interactions with the recipient's biological systems according to completely deterministic specifications usually summarized by the "key and lock" model.

[0031] Therefore, knowing the identity and quantity of each and every molecule in a natural matrix is insufficient to predict the dynamic and kinetic properties of the matrix itself and the therapeutic effectiveness. The opposite is true when considering selected single molecules (e.g., APIs), where SAR, pharmacodynamics, and pharmacokinetic properties are intrinsically linked to the chemical properties of the active ingredient and the pharmacodynamic inertness of the excipients. Therefore, the classical concepts of pharmacodynamics and pharmacokinetics are only meaningful when referring to single molecules (active ingredients) or their representatives (functional markers).

[0032] The network established between all components of the matrix produces a “matrix effect” that makes it impossible to identify a single marker as representative of the network, as no single component alone can convey all properties unique to the matrix, and because no single component reflects the interactions between the matrix and the target organism.

[0033] Matrix effects impart specific and unique properties to a matrix itself or to a mixture of matrices, resulting in new and different matrices, known as emergent properties, which cannot be reconverted back into the properties of any of the components considered individually. This perfectly reflects the impossibility of properly studying these properties using the deterministic chemical methods commonly used in classical pharmacological chemistry, which, as mentioned above, are only well-suited for single active ingredients and excipients in a pharmaceutical setting.

[0034] Instead, the dynamic and kinetic behavior of the matrix is the result of a network of dynamic interactions occurring within the matrix, showing:

[0035] The presence of a large number of components,

[0036] It is impossible to convert the properties of the matrix back into the sum of the properties of the individual substances

[0037] • It is not possible to describe the interaction between substrate and receiving organism according to the key-lock paradigm (model) that is the basis of SAR.

[0038] Humanity is now beginning to realize that the response to most problems lies within nature itself, and that it is necessary to develop processes and methods that can understand and, therefore, somehow standardize the self-organization of supramolecular networks by complex natural entities (e.g., natural matrices). These entities are the only ones physiologically compatible with everything that constitutes creation. Consequently, the need to shift from Enlightenment reductionist verification to probabilistic methods has inspired the latest evolution of scientific thinking, ultimately contrasting linear dynamics with circular dynamics. Consequently, deterministic chemical methods are insufficient for studying and monitoring matrix properties and quality. Methods for evaluating interactions within complex systems are necessary to identify properties relevant to the reproducibility of matrix therapeutic properties, as needed.

[0039] Hence the need to move towards approaches inspired by systems theory.

[0040] The study of these properties was previously unattainable and requires tools such as “omics” science, of which transcriptomics and metabolomics are considered crucial.

[0041] With regard to products with therapeutic effects containing or consisting of natural matrices, it is reminded that the EU Regulation 2017 / 745 (the Regulation) on medical devices (MD) 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, Regulation (EC) No 178 / 2002 and Regulation (EC) No 1223 / 2009 and repealing Council Directives 90 / 385 / EEC and 93 / 42 / EEC] and introduced new management in all aspects of the MD life cycle.

[0042] Under the regulation, the term "medical device" includes products that achieve a therapeutic effect but do not possess a pharmacological, immunological, or metabolic (Ph.IM) mode of action (MOA). A Ph.IM MOA is a mode of action characterized by a key-lock model, where the selected API adheres to SAR rules and acts on its target receptor. Therefore, products containing or composed of complex systems (such as natural matrices) can comply with the regulation. Specifically, the regulation also states that products that alter a pathological or physiological state or process through a non-Ph.IM mechanism of action are MDs.

[0043] Therefore, the regulation raises a dual issue that needs to be addressed: on the one hand, MDs composed of materials of natural origin (e.g., plant matrices, etc.) need to undergo quality control validation before they can be used for therapeutic purposes, and on the other hand, it needs to be demonstrated that the therapeutic effects of the products are achieved through non-Ph-IM mechanisms of action.

[0044] Currently, validation of products for therapeutic use is based solely on the reproducibility of their chemical composition and is only applicable to products that act via a Ph-IM mechanism of action.

[0045] Despite the complexity of natural matrices, the prior art is based on the validation of products for the treatment of pathological conditions (i.e., products that meet the definition of MD according to EU regulations) that contain or consist of natural matrices, as for APIs, at the chemical level. For all the reasons mentioned above, this is in stark contrast to the intimate nature of such products. Therefore, there is a need in the art to develop validation procedures that are based on an understanding of such complexity and are not limited to evaluating the reproducibility of such products based solely on the molecular composition of these products. In addition, the prior art does not provide methods for evaluating the mechanism of action of such products.

[0046] There is a strong need to find alternatives to traditional pharmacology, but at the same time guaranteeing the validation and standardization of products containing or consisting of one or more natural matrices for therapeutic purposes.

[0047] Providing methods for verifying the quality of products containing or consisting of natural matrices, not solely based on their chemical composition, would allow the use of products of natural origin in therapy that have circular rather than linear dynamics, i.e., acting on the entire physiological state altered by the pathological condition, rather than on a single alteration. This would lead to the development of new research areas and the possibility of using entire networks (e.g., natural matrices) in therapy, operating on a network represented by the subject being treated, i.e., with circular dynamics, rather than individual compounds acting on a single point of the receiving network, i.e., with linear dynamics.

[0048] The present invention solves the first problem summarized in the previous paragraph. Summary of the Invention

[0049] The present invention provides a novel method for defining acceptability values for spectroscopic or spectrophotometric analyses for compliance verification of one or more batches of a product comprising or consisting of one or more natural matrices for use in treating a pathological condition, the method comprising the steps of: wherein the acceptability values are calculated for spectroscopic or spectrophotometric spectra of a reference standard of the product and one or more different batches of the product, the reference standard having a defined therapeutic effect in treating the pathological condition, wherein the spectra are defined as acceptable or unacceptable based on selected biological activities exerted by the reference standard and the one or more different batches on one or more characteristics of the pathological condition in at least one cell-based assay, and not solely on their chemical composition.

[0050] In other words, the acceptability value is defined based on the deviation of said aforementioned spectra from the mean spectrum obtained from them.

[0051] The products that can be validated with the method of the invention are preferably prepared according to good manufacturing practices, thus following standardized procedures to obtain a priori high homogeneity between batches, despite the fact that they comprise or consist of a natural matrix and are therefore obtained from natural products.

[0052] As disclosed above, due to the complex interactions within one or more natural matrices and therapeutic or beneficial (health-related) products comprising or consisting of said matrices and the impossibility of attributing therapeutic or beneficial effects to a specific API, there is a clear need in the art not only for best practices and standardization throughout the entire manufacturing process of a health product comprising or consisting of a natural matrix, but also for a batch control model for said product that is not based on the identification, quantification and evaluation of individual chemical entities contained in said one or more matrices, since their therapeutic or beneficial emergent properties cannot be attributed to the simple sum of the properties of the individual components of said one or more matrices. Therefore, the control model should consider the entire system, allowing batch evaluation to be performed in the context of the mutual interactions between all components. This different evaluation approach is necessary because the properties (emergent properties) of a product comprising or consisting of one or more natural matrices, in particular plant matrices, animal matrices or mixtures thereof, are due to the interrelationships between all components of the natural matrix present in such a product. This means that, as described above, in contrast to classic pharmaceutical products whose activity is defined by a specific API, it is not possible to attribute the typical emergent properties of a natural matrix to the functional interactions of a single or a few components. In fact, the properties of natural matrices derive not only from each and every single component within them, but also from the supramolecular interconnections between these components, including the way they self-assemble at the supramolecular level, which results in a network of interactions between all components of the matrix. In other words, in products comprising or composed of natural matrices, there is no "active ingredient" responsible for the product's therapeutic properties, as in typical pharmaceutical products, or "excipients" responsible for not interfering with the properties of the active ingredient. Instead, there are multiple interconnected and interacting components that collectively contribute to the emergent properties of the matrix. "Emergence" is the term most commonly used to describe the observed integrated properties of the system.

[0053] It is also characterized by the interaction between the natural matrix and the receiving organism (e.g., the human body), that is, the interaction between the donor network (the matrix or natural material according to the instructions) and the receiving network (the body of the subject to whom the product is administered, e.g., the human body). This interaction alters multiple interconnected biological pathways in a manner unique to each biological matrix. Unlike specific APIs, the effects of therapeutic products containing or consisting of one or more natural matrices are broad, covering many aspects of physiology, with the result that the product affects the overall pathological state rather than changing a single function that causes the pathological state. The change in the overall pathological state is the result of the multiple biological components that constitute the natural material (i.e., the product) composed of or containing one or more natural matrices acting in a coordinated manner (i.e., emergent properties or matrix effects) through functional and structural interactions.

[0054] As mentioned above, this paper also reminds us that although chemically similar to their synthetic counterparts if taken individually, natural molecules within natural matrices may have fingerprints that are different from their synthetic analogs due to completely different synthetic pathways in terms of primary metabolites, reactants, reaction temperatures, energy sources, catalysts, etc., which may affect their physicochemical behavior and reactivity, and thus their biological activity.

[0055] For the reasons stated above, a preferred standardized regimen is used to produce natural substrates, particularly plant substrates, and the final product to be validated using the method of the present invention. The regimen is preferably designed to preserve the fundamental natural process rules that have allowed all components of a living organism (organic and inorganic) to interact with each other for millions of years, starting from agricultural production to the final transformation of the raw materials.

[0056] The applicant's research disclosed herein has shown that when a product comprises or consists of a complex natural system (i.e., a natural matrix), the classical methods used for standard pharmaceutical products (i.e., qualitative and quantitative characterization of the matrix) are not applicable to products that provide therapeutic and / or health benefits. As is known in the art, one of the main problems associated with the validation of therapeutic products comprising one or more natural matrices or their compositions is that, from the perspective of molecular components, a natural matrix extracted from, for example, a given plant will never be exactly the same as the "same" natural matrix extracted in the same way from another plant of the same species or even the same variety.

[0057] Due to the very nature of natural matrices, and contrary to classical quality control acceptance parameters for classical pharmaceutical products based on specific API rules, a certain degree of variability in the qualitative and quantitative composition of products comprising or consisting of natural matrices must be tolerated as a reflection of the most intimate properties of such entities and their mode of action on the receiving organism; however, the question is how to determine the acceptability of said variability.

[0058] The present application provides a new and reliable method for evaluating the acceptability values of spectroscopic or spectrophotometric methods for quality processes applicable to products with therapeutic or health effects that contain or consist of complex natural systems, where the acceptability values are based on the biological activity of the product of said kind against the characteristics of a given pathological state rather than on the qualitative and quantitative analysis of specific chemicals in the product.

[0059] The author of the present invention has unexpectedly found that, although there are qualitative and quantitative differences (even if by identical production procedures) between the natural matrix that different members from the same source obtain, the different molecular entities in the described matrix seem to work in a redundant mode with each other functionally and structurally.This redundancy causes comprising the natural matrix or the obvious maintenance of the bioactive that the product being composed of it is brought into play, even if use the classical batch control scheme required by the legislation of being intended to supervision deterministic effect API at present, the qualitative and quantitative composition of the different batches of described product can be considered to be unacceptable.Not bound by theory, the maintenance of observed bioactivity may be due to such fact: as mentioned above, the emergent attribute of natural matrix is due to matrix network as a whole entity with various unique attributes and produces, and may not be attributed to as isolated each single molecule.

[0060] Thus, the present inventors have discovered that different batches of products comprising or consisting of complex natural systems, which would result in a determination of non-compliance according to universal standard quality control validation techniques based on their qualitative and quantitative composition, unexpectedly maintain equivalent biological effects and produce their desired biological activities despite their different compositions.

[0061] Therefore, for therapeutic products containing or consisting of one or more natural matrices, where the quality control acceptability values are not based on the identification and evaluation of selected individual chemical entities and / or statistical pre-cleaning of the spectroscopic data to discard outliers typically accepted for the API, the applicant has developed a new method for validating the evaluation of quality control parameters for different batches of said products based on the analysis of selected parameters representative of their biological effects, which are key characteristics of medical devices composed of natural matrices. The acceptability values and the evaluation of the validation method presented herein are sufficient for quality control of therapeutically active biological materials as defined in Regulation 2017 / 745, reflecting compliance with GSPR 1 of Annex I to that Regulation, specifically the first line of which states: "Device devices shall perform as intended by the manufacturer and be designed and manufactured in such a way that they are fit for their intended purpose under conditions of normal use."

[0062] Thus, the present invention provides a method for defining acceptability values for a spectroscopic or spectrophotometric analysis for conformity verification of one or more batches of a product for treating a pathological condition or for assisting homeostasis under altered physiological conditions, the product comprising or consisting of one or more natural matrices, the method comprising

[0063] performing at least one in vitro cell-based assay and calculating said acceptability values for spectroscopic or spectrophotometric spectra of a reference standard and one or more batches of said product having a known therapeutic or beneficial effect in treating said pathological condition or in assisting homeostasis in said altered physiological state, defining said spectra as acceptable or unacceptable based on the biological activity exerted by said reference standard and said one or more batches against said pathological condition or one or more characteristics of a pathological condition that can result from said altered physiological state in said at least one in vitro cell-based assay.

[0064] The present invention also provides a method for selecting a reference standard of a product comprising one or more natural matrices as defined in the claims for use in treating a pathological condition from different batches. The present invention also provides a method for verifying (i.e., quality control compliance) one or more batches of a product for use in treating a pathological condition or a beneficial product, wherein the product comprises one or more natural matrices, the method comprising the following steps:

[0065] a. Perform spectroscopy or spectrophotometry analysis on each batch,

[0066] b. Validate each batch where the parameters obtained fall within the acceptability values defined according to the method provided for the definition in this invention.

[0067] the term

[0068] In the present application, "natural matrix" refers to a material composed of a network of components / ingredients obtained (e.g., extracted) directly from a member of nature or its naturally occurring part (i.e., from a natural raw material source) without significant processing or synthetic changes, where "without significant processing or synthetic changes" means processed only by manual, mechanical or gravity means, for example, by dissolution in water or other naturally occurring solvents such as water, water-alcohol solutions, etc.; by flotation; by extraction with water or other naturally occurring solvents; by steam distillation or by heating alone to remove water or any other naturally occurring solvent; or by extraction from air by any means, and with the proviso that "natural matrix" does not include the member of nature or its own naturally occurring part. In other words, a natural matrix or a mixture of natural matrices is a material obtained and processed from an entity that self-assembles in nature while retaining its natural biophysical characteristics, which determine their physiological interactions with other living organisms (e.g., human organisms). Their emergent properties can be expressed by promoting the rebalancing of metabolic processes or states of the receiving organism and / or certain organs or tissues and the physiological effects that will be activated in each specific environment. According to the present invention, natural matrix can be derived from materials obtained from any source in the living world (i.e., prokaryotes, protists, fungi, plant kingdom and animal kingdom). Thus, the term encompasses plant natural matrices, animal natural matrices, fungal natural matrices, protist (archaea or bacteria) natural matrices, prokaryotic natural matrices. Natural matrix can also include natural inorganic materials, such as minerals extracted from natural raw materials. In this specification, a synonym for natural matrix or one or more natural matrices is "natural material" as defined below.

[0069] Examples of naturally occurring parts of an organism may be represented by, for example, roots, leaves, bark, fruits, flowers of a plant or parts, organs, tissues thereof.

[0070] In any part of the description, the general term natural substrate may be replaced by:

[0071] Natural substrates of plant origin or obtained from plants,

[0072] Natural matrices of animal origin or obtained from animals,

[0073] Fungal natural substrates or natural substrates obtained from fungi,

[0074] A natural matrix of protists or a natural matrix obtained from protists,

[0075] A natural matrix of a prokaryotic organism or a natural matrix obtained from a prokaryotic organism,

[0076] Or plant materials and / or extracts, extracts from animal tissues or organs, fungi and / or fungal extracts, or mixtures thereof. Furthermore, the natural matrix may comprise minerals or components obtained from minerals.

[0077] Plant is a synonym for herb.

[0078] For example, in the case of a product comprising or consisting of material of plant origin (obtained from a plant) (e.g., an herbal supplement), the natural matrix will comprise a portion of the original, unintentionally altered, preferably unaltered, components naturally present in the source material (e.g., an extract of the source material), and thus will include the various organic and inorganic components found in the aforementioned kingdoms.

[0079] The term “natural” matrix emphasizes the preservation of the integrity and complexity of the network of ingredients / components in the original natural source, rather than extensive processing or chemical modification to isolate, purify, or extract specific molecules or classes of molecules.

[0080] Due to the supramolecular self-assembly of the components / fragments of the natural matrix, the entire matrix behaves as a complex network that interacts not with a single target molecule, but rather with a network of receptors (also organized as a network) within the receiving organism. Therefore, the natural matrix-receiving organism interaction is not the result of a point-to-point interaction like that of common pharmaceutical APIs, but rather the result of an interaction between a network of "interactors" (i.e., the matrix) and a network of "receivers" (i.e., the organism to which the matrix is administered).

[0081] The term "natural matrix" may also be replaced by a complex natural system in any part of the description and claims.

[0082] The term "natural matrix" anywhere in the specification and claims is not to be construed as a "natural product"; rather, a natural matrix is a product obtained from a natural organism and processed (e.g., extracted) by techniques that do not substantially alter the biological structure and supramolecular interconnections between components within the matrix.

[0083] Emergent properties according to the present specification and the art define properties of a natural matrix or natural material according to the present specification, i.e. properties that are not represented by the simple sum of the properties of each individual constituent / component of said matrix / material, but rather are represented by the intermolecular interactions between all constituents / components of the matrix / material, said intermolecular interactions being the result of the supramolecular self-assembly of said constituents / components within the matrix / material itself.

[0084] Therefore, " emergent properties " refer to the interaction and relationship between the composition / component of natural matrix to the technical effect that receives life system, such as treatment or homeostasis auxiliary property (that is, beneficial effect).Emergent properties are not just immediately obvious or predictable based on the individual characteristics of each composition / component of matrix.On the contrary, they " emerge " along with all the compositions / components of matrix network interacting with each other in a dynamic and complex manner and interacting with the life system receiving network.Emergent properties have been widely discussed in various scientific and system-oriented fields, including physics, chemistry, biology and complex systems theory.

[0085] Key points about emergent properties include:

[0086] System complexity: Emergent properties are associated with systems that exhibit a certain level of complexity. In simple systems, the interactions between components are limited, and properties can be more easily inferred from the properties of individual components. However, in complex systems, the interactions between components and their supramolecular organization can give rise to new and unexpected properties.

[0087] Nonlinearity: Emergent properties often arise from nonlinear interactions, where the relationship between cause and effect is disproportionate.

[0088] Holism: The concept of emergent properties emphasizes a holistic perspective, recognizing that the entire system is more than the sum of its parts.

[0089] The product according to the present invention comprising or consisting of one or more natural matrices (also referred to as "product comprising or consisting of one or more complex natural systems") is a product comprising or consisting of one or more natural matrices, which are also defined herein as "natural materials", i.e. "materials obtained / manufactured / processed from natural original sources (raw materials) or members of nature", as described below.

[0090] In any part of the description and claims, “product comprising or consisting of one or more natural matrices” may be replaced by “product comprising or consisting of one or more plant matrices” or “product comprising or consisting of one or more complex natural systems”, “natural material or material of natural origin”.

