Epigenau / 11: a natural matrix with therapeutic activity via a physiological network mechanism of action (not pharmacological) to restore homeostasis in tissues infiltrated by cancer cells

Abstract

To provide a 100% natural product comprising a natural matrix exhibiting emergence properties that enable re-establishment of correct metabolism, cancer treatment and support of tissue homeostasis in tissues infiltrated by cancer cells.SOLUTION: The product of the present invention, which serves to solve the above problems, is a natural matrix which, as demonstrated by the inventors, represents a native natural intelligence in itself, said natural intelligence being the only one capable of allowing physiological endogenous interconnections with other entities self-assembled in nature, such as human species. By modulating the tumor microenvironment and thus selectively inducing cancer cell mortality, said product achieves a reconstitution of conditions favorable to tissue homeostasis in tissues infiltrated by cancer cells. Indeed, the present invention allows a paradigm shift based on the transition from deterministic validation of properties to probabilistic validation based on functional redundancy logic, which will provide an industrially viable source of innovation for manufacturers in the field of 100% natural therapeutic or beneficial products.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to novel compositions that are made from 100% natural substances, that exert therapeutic or adjunctive effects in the treatment of cancer, and that have a physiological (not pharmacological) mechanism of action.

[0002] In particular, the present invention relates to the exclusive selection and use of native matrices to restore or assist the organism in restoring a healthy physiological state in cancer patients, appropriately processed by specific processes and methods to create a final product intended for therapeutic or supportive purposes. All stages of the manufacturing process of such products are under the protection of the One Health principle (which recognizes the interconnectedness of human health, animal health, and environmental health), and therefore, the use of artificial forces or substances is not permitted.

[0003] Indeed, in the field of the present invention, a fundamental requirement is represented by the fact that the final product, i.e., a product comprising or consisting of one or more natural matrices, must maintain a natural intelligence, i.e., an imprint of the biological domain to which each component of the product belongs, thereby maintaining a network capable of interconnecting and recognizing other networks, whether natural or artificial, i.e., networks originally natural that have acquired a degree of artificiality due to their interaction with artificial components. This interconnection is considered to be fundamental for rebalancing any disturbance in the network of events active in each interacting biological system. All identified matrices present biophysical specifications that themselves represent an invention.

[0004] Each network of each native natural matrix contained in the product that contributes to the formation of the final matrix network of the product of the present invention can be defined as a UVCB substance (i.e., Substances of Unknown or Variable composition, Complex reaction products, or Biological materials) according to the REACH (Registration, Evaluation, Authorisation, and Restriction of Chemicals) definition, as it is a processed product according to its self-assembly properties and therefore cannot be determined or verified based on small molecule chemistry protocols.

[0005] Each network is characterized by the establishment of connections within the matrix of the final product and within the physiological effects exerted by the product on the recipient organism. Product validation can be performed and confirmed using probabilistic models based on associations between the preservation of physiological activity profiles and descriptors of the matrix itself, generated using multiple biophysical analytical systems, including spectroscopy (NIR and other techniques), mass spectrometry, and paper or X-ray crystallography (fractal measurements). While useful, traditional molecular chemical definitions of the individual substances contained in an object cannot be used to validate this type of product, as they do not represent its overall efficacy and quality.

[0006] The choice of matrices intended for administration must be verified according to the updated and specific current taxonomic criteria of the animal, plant and mineral kingdoms. When used in combination with natural physical phenomena, the relationship between action and efficacy must be verified separately, taking into account acoustic effects (musical or other forms) and effects in the wave-particle field, including those of a quantum nature.

[0007] At the current state of the art, it is not always possible to outline a fully explained mechanism of action, but it is possible to examine the actions and reactions at the interconnections of the respective networks, which have already been examined at the biophysical level.

[0008] The present invention aims to select and provide new entities or products and systems capable of rebalancing, activating or limiting physiological functions in specific metabolic states of organisms that are constantly in a state of continuous change.

[0009] The preparations thus conceived are capable of rebalancing the psychoneuroendocrine immune system, which is considered as a single system that governs and controls all other systems.

[0010] This invention contributes to a new state-of-the-art technology in the field of medicine that goes beyond alchemical techniques, whose origins can be traced back to the early 16th century, and returns products and processes to the conceptual One Health objective already mentioned. Based primarily on the concept of verifying effects and activity on other organisms, this invention proposes a new deconvolution of artificial techniques and naturally self-assembling substances, recognizing existing rules or finding new ones to ensure the formation of verifiable entities. The latter are living organisms in a continuous state of change, requiring assessment of their physiological state within defined intervals—a concept now encompassed in personalized medicine. This invention fits into the concept of science, understood as a set of knowledge that can verifiably verify the effects of theoretical mechanisms of action. Today, these methods find application in establishing interconnections between all forms of life, in a context where technological innovation advances at such a pace that it risks damaging the interconnections between human-generated (artificial) intelligence and nature.

[0011] The activity of the invention disclosed herein is not currently covered by the state of the art, and therefore the entire product cycle from the end user to the relevant societal context needs to be considered under the One Health concept.

[0012] The operational paradigm within which the present invention is formulated is referred to herein as "Bios Physiological Health."

[0013] This paradigm aims to introduce into the field of medical technology an innovative approach for treatment and health self-management using natural matrices, alone or in combination, to rebalance the normal physiological state of various biological entities, including humans, through endogenous physiological effects induced by the product. The problem is to identify, select and assemble natural entities with emergent properties that can be verified by the physiological mechanism of action of the final product and other methods evolved in recent decades.

[0014] The reading of the context by both technoscientific and humanistic norms, integrated in their transversality, constitutes the basis of the proposed invention. Some of the properties of each matrix part of the product may already be known, but the emerging properties of the new composition are unexpected.

[0015] Of particular relevance is the role of determining the genetic and epigenetic aspects that determine the networks representing natural matrices and their interpretation at the level of their specific isotope abundances.

[0016] To fulfill the Bios Physiological Health paradigm, each stage of processing, from the selection of regenerative materials to agricultural and industrial stages and methods of use, must preserve as much as possible the integrity of the inheritance of the native programming inserted into the natural intelligence (natural capacities) of each entity of creation, at least as far as is known on a global scale. It is essential to verify matrices derived from epigenetic entities similar to those recognized as reference standards for the specific emergent characteristics of the metabolism of other organisms, including humans. For example, one of the factors that negatively influence epigenetic differentiation is represented by different soil conditions, along with diurnal, monthly, and annual variations. To preserve the properties of natural systems, which are the only ones that can claim physiological interconnection with the whole of creation, it is impossible to use substances derived from alchemical processes such as distillation, synthetic or semi-synthetic processes, or products derived from genetically modified or genetically altered organisms. A new interpretation of the mystery of natural programming responsible for the crucial evolution of organic and inorganic matter is needed. The consolidation of scientific evolution in recent decades makes it possible to revise our understanding of the origins of progress based on reductionist determinism, based on the development of alchemical processes from the beginning of the 16th century, which, together with Paracelsus in medicine, marked the beginning of the current evolutionary process known as the Anthropocene.