[0091] Furthermore, the term "product comprising or consisting of one or more natural matrices" according to the present specification may be an intermediate, or a final formulation for the intended use (e.g. a dry product to be resuspended), or, in particular when the formulation for the intended use is in liquid form, the term may define its dried or lyophilized or concentrated form to which the user or physician will add water to prepare the formulation for administration.

[0092] The phrase "a product comprising or consisting of one or more natural substrates" anywhere in the specification and claims cannot refer to a natural product per se. Furthermore, when a single natural substrate is present in or constitutes the product, the natural substrate is obtained (e.g., extracted) from an organism as defined above by technological means; when a mixture of natural substrates is present in or constitutes the product, the mixture is an artificially created mixture of selected natural substrates, and the mixture itself cannot be found in any product of natural origin for each of the substrates contained therein. Therefore, when a product comprises or consists of multiple natural substrates, the natural substrates have been artificially combined, and the resulting product has been endowed with new, emergent properties.

[0093] According to this specification, the expression "biological activity associated with a pathological condition" refers to a group of biological activities associated with a departure from / deviation from homeostasis, which may or may not culminate in the onset, progression, or exacerbation of the pathological condition. Thus, the expression "alteration of biological activity associated with a pathological condition" refers to a modulation or change in the normal (healthy) physiological state of biological activities (processes) within an organism (preferably a human) that is directly associated with a change / impairment in homeostasis, up to a pathological condition or disease. In other words, it describes a specific modulation or deviation from the normal (healthy) physiological state of a group or "network" of biological activities that occurs as a result of or is consistent with the onset, progression, or exacerbation of a pathological condition or disease.

[0094] For example, in the case of diabetes, biological activities related to glucose metabolism, insulin production and management are altered in a manner that is directly related to the pathological condition of diabetes and, therefore, are associated with the pathological condition or state of diabetes according to the present description.

[0095] Syntheses according to this specification have the meanings conventionally accepted in chemistry.

[0096] Conventionally, in chemistry, the term "synthetic" refers to the origin or source of a material or substance. Synthetic substances or materials are produced by humans through artificial synthesis (i.e., through laboratory chemical reactions), typically by reacting simpler chemicals to produce more complex chemicals through processes that, in many cases, use pathways, temperature conditions, pressure conditions, energy sources, and / or catalysts that differ from those used by living organisms.

[0097] Examples: Synthetic substances or materials include plastics, pharmaceutical drugs, and many industrial chemicals. For example, nylon is a synthetic polymer made through chemical synthesis, and aspirin is a synthetic drug produced through a specific chemical reaction.

[0098] In this specification, in vitro cell-based assays have the meaning conventionally used in the art, in particular, they refer to cell-based analytical procedures used to assess cell behavior and responses to insults or stimuli in the context of a disease or a pathological or pre-pathological condition or a condition in which homeostasis is altered. This type of assay is intended to study the biological responses of cells in a controlled environment, typically in a culture dish or well plate. According to the present invention, suitable in vitro cell-based assays are assays whose readout is associated with the modulation of a biological activity that is associated with one or more characteristics of a given pathological or pre-pathological condition or a condition in which homeostasis is altered (altered physiological state).

[0099] Cells can be derived from humans, animals, or cell lines that mimic specific tissues or organs.

[0100] In the context of a disease or pathological / pre-pathological condition, or a condition in which homeostasis is altered, cell-based assays are specifically designed to mimic or simulate conditions associated with the disease or pathological / pre-pathological condition, or a condition in which homeostasis is altered. In particular, cell-based assays can be used to evaluate the therapeutic, adjuvant, and / or beneficial activity of various compounds or products in vitro. These may involve exposing cells to factors known to be associated with the disease or pathological condition, to potential therapeutic or adjuvant products that aid in the restoration of physiological states, or using cells that have been or have been genetically modified to carry disease- or pathological-specific characteristics.

[0101] The selected cells may be treated to induce a pathological, pre-pathological, or altered homeostatic condition, or the selected cells may be cells that already exhibit the desired altered phenotype.

[0102] A healthy physiological state is a condition in which the body, organs, mechanisms, systems, or regions of an organism and their internal processes function optimally within the individual's normal parameters, i.e., a state toward which homeostasis is directed. In the context of biological activities known to contribute to the characteristics of a given disease or pathological condition, a healthy physiological state is a condition in which the various biological activities are functioning optimally within normal (healthy) parameters. This state is characterized by the absence of significant abnormal cellular or molecular processes associated with the particular disease in question.

[0103] The term can refer to hallmarks of a particular disease, which are unique characteristics or features typically observed in individuals affected by the disease. These hallmarks can include specific cellular behaviors, molecular pathways, or physiological responses that play a key role in the development or progression of the disease.

[0104] In general, a healthy physiological state in the context of a specific disease or pathological condition refers to a state in which biological activities associated with known characteristics of the disease or pathological condition are regulated in a direction consistent with the non-disease (non-pathological) state (in other words, in a direction opposite to the disease (pathological) state).

[0105] Thus, a healthy physiological state also indicates the direction of regulation of biological activities that are known to be characteristic of pathological conditions in homeostasis, i.e., before the onset of a pathological condition, in other words, the direction of homeostatic regulation of a set of biological activities attributed to a specific system, region, mechanism, or organ of a healthy subject. In this specification, healthy physiological state and health state are used as synonyms.

[0106] Altered physiological states and altered homeostasis are closely related concepts that describe deviations from the normal function and balance of the body's internal environment. Although there is overlap between them, there are some distinctions between the two terms:

[0107] Altered physiological state: This term encompasses a broad range of changes in the body's normal function, including disruptions in organ systems, biochemical processes, and cellular function. Altered physiological states can be caused by a variety of factors, such as illness, injury, medication, environmental factors, and psychological stress. Examples include fever, inflammation, hormone imbalances, and impaired organ function.

[0108] Altered homeostasis: Homeostasis refers to the body's ability to maintain a stable internal environment despite external changes. This stability is achieved through regulatory mechanisms that keep variables such as body temperature, blood pressure, pH balance, and blood glucose levels within narrow ranges. Altered homeostasis occurs when these regulatory mechanisms fail to maintain equilibrium, resulting in deviations from the body's normal set point. These deviations can be temporary or long-lasting and may involve compensatory mechanisms to restore balance.

[0109] In summary, altered physiological state describes observable changes in the body's normal functioning, while altered homeostasis refers to the potential disruption of the body's regulatory mechanisms that maintain internal stability.

[0110] Altered homeostasis underlies altered physiological states, such as disruption of homeostatic mechanisms that may lead to physiological imbalance and manifestations of disease or dysfunction.

[0111] As used herein, the terms "Hallmarks" of a disease, pathology, or medical condition have the meanings commonly used in the art. According to the prior art, hallmarks of a disease are indicators that can mark the progression or control of a given disease or pathology. These hallmarks (also known as "keystones") are typically a set of characteristics or patterns that physicians monitor over time to track the progression or regression of a specific disease. In summary, a hallmark of a disease is a defining characteristic or feature whose changes indicate a specific medical condition, aiding in its identification, diagnosis, monitoring, and understanding. For example, for neurodegenerative diseases (NDDs), at least the following eight hallmarks of NDD are known in the art: (pathological protein) aggregation, (dysfunction) of synapses and neuronal networks, (abnormal) protein homeostasis, (abnormal) cytoskeleton, (altered) energy homeostasis, (defects) in DNA and RNA, (increased) inflammation, and (increased) neuronal cell death. In cancer research, hallmarks of cancer are a set of unique features commonly found in cancer cells. These hallmarks include (sustained) proliferative signaling, (evasion) of growth inhibitors, (resistance) to cell death, (achievement of) replicative immortality, (induction) of angiogenesis, and (activation) of invasion and metastasis.

[0112] Characteristics of a disease, biological activities associated with said characteristics, parameters whose analysis allows assessment of changes in said biological activities, etc. are the framework for studying a disease or pathological or medical condition using an integrative / holistic approach.

[0113] According to this specification, the expression "natural material" refers to a material consisting of one or more natural matrices, provided that the one or more materials themselves are not found in nature, but are the result of human technological intervention (such as, for example, extraction processes, filtration, etc., i.e., elaborate). These materials are typically obtained from plants, animals, fungi or microorganisms and minerals through a preparation process that is intended to maintain the integrity of the network within the natural raw material source for preparing the natural material. In this specification, "natural material" is considered to be a synonym for one or more natural matrices. Therefore, the natural material according to this specification can be a product, such as a product with a therapeutic effect, which is composed of or comprises only selectively assembled different natural matrices (which are not combined in this combination in nature) to produce a given therapeutic effect, thereby forming an "interaction network" whose administration to a subject (i.e., receiving a life network) shows the emergent properties of providing a therapeutic effect or a homeostatic auxiliary effect (i.e., an effect that is beneficial to the health of the subject).

[0114] "Has a therapeutic effect": According to the present specification, a product with a therapeutic effect is a product that, upon administration to a subject affected by 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 degree of relief, alleviation or reduction of at least one clinical symptom and / or delays the progression of the condition, or restores (completely or partially) a healthy physiological condition in the area affected by the pathological condition.

[0115] According to the present specification, having a beneficial effect encompasses a product whose administration to a healthy subject or a subject that is healthy but not in homeostasis or an in vitro cellular assay representing a sufficiently healthy state produces in vitro or in vivo evidence of restoration or assistance of homeostasis in the cellular assay or in a system / region / organ / organ of interest of the recipient after administration.

[0116] The terms "prevent," "preventing," and "prevention of" (and grammatical variations thereof) refer to reducing and / or delaying the onset and / or progression of a disease, disorder, and / or clinical symptom in a subject, and / or reducing the severity of the onset and / or progression of a disease, disorder, and / or clinical symptom, relative to what would occur in the absence of the methods of the present invention. Prevention can be complete, such as the complete absence of the disease, disorder, and / or clinical symptom. Prevention can also be partial, such that the onset and / or onset and / or progression of a disease, disorder, and / or clinical symptom in a subject is less severe than what would occur in the absence of the compositions according to the invention.

[0117] According to the present specification, having a "beneficial / healthy / health-promoting" effect encompasses a product whose administration to a healthy subject or to a healthy subject not in homeostasis or to an in vitro cellular assay representing a fully healthy state produces in vitro or in vivo evidence of restoration or assistance of homeostasis in said cellular assay or in a system / region / organ / organ of interest of the recipient following administration.

[0118] The term "product with (defined) therapeutic properties comprising one or more natural matrices" or "product for the treatment of a pathological condition, said product comprising one or more natural matrices" according to the present invention is a product as defined above, wherein the emergent properties of said product provide a therapeutic effect as defined below in this glossary.

[0119] This term may be replaced in any part of the description and claims by “a therapeutically active product comprising or consisting of a complex natural system,” “a preparation comprising (or consisting of) a complex natural system with therapeutic properties,” or “a composition comprising (or consisting of) a complex natural system with therapeutic properties,” or “a mixture comprising (or consisting of) a complex natural system with therapeutic properties,” where the term “complex natural system” may be replaced by “one or more natural matrices” or “natural material.”

[0120] This definition applies mutatis mutandis to the term “products having beneficial / healthy / wholesome properties comprising one or more natural bases”.

[0121] According to this specification, the term homeostasis has the meaning conventionally accepted in the art and thus refers to the physiological process by which a living organism maintains a stable internal environment despite external changes. This stability is essential for the normal functioning of cells, tissues, and organs. The goal of homeostasis is to ensure that the internal conditions of an organism remain within the optimal range for survival and normal physiological functioning (a healthy physiological state). Organisms achieve homeostasis by regulating a series of biological activities and processes designed to maintain a healthy physiological state.

[0122] Products that assist homeostatic processes are products that modulate biological activity toward a healthy physiological state and, therefore, are products that are suitable for healthy individuals and support homeostatic mechanisms that contribute to a healthy physiological state and can be used by healthy individuals to assist in the homeostatic regulation of biological activity associated with the characteristics of a given pathological condition.

[0123] For the purposes of this specification, a medical device (also referred to as MD) is a product as defined above, which must be intended for therapeutic purposes within the meaning of Article 2(1) (1) to (3) of Regulation (EU) 2017 / 745, and therefore, a “medical device” means any … [omitted] … material intended by the manufacturer to be used, alone or in combination, for one or more of the following specific medical purposes for human beings:

[0124] — Treat or alleviate disease,

[0125] — treatment, relief or compensation for injury or disability,

[0126] — altering physiological or pathological processes or states,

[0127] …[omitted]…

[0128] And it cannot achieve its main intended effect in or on the human body through pharmacological, immunological or metabolic means, but its function can be assisted by these means.

[0129] “Performance” of a medical device means the ability of a medical device, as defined herein, to achieve its intended purpose as specified by the manufacturer;

[0130] “Clinical performance” of a medical device means the ability of a medical device, as defined herein, resulting from any direct or indirect medical effect produced by its technical or functional characteristics (including diagnostic characteristics) to achieve its intended purpose as claimed by the manufacturer, thereby providing clinical benefit to the patient when used as intended by the manufacturer;

[0131] “Clinical benefit” of a medical device means a positive effect of the device, as defined herein, on an individual’s health, expressed in terms of meaningful, measurable, patient-relevant clinical outcomes, including those related to diagnosis, or a positive impact on patient management or public health.

[0132] Additionally, if a composition (e.g., a contrivance, such as a product with therapeutic properties comprising one or more natural substances) is intended to have a medical purpose, such as to diagnose, treat, mitigate, or prevent disease or to affect the structure or function of the body, and meets the criteria outlined in the definition, it can be classified as a medical device by the U.S. FDA.

[0133] Under section 201(h)(1) of the Food, Drug, and Cosmetic Act, a device is:

[0134] Apparatus, apparatus, tool, machine, device, implant, in vitro reagent or other similar or related article, including any component part or accessory thereof, which is:

[0135] (A) has been recognized in the official National Formulary or the United States Pharmacopeia or any supplement thereto,

[0136] (B) is intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease in humans or other animals, or

[0137] (C) is intended to affect the structure or any function of the body of man or other animals and does not achieve its primary intended purpose by chemical action in or on the body of man or other animals and does not rely on being metabolized to achieve its primary intended purpose. The term “device” does not include software functionality excluded under section 520(o).

[0138] The classification of medical devices into risk categories is typically based on factors such as intended use, indications for use, and the risks associated with the device.

[0139] According to the present invention, a product that is considered to have a defined or known therapeutic effect is a product, at least one batch of which (hereinafter: reference standard) shows the desired therapeutic effect at least in vitro (e.g. in a laboratory environment using cells, organoids, tissues) and / or in in vivo animal models or clinical trials (i.e. a batch whose desired therapeutic activity has been verified at least in vitro).

[0140] The expression having an established or known beneficial / healthy / beneficial effect according to the present invention refers to a product, at least one batch of which (hereinafter: reference standard) shows the desired effect of restoring / supporting homeostasis at least in vitro (e.g. in a laboratory environment using cells, organoids, tissues) and / or in in vivo animal models or clinical trials (i.e. batches whose desired beneficial activity has been verified at least in vitro).

[0141] As used herein, a subject "in need thereof" refers to a subject who can benefit from the therapeutic and / or prophylactic effects of a therapeutic composition. Such a subject can be diagnosed with a disease or disorder, suspected of having or developing a disorder, and / or determined to be at increased risk of having or developing a disease or disorder.

[0142] The terms "treat," "treating," or "treatment of" (and grammatical variations thereof) refer to reducing the severity of, at least partially ameliorating, or alleviating a subject's condition, and / or achieving some reduction, alleviation, or decrease in at least one clinical symptom and / or delaying the progression of a disease or disorder.

[0143] Conformity verification refers to the verification of batch-to-batch conformity during the production of a given product, i.e., the different batches obtained in production maintain the desired therapeutic or beneficial activity in accordance with the reference standard (also defined as the "gold standard" in industrial production processes).

[0144] The acceptability values (also called acceptability ranges or cut-off values) of spectroscopic or spectrophotometric spectra are defined as the acceptability range of variability relative to the average spectrum obtained from the spectra of a reference standard batch of the product and the spectra of an acceptable batch of said product, and preferably refined by the spectra of unacceptable batches according to method (c) of the invention, wherein the deviation values calculated by superimposing the spectra of unknown batches of the test product (not validated by a cell-based assay) with the average spectrum are considered to maintain its compliance with the reference standard of said product, i.e. maintain the desired formulation and therapeutic / beneficial activity. As already explained in the description above, they are defined based on the deviations of the spectra of the above-mentioned (c) from the average spectrum obtained from them.

[0145] The "weakest performance" of a reference standard compared to a reference drug (i.e., a drug that is typically prescribed to treat the same pathological condition) refers to the lowest therapeutic or least beneficial modulation value of a given biological activity calculated when the same modulation values are compared in a cell-based assay according to the present invention.

[0146] Pathophysiology or physiopathological states refer to abnormal physiological conditions or processes in the body that are often associated with disease or dysfunction. In this specification and claims, the term "pathological state" is also defined. It involves the study of functional changes that occur due to disease or injury, and how these changes manifest at the cellular, tissue, organ, and system levels. Pathophysiology encompasses the understanding of both the underlying mechanisms of disease and the body's responses to these disruptions in order to diagnose, treat, and manage a variety of health conditions. Understanding pathophysiological states is crucial to both research and clinical practice in medicine.

[0147] Pathophysiology involves the study of how various factors (such as genetic abnormalities, environmental influences, or disease processes) disrupt the body's normal physiological functions, leading to the development of health disorders or diseases. Understanding physiopathological states is crucial for the diagnosis, treatment, and management of a wide range of medical conditions across different specialties in healthcare.

[0148] In this specification, as in the prior art, different batches or lots of a product refer to different groups of items produced or manufactured at different times or under different conditions, but still belonging to the same product line. The starting raw materials in different batches can come from the same or different stockpiles. Each batch or lot typically receives a unique identifier to distinguish it from other batches. These identifiers facilitate quality control, inventory management, and traceability throughout the production process and supply chain.

[0149] Batches of products containing or consisting of one or more natural matrices are expected to vary in their qualitative and quantitative chemical composition due to factors such as variations in the starting materials. In addition, individual batches may differ from any other batch of product due to manufacturing conditions or the instrumentation used. BRIEF DESCRIPTION OF THE DRAWINGS

[0150] Batch symbol:

[0151] Figure 2-7 and 12:

[0152] The product Arté-Gx in lyophilized form (see Example 1 for detailed composition of the product):

[0153] Batch 20B1955 is also the reference standard L 20B1955 (denoted as gold standard in the figure)

[0154] Batch 20B0596 is also L 20B0596

[0155] Batch 20I1297 is also L 20I1297

[0156] Batch 21E1640 is also L 21E1640

[0157] Batch 20J1770 is also L 20J1770

[0158] Batch Dest 21E1640

[0159] Figure 9 Product B reference standard (represented as gold standard in the figure)

[0160] Figure 11 Product C reference standard (represented as gold standard in the figure)

[0161] (See Example 1 for the detailed composition of the product).

[0162] exist Figure 2-4 , 9 and 11, the adjustment values were calculated as Z scores, as described in the specification and examples).

[0163] Figure 1 Characteristics of osteoarthritis are listed, including trends representing characteristics of improvement in the disease state (column 1), biological activities consistent with each disease (column 2) and their regulation under pathological conditions (column 3), and the regulation of each of said biological activities representing a healthy physiological state (column 4). Dark gray: upward regulation Light gray: downward regulation

[0164] Figure 2 Modulation of selected bioactivities in osteoarthritis in a chondrocyte-based assay is shown: Column 1 features trends representing features of improved disease state, Column 2 bioactivity, Column 3 predicted modulation of bioactivity in pathological state, Column 4 expected modulation of bioactivity in healthy physiological state, Column 5 cell-based assay without therapeutic treatment, representing modulation of bioactivity in pathological state, and Column 6 modulation induced by a reference standard of the test product. The cell-based assay shows that the reference standard modulates the selected activity relative to healthy physiological state. The number reported in each box represents the Z score calculated using the method of the present invention and represents the observed modulation of each bioactivity.

[0165] Figure 3Modulation of selected bioactivities in a chondrocyte-based assay representing osteoarthritis is shown: Column 1 features trends representing features that improve the disease state, Column 2 bioactivity, Column 3 predicted modulation of bioactivity under pathological conditions, Column 4 expected modulation of bioactivity under healthy physiological conditions, Column 5 cell-based assay without therapeutic treatment, representing modulation of bioactivity under pathological conditions, Column 6 modulation induced by the reference drug (triamcinolone acetonide), Column 7 modulation induced by the reference standard of the test product, and Columns 8-11 modulation induced by four different batches of the test product. Column 11 represents modulation induced by an intentionally destabilized batch (DEST 21E1640), which exhibits weaker therapeutic activity. The cell-based assay shows that the reference standard and additional batches similarly modulate the selected activity according to healthy physiological conditions. The numbers reported in each box represent the calculated Z-score values representing the observed modulation of each bioactivity.

[0166] Figure 4 Corresponding to Figure 3 Column 12 is added, which shows a control analysis of the modulation induced by a non-destabilized batch (21E1640) that was validated as compliant according to the method of the present invention. The cell-based assay shows that the reference standard and the additional batch similarly modulate the selected activity according to a healthy physiological state and thus confirms the compliance of the batch validated with the method of the present invention. The number reported in each box represents the calculated Z score value (modulation value) representing the modulation observed for each biological activity. The reference Z score value is calculated according to the present invention, taking into account the reference standard Z score value ( Figure 4 8) and select as the reference Z score value ( Figure 4 The drug Z score value (column 13 of Figure 4 ), the Z-score values associated with the weakest performance are shown in the following table (gold standard = reference standard):

[0167]

[0168] Because the therapeutic effects of both the product and the drug product have been established, it is correct to accept that when the reference drug product and the reference standard provide modulation of a selected biological activity in the same direction of the healthy physiological state, the weakest performance z-score is the reference cutoff for that modulation.

[0169] Figure 5 The targeted metabolomics profile of five batches of the main chemical classes of ArtéGx, including a reference standard, is shown. The figure clearly shows that each batch tested differs from each other and from the reference standard in terms of qualitative and quantitative composition. Comparison of selected bioactivities tested in cell-based assays with the same batches ( Figure 3 and Figure 4) showed that qualitative and quantitative analysis of different batches of products for the treatment of pathological conditions (products comprising or consisting of one or more natural matrices) does not allow a correct estimation of their activity profile.

[0170] Figure 6 shows (6a). NIR spectra of the reference standard and three different positive batches selected in iv) in the wavelength range of interest: (6b). NIR average spectrum of four batches of 6a and NIR spectrum of negative batch 21E1640 Dest; (6c). NIR average spectrum of four batches of 6a and two a priori undesirable spectra (undesirable A Centella asiatica extract, undesirable B Echinacea extract); (6d). NIR average spectrum of four batches of 6a and NIR spectrum of unevaluated batch 21E1640 (not destabilized).

[0171] Figure 7 The ROS scavenging activity of 4 validated batches, including the reference standard of Arté-Gx, is shown. The amount of ROS detected in the sample treated with AAPH was considered to be the maximum release of ROS (100%), while the amount of ROS detected in the other samples was calculated as a percentage relative to the maximum release induced by AAPH. One-way analysis of variance and Dunnett's post-test were applied. Only values that returned p<0.05 were considered significant (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). Statistical significance of all samples compared to untreated cells.

[0172] This figure demonstrates that the validated batches are indeed capable of inducing the ROS scavenging activity required for the desired therapeutic use.

[0173] Figure 8a and 8b Listed are the characteristics of mild cognitive impairment (MCI) (column 1), the biological activities consistent with each disease (column 2), and their regulation under pathological conditions (represented as changes from a healthy physiological state) (column 3), and the regulation of each of said biological activities representative of a healthy physiological state (column 4). Dark grey: up-regulation Light grey: down-regulation

[0174] Figure 9a and 9bMCI is shown. Modulation of selected biological activities in a human neuronal cell-based assay (SH-SY5Y cells): Column 1: Feature, Column 2: Biological activity, Column 3: Modulation of the biological activity under predicted pathological conditions, Column 4: Desired modulation of the biological activity under healthy physiological conditions, Column 5: Modulation induced by the reference standard of Test Product B. The cell-based assay shows that the reference standard modulates the selected activity according to healthy physiological conditions. The numbers reported in each box represent the Z scores calculated using the method of the present invention, representing the observed modulation of each biological activity.

[0175] exist Figure 9a and 9b In the test product B used, the test product B is as described in Example 1.

[0176] Figure 10a and 10b Characteristics of osteoporosis (OP) are listed, including trends in characteristics representing improvements in the disease state (column 1), biological activities consistent with each characteristic (column 2) and their regulation under pathological conditions (represented as changes from a healthy physiological state) (column 3) and the regulation of each of said biological activities representing a healthy physiological state (column 4). Dark grey: upward regulation Light grey: downward regulation

[0177] Figure 11a and 11b OP. Modulation of selected bioactivities in adipose-derived mesenchymal stem cell line (hADMSC) capable of differentiating into osteoblasts and mineralizing the extracellular matrix (ECM): Column 1: Characteristics, Column 2: Bioactivity, Column 3: Predicted modulation of bioactivity under pathological conditions, Column 4: Expected modulation of bioactivity under healthy physiological conditions, Column 5: Modulation induced by a reference standard of Test Product C. Cell-based assays show that the reference standard modulates the selected activity according to healthy physiological conditions. The numbers reported in each box represent the Z scores calculated using the method of the present invention, representing the observed modulation of each bioactivity.

[0178] exist Figure 11a and 11b The test product C used is as described in Example 1

[0179] Figure 12 The figure shows the modulation of oxidative stress (inflammatory signature) in bioactive substances for four validation batches, including the Arté-Gx reference standard. Ascorbic acid was used as a positive control, and AAPH lesions were used as negative controls, representing a pathological state. It is clear from the figure that the use of different parameters to monitor the modulation of bioactive substances causally related to the pathological signatures of osteoarthritis (OA) is also suitable as an alternative to transcriptomic parameters for batch validation.

[0180] Figure 13 Biophysical characterization of total RNA from biological plant material is shown.

[0181] Figure 13 The electrophoresis diagram of ArtéGX, a production intermediate of Product A (i.e., a co-extract of Centella asiatica and Echinacea in the proportions described in Example 1) before ultrafiltration is shown, with Figure "A" showing the size distribution of total RNA and "B" showing the size distribution of RNA between 4 and 150 nt.

[0182] Figure 14 shows (14a). Raman spectra of the reference standard and three different positive batches selected in iv) in the wavelength range of interest; (14b). Raman average spectrum of four batches of 14a and Raman spectrum of negative batch 21E1640 Dest; (14c). Raman average spectrum of four batches of 14a and two a priori undesirable spectra (undesirable A Centella asiatica extract, undesirable B Echinacea purpurea extract); (14d). Raman average spectrum of four batches of 14a and NIR spectrum of unevaluated batch 21E1640 (not destabilized). Figure 15 A timeline showing the experimental setup for the chondrocyte experiments is shown. Detailed Description of the Invention

[0183] The present invention provides methods and processes for batch-to-batch verification of the quality compliance of products comprising or consisting of natural matrices, for example, products consisting of 100% natural materials and exerting a therapeutic or beneficial activity (the latter by allowing a physiological or pathological state or a slight imbalance of homeostasis in an organism (e.g., a human organism) to rebalance), by providing spectroscopic or spectrophotometric acceptability values based on the measurement of changes in specific biological activities consistent with the therapeutic or beneficial effect. Thus, the applicants hereby provide for the first time a method and process that will allow the standardization of products of this type and, therefore, compliance with a regulatory framework that provides viable space for innovative uses of said products in therapy. Over the past decades, the applicants have indeed pursued a cross-sectoral research path that, together with scientific innovations, has led to the development of regimens for agricultural production and transformation processes of raw materials (starting materials) that preserve the fundamental laws of natural processes that have interconnected all the organic and inorganic components of living things for millions of years.

[0184] According to the teachings of the present invention, precise parameters can now be assessed to verify batch-to-batch consistency of products having emergent properties that result in physiological therapeutic or beneficial activities when the product comprises or consists of one or more natural matrices.

[0185] This is of particular interest for all products intended for therapeutic / beneficial use that are not based on the classical pharmacological formulation of “API plus excipients” (e.g. products containing or consisting of one or more natural matrices). The main problem with such products is that, despite exerting important therapeutic / beneficial effects, there is no way to ensure that the products meet the claimed therapeutic / beneficial effects due to the lack of reproducible and accurate batch-to-batch validation methods. This is because their origin (nature) presents inherent variability in their qualitative and quantitative composition, and therefore cannot be properly assessed through classical validation processes based solely on qualitative and quantitative composition. In fact, to date, it has not been possible to include products containing or consisting of one or more natural matrices in a regulatory framework that takes this into account and allows for a high degree of innovation. Currently, such products are validated according to standard procedures, such as quantification of compounds from one or more chemical classes, which does not represent the complexity and full effectiveness of products with emergent properties (e.g. products based on natural matrices). The present invention solves this problem.

[0186] Since the methods and processes of the present invention are designed for products comprising or consisting of natural substrates, it is preferred that the production of these products is carried out through the entire production process in standardized agricultural and manufacturing processes.

[0187] The inventors have demonstrated here that a method based solely on reproducible measurements using classical targeted metabolomics, for example, due to the existence of a well-defined SAR, using a standard designed for the regulation of a single API, acting through a deterministic key-lock mechanism, for the qualitative and quantitative analysis of a number of chemical classes or specific chemical compounds of a product with a therapeutic or beneficial effect, is not suitable for quality control when the product contains or consists of one or more natural matrices. In fact, the results obtained by the inventors by analyzing different batches of the same product by chemical class, when faced with the selected biological activity (the basis of the therapeutic or beneficial effect) of each batch, show that the quantitative fluctuations of the substances of each chemical class present in the different batches (if used as a means of assessing the quality of the batches according to the standard applied to the API) would lead to the a priori assumption that these batches have different biological activities from each other (see the second table and the second table of Example 3.1). Figure 5 In contrast, the inventors conducted experiments on different batches of therapeutic products containing one or more natural matrices (see Example 3.1, in particular Figure 3 、 4 and 5) show that, despite their different qualitative and quantitative chemical compositions, the batches are still able to achieve the same therapeutic activity, with a resilient behavior, which may be due to the redundancy between the individual components at the structural and functional levels.

[0188] Therefore, the experiments carried out by the inventors (see in particular Figure 3 、4 and 5) show that, when considered individually, qualitative and quantitative analysis of different batches of products for the treatment of pathological conditions does not allow for a correct estimation of the activity profile when the product comprises or consists of one or more natural substances. Thus, the data presented herein indicate that, in contrast to pharmaceutical products based on traditional (i.e., synthetic chemistry) APIs, qualitative and quantitative analysis of individual components of therapeutic products comprising or consisting of one or more natural substances (i.e., providing therapeutic effects based on network-to-network interactions) (when used as a method to assess the therapeutic and quality reproducibility of non-SAR-based entities) is not suitable for assessing correct compliance between batches of said products.

[0189] Indeed, given the very nature of natural matrices, a chemical profile that varies quantitatively from batch to batch would prompt a validator to consider individual batches of a product comprising or consisting of one or more natural matrices as "different materials" relative to a given reference standard of said product, and therefore to discard said batches. Conversely, the results presented herein by the present inventors demonstrate that, in biological systems, qualitatively and quantitatively different batches of a given product exert the same relevant effects for its intended therapeutic use. This demonstrates once again that the therapeutic or beneficial activity of a complex matrix cannot be traced back to the sum of the activities of each individual molecule within the matrix itself, and that, when it comes to natural matrices, unlike classical APIs, the reproducibility of the therapeutic or beneficial activity of a matrix does not entirely depend on the reproducibility of the identity and quantity of its constituent molecular components.

[0190] The results obtained by the inventors indicate that there are structural and functional redundancy mechanisms within the natural matrix that confer a specific functional resilience to said matrix and that the matrix itself should not be considered as a compilation of molecules acting independently of one another, as if they were still subject to the SAR that is usually attributed to these molecules when studied individually.

[0191] As shown in the present specification (see Examples and Figures), different batches of test products comprising or consisting of one or more natural matrices, which have defined differences in qualitative and quantitative composition from each other and from a reference standard of said product, may retain the ability to mediate the same therapeutic or beneficial activity despite their different quantitative composition at the molecular level.

[0192] Thus, the authors of the present invention have developed a novel method for defining acceptability values for spectroscopic or spectrophotometric analyses suitable for use in conformity verification of one or more batches of a product for the treatment of a pathological condition, wherein the product comprises or consists of one or more natural matrices; and a process for conformity verification (e.g., quality control in an industrial production process) of different batches of a product comprising or consisting of one or more natural matrices, based on the preservation of selected intrinsic characteristics of the matrix (modulation of selected biological properties), rather than the absolute identity of its individual molecular components. The method of the present invention allows the definition of a validation acceptability value based on the analysis of selected parameters, which, as demonstrated in this specification, is effectively correlated with the maintenance of a desired overall biological activity.

[0193] The present description discloses in the examples experimental data on a model product herein denoted Arté-GX or product A for the treatment of osteoarthritis (disclosed in WO 2018 / 138678) and consisting essentially of a natural matrix of plant origin (see the examples for the composition of the product). Faced with the problem of meeting the regulatory requirements for the use of the above-mentioned product for therapeutic purposes, the inventors tested the classical validation methods and realized that said methods (based on the analysis of the qualitative and quantitative chemical composition) were no longer suitable for a correct assessment of the therapeutic effect of the product (comparison Figure 3 、 4 、5).

[0194] Thus, the present inventors developed the methods and processes disclosed herein and found results consistent with those also reported herein for other various products comprising or consisting of one or more natural matrices having therapeutic effects.

[0195] All test products disclosed in this specification are composed of or comprise a natural matrix and are therapeutic or beneficial products. The matrix wherein comprised is obtained from plant biomaterials, which are suitably processed and formulated to obtain final natural materials (as defined in the glossary) that can improve pathological conditions or altered physiological states and promote the recovery of healthy physiological conditions after application. For all test products, reference standards with known and verified therapeutic or beneficial effects are provided. The Examples section provides a detailed description of the test products.

[0196] Among the products tested, hundreds of components from crude original plant parts were not deprived of the natural biosourced material capabilities and characteristics to establish diverse combinations of molecular and supramolecular interactions among themselves and with target tissues and, therefore, maintain therapeutic emergent properties.

[0197] Specifically, from soil preparation to final product production, the applicant's test products were prepared using a regimen selected and standardized by the applicant based on over 40 years of experience to a priori ensure that the final product was as uniform as possible, thereby increasing the efficiency of effective batch production. The regimen developed by the applicant was designed so that each step leading to the desired final product was standardized as much as possible in terms of the regimen of each step, thereby providing a 100% natural final product, rather than a synthetic or partially synthetic product (i.e., a product that does not contain a single component obtained through artificial chemical synthesis), where each component is produced under regimented conditions. By comparing, or more precisely, integrating, the reductionist approach discussed above with methods from systems theory and quantum biology, a fully regimented, standardized production process was developed that integrates cross-sectoral technologies and research from multiple different fields, from agriculture to omics and mathematical sciences. Preferably, according to the present invention, the test products comprising or consisting of one or more natural matrices do not contain chemically synthesized molecules, nor do they contain natural matrices that have been exposed to and may have internalized chemically synthesized molecules, thereby allowing the provision of natural matrices and final products composed of 100% natural ingredients.

[0198] An object of the present invention is a method for defining acceptability values for a spectroscopic or spectrophotometric analysis for conformity verification of one or more batches of a product intended for treating a pathological condition or for assisting homeostasis in an altered physiological state, the method comprising

[0199] performing at least one in vitro cell-based assay and calculating said acceptability values for spectroscopic or spectrophotometric spectra of a reference standard and one or more batches of said product having a known therapeutic or beneficial effect in treating said pathological condition or in assisting homeostasis in said altered physiological state, defining said spectra as acceptable or unacceptable based on the biological activity exerted by said reference standard and said one or more batches against said pathological condition or one or more characteristics of a pathological condition that can result from said altered physiological state in said at least one in vitro cell-based assay.

[0200] Depending on the pathological condition of interest, one or more characteristics may be selected. Preferably, multiple characteristics are selected, although in the case of cancer, for example, it is well known to the skilled artisan that the most relevant characteristic is the proliferation of cancer cells. Thus, in this case, the cell-based assay selected may be an assay that verifies the viability of the neoplastic cells or tumor mass after administration of the product of interest. Furthermore, according to the present invention, it is preferred to use a single cell-based assay, however, more than one cell-based assay may also be used. In a non-limiting example, additional cell-based assays may be performed for analysis of different characteristics when different cell-based assays are deemed more appropriate.

[0201] According to the present invention, cell-based assays are designed to mimic conditions associated with said pathological condition or said altered physiological state.

[0202] The main difference between the product validation procedures of the present invention and those of the prior art is based on the demonstration that the qualitative and quantitative characterization of products comprising or consisting of one or more natural matrices (due to emergent properties arising from the dynamic interaction of all their components), although informative, is not suitable for assessing the true efficacy of such products. Therefore, it is necessary to perform the validation procedure on a basis different from that underlying the validation procedures used for classical API-based therapeutic products. In fact, in the case of products comprising or consisting of natural matrices, as shown by the data provided in the Examples and Figures, qualitative and quantitative validation is neither sufficient nor suitable for ensuring the therapeutic efficacy of the product.

[0203] Therefore, the applicant developed a new method and process whose validation procedure is based on the definition of validation parameters that truly represent the therapeutic effectiveness of the product.

[0204] Nonetheless, manufacturers may still require additional metabolomic analysis, for example to assess the toxicological profile of a product.

[0205] Depending on the pathological condition of interest, the characteristic may be one or more, preferably more characteristics are selected when available, however, for example in the case of cancer, the skilled person is well aware that the most relevant characteristic is the proliferation of cancer cells, so the skilled person may limit the method of the invention to this single characteristic, and in this case the cell-based assay of choice would be an assay that verifies the viability of the neoplastic cells or tumor mass after administration of the product of interest.