[0017] The term Anthropocene refers to the current stage of human evolution and can be traced back to different eras. When considered in the context of this invention, the only significant date is 1492, which marks the end of the Early Renaissance Humanist / Neoplatonic period. This period was politically represented by Cosimo the Elder and Lorenzo de' Medici, along with artists and scientists such as Piero della Francesca, Luca Pacioli, Leonardo, and Dürer. In the 16th century, alchemical research, which considered humans' potential dominion over nature, was inspired by the biblical idea that "man has dominion over all creation" with the aim of improving God's creation. It has continued to develop to this day under the aegis of artificial intelligence as opposed to natural science.

[0018] The year 1492 is symbolic: the year Lorenzo de' Medici and Piero della Francesca died, while Columbus discovered America. The human species abandoned its 15th-century Neoplatonic path to follow a Judeo-Catholic one, and the alchemical practices of Paracelsus were applied to medicine, marking the transition to Renaissance Mannerism in the 1500s that, to this day, is heading us toward a full-scale, irreversible sixth extinction.

[0019] The present invention demonstrates the feasibility of the resulting industrial discovery in the field of medicine, but is in principle applicable to any field of production and is intended to address a shift in evolutionary paradigm. We often speak of protecting biodiversity without addressing the real problem, a culpably obscured issue, of billions of tons of exogenous, non-biodegradable, artificial materials released into the planetary system that are sure to irreversibly contaminate the sources of life, while the "carpe diem" approach prevails over the survival instinct of the species.

[0020] This invention, presented primarily in the context of a patent, hopes to open a new field of research exploring and sharing natural intelligence (natural capabilities) rather than artificial intelligence. Artificial intelligence can do little to stop or slow the sixth extinction or to build the foundation for alternative advances to current ones. Inventor Valentino Mercati, together with his collaborator Jacopo Lucci, has chosen the path of studying nature itself in ways that may be useful for biological systems. He has developed knowledge in agricultural and industrial production systems for over 40 years and has filed numerous patent applications following this operational strategy. Previously filed patents related to the process of this invention are essentially based on instrumental and diagnostic readouts based on principles related to the chemistry of physiological processes and their correlation with the emergent properties of natural matrices and the innate defenses of individual organisms to which they are interconnected.

[0021] The analysis that follows and inspired the approach disclosed herein was unthinkable just a few decades ago due to the technical inability to read the genetic and epigenetic information written into the cells of every living organism, as well as the role of atomic isotope differentiation in molecular self-assembly and the interconnection of all singularity / individuality with the "universe." The conceptual difficulty of moving from the reassuringly controlled parameters of molecular artificiality (at least partially purified and linked by strong thermodynamic forces that allow strong bonds, such as covalent bonds, that act on a reduced molecular range of other organisms) to natural matrices that are by definition mysterious and still considered therapeutically unreliable today is enormous.

[0022] If, after five centuries of alchemical reductionism, a new interpretation of the invention is needed for the new state of the art in medicine, this interpretation must connect the most distant concepts and processes in a single field of application. This, as already mentioned, is due to a philosophical heritage that questions the human condition: was the human species produced by an original, vital intelligence, like all other species, for the purpose of life itself, so far as it can be assumed to dominate creation, or has it been experimentally endowed with capacities different from those of other organisms already suitably inserted into creation in order to constitute a new ecological niche in the service of the universe?

[0023] The answer to this dilemma does not lie in this invention: humanity must return to early Renaissance Neoplatonic thought, and the experimental duality of the human species must be liberated from the spirit of domination in order to share its unique capacities within the universe with all of creation. Humanity needs to reconsider Leonardo da Vinci's warning: "Man can only procreate himself..." and ponder the depressing thoughts of sensible figures like Piero della Francesca, Luca Pacioli, and Dürer regarding the impossibility of understanding and expressing the beauty of creation and deciphering its mysteries.

[0024] The time has come to acquire new research centers in molecular and cell biology, with an essential focus on bioinformatics and the new physical sciences. Today, the inventors can base their research strategies and socio-economic applications on new therapeutic fields, especially in the field of complex and / or chronic degeneration, where the restoration of metabolic balance in organisms disturbed naturally or artificially will become an integral part of the already existing future.

[0025] This invention represents a new vision of medical technology that reconsiders scientific evolution from a perspective different from reductionist determinism. This alternative progress does not have to rely so much on artificial intelligence and technological advances, as opposed to universal or planetary rules, but on the evolution of laws that regulate our universe and life itself. The transition from the artificial treatment of identified symptoms to a holistic approach that embraces the whole, even from a systemic perspective through modern techniques of systems biology, represents the basis of current progress.

[0026] The present invention addresses the need to provide a product comprised of a natural matrix for the treatment of, or to assist in the treatment of, cancer when combined with an anti-cancer drug. [Background technology]

[0027] Cancer cells, driven by their intrinsic properties, orchestrate significant intra- and extracellular modifications at the structural and metabolic levels, with the aim of enhancing and promoting cellular development and creating optimal conditions for tumor growth, while also establishing mechanisms for immune evasion.

[0028] Tumors organize themselves through a dense and complex network of actions that set up optimal organization for their own survival and growth, thus activating a wide range of pleiotropic genetic and metabolic mechanisms.

[0029] These properties often affect this type of cell laterally, regardless of the nature of the tumor or the tissue in which it arises.

[0030] Carcinogenesis is a process that arises and develops in the complexities of cellular transformation, both within its internal processes and in the surrounding environment, establishing a network of interactions with both other tumor cells, the environment, and the organism. The origin and development of the tumor microenvironment, understood as the critical network of relationships in which a tumor grows, has proven to be a fundamental and important aspect for the management and treatment of the pathology.

[0031] Development, organization into 3D structures, creation of new blood vessels, extracellular acidification, and glycolytic switching are essential processes that contribute to the larger design of the tumor microenvironment. In this context, a key aspect is represented by the metabolic transformation orchestrated by cancer cells, including a shift in energy production.

[0032] Unlike healthy cells, cancer cells prefer glycolytic anaerobic metabolism over oxidative metabolism. This preference for anaerobic metabolism, a hallmark feature known as the Warburg effect, seems paradoxical given the increased energy demands of cancer cells, even in the presence of oxygen. Although cancer cells use less efficient energy systems, such as glycolysis, they produce larger amounts of energy than healthy cells and have higher ATP production than non-cancerous cell lines.

[0033] The selection of glycolytic metabolism has proven advantageous for cancer cells: despite oxygen availability, rapid glycolytic processes efficiently meet cellular energy requirements while inducing changes in the intracellular and extracellular environment that favor tumor survival and progression.

[0034] The effects of glycolytic metabolism are manifested both upstream and downstream in cellular processes. Upstream, cancer cells require a high influx of glucose and nutrients, thus further strengthening their growth advantage over normal cells by reducing the availability of free glucose. Downstream, this process leads to the production of metabolic products such as lactate and H+, resulting in extracellular acidification as a result of these efforts. Acidification of extracellular pH (pHe) is a useful strategy for evading immune system control.

[0035] These aspects are established within the tumor context to perpetuate changes in the extracellular and peritumoral environment: for example, the need to bring more nutrients to the cell and the acidification of the adjacent environment are interpreted by the organism as a need to counter the establishment of hypoxic zones, leading to the stimulation of angiogenesis and thus the perpetuation of a vicious cycle beneficial to tumor establishment and progression.