[0206] According to an embodiment of the present invention, the method is a method for defining an acceptability value for a spectroscopic or spectrophotometric analysis for conformity verification of one or more batches of a product for treating a pathological condition, wherein the product comprises one or more natural matrices; the method comprising:

[0207] (a) performing at least one in vitro cell-based assay on a reference standard batch of the product and on one or more test batches of the product, wherein the reference standard has a known therapeutic effect for treating the pathological condition, wherein a readout of the cell-based assay represents modulation of one or more biological activities associated with one or more characteristics of the pathological condition;

[0208] (b) quantifying in numerical terms, for each cell-based assay readout, the modulation of the one or more biological activities induced by each batch of step (a) ("modulation value"), defining the value calculated for the reference standard batch as the reference value;

[0209] (c) defining as acceptable test batches for which the modulus of values calculated in (b) to induce modulation of each biological activity measured in the cell-based assay is ≥ the modulus of the reference value calculated in (b), and defining as unacceptable test batches for which the modulus of values calculated in (b) to induce modulation of at least one of the biological activities measured in the cell-based assay is < the modulus of the reference value calculated in (b);

[0210] (d) performing a spectroscopic or spectrophotometric measurement on the reference standard batch and on the one or more different test batches; and

[0211] (e) defining the acceptability value of the spectroscopic or spectrophotometric spectrum as the range of variation of the spectroscopic or spectrophotometric spectrum values of all the acceptable batches and the reference standard batch, preferably refined by the spectrum of the unacceptable batches.

[0212] The expression "one or more values calculated in (b)" may be replaced by "one or more adjusted values" or "one or more adjusted values calculated in (b)" in any part of the description and claims.

[0213] When the same characteristic can be associated with a biological activity that can be monitored by different biological parameters, a skilled person may decide to perform more than one cell-based assay to monitor said activity. In the Examples section and figures, definitions of acceptability values using different parameters are provided, and the results show that in each case, despite the selection of different parameters to analyze the modulation of one or more biological activities, the results are consistent and the resulting spectral or spectrophotometric spectral variation ranges defining the acceptability values are the same when the same spectroscopic technique is used.

[0214] The skilled person will be able to select more appropriate parameters based on selected characteristics of the pathological condition of interest.

[0215] Said parameters may be, for example, genes and their expression patterns, ROS, oxidative stress, cell viability, etc.

[0216] Mutual amendments apply to beneficial products (homeostasis-supporting agents) comprising one or more natural matrices. Therefore, the present invention also encompasses a method according to claim 1 for defining an acceptability value for a spectroscopic or spectrophotometric analysis for conformity verification of one or more batches of a beneficial product for supporting homeostasis under altered physiological conditions, wherein the product comprises one or more natural matrices; the method comprising:

[0217] (a) subjecting a reference standard batch of the product and one or more test batches of the product to at least one in vitro cell-based assay, wherein the reference standard has a known beneficial effect for assisting homeostasis under an altered physiological condition, wherein a readout of the cell-based assay represents modulation of one or more biological activities associated with one or more characteristics of a pathological condition that may develop from the altered physiological condition;

[0218] (b) quantifying in numerical terms, for each cell-based assay readout, the modulation of the one or more biological activities induced by each batch of step (a), defining the value calculated for the reference standard batch as the reference value;

[0219] (c) defining as acceptable test batches for which the modulus of values calculated in (b) to induce modulation of each biological activity measured in the cell-based assay is ≥ the modulus of the reference value calculated in (b), and defining as unacceptable test batches for which the modulus of values calculated in (b) to induce modulation of at least one of the biological activities measured in the cell-based assay is < the modulus of the reference value calculated in (b);

[0220] (d) performing a spectroscopic or spectrophotometric measurement on the reference standard batch and on the one or more different test batches; and

[0221] (e) defining the acceptability value of the spectroscopic or spectrophotometric spectrum as the range of variation of the spectroscopic or spectrophotometric spectrum values of all the acceptable batches and the reference standard batch, preferably refined by the spectrum of the unacceptable batches.

[0222] According to the present invention, step a) may comprise:

[0223] a. Retrieve a list of characteristics of the pathological condition from the prior art;

[0224] b. for each of said characteristics, identifying a set of biological activities that are detectable in said pathological condition and determining the modulation of each of said activities consistent with the desired therapeutic effect, thereby designing a modulation pattern for each of said activities that is representative of a healthy physiological state;

[0225] c. identifying parameters and their regulatory patterns (e.g., genes and their expression patterns) underlying the detectable modulation of each of the biological activities in the pathological condition, and assigning to each of the parameters a regulatory pattern that is opposite to the expression pattern identified as indicative of the healthy physiological state;

[0226] Step b) may include:

[0227] analyzing the pattern of regulation of each of the parameters identified in a) c (e.g., genes and their expression) induced by a reference standard of the product being analyzed in a suitable in vitro cell-based assay, determining the qualitative and quantitative modulation of each of said parameters induced by said reference standard relative to a pathophysiological control of said in vitro cell-based assay, and calculating a reference standard modulation value for each of said biological activities induced by said reference standard, and selecting each of said reference standard modulation values as a reference value (cut-off value) indicative of said desired therapeutic effect;

[0228] and analyzing the pattern of regulation of the parameters identified in a) c (e.g. genes and their expression) induced by further different batches of said product in said in vitro cell-based assay and determining the qualitative and quantitative modulation of each of said parameters induced by each of said batches, thereby calculating the modulation value induced by each of said batches for each of said biological activities;

[0229] Step c) may include:

[0230] comparing the adjusted values calculated in b) for each of said biological activities induced by each of said batches with the corresponding reference values, and defining as acceptable the test batches (preferably at least three) for which the adjusted values calculated in b) comply with the corresponding reference values (i.e. the reference values are intended as cut-off values and the batch is defined as acceptable when each biological activity reaches the reference cut-off value), and preferably at least one negative batch for which at least one adjusted value calculated in b) does not comply with the corresponding reference adjusted value (and thus does not reach the desired cut-off value); the method further comprising the following steps

[0231] d) performing spectroscopic or spectrophotometric analysis on the reference standard and on the batch selected in c), and

[0232] e) defining an acceptability value for the spectroscopic or spectrophotometric spectrum as a variable range of spectral values produced by acceptable batches, preferably refined by spectra of unacceptable batches. In fact, when unacceptable batches exist, their spectra will define the unacceptable value when determining the compliance variation range. Thus, the method provides an acceptability value for the spectroscopic or spectrophotometric spectrum.

[0233] As described above, the reference adjustment value is intended to serve as a cut-off value (positive in the case of up-regulation and negative in the case of down-regulation) that each selected biological activity of a test batch must reach in order to be defined as acceptable.

[0234] The range of variation at each point of the spectra of the accepted batch and the reference standard batch can then be used as the acceptability range of values for new batches of product in the industrial level conformity verification process.

[0235] According to the present invention, the product that is subjected to the batch-to-batch validation process of the present invention and for which the method of the present invention provides an appropriate acceptability value is a product comprising or consisting of one or more natural matrices for the treatment of a pathological condition, i.e. a product having a therapeutic effect validated at least in preclinical in vitro cell and / or tissue and / or organoid and / or in vivo animal model, and therefore, when administered to a patient suffering from a given pathological condition, is expected to reduce the severity of the subject's condition (i.e., at least partially improve or alleviate the severity) and / or provide some degree of relief, alleviation or reduction of at least one clinical symptom of the condition and / or delay the progression of the condition. According to the present invention, the subject to be treated is an animal, including a human (so that the product is for human or veterinary use), or even a plant.

[0236] The methods and processes provided by the present invention are in fact processes that can be carried out with the goal of validating batches of a given therapeutic product containing or consisting of a natural matrix in a production chain.

[0237] As mentioned above, a product is a product comprising or consisting of one or more natural matrices (i.e. complex natural systems); non-limiting examples of said natural matrices are represented by one or more of the following: cut or comminuted plant parts, plant extracts, processed plant parts, fractions of plant extracts, for example fractions obtained by filtration on semipermeable membranes (microfiltration, ultrafiltration, nanofiltration) or by treatment on adsorption resins, microorganisms, honey, propolis, silk, wax, plant resins, plant gums, plant exudates, plant oils, plant essential oils, animal tissue lysates, plant or animal fluids.

[0238] Preferably, the microorganism is an inactivated microorganism, such as a tyndallized organism.

[0239] In a most preferred embodiment, therapeutic product is the product being made up of 100% natural components, is intended as the component that is not obtained by human by chemical synthesis reaction, therefore, when product comprises one or more natural matrix, it can also comprise mineral matter, and generally speaking, any other organic or inorganic material found in nature.Preferably, the product carrying out method and process of the present invention is according to standardization scheme, more preferably obtains or obtainable product by health preservation standardization scheme.When there is no available standardization scheme, technicians can still minimize the difference between the batch of same product by using the collection of initial original source or intermediate material or natural matrix for each kind of natural matrix comprised in the product.In this way, the inherent variability of the natural matrix of different samples (for example, from the same plant of different cultivars) that is derived from same kind source can be reduced by described collection.

[0240] According to the present invention, the product may be, for example, a food supplement, a medical device or a pharmaceutical.

[0241] In one embodiment, the product is a medical device as defined in Article 2(1) paragraphs 1-3 of Regulation (EU) 2017 / 745, where the medical purpose is to treat or alleviate a disease or to modify a pathological process or state.

[0242] Article 2(1) paragraphs 1-3 of Regulation (EU) 2017 / 745 provides that:

[0243] For the purposes of this Regulation, the following definitions apply:

[0244] (1) “Medical device” means any [...] material or other article intended by the manufacturer to be used, alone or in combination, for the specific medical purpose of human beings for one or more of the following:

[0245] — diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of disease,

[0246] — diagnosis, monitoring, treatment, relief or compensation for injury or disability,

[0247] — investigation, substitution or modification of anatomical or physiological or pathological processes or conditions,

[0248] […]

[0249] It cannot achieve its primary intended effect in or on the human body through pharmacological, immunological, or metabolic means, but may assist its function through such means. The product may also be classified as a medical device by the FDA.

[0250] Under section 201(h)(1) of the Food, Drug, and Cosmetic Act, a device is:

[0251] An apparatus, device, implement, machine, device, implant, in vitro reagent or other similar or related article of manufacture, including its components, parts or accessories, having the following characteristics:

[0252] (A) has been recognized in the official National Formulary or the United States Pharmacopeia or any supplement thereto,

[0253] (B) is intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease in humans or other animals, or

[0254] (C) is intended to affect the structure or any function of the human or other animal body and does not achieve its primary intended purpose by chemical action in or on the human or other animal body and does not rely on being metabolized to achieve its primary intended purpose. The term “device” does not include software functionality excluded under section 520(o).

[0255] The spectroscopic or spectrophotometric analysis of the method of the invention is preferably performed on the product of interest in dry form, so it can be performed on a lyophilized product before rehydration when the intended use of the final product is a solution, suspension or other liquid form.

[0256] In its final form of administration, the product may be in the form of powder, granules, tablets, syrups, solvents, suspensions, hard or soft gelatin, capsules, sprays, creams, and the like.

[0257] According to the present invention, a pathological condition is a specific disease or pathological state. Non-limiting examples of pathological conditions include mild cognitive impairment (MCI), osteoporosis (OP) (including postmenopausal or perimenopausal osteoporosis (PMO)), osteoarthritis (OA), cancer.

[0258] These include, but are not limited to, cancers of primary concern such as head and neck cancer, melanoma, breast cancer, bladder cancer, and osteosarcoma.

[0259] The characteristics of pathological conditions and specific diseases are well known in the art. A skilled person can easily search the scientific literature for the characteristics of a pathological condition of interest and the biological activities underlying said characteristics. Obviously, the skilled person will select the biological activity underlying a given characteristic based on the specific pathological condition of interest.

[0260] For example, a skilled artisan can use various prior art sources to study the pathophysiology of a disease of interest.

[0261] A skilled person who wishes to define the characteristics of a disease of interest will be able to retrieve the desired information from the scientific literature. For example, non-limiting examples of sources that can be used are Robbins & Cotran Pathologic Basis of Disease (Robbins Pathology), 10th edition; https: / / calgaryguide.ucalgary.ca / ; from PubMedCentral( https: / / pubmed.ncbi.nlm.nih.gov / ) biomedical literature, etc.

[0262] For each of the features, the multiple biological activities underlying them are also known in the art, and a skilled person can select the functions from those disclosed in the art. When more biological activities are attributed in the art to a given feature of a given pathology in the method of the present invention, it is preferred to select at least two, at least three or more of the activities.

[0263] When it is desired to use available specific software to easily perform certain steps of the method of the present invention, such as finding the biological activity behind a disease feature, the skilled person may wish to adjust the retrieved feature to suit its definition to better interrogate the software being used. For example, if the software being used is Qiagen IPA (IPA version 94302991 Qiagen), if IPA uses a different internal definition of the feature, then if necessary, the feature can be redefined using the information found in the above resources to interrogate IPA. In order to quickly identify the biological activity behind a disease feature, when using IPA, the following procedure can be followed:

[0264] You can fill in the characteristics one by one in the "Disease and Function" query box and then start the search.

[0265] The resulting recovery table allows technicians to filter diseases / activities from multiple lines of evidence. For example, the source of the relationship can be the Ingenuity Knowledge Base, including journal articles, OMIM, JAX, and the curation of ClinicalTrials.gov.

[0266] This tool is therefore able to associate each biological activity with a certain number of genes, the regulation of which can influence the regulation of the biological activity itself.

[0267] Examples of known features associated with pathological conditions include Figure 1-4 , as shown in 8-12.

[0268] By way of example only, characteristics of OA known in the art include: proliferation (skeletal and muscular system development and function, such as joint dysfunction and joint space); inflammation; anatomical damage. Still by way of example, suitable biological activities behind the above-mentioned OA characteristics may include the following:

[0269] Proliferation: The biological activities of interest are, for example, the development and function of the skeletal and muscular systems, such as joint dysfunction and joint space, the formation of joint dysfunction, joint space and cartilage tissue,

[0270] Inflammation: Biological activities of interest are inflammatory diseases, inflammation and nociception, joint inflammation,

[0271] Protection from anatomical damage: The biological activity of interest is tissue damage and abnormalities, such as joint inflammation and swelling, difficulty in joint movement: osteoarthritis.

[0272] Possible prior art keywords defining the activity are Figure 1-4 It is pointed out in.

[0273] Furthermore, known features of MCI may include, for example, cognition (impaired), activation and viability (neurons, reduced), myelination and branching (reduced), inflammation (increased), skeletal and muscular system function (reduced).

[0274] Cognitive: The biological functions of interest are cognition and learning;

[0275] Activation and Viability: The biological activities of interest are development, differentiation of neurons, and proliferation of neuronal cells;

[0276] Myelination and branching: The biological activities of interest are neuronal branching, neuronal sprouting;

[0277] Inflammation: The biological activity of interest is chronic inflammatory disorders;

[0278] Skeletal and Muscle System Function: The biological activities of interest are muscle cell proliferation and muscle necrosis.

[0279] Possible prior art keywords defining the activities are indicated in 8 and FIG. 9 .

[0280] Still for example, known characteristics of OP (including PMO) may include mineralization, inflammation (increased), functional adipose tissue (increased), bone remodeling, osteoporosis, osteoblast differentiation (decreased).

[0281] Mineralization: The biological activity of interest is mineralization and bone formation by osteoblasts and osteoblasts;

[0282] Inflammation: The biological activity of interest is inflammation of adipose, connective tissue, and white adipose tissue;

[0283] Functions of adipose tissue: Biological activities of interest are weight gain, transdifferentiation, and differentiation of adipocytes;

[0284] Bone remodeling: The biological activity of interest is the remodeling and resorption of bone;

[0285] Osteoporosis: The biological activity of interest is osteoporosis itself;

[0286] Osteoblast Differentiation: The biological activities of interest are activation of alkaline phosphatase, differentiation of osteocytes, and differentiation of osteoblasts.

[0287] Possible keywords associated with the activities are indicated in Figures 10 and 11.

[0288] For each of the described characteristics, the biological activities underlying them are known in the art.

[0289] For each of the biological activities, modulation that is causally related to pathological conditions is also known in the art, and thus, opposite modulation can be considered modulation consistent with a desired therapeutic effect. Thus, a panel can be designed that indicates the desired modulation pattern for each of the activities, the panel representing the "regulatory trend of the activity under a healthy physiological state," i.e., the panel represents the manner in which the activity should be modulated to restore a healthy physiological state (see Figure 1-4 , 8-11). Regulation in this specification is intended to regulate a given activity and a specific parameter associated with the development or presence of a specific condition (e.g., pathological, changed but not yet pathological, or healthy) upward or downward. Upregulation refers to a change in the activity or expression of a specific gene, protein, cell pathway or cell component, resulting in an enhancement of a given biological activity. Downregulation is the opposite of upregulation. It involves a change in the activity or expression of a gene, protein, cell pathway or cell component, resulting in a reduction in a given biological activity. Therefore, the regulatory trend for restoring a healthy physiological state is intended to be the directionality (upward or downward) of the regulation of the selected biological activity that can be observed or expected when transitioning from a pathological or changed condition to a healthy state. Therefore, if the given activity behind the pathological condition is upregulated under a pathological or changed condition, the regulatory trend for restoring a healthy physiological state is downregulated. In other words, the regulatory trend for restoring a healthy physiological state of one or more activities behind a pathological or changed condition selected according to the method of the present invention is opposite to the regulatory trend detectable under a pathological or changed condition.

[0290] Non-limiting examples of modulation of biological activities causally related to pathological conditions (OA...PMO) are Figure 1-4 and 8-12.

[0291] Thus, conversely, restoration from an existing pathology of interest to a healthy physiological state can be designed to require reverse regulation of one or more selected biological activities. By way of example and not limitation, for OA, MCI, and OP, particularly PMO, the regulation leading to a healthy physiological state such as Figure 1-4 and 8-12.

[0292] When, for one or more, preferably most, and ideally all, biological activities causally related to the characteristics of a given disease, a pattern of regulation leading to a healthy physiological state is observed after treatment with a given product, the product can be identified as having a desired therapeutic effect. Thus, a product that induces regulation of biological activities causally related to the characteristics of a given pathological condition in the direction of a healthy physiological state can be identified as having a desired therapeutic effect on the overall pathological condition. When only some biological activities causally related to the characteristics of the disease are altered in the direction of the aforementioned physiological state, only a partial therapeutic effect is possessed, which does not lead to a fully healthy physiological state. However, a partial therapeutic effect is considered to fall within the scope of the present invention.

[0293] When gene expression is selected as a parameter, the skilled person can retrieve from existing techniques the genes underlying the alterations in each biological activity causally associated with each selected characteristic of the pathological condition, as well as the expression patterns of each of these genes. This work can be facilitated by the use of ad hoc bioinformatics tools. The same Qiagen IPA mentioned above is suitable for rapidly collating this information from the scientific literature, as it is an aggregator of scientific references, allowing the search for information on genes / proteins and the construction of networks that predict the behavior of biological systems based on their gene expression status.

[0294] For a given pathological condition, pathophysiological properties (features) available in the prior art are used to query the IPA via the "IPABioprofiler" tool using them as keywords, and other keywords related to the features can also be added.

[0295] The use of "IPABioprofiler" enables technicians to identify expressed genes causally associated with each of the identified biological activities and the specific molecular pathways that support them. Information on the measured gene expression data induced by each batch (for example, following the manufacturer's instructions, fold change value cutoffs ≤-2 and ≥+2 and p-value ≤0.05) is then superimposed on the obtained network to define the affected genes and the regulation of the relevant biological functions.

[0296] Once the most relevant genes and their expression patterns underlying the detectable alterations in each of the selected biological activities under the pathological condition of interest are identified, for each of the genes, an expression pattern opposite to the identified expression pattern is set as the expression pattern indicative of a healthy physiological state of the biological activity.

[0297] As described above, modulation of a biological activity is classified as downregulation or upregulation based on the regulation of the relevant gene. The expression pattern induced by a reference batch of the product of interest can be used to calculate the expected effect on one or more relevant biological activities. Specifically, based on the literature, the calculated expected effect on the relevant biological function can be determined using the "IPAMolecule Activity Predictor" tool (MAP) and restored in a heatmap visualization using a color code that can be easily converted to a numerical value by the user.

[0298] In vitro cell-based assays are well-known laboratory techniques that involve the use of isolated cells to study biological processes or test the effects of drugs, chemicals, or other substances.

[0299] According to the present invention, cell culture models such as monolayer cultures or three-dimensional (3D) systems may be used. Where appropriate, disease-specific cell lines may be used and proliferation assays may also be used depending on the disease of interest (eg, cancer).

[0300] Suitable in vitro cell-based assays are those designed to mimic disease, for example due to the nature of the cells used, or by inducing a disease phenotype in cells treated with specific compounds, ie "disease model assays" or "disease in a dish" models.

[0301] Cell Type Selection: Choose a cell line or primary cell that is relevant to the disease being modeled. For example, if studying OA, a suitable and well-established cell-based assay would use chondrocytes, which are an art-recognized model of OA disease after treatment with IL1B. For another example, if studying neurodegenerative diseases, one could choose a neuronal cell line such as SH-SY5Y, primary neurons, or primary cells in which the desired phenotype can be induced by "damage" with a given compound.

[0302] For the study of osteoporosis, and in particular PMO, a suitable cell-based assay can be prepared using a human adipocyte-derived mesenchymal stem cell line (hADMSC), which is capable of differentiating into osteoblasts and mineralizing the extracellular matrix (ECM), as described in the Examples.

[0303] For cancer research, viability testing can be performed in an appropriate (depending on the cancer of interest) cell-based assay.

[0304] Where, for example, ROS scavenging activity is the biological activity of choice, suitable cell-based assays can be performed with human fibroblast (HuDe) cell lines damaged with ROS-generating agents (eg, AAPH 2,2'-azobis-2-methyl-propionimide, dihydrochloride) known in the art.

[0305] For cell-based assays where a pathological state must be induced by insult, it is also possible to test the assay cells directly with the product of interest to verify that modulation of the selected bioactivity follows the same trend as would be expected to result in a healthy physiological state. This is particularly useful for evaluating the beneficial (homeostatic) effects of a product.

[0306] Cell-based assays preferably include appropriate control groups, such as untreated cells, vehicle-treated cells, and cells treated with a compound known to have no effect on the disease phenotype. These controls help to distinguish specific effects of the test compound.

[0307] In those embodiments where the expression of one or more genes (e.g., gene expression profiles) is used as a parameter of one or more biological activities associated with the pathological condition of interest, transcriptomic analysis can be performed on a suitable in vitro cell-based assay that mimics the pathological condition of interest, and the genes and their expression patterns underlying the detectable changes in each of the selected biological activities under the pathological condition can be identified. In cases where the disease phenotype is caused by the administration of a specific agent to cultured cells, the changes representative of the pathological condition are those in the lesioned cells compared to untreated cells prior to lesioning, and the changes induced by a reference standard are those in the lesioned cells compared to the lesioned cells + reference standard.

[0308] Transcriptome analysis can be performed using any suitable technique known in the art, including next-generation sequencing and gene expression microarrays, and the transcriptome expression profile in basal cells can be assessed relative to cells treated to mimic a pathological condition to identify significantly differentially expressed genes and their expression patterns. According to the methods of the present invention, once the expression pattern of significantly differentially expressed genes in cells representing a disease phenotype compared to cells before the injury that induced the disease phenotype is assessed, the opposite expression pattern is considered to represent a restoration of a healthy physiological state (also referred to herein as "representing a healthy physiological state").

[0309] When gene expression is the parameter of choice, for each biological activity in a) the genes and their expression patterns underlying the detectable alterations of each of said biological activities in said pathological condition can be identified using appropriate tools from the prior art.

[0310] For example, a skilled artisan can derive this information using any suitable method, including using software designed specifically for this field, such as Ingenuity Pathway Analysis (IPA version 94302991 Qiagen).

[0311] The interpretation of high-throughput gene expression data is greatly facilitated by taking into account existing biological knowledge. This can be done using statistical gene set enrichment methods, where differentially expressed genes are intersected with gene sets that are associated with specific biological activities or pathways (Abatangelo, L. et al. (2009) Comparative study of gene set enrichment methods. BMC Bioinform., 10, 275). A recent approach involves the application of causal networks that integrate previously observed causal relationships reported in the literature (Chindelevitch, L. et al. (2012a) Causal reasoning on biological networks: interpreting transcriptional changes. Bioinformatics, 28, 1114-1121; Felciano, RM et al. (2013) Predictive systems biology approach to broad-spectrum, host-directed drug target discovery in infectious diseases. Pac. Symp. Biocomput., 2013, 17-28; Kumar, R. et al. (2010) Causal reasoning identifies mechanisms of sensitivity for a novel AKT kinase inhibitor, GSK690693. BMC Genom., 11, 419; Martin, F et al. (2012) Assessment of network perturbation amplitudes by applying high-throughput data to causal networks. BMC Syst. Biol., 6, 54; Pollard, J. Jr. et al. (2005) A computational model to define the molecular causes of type 2 diabetes mellitus. Diabetes Technol. Ther., 7, 323-336). While still relying on statistics, this is more powerful than gene set enrichment because it leverages knowledge about the direction of effect, not just association.

[0312] In a preferred embodiment, the skilled person can follow the protocol provided in the publication by Kramer et al., Bioinformatics vol 30no4 2014, pages 523-530 "Causal analysis approaches in Ingenuity Pathway Analysis provides and discuss asuite of algorithms and tools for inferring and scoringregulator networks upstream of gene expression data based on a large-scalecausal network derived from the Ingenuity Knowledge Base" or the manufacturer's instructions (IPA version 94302991 Qiagen). The methods and algorithms disclosed in the article enable the skilled person to predict downstream effects on biological activity and disease.

[0313] In the article, the authors describe the causal analysis method implemented in Ingenuity Pathway Analysis (IPA), focusing on the details of the underlying algorithm and its application in several real-world use cases. In particular, points a) b. and a) c. can be easily performed by technicians using Ingenuity Pathway Analysis (IPA version 94302991 Qiagen), a pathway analysis application well-known in the life science research community, cited in tens of thousands of articles, and helping us understand the causal relationships between diseases, genes, and upstream regulatory networks.

[0314] Step b) of the method of the present invention comprises:

[0315] quantifying in numerical terms the modulation of said one or more biological activities induced by each batch of step a) for each cell-based assay readout, defining the value calculated for the reference standard batch as the reference value;

[0316] In more detail, this step may comprise analyzing the modulation of each of one or more biological activities and / or parameters thereof induced by a reference standard of the product in the in vitro cell-based assay performed in step a), and determining the qualitative and quantitative modulation of each of the one or more biological activities and / or parameters thereof induced by the reference standard, and calculating a modulation value for each of each of said biological activities induced by the reference standard, thereby providing a reference standard modulation value (cut-off value) for each of said biological activities indicative of said desired therapeutic effect.

[0317] From the results obtained using the cell-based assay, it is possible to determine the qualitative and quantitative modulation of each of the activities and / or its previously identified parameters induced by each product batch sample relative to the control group, and thus to obtain a value representing the qualitative (which activity is modulated and in which direction, i.e., upregulation (positive value) or downregulation (negative value)) and quantitative (how much each activity is modulated relative to the control group) modulation induced by each batch on each of the biological activities; the magnitude of the value represents the distance relative to the control group (in the form of %, fold, etc.). The modulation of each activity can be expressed as a numerical value, such as a statistical value.

[0318] Depending on the parameters chosen, the modulation of a biological activity can be defined and characterized by various quantitative values commonly used by the skilled artisan depending on the specific context and type of biological activity under investigation. Some common values used to define modulation include: fold change, which is the ratio of the value of a biological activity under a specific condition or treatment to its value under a control or reference condition; for example, a fold change of 1 indicates no change, while a value greater than 1 indicates upregulation, and a value less than 1 indicates downregulation; log fold change, which is the logarithm of the fold change (usually to the base 2 or 10); percent change, which is the percentage difference between the value of the biological activity under a specific condition and the value of the biological activity under a control or reference condition; z-score, where the z-score represents the deviation of the observed value of the biological activity from its mean, normalized by the standard deviation (a positive z-score indicates an increase in activity, while a negative z-score indicates a decrease in activity); effect size, which is a measure of the size of the difference between two groups, often normalized to facilitate comparison across studies or datasets (Cohen's d is a common effect size measure calculated as the difference in means divided by the standard deviation); and area under the curve (AUC), which, for dynamic biological activities, such as signaling pathways or physiological responses, can be used to quantify the overall activity or response over time.

[0319] These values can be used alone or in combination to provide a comprehensive characterization of the modulation of a biological activity under different conditions or treatments. The choice of which value or values to use will depend on the specific research question, the nature of the biological activity, and the available data.

[0320] In the context of biological activities, z-scores can be used to express the modulation or change of a particular biological activity relative to its typical or baseline behavior. This is often used in fields such as systems biology, where researchers analyze high-dimensional datasets to understand complex biological processes.

[0321] In this context, the z-score indicates the degree to which a particular biological activity deviates from its expected or average behavior in a given context, usually in response to some stimulus, treatment, or condition.

[0322] For example, in gene expression analysis, a z-score can be calculated to assess how much the expression level of a gene changes in response to a therapeutic treatment compared to its expression under control conditions. A positive z-score indicates upregulation, while a negative z-score indicates downregulation.

[0323] Mathematically, a suitable formula for calculating a z-score for biological activity regulation might involve comparing an observed value under a particular condition to the mean and standard deviation of its values across multiple conditions or replicates:

[0324] z=x-μ / σ

[0325] where x represents the observed value of the biological activity (eg, gene expression level), μ is the mean of the activity across all conditions, and σ is the standard deviation of the activity across all conditions.

[0326] This z-score approach enables researchers to identify and prioritize biological activities that are significantly altered under certain experimental conditions, providing insight into the underlying mechanisms of biological systems.

[0327] Once the desired modulation of a biological activity is defined (i.e., modulation representative of a healthy physiological state) and, optionally, the desired modulation of relevant parameters (e.g., ROS scavenging activity, genes, etc.) for the pathological condition of interest is identified, the modulation of the biological activity induced by a reference standard of the therapeutic product (optionally modulation of one or more parameters thereof, such as gene expression determined by transcriptomic analysis) is analyzed in an in vitro cell-based assay representative of the pathological condition. As previously clarified, the reference standard has a previously assessed therapeutic or beneficial effect. The qualitative and quantitative modulation of one or more selected biological activities and / or one or more parameters thereof (e.g., expression of a gene of interest) induced by the reference standard is determined, and a modulation value for each of the selected biological activities is calculated and subsequently used as a reference modulation value or "cut-off value" for each of the biological activities indicative of the desired therapeutic effect.

[0328] As mentioned above, the reference standard for a test product is a batch of the product of interest whose therapeutic or beneficial effects have been evaluated in vitro and / or in vivo, preclinically or clinically. In any case, it is a batch of the product of interest whose therapeutic or beneficial effects have been previously validated and therefore defined as a batch with known therapeutic or beneficial effects.

[0329] According to one embodiment, the reference standard adjustment value for each biological activity is considered to be a reference adjustment value representing the desired therapeutic or beneficial effect. When a cell-based assay is also performed on one or more reference drugs (i.e., drugs known in the art that are indicated for treating the pathological condition of interest), the reference adjustment value can be adjusted, as described below. Although it is expected that the drug will adjust at least some of the selected biological activities in a desired trend, due to its different mechanism of action (SAR), it is expected that the drug will not adjust all of the selected biological activities in a desired trend. Therefore, as explained in more detail below, the adjustment of the reference adjustment value that also takes into account the drug adjustment value will only be performed for the biological activities that are adjusted by the test drug in the direction of having the same trend as the healthy physiological state.

[0330] The modulation values in step b) are calculated to represent the directionality and magnitude of modulation of each biological activity exerted by a given batch of product. For transcriptomics, the skilled person can readily obtain the modulation values in terms of the above-mentioned Z-score values using the core analysis of Qiagen IPA version 94302991 following the manufacturer's instructions.

[0331] In cases where the core analysis does not yield sufficient relevant information, an alternative approach may be employed. An example of an alternative approach is provided below (overlay analysis). Step b) of the method of the invention comprises quantifying numerically the pattern of regulation of the parameters identified in a) c. induced by further different batches of the product in the in vitro cell-based assay by determining the qualitative and quantitative regulation of each of the parameters induced by each of the batches, thereby calculating a Z-score regulation value for each of the biological activities induced by each of the batches.

[0332] Preferably, at least three acceptable batches and one unacceptable batch are required, so the technician must analyze at least four additional batches of the product of interest.

[0333] As described above, a batch is considered acceptable if the adjusted value for each biological activity is greater than or equal to the reference adjusted value when the desired adjustment of the biological activity is upward, and if the desired adjustment of the biological activity is downward, the adjusted value for each biological activity is less than or equal to the reference adjusted value. Conversely, if the adjusted value for at least one biological activity does not meet the above requirements, the batch is considered non-compliant (unacceptable) and can be used as a reference for the final evaluation of the acceptability of the spectroscopic or spectrophotometric spectrum.

[0334] According to a preferred embodiment of the present invention, additional different batches of the product of interest can be analyzed. In particular, when a batch X of the product of interest that has not been analyzed using the cell-based assay described herein does not fall within the acceptability values for the spectroscopic or spectrophotometric spectrum in the inter-batch validation process of the present invention, the batch can be subjected to steps a) through c) of the method for determining the acceptability value for the spectroscopic or spectrophotometric analysis. If the batch meets the reference adjustment value (i.e., the batch has the desired adjustment of the biological activity, which indicates the desired therapeutic effect), then the batch X is considered acceptable, and the acceptability value for the spectroscopic or spectrophotometric spectrum used in the method of the present invention can be adjusted accordingly.

[0335] Additionally, if desired, steps a) and b) can also be performed using one or more reference pharmaceutical products (i.e., pharmaceutical products routinely administered to treat the pathological condition of interest). For each biological activity that is also altered in the direction of a healthy physiological state by the one or more pharmaceutical products, the reference regulatory value can be adjusted by comparing the pharmaceutical product regulatory value with the reference standard regulatory value and selecting the regulatory value associated with the weakest property as the reference regulatory value.

[0336] Conventional pharmaceuticals, due to their mechanism of action (SAR), are expected to modulate only a few selected biological activities in the desired direction, and therefore only regulatory values related to activities that are significantly modulated in the same direction as in the healthy physiological state are considered.

[0337] As known to the skilled person, reference drugs for treating pathological conditions may be known a priori to provide therapeutic effects on only one or several features of the disease. In this case, the information to be incorporated into the method of the present invention will only relate to the features of interest and the associated biological activities.

[0338] As described above, the methods of the present invention can include determining one or more parameters and their regulatory trends underlying the changes detectable under the pathological condition for each of the biological activities in both diseased and healthy physiological states. In a preferred embodiment, the parameters are genes. Preferably, gene regulation is assessed by transcriptome analysis.

[0339] In a non-limiting embodiment, the method of the present invention can be performed with the aid of IPA version 94302991 Qiagen as follows:

[0340] Pathophysiological state-of-the-art definitions of diseases and pathophysiological features of diseases used to interrogate IPA

[0341] Existing techniques for studying the pathophysiology of diseases of interest using different specific sources:

[0342] -Robbins&Cotran Pathologic Basis of Disease (Robbins Pathology) 10th Edition

[0343] -https: / / calgaryguide.ucalgary.ca /

[0344] - Biomedical literature from PubMed Central (https: / / pubmed.ncbi.nlm.nih.gov / )

[0345] The information found in the above resources is used to identify characteristics of the IPA to be interrogated through the following procedures:

[0346] Fill in the features one by one in the “Disease and Function” query box and start the search.

[0347] The resulting recovery table allows one to filter diseases / activities from multiple lines of evidence. The source of the relationships is the Ingenuity Knowledge Base, including curation of journal articles, OMIM, JAX, and ClinicalTrials.gov.

[0348] Computer models will be limited to genes and mRNA.

[0349] This tool can associate each biological activity with a certain number of genes, whose regulation can affect the regulation of the biological activity itself.

[0350] The following applies to any step of the method of the invention in any embodiment described herein, wherein an in vitro cell-based assay is performed and cells with a disease phenotype are treated with a given compound, which may be a reference standard, different batches of a product of interest, a reference pharmaceutical product, etc.

[0351] Whole transcriptome raw data analysis

[0352] Global transcriptome expression profiles were assessed in in vitro cell models of disease representing both control and model cells. HumanClariom on a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific) TM S Pico Assay HT (Applied Biosystems, ThermoFisher Scientific) can be used according to the instructions of the manufacturer. CEL intensity files can be generated by Affymetrix GeneChip Command Console Software (AGCC, ThermoFisher Scientific). Data analysis can be performed using Transcriptomic Analysis Console Software (TAC, ThermoFisher Scientific), which provides quality control analysis, performs standardization and aggregation based on Signal Space Transformation-Robust Multi-Chip Analysis (SST-RMA) analysis algorithm, and provides a list (Limma Bioconductor bag) of differentially expressed genes. This stage allows users to obtain a list of differentially expressed genes (DEGs), which are identified according to their expression fold change relative to relevant control experimental conditions (in this case, conditions that reproduce pathological conditions in vitro).

[0353] The transcriptional modification profiles thus obtained were subjected to functional pathway enrichment analysis. One commercial tool that can be used is Ingenuity Pathway Analysis (IPA version 94302991, Qiagen) [ et al. (2014)]. The use of IPA allows users to estimate how and to what extent modulation of gene expression in a cellular system (cell-based assay) affects biological activities relevant to a pathology of interest.

[0354] IPA pre-analysis filtering of transcriptional profiles (Contextual Data Analysis)

[0355] In preparation for subsequent analysis, the transcriptome profile is filtered to identify relevant genes and their corresponding measurements. The purpose of this filtering is to select only genes that are significantly disturbed, as indicated by their fold change compared to the pathological condition. Typically (e.g., according to the manufacturer's instructions), the fold change threshold is set to include values ≤-2 and ≥+2, with a statistical significance represented by a p-value ≤ 0.05. However, taking into account the successful performance of negative controls (samples representing pathological conditions) or reference standards known to be able to fully or partially offset pathological conditions, skilled operators can flexibly adjust the cutoff value based on their expertise.

[0356] There are two possible approaches to extract biological meaning from the list of modifications in gene expression profiles by IPA: “core analysis” and “superimposition analysis of in silico models of pathophysiological states” (abbreviated as superimposition analysis).

[0357] Therefore, at this stage of the procedure, two different alternatives can be pursued.