[0036] Therefore, the tumor microenvironment and the Warburg effect are important aspects in understanding tumor pathophysiology. In this context, intracellular and extracellular pH and ATP glycolytic production are highly useful parameters for assessing the potential effectiveness of tumor therapies.

[0037] Altering the physiological parameters of a tumor offers a significant opportunity to alter its establishment and growth, allowing the body to regain greater efficiency in fighting it.

[0038] A complex view of pathology and an approach to interactions characterized by the same degree of complexity lays the foundation for novel and innovative treatments of cancer based on targeting the sum of physiological aspects that distinguish cancer from its healthy counterpart, thus abandoning the reductionist vision of therapy targeting single molecular entities.

[0039] As oncology research and development undoubtedly gravitates towards personalized precision medicine, therapeutic strategies that address the fundamental characteristics that underpin tumor establishment and growth may prove highly effective additional desirable tools in the fight against diverse tumor forms.

[0040] As is known in the art, some anti-cancer drugs exhibit a lack of specificity, induce drug resistance, and exhibit potent toxic side effects in the patient's whole organism, limiting their effectiveness against certain cancers.

[0041] In recent years, interest in the potential of plant-based medicines for cancer treatment has been increasing.Natural products often exhibit various mechanisms of action that can complement or even provide alternatives to conventional treatments.In fact, various plant-based materials have shown promise in targeting cancer cells with higher specificity than conventional chemotherapy, along with lower toxicity and synergistic effects with conventional drugs, and their potential in cancer prevention and supportive care has also been investigated.

[0042] Despite growing interest in plant-based cancer therapies, there are several regulatory and practical challenges that must be addressed before these treatments can become a mainstream option for cancer patients.

[0043] One of the key challenges of plant-based medicines is the lack of standardization regarding their composition and efficacy. Unlike traditional drugs, which are strictly formulated to contain specific concentrations of active ingredients, plant-based medicines vary in quality due to differences in growing conditions, harvest time, and processing methods. This can make it difficult to determine appropriate dosages or ensure consistent treatment outcomes. For these reasons, regulatory agencies are currently not ready to accept plant-based materials for cancer treatment, despite strong experimental data demonstrating promising efficacy.

[0044] Plant-based medicines offer a promising alternative with potentially lower toxicity, fewer side effects, and complementary effects when used alongside conventional treatments. However, the use of plant-based treatments for cancer is hindered by a lack of standardization, insufficient clinical evidence, and regulatory issues, including concerns about interactions with conventional therapies. To fully realize the potential of plant-based medicines in cancer treatment, further research, clinical trials, and regulatory frameworks are needed to ensure safety, efficacy, and integration into mainstream cancer treatment strategies.

[0045] Indeed, the conceptual framework previously applied to the study of matrices has significantly hindered their use, as its deterministic inspiration forced such inherently structurally variable matrices into a framework designed for structurally reproducible single molecules. As a practical consequence, matrices have historically ceased to represent a viable source of therapeutics and have been relegated to improvised, non-scientific applications that contradict the innovation ghetto represented by their traditional use. The paradigm shift provided by the application discussed herein, based on a transition from deterministic validation of properties to probabilistic validation based on functional redundancy logic, will provide manufacturers with an industrially viable source of innovation. Summary of the Invention

[0046] The present invention relates to a product comprised of a natural matrix derived from the genera Filipendula, Laurus, Brassica, Withania, Cynara, Curcuma, and Agave, which is effective in the treatment of cancer and which, when combined with known anti-cancer drugs, can aid their anti-cancer therapeutic effects (e.g., by enhancing their activity and / or reducing drug resistance), which acts with physiological mechanisms of action by modifying the entire pathological condition rather than one or a few biological functions, and by exhibiting therapeutic functional resilience, i.e., by maintaining the desired therapeutic effect despite batch-to-batch variations in chemical composition.

[0047] The experiments performed by the inventors demonstrate that the product can be standardized, providing robust in vitro and in vivo experimental evidence of its therapeutic and adjunctive effects when combined with conventional anti-cancer drugs, and also providing safety data, as well as the means to define the product's unit of activity, quality control, and pharmacokinetic, ADME, and biodegradability assessment of the product.

[0048] Furthermore, we also demonstrate the naturalness of the product and its native natural intelligence (natural capabilities).

[0049] The present invention also relates to said product or a composition comprising said product for use in treating or assisting in treating cancer in a subject in need thereof, and a method of treating or assisting in treating cancer in a subject in need thereof, comprising administering said product or composition.Furthermore, the present invention relates to the above medical uses or treatments, in which the product or composition is administered in combination with a known anti-cancer agent, either simultaneously or subsequently.

[0050] The extensive characterization studies of the claimed products are detailed by the figures and experiments provided herein.

[0051] As the reader will appreciate, several experiments have been performed simultaneously on different batches of product demonstrating that the products of the present invention maintain repeatable and consistent functional consistency with respect to their therapeutic efficacy, thereby enabling the definition of an active unit of product, i.e., a standardized measure of product potency or efficacy that defines the amount of product required to produce a specific desired therapeutic effect or achieve a specific biological response in a given system. This measure ensures consistency and reproducibility of product efficacy across different doses, formulations, or batches, provided that reproducibility based on chemical characterization is irrelevant based on the intimate nature of the product.

[0052] Therefore, the object of the present invention is to 20-50% by weight of component a., 49-80% by weight of component b., and 0.6 to 1.2 wt.% of component c., Total 100% It consists of Component a. is a co-extract of Filipendula leaves and flowers, Laurus leaves, Brassica seeds, and Withania roots, and the weight percentages of the raw materials for preparing the co-extract are 17.5 to 32.5% by weight of Filipendula leaves and flowers, 17.5 to 32.5% by weight of Laurus leaves, 17.5 to 32.5% by weight of Brassica seeds, and 17.5 to 32.5% by weight of Withania roots, totaling 100%; and Component b. is a co-extract of Cynara leaves, Curcuma roots, and Tanacetum flowers, and the weight percentages of the raw materials for preparing it are 10-19% by weight of Cynara leaves, 29-55% by weight of Curcuma roots, and 29-55% by weight of Tanacetum flowers, totaling 100%; and Ingredient c. is an extract of Agave leaves. product, An active unit of product as claimed and defined herein, which when administered separately to HuDe cells, FaDu cells and A431 cells in culture in a cell culture plate, results in the following cell mortality 24 hours after said administration: HuDe healthy cell mortality rate: 40-50% FaDu tumor cell mortality ≥ 90%, and A431 tumor cell mortality rate ≥ 65% is defined as a necessary and sufficient amount of said product to induce HuDe cells are seeded at about 7,000 cells / well in 200 μl of an appropriate medium, FaDu cells are seeded at about 12,500 cells / well in 200 μl of an appropriate medium, and A431 cells are seeded at about 8,500 cells / well in 200 μl of an appropriate culture medium, and the cells are treated with the product and then cultured for 24 hours, and cell mortality is measured by assessing cell viability by nuclear staining. activity units, A composition comprising the product as defined in the claims and herein, and at least one of an antitumor active ingredient and a pharmaceutically acceptable carrier. A therapeutic adjuvant or vehicle for anti-cancer therapy comprising the product as defined in the claims and herein and a pharmaceutically acceptable carrier. A kit-of-parts for combined or sequential administration, comprising separate vials of a therapeutic adjuvant or vehicle as defined in the claims and herein and at least one active antitumor ingredient. A product, composition, or kit-of-parts as defined in the claims and herein for use in the treatment of cancer; a method for treating cancer, wherein the product, composition, or kit-of-parts as defined in the claims and herein is administered in a therapeutically effective amount to a patient in need thereof; 1. A method for determining the presence of native natural intelligence (natural capacity) in a therapeutic or beneficial product, said product comprising or consisting of a natural matrix as defined in the claims and herein. is.