[0358] Core Analysis

[0359] Upload the list of differentially expressed genes (DEGs) after administration of the reference standard or any other product batch / reference drug or other substance, along with the corresponding data measurements (fold change relative to the pathological state) identified under different experimental conditions, into the application. Map the available identifiers to the corresponding entities in the QIAGEN knowledgebase.

[0360] By initiating "core analysis," significantly perturbed DEGs (referred to as network-qualified molecules) were overlaid onto a global molecular network developed based on information contained in the QIAGEN knowledgebase. A network of network-qualified molecules was then algorithmically generated based on their connectivity.

[0361] Core analysis provides a comprehensive list of approximately the top 500 biological activities derived from the generated network. The program's "biological function-gene" associations are always supported by annotations corresponding to scientific peer-reviewed publications, which are automatically correlated by Z-scores [ et al. (2014)] confirmed the directionality and magnitude of the regulation of the calculated biological activity. Essentially, 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 the existing literature for a given annotation.

[0362] It is the responsibility of the skilled practitioner to carefully select a biological activity that is relevant to the particular condition being studied. The choice of biological activity will be constructed based on the identified characteristics of the condition of interest.

[0363] The associated Z-score values will then be used to indicate the directionality and magnitude of regulation of each biological activity.

[0364] Overlay analysis

[0365] If the core analysis does not yield sufficient relevant information, an alternative approach called "overlay analysis" can be employed. This analysis focuses on bioactivities identified through "in silico models of the pathophysiological state." The selection of bioactivities is structured based on identified features of the pathophysiological condition of interest.

[0366] "Overlay analysis" was constructed by establishing relationships between patterns of differentially expressed genes and selected biological activities (always supported by annotations corresponding to scientific peer-reviewed publications confirming the directionality and magnitude of modulation of the biological activity) using the following procedures:

[0367] Import a set of bioactivities selected from a computer model of a pathophysiological state into a new worksheet called "My Pathways."

[0368] Utilize the "Build Tool" and "Grow Tool" to identify differentially expressed genes (DEGs) that belong to the transcriptome profile under investigation and are associated with the regulation of the biological activity selected in the previous step.

[0369] Regulation of the identified DEGs is indicated using green (indicating down-regulation) and red (indicating up-regulation).

[0370] To determine the calculated expected effect of this experimentally observed modulation of gene expression on biological activity, the "Superposition" and "Molecular Activity Predictor" tools (MAP) were used. The "Predict" function was activated within the MAP tool to calculate the expected modulation of biological activity. The color coding was established from this:

[0371] -Orange: Increased activity

[0372] -Blue: Decreased activity

[0373] - White: Unattainable / Unpredictable

[0374] Since Overlay Analysis does not directly calculate a Z-score for each biological activity, but rather provides results in the form of colors that indicate the direction of the change, and the intensity of the color signal is proportional to the magnitude of the modulation of interest, it is necessary to convert the intensity of the modulation signal (graphically represented in the My Pathway tab) into a numerical value. This is achieved by converting the color intensity obtained for each biological activity into a Z-score.

[0375] One possible tool that can be used for this purpose is the "IPAmap_Parser" application, a web port of PipelinePilot that is designed to assign scores, called z-scores, to genes and biological functions based on the colors in the biological pathways generated by QIAGEN's Ingenuity Pathway Analysis software. The key step in this algorithm is the conversion from the RGB color model to the LAB model (https: / / www.xrite.com / it-it / blog / lab-color-space, published by Tim Mouw in October 2018), a colorimetric encoding that also allows the intensity of the color to be recorded, not just the RGB composition. This conversion occurs within the PipelinePilot "component," which uses a program written in R software based on specific functions of the colorspace package (https: / / cran.r-project.org / web / packages / colorspace / index.html, for details see Zeileis et al. 2020 Journal of Statistical Software, doi:10.18637 / jss.v096.i01).

[0376] Z-scores allow objective comparison of the effects of different treatments.

[0377] When the above regimen is performed using a reference standard, and optionally one or more reference medicinal products, the modulation (Z score) value obtained for each biological activity disclosed above is considered to be a reference cutoff Z score value for the desired modulation of said activity, such that when the desired modulation is upward modulation, the cutoff Z score value will correspond to ≥ the reference Z score value obtained according to the present specification, and when the desired modulation is downward modulation, the cutoff Z score value will correspond to ≤ the reference Z score value obtained according to the present specification.

[0378] If one or more reference products are also tested in the selected in vitro cell-based assay, the modulation Z-score values observed for the biological activity known to be modulated by the reference product can be considered to establish the compliance criteria (acceptable or unacceptable batch).

[0379] Reference medicines are medicines recommended by clinical guidelines for the treatment of a condition or condition of interest.

[0380] When the reference drug product tested in vitro in a) modulates one or more biological activities associated with the characteristics of the pathological condition of interest in the desired direction (healthy physiological state), the Z scores obtained using both the reference standard and the reference drug product are considered valid for the one or more biological activities, and therefore, the value associated with the weakest performance is assumed to identify the lower limit of compliance for each of the one or more biological activities and will be considered as the reference (cut-off) Z score for defining acceptable or unacceptable test batches of the product.

[0381] Step d) of the method comprises:

[0382] (d) performing a spectroscopic or spectrophotometric analysis on the reference standard batch and on the one or more different test batches; 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 (ultraviolet visible), fluorescence spectroscopy, light scattering. A skilled person will readily select a spectroscopic or spectrophotometric technique that is more suitable for analyzing the selected product, depending on the formulation of the product being analyzed (e.g., dry powder, liquid, etc.).

[0383] According to a preferred embodiment of the present invention, the spectroscopic analysis is performed using NIR. As is known to those skilled in the art, NIR spectroscopy is a vibrational spectroscopy technique that provides qualitative information about the chemical species present in the material being analyzed, as well as information about their physical state. Performing NIR analysis involves exposing the material to light of different wavelengths and measuring its vibrations at each wavelength. The vibrations detected depend on the composition and the interactions between the components, which influence the vibrational capacity of each component within the matrix. This analysis generates a vibrational footprint specific to the material.

[0384] NIR fingerprint analysis allows reconstruction of the chemical and physical profile of the molecular composition of each analytical sample affected by the chemical environment. In fact, the molecules in the sample can form bonds between them, particularly intermolecular and intramolecular hydrogen bonds. This causes the vibrational frequencies of both hydrogen atom stretching and bending to change, and causes the vibrational frequencies relative to single isolated molecules to change. Therefore, NIR spectroscopy can become an excellent means for characterizing complex matrices. Therefore, this technology is particularly suitable for the analysis of natural matrices because it provides the fingerprint of the entire matrix network and the fingerprint of the interaction between the various components of the matrix.

[0385] An example of an NIR spectrum curve is shown in FIG6 .

[0386] Step e) of the method comprises:

[0387] The acceptability value of the spectroscopic or spectrophotometric spectrum is defined as the range of variation of the spectroscopic or spectrophotometric spectrum values of all said acceptable batches and said reference standard batch, preferably refined by the spectrum of said unacceptable batches.

[0388] The range of variation obtained will depend on the spectroscopic or spectrophotometric technique used and the product tested.

[0389] Independent of the spectroscopic or spectrophotometric technique used, the common characteristic is that each of the "acceptable" batches and the reference standard is considered acceptable due to its assessed effect on the selected biological activity. a priori Set to a valid and acceptable product.

[0390] When NIR is used, the NIR acceptability values obtained by the method of the present invention are suitable for NIR conformity testing for batch-to-batch conformity (ie, validation of production batches).

[0391] Obviously, compliance testing must be performed using the same spectroscopic or spectrophotometric techniques as those used to assess acceptability values.

[0392] To define the acceptability value, complete NIR spectra of all acceptable batch samples and reference standards were obtained, the spectra were aligned and normalized (standard normal variate), and thus the wavelength (λ) region of interest of the spectra was defined, and the average spectrum of all spectra of the conforming (positive) samples + reference standards was generated.

[0393] The average spectrum obtained will be used as the Reference spectrum .

[0394] When performing NIR compliance testing on pharmaceutical API based products, pre-processing includes the (SNV) as described above, definition of the lambda region of interest, and a maximum compliance index value is typically used for compliance testing and is typically imposed as 3.5, meaning that the highest acceptable standard deviation value for a pharmaceutical product at any point in the spectrum is typically 3.5.

[0395] In the method disclosed herein, the acceptability value is not based on the qualitative and quantitative analysis of specific chemical substances in the product, but on the modulatory activity exerted by the product on the selected biological activity, therefore, the maximum conformity index (MCI) value usually applied in the quality control of classical APIs (related to the qualitative and quantitative chemical composition) cannot be considered a priori acceptable, and therefore this value is assigned based on the spectra of the batch and reference standard selected in iv).

[0396] Additionally, Sum2, which is more suitable for heterogeneous samples and is derived from CI but also takes into account the NIR spectra of one or more undesired samples, is preferably used as an acceptability parameter according to the present invention.

[0397] According to this embodiment of the invention, the CI (Conformity Index) limit for which the conformity test pretreatment is to be performed corresponds to the maximum value of the CI MAX (herein also defined as CI limit) defined by the spectra of the batch selected in iv) and the reference standard.

[0398] Thus, according to the present invention, the acceptability values of the spectroscopic or spectrophotometric analysis are defined based on the modulating activity for each selected biological activity exerted by the reference standard and the product batch that complies with the reference standard in said modulation.

[0399] Therefore, in the case of NIR spectroscopy, the CI limit (i.e., acceptability cutoff) is calculated according to the following formula:

[0400] CI=(A 参考,i -A 样品,i ) / s 参考,i

[0401] in

[0402] A 参考,i = Reference average absorbance (average spectrum) at a given wavelength (i)

[0403] A 样品,i = absorbance of the test sample at a given wavelength (i)

[0404] s 参考,i = Standard deviation of the reference spectrum at a given wavelength (i)

[0405] In compliance testing associated with heterogeneous samples, as mentioned above, the Sum2 parameter is more appropriate.

[0406] Sum2 = (sum of all CIs > CI limit - CI limit) / (sum of the number of points in the spectrum where CI > CI limit)

[0407] The selection of an appropriate parameter in compliance testing depends on the user-specific control problem that can be easily solved by the skilled person. In cases where the product contains or consists of one or more natural matrices (i.e., an extremely heterogeneous sample), Sum2 is a suitable parameter.

[0408] In one embodiment of the present invention, the Sum2 parameter is selected to determine the acceptability cutoff value for the compliance test.

[0409] Depending on the spectroscopic or spectrophotometric assay used, acceptability values are calculated mutatis mutandis using the same ratios as used for NIR spectra, i.e. by defining as acceptable the spectra obtained from an acceptable batch according to the invention and a reference standard.

[0410] According to the present invention, when one or more batches of a product comprising one or more natural matrices for use in the treatment of a pathological condition are subjected to a conformity verification process (conformity testing), the batch may, in the first analysis, result in "non-conformity" because its spectroscopic or spectrophotometric spectrum does not fall within the acceptable values defined by the method of the present invention.

[0411] In this case, it may be necessary to verify whether the nonconforming result is due to the batch's effective nonconformity with the desired regulation of biological activity (i.e., therapeutic effect) or to the fact that the acceptability parameters can be expanded, in which case the parameters can be adjusted.

[0412] According to the method of the invention, steps a) to c) may be repeated for the batch and if the batch results are acceptable, the acceptability value of the spectroscopic or spectrophotometric spectrum may be recalculated, also including the spectrum of the new batch.

[0413] The greater the number of acceptable batches, the more accurate the acceptability value of the spectroscopic or spectrophotometric spectrum obtained using the method of the present invention.

[0414] Furthermore, the method of the present invention may further include:

[0415] In step d), spectroscopic or spectrophotometric determination is performed on one or more a priori undesired batches of the product and it is verified that the spectra of the one or more undesired batches do not fall within the acceptability values defined in e) and, in the negative (i.e. when the batch result is within the acceptability values defined in e))

[0416] e') defining a new narrower acceptability value for the spectroscopic or spectrophotometric spectrum generated by taking into account the range of variation of the spectroscopic or spectrophotometric spectrum values of all said acceptable batches and said reference standard batch and all said undesirable batches as unacceptable.

[0417] Product manufacturers may desire the above additional features to ensure that batches resulting from foreseeable formulation errors in the production chain (e.g. absence of an ingredient, etc.) are a priori excluded from acceptable values for spectroscopic or spectrophotometric spectra in batch-to-batch conformity control.

[0418] The present invention also provides a method for determining a reference standard for a therapeutic product for treating a pathological condition, wherein the product comprises one or more natural matrices; the method comprising:

[0419] (1) subjecting multiple batches of the product and one or more reference drug products for treating the pathological condition to at least one in vitro cell-based assay designed to mimic conditions associated with the pathological condition, wherein a readout of the cell-based assay represents modulation of one or more biological activities associated with one or more characteristics of the pathological condition, and for each of the one or more biological activities, determining a trend in modulation toward restoration of a healthy state;

[0420] (2) quantifying, for each cell-based assay readout, the modulation of the one or more biological activities induced by each batch and drug product of step (1) in numerical terms, and defining the value associated with the weakest performance as the reference value for each biological activity altered by the one or more reference drugs based on the modulation trend for restoring a healthy state;

[0421] (3) selecting batches for which the modulus of the value calculated in (1) for inducing regulation of each measured biological activity in the cell-based assay is ≥ the modulus of the reference value calculated in (2), and defining the batch with the highest modulus value over a greater number of biological activities as the product reference standard batch.

[0422] Steps (1) and (2) are performed mutatis mutandis as described above and in the Examples as steps a) and b).

[0423] The parameters and their regulation patterns of the method for defining the acceptability values of the spectroscopic or spectrophotometric analysis for conformity verification of one or more batches of a product as described above are applicable mutatis mutandis to the method for defining a reference standard. Thus, in one embodiment, the parameters are genes and their regulation is their expression pattern.

[0424] Finally, the present invention provides a method for conformity verification (i.e., production quality control) of one or more batches of a product for treating a pathological condition or a beneficial product, said product comprising one or more natural matrices, said method comprising the following steps:

[0425] a. Perform spectroscopy or spectrophotometry analysis on each batch,

[0426] b. verify that the spectrum obtained satisfies each batch of the acceptability value defined according to the method of the present invention. In view of the fact that the method of the present invention provides reliable parameters for batch-to-batch verification of compliance of products comprising or consisting of one or more natural matrices, the skilled person will readily understand that the method of the present invention is also applicable, mutatis mutandis, to defining acceptability values for spectroscopic or spectrophotometric analysis of one or more batches of products comprising or consisting of one or more natural matrices for compliance verification of assisting the homeostasis of a system, organ or mechanism of a subject; comprising a step of calculating the acceptability value for a reference standard of the product and for spectroscopic or spectrophotometric spectra of one or more different batches of the product, the reference standard having a defined homeostasis-assisting effect in maintaining a healthy physiological state of the system, organ or mechanism; wherein the spectra are defined as acceptable based on the biological activity exerted by the reference standard and the one or more different batches of the product on one or more biological activities underlying the healthy physiological state in a cell-based assay.

[0427] In one embodiment of the present invention, the method may also be defined as follows:

[0428] A method for defining an acceptability range or cutoff value for a spectroscopic or spectrophotometric analysis for use in validating one or more batches of a product comprising or consisting of one or more natural matrices for use in treating a pathological condition; comprising calculating the acceptability range or cutoff value from spectroscopic or spectrophotometric spectra of a gold standard (reference standard) of the product and one or more different batches of the product, the gold standard having a demonstrated therapeutic effect in treating the pathological condition; wherein the spectra are defined as acceptable or unacceptable based on the biological activity exerted by the gold standard (reference standard) and the one or more different batches against one or more characteristics of the pathological condition in at least one cell-based assay.

[0429] The method as defined above may comprise the following steps:

[0430] i) a. Retrieving a list of characteristics of the pathological condition from the prior art;

[0431] b. for each of said characteristics, identifying a set of biological activities that are detectable in said pathological condition and determining the modulation of each of said activities that is consistent with the desired therapeutic effect, thereby designing a modulation pattern for each of said activities that is representative of a healthy physiological state;

[0432] c. identifying the parameters and their regulation patterns underlying the modulation of each of the biological activities detectable in the pathological condition, and setting a regulation pattern for each of the parameters that is opposite to the regulation pattern identified as indicative of the healthy physiological state;

[0433] ii) analyzing the expression pattern of each of the parameters identified in i) c. induced by a gold standard (reference standard) of the product in a suitable in vitro cell-based assay, determining the qualitative and quantitative modulation of each of the parameters induced by the gold standard (reference standard) relative to a pathophysiological control of the in vitro cell-based assay, and calculating a gold standard (reference standard) Z score value (i.e., modulation value) for each of the biological activities induced by the gold standard, and selecting each of the gold standard (reference standard) Z score values as a reference cut-off Z score value indicative of the desired therapeutic effect,

[0434] iii) analyzing the pattern of modulation of the parameters identified in i) c. induced by further different batches of said product in said in vitro cell-based assay and determining the qualitative and quantitative modulation of each of said parameters induced by each of said batches, thereby calculating a Z-score value for the modulation of each of said biological activities induced by each of said batches,

[0435] iv) comparing the adjusted Z-score value for each of said biological activities induced by each of said batches calculated in iii) with the corresponding reference cutoff Z-score value, and selecting at least three positive batches for which each Z-score value calculated in iii) complies with the corresponding reference cutoff Z-score value and at least one negative batch for which at least one Z-score value calculated in iii) does not comply with the corresponding reference cutoff Z-score value,

[0436] v) performing spectroscopic or spectrophotometric analysis on the gold standard and on the batches selected in iv)

[0437] vi) defining a variability spectroscopic or spectrophotometric range by considering each of the results obtained in v) to be acceptable for each positive batch and unacceptable for each negative batch, thereby providing said acceptability spectroscopic or spectrophotometric range or cut-off value.

[0438] The method may also include analyzing in step ii) the modulation pattern of the parameters identified in i)c. induced by one or more reference drugs for treating the pathological condition in the in vitro cell-based assay, and determining the qualitative and quantitative modulation of each of the parameters induced by each drug and calculating the drug Z score value (modulation value) for the modulation of each of the biological activities induced by each of the drugs, and for each biological function that is also altered in the direction of a healthy physiological state by the one or more drugs, comparing the drug Z score value with the gold standard (reference standard) Z score value, and selecting the Z score value associated with the weakest performance as the reference cutoff Z score value.

[0439] In one embodiment, the parameters and their regulation patterns correspond to the genes and their expression patterns underlying each of said biological activities that are detectably altered in said pathological condition.

[0440] For example, the product analyzed by the method of the present invention may be in dried or lyophilized form.

[0441] Additionally, in the method defined in the above paragraph, step iii) may be performed on one or more additional different batches of the product and the same spectroscopic or spectrophotometric analysis as performed in v) may be performed on one or more additional batches wherein the adjusted Z-score (adjusted value) value for each of the biological activities meets the corresponding cutoff Z-score value, and the acceptability range or cutoff value defined in vi) may be recalculated by defining each of the batches as also acceptable.

[0442] Furthermore, the method may further comprise the following steps:

[0443] vii) performing spectroscopic or spectrophotometric analysis on one or more a priori undesirable batches of said product and verifying that said one or more undesirable batches do not yield results within the acceptability range or cut-off value defined in vi), and, in the event of a negative

[0444] viii) defining a new, narrower spectroscopic or spectrophotometric range or cut-off value for variability by considering each of the results obtained in vii) as unacceptable.