[0053] Glossary Unless otherwise defined herein, scientific and technical terms used in connection with the present invention shall have the meanings commonly understood by those of ordinary skill in the art. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular.

[0054] At any point in this specification or claims, the words "comprising" or "comprise(s)" may be replaced with "consisting of" or "consist(s) of."

[0055] In this application, "natural matrix" refers to a material consisting of a network represented by a wide range of components / building blocks obtained (e.g., extracted) directly from a member of nature or its naturally occurring parts (i.e., from a natural raw material) without significant processing or synthetic alteration. "Without significant processing or synthetic alteration" means that no modification process is used to obtain the matrix from the raw material. In other words, the natural raw material is processed only by manual, mechanical, or gravitational means, for example, by dissolving in water or other naturally occurring solvents such as water or water-alcohol solutions, by flotation, by extraction with water or other naturally occurring solvents, by steam distillation, or by heating only to remove water or any other naturally occurring solvent, or extracted from air by any means, provided that "natural matrix" excludes said member of nature "as such," i.e., unprocessed. In particular, according to the present invention, a natural matrix is ​​a 100% natural and biodegradable material consisting of natural components that have not been modified by the process for producing the matrix from starting raw materials, without the intentional addition of synthetic products along the entire process. Herein, 100% biodegradability is considered "readily biodegradable" according to the OECD biodegradability test. These characteristics ensure the maintenance of the matrix effect conferred by its components through structural interactions (material interactions) and the presence of functional interactions (non-material interactions) that become apparent upon exposure of a biological system to the natural matrix. In other words, a natural matrix, or a mixture of natural matrices, is a material obtained from entities that self-assemble in nature and have been processed to preserve their native biophysical properties that determine their physiological interactions with other organisms, such as human organisms. These properties may be expressed by contributing to the rebalancing of metabolic processes or states of the recipient organism and / or some organs or tissues, along with physiological effects activated in each specific context. According to the present invention, the natural matrix may be derived from materials obtained from any source within the kingdoms of life, namely Monera, Protista, Fungi, Plantae, and Animalia.Thus, the term encompasses plant natural matrices, animal natural matrices, fungal natural matrices, protist (archaeal or bacterial) natural matrices, and monera natural matrices. Natural matrices may also include natural inorganic materials such as minerals obtained from natural raw materials. Synonyms for natural matrix or one or more natural matrices herein are "complex natural systems" or "natural materials," as defined below.

[0056] Examples of naturally occurring parts of an organism may be represented by, for example, roots, leaves, bark, fruit, flowers of a plant, or sections, organs, tissues thereof.

[0057] In any part of this specification the general term natural matrix may be replaced by: Plant natural matrices or natural matrices obtained from plants, Animal natural matrices or natural matrices obtained from animals or animal products such as eggs or milk, a fungal natural matrix or a natural matrix obtained from a fungus; a protist natural matrix or a natural matrix obtained from a protist; Monera natural matrix or natural matrix obtained from Monera; or plant material and / or extracts, extracts from animal tissues or organs, fungi and / or fungal extracts, or mixtures thereof (the extraction process does not include a denaturing step (e.g., temperature or use of denaturing solvents)).

[0058] Plants are synonymous with herbs.

[0059] The term "natural" matrix emphasizes that it retains the integrity and complexity of the network of components / ingredients as in the original natural source due to the absence of denaturing treatments to obtain it. Thus, natural matrices do not encompass compositions of natural origin that are enriched with specific molecules that have been artificially synthesized or isolated from natural raw materials. Furthermore, natural matrices can only be obtained by processes that do not involve extensive treatment or chemical modification, isolation, purification, or molecular extraction.

[0060] Due to the supramolecular self-assembly of the components / ingredients of the natural matrix and the existence of functional interactions between them, the entire matrix behaves as a complex network that does not interact with a single target molecule, but with a network of recipients (also organized as a network) in the recipient organism. Thus, the interaction of the natural matrix recipient organism is not the result of point-to-point interactions, as with typical pharmaceutical APIs, but rather the result of an "interactant" network (i.e., the matrix) - "receiver" network (i.e., the organism to which the matrix is ​​administered) interaction.

[0061] The term natural matrix may also be substituted for complex natural system in any part of the specification and claims.

[0062] Nowhere in this specification and claims can the term natural matrix be construed as a "natural product" per se; rather, a natural matrix is ​​a product obtained from a natural organism and processed (e.g., extracted) therefrom by techniques that do not substantially alter the biological structure and associated supramolecular and functional interconnections between components within said matrix, i.e., by techniques that do not use denaturing techniques and do not include additional isolated or synthetic molecules or classes of molecules.

[0063] As it appears in this specification and in the art, this term defines a property of a natural matrix or material according to this specification, i.e. a property that is not represented by the mere sum of the properties of each identified constituent / component of said matrix / material, but by both functional and structural interactions between all constituents / components of said matrix / material, which is also the result of supramolecular self-assembly of said constituents / components within the matrix / material itself.

[0064] Thus, "emergent properties" refer to the technical effects, e.g., therapeutic or homeostatic-supportive properties (i.e., beneficial effects), that the interactions and relationships between components / ingredients of a natural matrix have on a recipient biological system. By definition, emergent properties are properties that are not immediately apparent or even predictable based solely on the individual properties of each component / ingredient of the matrix. Instead, they "emerge" when all components / ingredients of the matrix network interact with each other and with the recipient biological system network in dynamic and complex ways. Emergent properties have been widely discussed in the art in various scientific and systems-oriented fields, including physics, chemistry, biology, and complex systems theory.

[0065] Thus, emergent properties are properties that cannot be predicted a priori by qualitative and quantitative knowledge of each component of a given composition or matrix, and therefore cannot be attributed to one or more specific APIs. Thus, while a multi-drug composition may exhibit unexpected synergistic effects, the properties of the composition are still attributable to the specific APIs and amounts thereof contained therein.

[0066] In the case of emergence properties characteristic of a natural matrix, the observed emergence properties cannot be replicated for a particular API and are maintained in different batches of a given matrix or in a given mixture of matrices, despite different qualitative and quantitative compositions of said batches (functional consistency see below).

[0067] Synthetic herein has its conventionally accepted meaning in chemistry. Traditionally, in chemistry, the term "synthetic" refers to the origin or source of a material or substance. Synthetic substances or materials are produced by humans by artificial synthesis, i.e., laboratory chemical reactions that typically react simpler chemicals to produce more complex chemicals via processes that often employ different pathways, temperature conditions, pressure conditions, energy sources, and / or catalysts than those used by living organisms.