[0445] In any part of the description and claims, the term "comprising" may be replaced by "consisting of," and "one or more reference adjustment values" may be replaced by "one or more adjustment cutoff values" or "one or more reference adjustment cutoff values."

[0446] The following examples are not intended to limit the present invention. Example

[0447] 1. Test product composition

[0448] Product A (Arté GX) Figure 2 -6)

[0449] Centella Asiatica dried leaf 90% w / w

[0450] Echinacea purpurea dried flowers 10% w / w

[0451] Extracted in water

[0452] Product B (Figure 9)

[0453]

[0454]

[0455] Product C (Figure 11)

[0456]

[0457] In the Examples, the word "conforms" when referring to cell-based assay samples refers to the acceptability of the adjusted value between batches relative to a reference standard, and when referring to spectroscopic or spectrophotometric analysis, it means that the batch meets the desired quality of the final commercial product.

[0458] 2. Representative In Vitro Cellular Assays for Osteoarthritis

[0459] An in vitro cell model reproducing 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 [1-3]. After the cell model was established, it was exposed to five different batches of "Arté-GX" [1.4 mg / ml] for 24 hours:

[0460] Batch 20B1955 (reference standard)

[0461] Batch 20I1279

[0462] Batch 20J1770

[0463] Batch 20B0596

[0464] Subsequently, batch 21E1640 and an aliquot of said batch that had been treated to induce product destabilization (referred to herein as batch DEST 21E1640) were also analyzed separately (see Figure 3 and 4 ).

[0465] Each time one of the batch solutions was added, fresh IL1B [5 ng / ml] was also added to the culture medium.

[0466] 2.1.1. Chondrocyte Experiment Timeline

[0467] The timeline of the experimental setup can be found in Figure 15 .

[0468] Gene expression analysis

[0469] At the end of the treatment period, cells were washed with 100 μl PBS, lysed and collected in RLT buffer (Qiagen, 1053393) supplemented with β-mercaptoethanol (Sigma, M3148) and DX reagent (Qiagen, 19088) for gene expression analysis. Total RNA was extracted from cell lysates using a QIAsymphony RNA kit (Qiagen) using a QIAsymphony SP instrument (Qiagen).

[0470] by Varioskan TM LUX Multi-Mode Microplate Reader (Thermo Scientific TM The quality and quantity of RNA were determined by measuring A230, A260, A280 and A320 on the PCR plate. The integrity of RNA was checked using the 2100expert_Eukaryote Total RNA Nano Kit (Agilent). The RNA was purified using Human Clariom TM The S Pico Assay HT (Applied Biosystems, ThermoFisher Scientific) was used to assess the whole transcriptome expression profile on a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific). Briefly, cDNA was generated using 6 ng of total RNA, and 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 CEL intensity files were generated using Affymetrix GeneChip Command Console Software (AGCC, ThermoFisher Scientific).

[0471] 2.1.3. Transcriptomics data analysis

[0472] Data analysis was performed using Transcriptomic Analysis Console Software (TAC, ThermoFisher Scientific), which provides quality control analysis, 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, p value ≤ 0.05).

[0473] 2.1.4. Bioinformatic modeling of experimentally observed transcriptome data

[0474] For each study batch, Ingenuity Pathways Analysis (IPA) (QIAGEN\Inc., https: / / www.qiagenbioinformatics.com / products / ingenuitypathway-analysis) [4] was used to assess the regulation of gene expression associated with the effect of interest.

[0475] IPA is an aggregator of scientific references that allows searching for information about genes / proteins and constructing networks that predict the behavior of biological systems based on their gene expression state.

[0476] The pathophysiology of the prior art "osteoarthritic condition" has been considered with particular attention to the following areas of concern:

[0477]

[0478] This knowledge is used to interrogate the IPA using the aforementioned keywords via the "IPABioprofiler" tool.

[0479] The use of "IPABioprofiler" allowed the identification of clusters of expressed genes causally associated with each of the identified biological activities and the specific molecular pathways that underpin them. Information on the measured gene expression data induced by each batch (fold change value cutoffs ≤-2 and ≥+2 and p-value ≤0.05) was then superimposed on the obtained network to define the affected genes and the regulation of the relevant biological functions.

[0480] Regulation of expressed genes is shown in varying intensities of blue (indicating downregulation) or red (indicating upregulation). Based on the literature, the calculated expected impact on relevant biological functions was determined by the "IPA Molecular Activity Predictor" tool (MAP) and restored in a heatmap visualization.

[0481] Converts a color and its intensity into numerical values.

[0482] 2.1.5. Results

[0483] The results of these tests compared the performance and mechanism of action of five different batches of Arté GX. The analysis showed that while all batches delivered reproducible biological effects, batch-specific fluctuations could also be identified in the induced transcriptional patterns. Clearly, the induction of slightly different transcriptional patterns still resulted in the modulation of the same desired biological activity. This is due to functional redundancy between the product's components and the body's interactions; thus, with multifocal mechanisms of action, slightly different compositions can produce the same effect. Figure 3 and Figure 4 ).

[0484] Since the induction and inhibition patterns were conserved, the five batches were considered to have equivalent biological output.

[0485] from Figure 4 As evident from the results summarized in , the transcriptional patterns observed across the five different batches elicited very reproducible biological effects, leading to Figure 4 Overall changes in pathological process and overall equivalence of pathological status across all batches reported in .

[0486] Targeted metabolomics

[0487] To understand whether the final matrix comprising "Arté GX" exhibits matrix effects, a series of analyses were performed on the aforementioned batch to characterize different aspects of the product. Targeted metabolomics analysis, which allowed the identification of most of these molecular components, was performed alongside the other analyses reported in this article.

[0488] As described above, the product is composed of two plant matrices that are combined to form the final new plant matrix. Several analytical techniques have been used to identify and quantify the major classes of compounds present in plants. Although metabolomics analysis cannot reveal dynamic changes within matrix components, it can provide a "picture" of the composition at the time of analysis.

[0489] In the following analysis, each individual component (plant metabolite) was specifically studied, hence the term "targeted metabolomics". This analysis allows for the capture of qualitative data by identifying the chemical compounds present in the material, and quantitative data by determining the concentration of each compound in the material.

[0490] For Arté GX, as many primary and secondary metabolites as possible were qualitatively and quantitatively characterized using an “omics” approach (based on targeted metabolomics analysis using multiple analytical methods).

[0491] The analytical method for chemical characterization of each batch is as follows. According to the chemical properties of the compound class present, the most appropriate analytical technique has been adopted. The analysis of chromatographic method and different detection technology combinations (for example, GC and LC are each combined with a suitable detector) makes it possible to identify and quantify organic compounds as appropriate. Inductively coupled plasma analysis using a single quadrupole mass spectrometer (ICP-MS) or an optical emission spectrometer (ICP-OES) makes it possible to determine the level of the element present, while anions are measured by ion chromatography and conductivity detector. Other gravimetric analysis methods are used to measure the material class that chromatographic method cannot quantify.

[0492] The following table summarizes all methods used.

[0493]

[0494]

[0495] The results summarized in the table below demonstrate significant compositional variability between batches and emphasize that it is impossible to generalize the multiple properties of a matrix to the sum of its individual components. The work performed and reported herein (see cell-based assay results), together with the following data, demonstrate that the biological effects elicited by products containing or consisting of one or more natural matrices cannot be summarized as the sum of the effects caused by their individual molecular components, but rather are the result of the interconnectedness and interactions between these components: matrix effects.

[0496] This means that it is not possible to formally define structure-activity relationships (SAR) according to the principles that are normatively applied to APIs.

[0497]

[0498]

[0499]

[0500]

[0501]

[0502]

[0503]

[0504]

[0505]

[0506] Note 1. Grey boxes represent chemical macro categories.

[0507] Note 2. % = concentration of the compound expressed as a percentage of the composition.

[0508] Note 3: (d%) = percentage deviation: (|reference standard (%) - test (%)| / (reference standard (%))) x 100).

[0509] Note 4: The term "total" refers to the sum of the values of the various compounds forming the respective group.

[0510] Note 5: <LdQ = below the limit of quantification.

[0511] Note 6. nd = compound not detected

[0512] Note 7. nq or NQ = non - quantifiable compound.

[0513] Note 8. / = compound not reported.

[0514] The results show that there are quantitative fluctuations (upward or downward) in the components of each chemical class among the five batches of co - extracts. If these fluctuations are used to predict the performance [or effect] of each batch, it would lead to a priori assumption that these batches have different biological functions, and if the applied criteria are valid for APIs that act through the key - lock paradigm due to the presence of an obvious SAR, it would lead to the rejection of batches that are not comparable to the reference standard. The analysis reported here asserts the following fact: Although all the different batches evaluated maintain biological functions, each of the identified single - molecule components does not meet the criteria set for a single API, thus indicating that the matrix should not be considered as an assembly of APIs.

[0515] As shown above, each batch retains its biological function.

[0516] Therefore, Figure 5 It is shown that relying solely on the quantitative analysis of individual components to estimate the reproducibility of the activity profile of a complex matrix is not representative and thus incorrect. In fact, considering the nature of the complex matrix, chemically distinct profiles (which should be considered different from a chemical perspective) in qualitative and quantitative terms elicit the same response related to the intended use in a biological system. This should not be an unexpected observation, but rather serves as further proof that the biological function of a complex matrix cannot be traced back to the sum of the activities of each single molecule within the matrix (i.e., from a chemical perspective). Therefore, the activity of the matrix cannot be predicted solely based on the nature and quantity of the molecules constituting the matrix.

[0517] This also highlights such a fact, promptly there is structural and functional redundancy mechanism, it gives matrix special elasticity, that is, as shown above, although qualitative and quantitative composition is different, still can mediate identical activity.In other words, it is incorrect to study matrix only from molecular angle, because the identification of its each component cannot predict its characteristic.This confirms the need to be able to describe the intrinsic characteristics of matrix rather than the method of just observing its molecular components.These methods, as the method provided among the present invention, should monitor the preservation of those parameters that the maintenance of biological function really depends on.

[0518] Near-infrared spectroscopy (NIR)

[0519] 3.2.1. Introduction

[0520] To create a control chart and provide NIR acceptability cutoffs, four batches of Arté GX manufactured on a prototype industrial scale (including a reference standard) selected as positive batches according to steps i) to iv) of the method of the present invention were analyzed and used to form a library of good quality samples (training set). The batches used to construct the training set were selected after conformity testing performed using the bioassay of the present invention (see also the Examples above).

[0521] Once the library was defined, batch DEGR 21E1640 of Arté GX, selected as negative batch according to steps i) to iv) of the method of the invention, was also analyzed.

[0522] These five batches were used to set the NIR acceptability parameters.

[0523] Once the acceptability parameters were defined, the two poor formulation qualities defined above (R19L4299 and R19L4298) and an unknown Arté GX batch (21E1640) were analyzed as test samples using the same operating procedures. Based on the results obtained after the compliance test analysis, the test samples were confirmed to be of good quality, depending on whether they passed the compliance test performed by the bioassay to confirm or possibly modify the acceptability criteria determined by the control chart as described above.

[0524] The aim of this study was to establish a control chart of predefined NIR spectra by evaluating the biofunctional compliance of a subset of multiple batches, as a fingerprint for differentiating valid compliant batches of Arté GX from samples of poor biological and / or formulation quality.

[0525] Below is a list of the four batches used to create the NIR library and a list of samples analyzed as tests:

[0526] Four batches of ArtéGX were used to construct libraries (Table 1) and freeze-dried.

[0527] 1 batch of low-quality ArtéGX (degraded, poor biological activity)

[0528] One batch of ArtéGX was freeze-dried as a library test (Table 2)

[0529] 2 batches of low formulation quality (Table 2)

[0530] Table 1. (Training set)

[0531]

[0532]

[0533] Table 2. (Test set)

[0534] product batch Arté GX 21E1640 Centella asiatica leaf aqueous extract R19L4299 Echinacea leaf aqueous extract R19L4298

[0535] 3.2.2. Instruments

[0536] Bruker NIR spectrometer, MPA model (Multi-Purpose Analyzer):

[0537] Resolution: 16cm-1

[0538] Wave number reproducibility: better than 0.04cm-1

[0539] Wave number accuracy: better than 0.1cm-1

[0540] Photometric accuracy: 0.1% T

[0541] Wavenumber range: 4000 to 12500 cm-1

[0542] Background scan: 64

[0543] Sample collection scan: 64

[0544] Statistical tests

[0545] Conformity testing

[0546] Conformity testing is a simple method for testing the deviation of a measured NIR spectrum within certain limits. To set these limits (acceptability values for the NIR spectrum), good and poor quality samples from at least one batch or production run of the final product are identified as reference spectra. According to the present invention, reference samples are identified using a bioassay (cell-based assay) deemed appropriate and studied using NIR to assess a minimum range within the specification, for example, to encompass the batch itself. According to the present invention, this range is imposed as acceptable to identify batches of unknown conformity (not tested in a cell-based assay and therefore unknown for acceptability based on their biological activity) as conforming. The NIR spectra of these samples reflect the variation in samples that achieve conforming and non-conforming performance in modulating one or more selected biological activities (therapeutic or beneficial), forming confidence bands within the spectral range. To pass the NIR conformity test, the spectrum of a 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 plus / minus the standard deviation defines the confidence bands within the spectral range and defines what amount of variation is acceptable for the product being analyzed at each spectral wavelength.

[0547] Secondly, it is necessary to check whether the spectrum of the sample under test falls within the confidence band defined within the spectral range. The difference between the sample and the mean value of the reference sample is calculated at each wavelength (i). This absolute deviation is then weighted by the corresponding standard deviation "s" at each wavelength, resulting in a relative deviation known as the Conformity Index (CI) equation (1).

[0548] (1) CI = (A 参考,i -A 样品,i ) / s 参考,i

[0549] A 参考,i = Reference average absorbance (average spectrum) at a given wavelength (i)

[0550] A 样品,i = absorbance of the test sample at a given wavelength (i)

[0551] s 参考,i = Standard deviation of the reference spectrum at a given wavelength (i)

[0552] In conformity testing, another parameter can be used to evaluate the batch against a reference library applying the CI limits.

[0553] This parameter, called Sum2, is expressed by equation (2):

[0554] (2) Sum2 = (the sum of all CIs > CI limit - CI limit) / (the sum of the number of points in the spectrum where CI > CI limit)

[0555] The selection of an appropriate parameter in compliance testing depends on the user-specific control problem that can be easily solved by the skilled person. In cases where the product contains or consists of one or more natural matrices (i.e., an extremely heterogeneous sample), Sum2 is a suitable parameter.

[0556] Therefore, in this example, the Sum2 parameter is selected to determine the acceptability cutoff for the compliance test.

[0557] 3.3.1 Sample preparation

[0558] Transfer each sample to a sample holder suitable for NIR analysis of heterogeneous solids. Before analysis, check that the bottom of the sample holder is completely covered.

[0559] 3.3.2 Sample collection

[0560] NIR spectra were acquired in reflectance mode using a rotating sample holder suitable for analyzing heterogeneous samples such as solids and powders to ensure high data reproducibility.

[0561] Quality control and background subtraction were performed before each acquisition.

[0562] The samples also reported in the previous tables (Table 1 and Table 2) were prepared as described above and analyzed under NIR.

[0563] Data preprocessing

[0564] Preprocessing is a mathematical operation used to infer spectral characteristics and reduce sources of variation.

[0565] To develop the preprocessing method, a preprocessing method involving the use of SNV normalization was chosen, and the 4200 to 9000 cm- 1 The spectral region of is taken as the spectral region most relevant to the model.

[0566] OPUS software (Opus 8.5, Bruker) was used to perform the compliance test.

[0567] By applying the preprocessing method, the following parameters in the OPUS conformity index method were set:

[0568] a) Preprocessing: SNV;

[0569] b) Region: 4200 to 9000 cm-1;

[0570] c) Compliance test parameters: Maximum compliance index value; Sum2

[0571] Data collection

[0572] The four batches shown in Table 1 and the batches in Table 2 were analyzed.

[0573] The spectra of the first four batches described above were used as reference spectra in generating the conformity indices (CIs) because they possessed the desired biological activity (acceptable according to the cell-based assay).

[0574] Perform SNV normalization preprocessing and select 4200 to 9000 cm -1 The CI MAX threshold and Sum2 value of each batch of this card are as follows:

[0575] CIMAX experimental determination of the method of the invention (intervals (steps i) to iv) based on biological data)

[0576] Batch Type Batch ID- Cell-based assays CI Max Sum2 refer to 20B1955 Reference standard, in accordance with 1.5 0.0 refer to 20I1279 conform to 1.5 0.0 refer to 20J1770 conform to 1.5 0.0 refer to 20B0596 conform to 1.3 0.0

[0577] ( Figure 6a NIR spectrum in

[0578] When referring to the cell-based assay, the table indicates "complies" when the batch is acceptable according to step c) of the method of the invention.

[0579] As reported above, the maximum conformity index value is assigned based on the maximum CI MAX value defined based on training of the cell-based assay consisting of conforming (positive) samples. Based on the first data (reported above), the CI limit was set to 1.5, so this value was used to calculate the Sum2 for the training and test sets.

[0580] To define the compliance limit for Sum2, the negative batch (i.e., non-compliant according to the biological data (cell-based assay) according to the method of the invention) DEST 21E160 was tested against the control chart. The table below shows the CI and Sum2 results for each batch.

[0581] Batch Type Reference ID- Formula compliance Cell-based assays CI Max Sum2 refer to 20B1955 conform to conform to 1.5 0.0 refer to 20I1279 conform to conform to 1.5 0.0 refer to 20J1770 conform to conform to 1.5 0.0 refer to 20B0596 conform to conform to 1.3 0.0 refer to DEG 21E1640 conform to Not compliant 5.8 1.3

[0582] (NIR average spectrum of the batch plus NIR spectrum of the batch that does not meet the requirements Figure 6b )

[0583] Based on the Sum2 value of batch DEG 21E1640 and its non-compliant results according to the cell-based assay, the threshold Sum2 value for defining a batch as non-compliant was set to ≤1.2. Once this acceptability cutoff was set according to the method of the present invention, spectra of a new unknown (not validated by the cell-based assay) batch of Arté GX and two known formulation non-compliant batches were tested to verify the reliability of the method of the present invention and its suitability for a quality control method according to the specification and claims.

[0584] result:

[0585]

[0586] Therefore, the results for the validation method batch 21E1640 of the present invention were in compliance according to the NIR assay with the acceptability cutoff value evaluated by the method of the present invention.

[0587] In order to confirm the effectiveness of the validation method of the present invention, batch 21E1640 was also adjusted for the biological activity identified above for the product ArtéGX, and the product results were acceptable, that is, the results were consistent with the reference adjustment values according to the method of the present invention.

[0588] Thus, processes and methods have been identified that allow the definition of acceptability criteria for products comprising or consisting of one or more natural matrices based on the concept of conservation of a variety of selected biological activities, regardless of their composition at the molecular level.

[0589] 3.4 Raman spectroscopy

[0590] Use the same batch of samples as in 3.2.

[0591] Each sample was deposited between two microscope slides to give a powder thickness of approximately 1 mm. Measurements were made using a Rigaku Xantus-2 spectrometer at 2000–200 cm -1 The scattering was performed in a range of 1000 nm using a 1064 nm laser line as the excitation source with an excitation power of about 100 mW and collecting radiation scattered at 180° relative to the excitation (backscattering).

[0592] 3.4.1 Collection conditions

[0593] The following measurement conditions were selected to acquire each spectrum:

[0594] Method of collecting the sample to be analyzed.

[0595]

[0596] For each sample, three replicates were taken to check the reproducibility of the data: the three replicates were then averaged to obtain a representative spectrum of the sample to be characterized. The average spectrum and standard deviation were obtained using Bruker Optics Opus 8.1 software.

[0597] 3.4.2 Preprocessing

[0598] The average spectrum of all samples thus obtained was processed to subtract the baseline; for this purpose, the 200, 790, 910, 1520, and 1800 cm -1 The intensity at 1610 cm was set to zero. -1 The intensity of the signal centered at is normalized ( FIG14 ). These operations were performed using Opus 8.1 software from Bruker Optics.

[0599] As shown in Figure 14, the spectrum shows a significant amplified signal in the low-frequency region. This signal may originate from the residual luminescence of the sample cover glass. Therefore, in subsequent processing, it was decided to limit the analysis range to 780 to 2000 cm -1 The area between.

[0600] 3.4.3 Statistical analysis

[0601] Statistical analysis of the spectral data was performed using Origin2023 software from OriginLab, and all steps required to obtain the parameters used in the conformity test were followed, e.g., the CI conformity index and Sum2 parameter using equations (1) and (2) in 3.3 above.

[0602] 3.4.4 Definition of Control Chart

[0603] The control charts were constructed using the same criteria as for NIR and ATR-FTIR spectroscopy.

[0604] Using Origin 2023 software, the spectra of 20B1955, 20I1279, 20J1770 and 20B0596 were used as reference spectra: the average spectra with relative standard deviations were obtained from them. The intensity values (normalized Raman) and the standard deviation as a function of frequency constitute the I in equation (1) using 3.3. 参考,i and s 参考,i Indicated data.

[0605] 3.4.5 Execution of conformity testing

[0606] For each of the reference spectra, the maximum value of CI as the frequency is varied is calculated using equation (1): In this way, the value of (CI Limit) used to calculate Sum2 can be determined using equation (2).

[0607] CI limit=CI Max=1.50

[0608] Using this value, two conformity tests were applied to the spectra of all analyzed samples via equation (2).

[0609] The table below summarizes the values of the co-extract samples used as reference spectra (R) when creating the conformity index method because they have the desired biological activity, the degraded 21E1640 sample that was required to define the conformity limit for Sum2, and those used as samples for method testing (T).

[0610]

[0611] In this case, the Sum2 value of the degraded sample was slightly higher than the Sum2 value obtained for the non-degraded sample from the same batch. Based on this compliance criterion, the unknown sample met the requirements of the co-extractive formulation.

[0612] 4. Free radical scavenger activity

[0613] As an additional control for the effectiveness of the methods and processes of the present invention, all Arté GX batches described above were also tested for their free radical scavenger activity, since this activity is known to have a significant promoting effect in osteogenesis. Figure 12 Characteristics and biological activities related to this parameter are summarized.

[0614] 4.1. Determination method

[0615] This assay involves the use of the human fibroblast (HuDe) cell line as a model to test the ability of products to have antioxidant activity based on scavenger activity.

[0616] Five different batches of Arté GX were tested at a concentration of 1.4 mg / ml, calculated by applying a dilution factor of 2.8, which reflects the dilution of the product in synovial fluid in an in vivo scenario.

[0617] The ROS scavenger activity assay is based on the use of the reactive oxygen species (ROS) generator AAPH (2,2'-azobis-2-methyl-propionimide, dihydrochloride), which mimics the appearance of exogenous prooxidative insults, thereby inducing endogenous ROS production. 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 intervals (every 10 minutes for a total of 90 minutes) using a fluorimeter (Varioskan Lux, Thermo-Scientific) and quantitatively correlated with the production of free radicals in cells. To account for cell number at the end of the assay, all calculated fluorescence values were normalized to the relative cell viability measured by the MTT (tetrazolium salt, [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, Sigma Aldrich) assay according to the manufacturer's instructions. The degree of protection provided by the tested products against ROS production was compared to the degree of protection obtained by protecting cells with ascorbic acid (considered a benchmark antioxidant molecule). The results are shown as the calculated integrated area under the fluorescence versus time curve (AUC) compared to AAPH (considered as 100% ROS production).

[0618] Results

[0619] Figure 7 All five batches of ArtéGX demonstrated equivalent free radical scavenger activity. All batches showed equally high and significant protective effects against fibroblasts.

[0620] The data discussed above further demonstrate that the five batches are equivalent in inducing the same biological effects due to their effects on gene expression as well as free radical scavenging activity.

[0621] Adjustment value (percentage) such as Figure 12 Calculation shown.

[0622] All batches were acceptable with respect to the modulation values determined against the reference standard, thus the NIR acceptability values calculated as described above demonstrate the suitability of the methods and processes of the present invention to monitor modulation of the selected biological activity or activities also using different parameters.

[0623] 4.Isotope abundance

[0624] 4.1. Introduction

[0625] Isotopic abundance analysis is a way to describe a substance from an atomic perspective. Characterizing the isotopic distribution of a starting material can be affected by phenomena of varying nature, which can lead to significant variations in the final product [ISPRA, Quaderni-Laboratorio 2 / 2018. ISBN 978-88-448-0873-0]. The isotopic composition of a sample is equal to the ratio between the abundance of the heavy and light isotopic forms (e.g., the relationship 13C / 12C) and is expressed as a deviation (in parts per thousand) from an internationally recognized standard reference material. A positive value of δ indicates an enrichment of the sample in the heavy isotope compared to the standard, while a negative value indicates a depletion of the sample in the heavy isotope.

[0626] The significant differences in the isotope abundance ratios of the samples compared to samples of known good quality can explain the different intramolecular and intermolecular interactions between the phytochemical classes that make up the matrix, regardless of the quantitative profiles of the individual species and the different chemical reaction kinetics. In the first case, this phenomenon is defined as the geometric isotope effect (GIE) and is particularly due to hydrogen bonding. In fact, the bond length between hydrogen and oxygen is smaller than the bond length between deuterium and oxygen. This may involve different structural rearrangements of both intramolecular and intermolecular structures.

[0627] Isotope abundance also alters reaction kinetics, a phenomenon known as the kinetic isotope effect (KIE), which can be primary or secondary, depending on whether the isotope modifies the reaction, making it faster or slower than the process of interest. Therefore, it is clear that the KIE establishes a link between a given isotopic abundance of a material and its ability to interact with biological systems in a reproducible manner. Therefore, analysis of isotope abundance appears to be a possible tool for monitoring product compliance from a physicochemical and potentially biological perspective.

[0628] Within a batch, variations in isotopic abundance ratios may indicate product adulteration, poor quality, and, when considering samples representing different intermediates in the production process, a general loss of the desired native conformation.

[0629] In this case, the acquisition of multiple good quality batches of the product, coupled with established conformity verification techniques such as NIR, may lead to the generation of a reference library in which individual batches can be evaluated and isotopic reproducibility verified within established ranges.

[0630] Furthermore, 14C activity assessment can define a system as 100% natural. This is because 14C is an unstable isotope (half-life of 5730 years) and therefore tends to accumulate in living materials, whereas the presence of this unstable carbon isotope is very low / absent in petroleum derivatives.

[0631] Results and discussion

[0632] Isotopic abundance analysis was performed on five batches (20B0596, 20B1955, 20I1279, 20J1770, 21E1640) that were included in the development and validation of the NIR method and thus constituted good quality batches. Batches 20B0596 and 20B1955 were prepared from different batches of starting materials compared to batches 20I1279, 20J1770, and 21E1640.

[0633] The samples were sent to Chelab (Tentamus Company) and analyzed for stable isotopes as follows:

[0634] -δ18O:Method IRMS,UNIT‰V-SMOW.

[0635] -δ13C:Method QMA-M-01,EA-IRMS,UNIT‰V-PDB.

[0636] C14 activity was also tested:

[0637] -14C activity: Method ISO-16620-2; 2015 (AMS), UNIT% modern carbon (pMC).

[0638] The results are as follows.

[0639] Delta ratios of major isotopes in Centella asiatica-Echinacea co-extracts.

[0640]

[0641] (The values in the table include percentage errors according to the official method used)

[0642] The C14 activity values measured for the Pmc samples corresponded to those obtained from pure bio-based carbon. There was no evidence of synthetic origin in the analyzed material. The C14 activity values overlapped perfectly between batches, as they were unaffected by the biological variability of the starting material. This conservatism of this parameter confirms the high reproducibility of the production process.

[0643] Two batches of co-extracts (20J1770 and 21E1640) were studied for their isotopic abundance during different steps of the manufacturing process.

[0644] The results are reported in the table below, which depicts the delta ratios of the major isotopes of the crude plant material of the Centella asiatica-Echinacea co-extract.

[0645]

[0646] Evaluation of the isotopic abundance of the material from the production process showed that the production process did not alter the abundance ratios, confirming the fact that the process retained the native biophysical properties of the starting material.

[0647] Analysis of the studied batches showed substantial similarity in values and maintenance of ratios during the manufacturing process. This is consistent with the previously described NIR results, according to which all batches were similar and there were no outliers with similar spectra after merging.

[0648] 5. RNA Assessment in Production Intermediates

[0649] Biophysical characterization of bioplant materials includes the evaluation of biomaterials in production intermediates.

[0650] "RIC199EL0, extract_BLEND CENT_ECH EL, batch R2014716" corresponds to the Arté GX production intermediate, an aqueous co-extract of Centella asiatica and Echinacea purpurea in the proportions described in Example 1 before ultrafiltration. The presence of RNA was quantitatively and qualitatively assessed. After homogenization using a QIAshredder column, RNA was extracted using a plant matrix-specific kit (RNeasy Power Plant Kit) and followed the kit extraction protocol. The obtained RNA was size-distributed using a Bioanalyzer 2100 and RNA6000 Nano, RNA6000 Pico, and small RNA kits.

[0651] exist Figure 13 In the figure, electropherogram "A" shows the size distribution of total RNA, and electropherogram "B" shows the size distribution of RNA between 4 and 150 nt.

[0652] To quantitatively assess the total RNA extracted from the samples, nucleic acid digestion was performed using the New England Biolabs Nucleoside Digestion Mix Kit. RNA concentration was expressed as total nucleosides by UHPLC-qToF analysis. The table below reports RNA expressed as total nucleosides.

[0653]

[0654] In addition to providing a method for verifying the biological origin of a matrix, these observations identify additional levels of both structural and functional complexity that need to be considered in product stewardship.

[0655] For ease of reference and comparison, the experimental protocols used for the three different products described in Example 1 are summarized in the table below.

[0656]

[0657]

[0658]

[0659]

[0660]

[0661] 5. Conclusion

[0662] In summary, the data reported here allow the definition of acceptability parameters that are crucial for ensuring the quality of the manufacturing process for products containing or consisting of one or more matrices of biological origin (natural matrices). Interestingly, the data suggest that exclusively monitoring compositional reproducibility at the molecular level does not represent a beneficial strategy, as this strategy overlooks key properties of the matrix that influence its ability to induce reproducible effects when used to treat biological systems. Presumably, due to the redundant effects between molecular components at the structural and functional levels and the presence of a complex network of physical and functional interactions within the matrix, its biological function depends largely on properties that can be better monitored by analyzing the biophysical properties of carefully selected matrices.

[0663] It is quite eloquent that the ability of different batches of the same product to elicit reproducible biological effects cannot be predicted using targeted metabolomics data alone, especially when judged according to the principles usually reserved for single APIs (see Figure 5 Compared to Figure 3 and Figure 4 By applying targeted metabolomics alone, these batches would have been mistakenly assumed to be unacceptably different from one another. In contrast, the application of techniques disclosed herein that monitor matrix properties that emerge and originate from interacting networks, and therefore differ from and only partially depend on individual single-molecule components, correctly identified a satisfactory degree of similarity between the different batches analyzed and expressed consistency with the fact that they indeed elicited reproducible, desired biological effects.

Claims

1. A method for defining acceptability values for a spectroscopic or spectrophotometric analysis for conformity verification of one or more batches of a product for treating a pathological condition or for assisting homeostasis under altered physiological conditions, the product comprising or consisting of one or more natural matrices, the method comprising: performing at least one in vitro cell-based assay and calculating said acceptability values for spectroscopic or spectrophotometric spectra of a reference standard and one or more batches of said product that have a known therapeutic or beneficial effect in treating said pathological condition or in assisting homeostasis in said altered physiological state, defining said spectra as acceptable or unacceptable based on the biological function of said reference standard and said one or more batches on said pathological condition or one or more characteristics of said pathological condition that may be derived from said altered physiological state in said at least one in vitro cell-based assay.

2. The method of claim 1 for defining an acceptability value for a spectroscopic or spectrophotometric analysis for conformity verification of one or more batches of a product for treating a pathological condition, wherein the product comprises one or more natural matrices; the method comprising: (a) performing at least one in vitro cell-based assay on a reference standard batch of the product and on one or more test batches of the product, wherein the reference standard has a known therapeutic effect for treating the pathological condition, wherein a readout of the cell-based assay represents modulation of one or more biological activities associated with one or more characteristics of the pathological condition; (b) quantifying in numerical terms, for each cell-based assay readout, the modulation of the one or more biological activities induced by each batch of step (a), defining the value calculated for the reference standard batch as the reference value; (c) defining as acceptable test batches for which the modulus of values calculated in (b) to induce modulation of each biological activity measured in the cell-based assay is ≥ the modulus of the reference value calculated in (b), and defining as unacceptable test batches for which the modulus of values calculated in (b) to induce modulation of at least one of the biological activities measured in the cell-based assay is < the modulus of the reference value calculated in (b); (d) performing a spectroscopic or spectrophotometric measurement on the reference standard batch and on the one or more different test batches; and (e) defining the acceptability value of the spectroscopic or spectrophotometric spectrum as the range of variation of the spectroscopic or spectrophotometric spectrum values of all the acceptable batches and the reference standard batch, preferably refined by the spectrum of the unacceptable batches.

3. The method of claim 2, further comprising determining, for each of the one or more biological activities, a regulatory trend thereof for restoring a healthy physiological state.

4. The method according to claim 3, further comprising performing said in vitro cell-based assay on one or more reference medicinal products for treating said pathological condition in step (a), In step (b), for each cell-based assay readout, the modulation induced by each reference drug in step (a) is quantified numerically, and for each biological activity altered by the reference standard and by the one or more reference drugs, the values calculated for each reference drug and for the reference standard are compared according to the modulation trend for restoring a healthy state, and the value associated with the weakest performance is selected as the reference value.

5. The method of claim 1 for defining acceptability values for a spectroscopic or spectrophotometric analysis for compliance verification of one or more batches of a beneficial product for assisting homeostasis under altered physiological conditions, wherein the product comprises one or more natural matrices; comprising: (a) performing at least one in vitro cell-based assay on a reference standard batch of the product and on one or more test batches of the product, wherein the reference standard has a known beneficial effect for assisting homeostasis under an altered physiological condition, wherein a readout of the cell-based assay represents modulation of one or more biological activities associated with one or more characteristics of a pathological condition that can develop from the altered physiological condition; (b) quantifying in numerical terms, for each cell-based assay readout, the modulation of the one or more biological activities induced by each batch of step (a), defining the value calculated for the reference standard batch as the reference value; (c) defining as acceptable test batches for which the modulus of values calculated in (b) to induce modulation of each biological activity measured in the cell-based assay is ≥ the modulus of the reference value calculated in (b), and defining as unacceptable test batches for which the modulus of values calculated in (b) to induce modulation of at least one of the biological activities measured in the cell-based assay is < the modulus of the reference value calculated in (b); (d) performing a spectroscopic or spectrophotometric measurement on the reference standard batch and on the one or more different test batches; and (e) defining the acceptability value of the spectroscopic or spectrophotometric spectrum as the range of variation of the spectroscopic or spectrophotometric spectrum values of all the acceptable batches and the reference standard batch, preferably refined by the spectrum of the unacceptable batches.

6. The method of claim 5, further comprising determining, for each of the one or more biological activities, a regulatory trend thereof for restoring a healthy physiological state.

7. The method according to claims 2 to 6, further comprising determining, for each of said biological activities, one or more parameters and their regulatory trends underlying the changes detectable in said pathological condition in diseased and healthy physiological states.

8. The method of claim 7, wherein the parameters are genes and their regulation.

9. The method of claim 6, wherein the regulatory trend of the parameter is assessed by transcriptome analysis.

10. The method according to any one of claims 1 to 9, wherein the cell-based assay is designed to mimic conditions associated with the pathological condition or with the altered physiological state.

11. The method according to any one of claims 1 to 10, wherein the one or more test batches are at least three test batches.

12. The method according to any one of claims 1 to 11, wherein the product comprises one or more of the following: cut or comminuted plant parts, plant extracts, fractions of said extracts, such as fractions obtained by filtration on semipermeable membranes (microfiltration, ultrafiltration, nanofiltration), or fractions obtained by treatment on adsorption resins, or microorganisms, honey, propolis, silk, wax, plant resins, plant gums, plant exudates, plant oils, plant essential oils, animal tissue lysates, plant or animal body fluids.

13. The method according to any one of claims 1 to 12, wherein the product is a medical device as defined in Article 2(1) paragraphs 1 to 3 of EU Directive 2017 / 745, or a medical device as defined in Section 201(h)(1) of the U.S. Food, Drug and Cosmetic Act (FDA), or a medicine or a food supplement.

14. The method of any one of claims 1 to 13, wherein the pathological condition comprises osteoarthritis, mild cognitive impairment, postmenopausal osteoporosis, or cancer.

15. The method according to any one of claims 1 to 14, wherein the spectroscopic analysis is selected from NIR, FTIR, RAMAN, and the spectrophotometric analysis is selected from UV and visible spectroscopy, fluorescence spectroscopy, light scattering.

16. A method for conformity verification of one or more batches of a product for treating a pathological condition or a beneficial product, said product comprising one or more natural substrates, said method comprising the steps of: a. Perform spectroscopy or spectrophotometry analysis on each batch, b. Verify for each batch that the obtained profile meets the acceptability values defined by the method according to any one of claims 1 to 15.

17. A method of determining a reference standard for a therapeutic product for treating a pathological condition, wherein the product comprises one or more natural matrices; the method comprising: (1) subjecting multiple batches of the product and one or more reference drug products for treating the pathological condition to at least one in vitro cell-based assay designed to mimic conditions associated with the pathological condition, wherein a readout of the cell-based assay represents modulation of one or more biological activities associated with one or more characteristics of the pathological condition, and determining, for each of the one or more biological activities, a trend toward restoration of a healthy state; (2) quantifying, for each cell-based assay readout, the modulation of the one or more biological activities induced by each batch and drug product of step (1) in numerical terms, and defining the value associated with the weakest performance as the reference value for each biological activity altered by the one or more reference drugs based on the modulation trend for restoring a healthy state; (3) selecting batches for which the modulus of the value calculated in (1) for inducing regulation of each measured biological activity in the cell-based assay is ≥ the modulus of the reference value calculated in (2), and defining the batch with the highest modulus value over a greater number of biological activities as the product reference standard batch.

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