[0068] Examples: Synthetic substances or materials include plastics, pharmaceuticals, and many industrial chemicals. For example, nylon is a synthetic polymer made by chemical synthesis, and aspirin is a synthetic drug made by a specific chemical reaction.

[0069] Functional consistency (also referred to as "redundancy") according to this specification is intended as the therapeutic or beneficial (homeostatic adjuvant) consistency of a therapeutic or beneficial product that comprises or consists of one or more natural matrices. This term describes the maintenance of the therapeutic or beneficial properties of different batches of a given product that comprises (or consists of) one or more natural matrices, despite the differences in qualitative and quantitative composition between batches, which is necessarily present (intrinsic) in a product that comprises or consists of one or more natural matrices. As known to those skilled in the art, each time a different batch of starting raw material is used, the resulting natural matrix will have a unique qualitative and quantitative composition at the molecular level, typical of the individual variations among organisms of the same species.

[0070] A healthy physiological state refers to the state of an organism's body, organ, device, system, or bodily region and its internal processes when they are functioning optimally within the individual's normal parameters, i.e., the state toward which homeostasis prevails. A healthy physiological state refers to a state in which one or more biological activities, in the context of those activities known to contribute to a given disease or pathological condition or hallmark of an altered physiological state, are operating optimally and within normal (healthy) parameters. This state is characterized by the absence of significant abnormal cellular or molecular processes associated with the particular disease under consideration. When trends in alterations of one or more biological activities consistent with a pathological or pre-pathological state are known, a healthy physiological state can be considered to be represented by the opposite trends in alterations for each of those activities.

[0071] The term considers the hallmarks of a particular disease, which are distinctive features or characteristics typically observed in individuals afflicted with that disease. These hallmarks may include specific cellular behaviors, molecular pathways, canonical pathways, or physiological responses that play a key role in the development or progression of the disease.

[0072] In summary, a healthy physiological state in the context of a particular disease or pathological / altered condition is one in which one or more biological activities associated with the known hallmarks of that disease or pathological condition are modulated in a direction consistent with a non-pathological / unaltered state, in other words, in a direction opposite to the pathological / altered state.

[0073] Therefore, a healthy physiological state according to the present invention also indicates a direction of regulation of one or more biological activities that are known hallmarks of a pathological state in homeostasis, i.e., before the onset of the pathological state, in other words, a homeostatic direction of regulation of one or more biological activities that are attributed to a particular system, region, apparatus or organ in a healthy subject.

[0074] Altered physiological state and altered homeostasis are closely related concepts that describe deviations from normal function and balance of the body's internal environment. While they overlap, there are some differences between the two terms.

[0075] Altered physiological state: This term encompasses a wide range of changes in the normal function of the body, including disruptions to organ systems, biochemical processes, and cellular function. Altered physiological states can result from a variety of factors, such as disease, injury, drugs, environmental factors, and psychological stress. Examples include fever, inflammation, hormonal imbalance, and organ dysfunction.

[0076] Homeostasis (Altered): Homeostasis refers to the body's ability to maintain a stable internal environment despite external or pathological changes. This stability is achieved by regulatory mechanisms that control 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 balance, leading to deviations from the body's normal set points. These deviations can be temporary or chronic and may involve compensatory mechanisms to restore balance.

[0077] In summary, an altered physiological state describes an observable change in the body's normal functioning, while altered homeostasis refers to a fundamental disruption of the body's regulatory mechanisms that maintain internal stability.

[0078] Alterations in homeostasis underlie altered physiological states as a disruption of homeostatic mechanisms can lead to physiological imbalances and the development of disease or dysfunction. Products that support homeostasis are those that assist the body in restoring stability to its internal environment when it is altered.

[0079] The term "hallmarks of a disease or pathological or medical condition" as used herein has the meaning conventionally used in the art. Disease hallmarks are known to be indicators that can mark the progression or control of a given disease or pathological or pre-pathological condition, and together typically represent the general pathological state associated with a given condition. These hallmarks (also called "key indicators") are typically a set of features or patterns that physicians monitor over time to track the onset, progression, or regression of a particular disease. In summary, disease hallmarks are defining characteristics or properties whose alterations indicate a given pre-medical or medical condition and aid in its identification, diagnosis, monitoring, and understanding. For example, for neurodegenerative diseases (NDDs), at least eight hallmarks of NDDs are known in the art: (pathological protein) aggregation, synapse and neuronal network (dysfunction), (abnormal) proteostasis, cytoskeleton (abnormal), (altered) energy homeostasis, DNA and RNA (deficiency), inflammation (increase), and neuronal cell death (increase). In cancer research, cancer hallmarks are a set of characteristic properties commonly found in cancer cells, including (sustained) proliferative signaling, (evasion of) growth suppressors, (resistance to) cell death, (enabling) replicative immortalization, (inducing) angiogenesis, and (activating) invasion and metastasis.

[0080] Disease hallmarks, parameters (e.g., biomarkers) associated with the hallmarks, one or more biological activities associated with the hallmarks, etc., provide a framework for studying a disease or pathological or medical condition using an integrated / holistic approach.

[0081] Hallmarks of an altered physiological state typically include observable changes in various aspects of bodily function, which may be manifested through symptoms, signs, or laboratory findings.

[0082] Altered physiological states typically reflect a disruption of the body's homeostatic mechanisms, resulting in deviations from normal physiological parameters. These imbalances may include changes in thermoregulation, fluid and electrolyte balance, acid-base balance, glucose metabolism, or other regulatory processes.

[0083] Overall, the hallmarks of altered physiological states provide valuable clues for healthcare providers to identify underlying causes, assess severity, and guide appropriate interventions to restore normal function and promote recovery.

[0084] A reference drug is a drug commonly selected or singled out as the standard or preferred treatment for a particular medical condition or disease. It is often established based on factors such as its effectiveness, safety profile, cost, and clinical experience. A reference drug serves as a benchmark for comparison with other drugs, especially when evaluating generic versions, new treatments, or alternative therapies. It is typically the first-choice drug recommended by medical guidelines or healthcare providers to treat a particular condition.

[0085] Native natural intelligence (natural capability) represents the inherent ability of natural matrices to store and transmit the biological and physicochemical information necessary to interact with and integrate other biological networks using logic specific to the receiving organism, since these networks are already known to the organism and therefore endogenous to it. This intelligence is a manifestation of natural autopoiesis, i.e., the ability to self-organize and adapt to environmental stimuli without artificial intervention, transmitting messages according to a punctate logic and via mediators unknown to the receiving organism and therefore exogenous to it.

[0086] The expression physiological interconnection, defined as "endogenous" physiological interconnection, describes the ability of a natural matrix to harmoniously and functionally interact with the recipient biological system, based on the fact that both belong to the domain of the organism (endogenous) and stimulate internal responses to restore a balanced physiological state. This interaction is based on natural dynamics without artificial intervention and represents a reciprocal dialogue between the matrix and the organism, promoting self-regulation and physiological recovery.

[0087] Self-assembled entities in nature define complex systems of multiple components that spontaneously organize into functional structures through chemical-physical interactions that occur in natural environments and conditions. These systems, found in living organisms or natural matrices, exhibit emergent properties that result from their dynamic interactions and cannot be artificially replicated.

[0088] When referring to a subject in need of beneficial or therapeutic treatment, the description relates to a human suffering from a pathological condition, in particular cancer.

[0089] An activity unit refers to a standardized measure of the potency or effectiveness of a therapeutic product. It defines the amount of therapeutic product required to produce a specific desired therapeutic effect or to achieve a specific biological response in a given system. This measurement ensures consistency and reproducibility of the therapeutic effect across different doses, formulations, or batches. The activity unit can vary depending on the type of drug and how its effect is assessed. It may be defined based on different factors, such as: [Brief explanation of the drawings]

[0090] [Figure 1] Dysregulation of pH creates a perfect storm for cancer progression: cancer cells have an inverse pH gradient compared to normal differentiated adult cells, involving a constitutively higher intracellular pH (pHi) and lower extracellular pH (pHe), which promotes the adaptive behavior exhibited. [Figure 2]Figure 1 is a graph reporting cell counts of tumor cell lines treated with EpigenAU / 11 at two different concentrations (0.66 mg / ml and 0.22 mg / ml) for 72 hours. Tumor cell lines were stained with HCS NuclearMask Red. Results are expressed as the percentage of viability between treated cells and corresponding untreated cells (set as 0% as reference and not shown on the graph). Negative numbers represent a decrease in cell vitality. Thus, by way of example, -x% for vitality corresponds to x% cell mortality. [Figure 3] Figure 1 shows differential ATP levels in tumor cell lines after 72 hours of treatment with EpigenAU / 11 (0.22 mg / ml) or cisplatin (CDDP, 15 μg / ml). ATP was quantified as a marker of cell viability using the CellTiter-Glo® 3D Viability Assay. Results are expressed as % viability between treated cells and their corresponding untreated controls. [Figure 4] Histograms showing normalized ATP levels in breast cancer spheroids (4A SUM159PT, 4B MDA-MB-231) and noncancerous spheroids (4C MCF 10A) after 72 hours of treatment with different concentrations of EpigenAU / 11. ATP content, measured by CellTiter-Glo® 3D, is expressed as a percentage of viability, with the untreated control set at 100%. A significant decrease in ATP levels was observed in cancer spheroids at 0.22 mg / ml, while noncancerous MCF 10A spheroids maintained high viability. Two-way ANOVA confirmed a significant interaction between cell type and concentration (p<0.05), with post-hoc multiple comparison testing. [Figure 5]Histogram showing normalized ATP levels in bladder cancer, breast cancer, endometrial cancer, epithelial cancer, and head and neck cancer organoids after 72 hours of treatment with 0.66 mg / ml EpigenAU / 11. ATP content measured by CellTiter-Glo® 3D is expressed as a percentage of viability, with the untreated control set as 100% for each organoid type (control histogram is 100% and not shown in the graph). [Figure 6] This heatmap depicts the efficacy of various treatments on a patient-derived gastric cancer organoid model over a 72-hour period. Each row corresponds to a different treatment, and the intensity of the shading indicates the level of cell mortality, decreasing from white to black, with black representing high cell mortality (strong cytotoxic effect) and white representing low cell mortality (minimal cytotoxic effect). [Figure 7] This heatmap represents the efficacy of various treatments on an ovarian-origin peritoneal carcinomatosis organoid model over a 72-hour period. Each row corresponds to a different treatment, and the intensity of the shading indicates the level of cell mortality. Viability decreases from white to black, with black representing high cell mortality (strong cytotoxic effect) and white representing low cell mortality (minimal cytotoxic effect). [Figure 8(AB)]Intracellular pH and ATP levels after EpigenAU / 11 treatment. Intracellular pH (Panel A) and ATP levels (Panel B) were measured in squamous cell carcinoma lines (FaDu and A431) and healthy HuDe cells after 1 hour of treatment with EpigenAU / 11 (0.66 mg / ml) and hydrochloric acid (HCl). Figure 8A shows the changes in intracellular pH across different cell lines, showing a significant increase in pH only in cells treated with EpigenAU / 11. Cells were labeled with pHrodo™ Green AM Intracellular pH Indicator according to the manufacturer's instructions. pH values ​​were normalized with respect to cell number, measured by Nuclear Mask Red staining. A 0% reference was applied to the untreated control (not reported in the graph), and pH changes in EpigenAU / 11-treated samples were calculated as a percentage of the untreated condition. Figure 8B shows ATP levels assessed using the CellTiter-Glo® Luminescent Cell Viability Assay according to the manufacturer's protocol. ATP values ​​were normalized with respect to cell number measured by Nuclear Mask Red staining. The untreated control was set to 0% as a reference (not plotted on the graph), and the amount of ATP detected in samples treated with EpigenAU / 11 was calculated as a percentage of the untreated condition. A conventional two-way ANOVA with α=0.05 was applied, with only values ​​returning p<0.05 considered significant (****p<0.0001). [Figure 9]Cell viability analysis was performed on explanted biopsies from FaDu (9A) and A431 (9B) cell lines after 72 hours of ex vivo treatment. Biopsies were treated with EpigenAU / 11 at a concentration of 50 mg / ml (measured pH 5.6), while the acid-treated group received hydrochloric acid (HCl) adjusted to the same pH of 5.6. Cell viability was analyzed using a flow cytometer with the Pacific Blue™ Annexin V / SYTOX™ AADvanced™ Apoptosis Kit according to the manufacturer's instructions. Untreated controls were set to 100%, and viability is expressed as a percentage. Significant differences between groups were confirmed by one-way ANOVA analysis followed by Dunnett's test. Data are presented as mean ± SD; *p<0.03; ***p<0.0002. [Figure 10] Cell viability analysis of FaDu, A431, and HuDe cell lines after 24 hours of treatment. Cells were treated with EpigenAU / 11 DoE 2 at a concentration of 0.66 mg / ml or a combination of citric acid and lactic acid, using the same concentrations found in EpigenAU / 11. Tumor cell lines were stained with HCS NuclearMask Red to assess cell viability. Results are expressed as the percentage of viability between treated and corresponding untreated cells, with untreated controls set at 0% as a reference (not shown in the graph). [Figure 11] Cell viability analysis was performed on explanted biopsies from the FaDu cell line after 72 hours of ex vivo treatment. Biopsies were treated with EpigenAU / 11 at a concentration of 50 mg / ml or cisplatin at 150 μg / ml. Cell viability was analyzed using a flow cytometer with the Pacific Blue™ Annexin V / SYTOX™ AADvanced™ Apoptosis Kit according to the manufacturer's instructions. Untreated controls were set to 100%, and viability is expressed as a percentage. Significant differences between groups were confirmed by one-way ANOVA analysis followed by Dunnett's test. Data are expressed as mean ± SD; *p<0.05; **p<0.02. [Figure 12]Gene expression pathway regulation after 24 hours of treatment with EpigenAU / 11 and cisplatin. This heatmap provides an overview of the sustained gene expression changes induced by each treatment over time, focusing on pathways related to cell cycle regulation, DNA replication, mitosis, and DNA repair. Upregulated (positive numbers) and downregulated (negative numbers) pathways are indicated by shading intensity, with dark gray indicating upregulation, light gray indicating downregulation, and white indicating upregulation or downregulation below threshold. [Figure 13(AB)] Gene expression pathway regulation after 6 hours of treatment with EpigenAU / 11 and cisplatin. This heatmap (divided into the latter two panels 13A and 13B) shows the differential impact of each compound on various cellular pathways, categorized by hallmarks such as stemness, epithelial-mesenchymal transition, energy metabolism, growth factor signaling, cell injury, mitotic regulation, and inflammation. Pathways that are significantly upregulated (positive numbers) or downregulated (negative numbers) are shown, with dark gray indicating upregulation, light gray indicating downregulation, and white indicating upregulation or downregulation below the threshold. [Figure 14] Cell viability analysis was performed on explanted biopsies from the FaDu cell line after 72 hours of ex vivo treatment. Biopsies were treated with EpigenAU / 11 at a concentration of 50 mg / ml, cisplatin at 150 μg / ml, and a combination of EpigenAU / 11 and cisplatin. Cell viability was analyzed using a flow cytometer with the Pacific Blue™ Annexin V / SYTOX™ AADvanced™ Apoptosis Kit according to the manufacturer's instructions. The untreated control was set to 100%, and viability is expressed as a percentage. Combination treatment showed an enhanced loss of viability compared to single-agent treatment. Statistical analysis was performed using one-way ANOVA followed by Dunnett's test to confirm significant differences between groups. Data are presented as mean ± SD; ***p<0.002; ****p<0.001. [Figure 15(AB)]Dendrogram (split into the latter two panels 15A and 15B) showing genome-wide gene expression profiling of biopsies derived from FaDu explants after 6 hours of treatment with EpigenAU / 11, cisplatin, and their combination. Numbers and shading represent the intensity of upregulation (positive numbers, dark gray) and downregulation (negative numbers, light gray). White indicates upregulation or downregulation below a threshold. Pathway clustering highlights the common and differential effects of EpigenAU / 11, cisplatin, and their combination on key cancer processes. [Figure 16] Cell viability analysis was performed on explanted biopsies from the A431 cell line after 72 hours of ex vivo treatment. Biopsies were treated with EpigenAU / 11 at a concentration of 50 mg / ml or cisplatin at 150 μg / ml. Cell viability was analyzed using a flow cytometer with the Pacific Blue™ Annexin V / SYTOX™ AADvanced™ Apoptosis Kit according to the manufacturer's instructions. Untreated controls were set to 100%, and viability is expressed as a percentage. Significant differences between groups were confirmed by one-way ANOVA analysis followed by Dunnett's test. Data are presented as mean ± SD; **p<0.02. [Figure 17] Gene expression modulation in an A431 ex vivo model after 2 hours of treatment with 50 mg / ml EpigenAU / 11. The heat map shows the down- and up-regulation of various pathways associated with cancer progression and cellular responses. Numbers and shading representing the intensity of up-regulation (positive numbers, dark gray) and down-regulation (negative numbers, light gray) indicate the magnitude of expression change on a scale ranging from -5 (strong down-regulation) to +5 (strong up-regulation), highlighting the impact of EpigenAU / 11 on cellular pathways over a short treatment period. [Figure 18] FTIR spectrum of reference standard EpigenAU / 11 DoE2. [Figure 19(AE)]Detection of supramolecular structures in EpigenAU / 11 DoE2 (19A and 19B) and exosomes (19C and 19D): 19A: Overlay of the average particle size distribution as a function of intensity for three instrumental replicates of a condition; line A - no filtration; line B - 0.45 μm filtration; line C - 0.10 μm filtration; 19B: Correlogram showing the correlation coefficient (g2-1) as a function of time (μs) for the three experimental conditions; line A - no filtration (average of three instrumental replicates), line B - 0.45 μm filtration (average of three instrumental replicates), line C - 0.10 μm filtration (average of three instrumental replicates). 19C: Overlay of particle size distribution as a function of intensity for three instrumental replicates. 19D: Overlay of the correlation functions for three instrumental replicates. 19E: Distribution of the average particle concentration as a function of size (nm). [Figure 20] Experimental workflow for treatment with EpigenAU / 11 and cisplatin in a mouse model using subcutaneous A431 cell xenografts. [Figure 21] Tumor growth curve of A431 xenografts in athymic mice over 15 days of treatment. Mice were treated with vehicle (saline), EpigenAU / 11 (50 mg / ml, intratumoral), or cisplatin (2 mg / kg, intraperitoneally, every 2 days). Tumor volumes were measured every other day. Data are expressed as mean ± SEM; **p<0.02; ****p<0.001. One-way ANOVA followed by Fisher's LSD test was used for statistical analysis. [Figure 22] Representative images of A431 xenografts from each treatment group (vehicle, EpigenAU / 11, and cisplatin) on days 1, 7, and 15. Each image corresponds to a single example from the respective treatment group, showing tumor size and appearance over time. [Figure 23] Experimental workflow for treatment with EpigenAU / 11 and cisplatin in a mouse model with subcutaneous FaDu cell xenografts. [Figure 24]Tumor growth curve of FaDu xenografts in athymic mice over 27 days of treatment. Mice were treated with vehicle (saline), EpigenAU / 11 (50 mg / ml, intratumorally, daily), cisplatin (2 mg / kg, intraperitoneally, every 2 days), or a combination of EpigenAU / 11 and cisplatin. Tumor volumes were measured every other day. Data are expressed as mean ± SEM; *p<0.05; **p<0.02. One-way ANOVA followed by Fisher's LSD test was used for statistical analysis. [Figure 25] Representative images of FaDu xenografts from each treatment group (vehicle, EpigenAU / 11, cisplatin, and combination) on days 1, 19, and 27. Each image corresponds to a single example from the respective treatment group, showing tumor size and appearance over time. [Figure 26] Figure 1 is a graph reporting cell counts of tumor cell lines treated with 0.66 mg / ml of DoE1, 2, 3, and 4.2 EpigenAU / 11 for 24 hours. Tumor cell lines were stained with HCS NuclearMask Red. Results are expressed as the percentage of viability between treated cells and corresponding untreated cells (set as 0% as reference and not shown on the graph). [Figure 27] Targeted metabolomics: Shown are the percentages of five chemical classes in the order of phenols, tannins, organic acids, sugars and their derivatives, and inorganic compounds for five batches of EpigenAU / 11, DoE1, 2, 3, 4, and 4.2. Each batch differs from the others in qualitative and quantitative composition. [Figure 28(AD)]Cell viability analysis of FaDu, A431, and HuDe cell lines after 24 hours of treatment. Cells were treated with different DoEs of Epigen AU / 11, the composition of which is detailed in Example 9.1, at a concentration of 0.66 mg / ml. Tumor cell lines were stained with HCS NuclearMask Red to assess cell viability. Results are expressed as the percentage of viability between treated and corresponding untreated cells, with the untreated control set at 0% as reference (not shown in the graph). 28A DoE1, 1.1, 1.2, 1.3 28B DoE2, 2.1, 2.2, 2.3 28C DoE3, 3.1, 3.2, 3.3 28D DoE4, 4.1, 4.2, 4.3 [Figure 29] Flowchart of the procedural process for calculating benefit / risk scores for EpigenAU / 11 and cisplatin based on transcriptional profiles obtained from in vitro or ex vivo experiments. [Figure 30] 1 is a flowchart of the procedural process for calculating benefit / risk scores for EpigenAU / 11 and cisplatin based on data obtained from in vivo experiments in animal models. [Figure 31] Annotated side effects of cisplatin and IPA-responsive biological functions (BF). The trends of desired modifications of selected biological functions are shown in the figure. [Figure 32(AD)] Calculation of the benefit score for EpigenAU / 11 and cisplatin treatments after 6 hours of treatment. 32A and 32C: Biological activities selected based on their consistency with the therapeutic indication of the product under consideration. Biological activities are grouped into activity hallmarks, and in this figure, each hallmark is assigned a weighting factor based on its relevance in the pathogenesis of interest (Panel A: only mandatory steps according to the instructions were performed; Panel C: mandatory and optional steps according to the instructions were performed). 32B and 32D: Z-score values ​​of biological activity converted to absolute values, and the values ​​thus obtained were exported to a table reporting the biological activity indicators and their relative modulation values. The sum of the respective values ​​for each treatment is considered the benefit score (Panel B: only mandatory steps according to the instructions were performed; Panel D: mandatory and optional steps according to the instructions were performed). [Figure 33(AC)] Calculation of risk scores for EpigenAU / 11 and cisplatin treatment after 6 hours of treatment. 33A Calculation of risk scores for EpigenAU / 11 after 6 hours of treatment. 33B Calculation of risk scores for cisplatin after 6 hours of treatment. 33C Summary of risk scores for EpigenAU / 11 and cisplatin after 6 hours of treatment. [Figure 34(AD)] 34A and 34C Benefit / risk scores obtained with EpigenAU / 11 and cisplatin treatment after 6 hours (34A only mandatory steps according to instructions were performed, 34C mandatory and optional steps according to instructions were performed). 34B and 34D Calculation of fold change in score obtained with EpigenAU / 11 compared to score obtained with cisplatin: EpigenAU / 11 score is twice the score for cisplatin (34B only mandatory steps according to instructions were performed, 34D mandatory and optional steps according to instructions were performed). [Figure 35] 35A Benefit / risk scores obtained with EpigenAU / 11 and cisplatin treatment in vivo. 35B Calculation of the fold change in the score obtained with EpigenAU / 11 compared to the score obtained with cisplatin: EpigenAU / 11 score is 3 times the score of cisplatin. [Figure 36] Graphical comparison of the resulting fold change in benefit / risk scores calculated according to the present invention, cylinders 1 and 2 are from ex vivo samples, cylinder 3 is from an in vivo animal model (1st cylinder: only essential steps according to instructions were performed; 2nd cylinder: essential and optional steps according to instructions were performed). [Figure 37] Cell viability analysis of FaDu and A431 cell lines after 24 hours of treatment. Cells were treated with EpigenAU / 11 alone or in combination with cisplatin at a concentration of 0.66 mg / ml. Tumor cell lines were stained with HCS NuclearMask Red to assess cell viability. Results are expressed as the percentage of viability between treated and corresponding untreated cells, with untreated controls set as 0% as a reference (not shown in the graph). [Figure 38] Histograms showing normalized ATP levels in breast cancer spheroids (MDA-MB-231 and SUM159PT) after 72 hours of treatment with EpigenAU / 11 alone or in combination with various chemotherapeutic agents (carboplatin, paclitaxel, and gemcitabine), and with each chemotherapeutic agent alone or in combination with each other. ATP content, measured using the CellTiter-Glo® 3D Viability Assay, is expressed as a percentage of viability, with the untreated control set at 100%. One-way ANOVA analysis confirmed a significant interaction between treatment type and cell line (p<0.05), with post hoc multiple comparison testing performed. C=carboplatin, P=paclitaxel, G=gemcitabine, A=EpigenAU / 11. In combination experiments, the amount of EpigenAU / 11 used was 0.22 mg / ml. [Figure 39(AD)] 39A is bladder 38, 39B is bladder 41, 39C is breast 203, and 39D is endometrial 12. Histograms showing normalized ATP levels in bladder, breast, and endometrial tumor organoids after treatment with EpigenAU / 11 (0.66 mg / ml) and various chemotherapy agents. Bladder organoids (bladder 41 and bladder 38): were treated with cisplatin (C, 5 μg), gemcitabine (G, 70 μg), or their combination for 72 hours. Breast organoids (breast 203): were treated sequentially with paclitaxel (P, 50 nM) and carboplatin (C, 100 nM) for 72 hours, followed by epirubicin (E, 1 μM) and cyclophosphamide (Cy, 7 μM) for an additional 72 hours. Endometrial organoids (endometrium 12): treated with carboplatin (C, 100 nM), paclitaxel (P, 100 nM), or their combination for 72 hours. ATP content measured by CellTiter-Glo® 3D is expressed as a percentage of cell viability, with untreated controls set at 100%. Statistical analysis was performed using one-way ANOVA followed by Dunnett's test, and significant differences were indicated with p<0.002 (**) and p<0.0001 (****). Data are expressed as mean ± SD. [Figure 40]Vitality assay for organoid models of head and neck squamous cell carcinoma 10847 and 10632 after treatment with EpigenAU / 11 (0.66 mg / ml) and different doses (0, 4, 8 Gy) of radiation therapy. HNSCC10847 (left) represents a radiotherapy-sensitive model, and HNSCC10632 (right) represents a radiotherapy-resistant model. Data represent the mean ± standard deviation of triplicate experiments. ATP content measured by CellTiter-Glo® 3D is expressed as a percentage of cell viability, with untreated controls set at 100%. Statistical significance was assessed using one-way ANOVA followed by Dunnett's test; significant differences were indicated by *p<0.05, **p<0.01, and ***p<0.001; ns = not significant). [Figure 41] Pharmacokinetic experimental design over the 48 hour experiment and aspects of data analysis for each organ harvested. [Figure 42] Time course perturbation of genes involved in ADME in liver samples from untreated mice, mice treated with physiological solution, or mice treated with EpigenAU / 11. [Figure 43] Time course perturbation of genes potentially involved in renal ADME in kidney samples from untreated mice, mice treated with physiological solution, or mice treated with EpigenAU / 11. [Figure 44(AC)]Network analysis of squamous cell carcinoma (44A) and treatment with a reference drug (44B) versus treatment with EpigenAU / 11 (44C). Gray boxes represent both the basic nodes characterizing the pathophysiological or altered physiological state and the specific sites where the pathology interconnects with the body. Arrows next to the nodes indicate specific modulation for each described condition, with strength indicated by a multiple of the arrow itself. The gray boxes then connect to a network of biological activities whose modulation has been experimentally demonstrated. These biological activities are represented by black (up-regulated) or white (down-regulated) circles, whose amplitude is directly proportional to the magnitude of their experimentally proven modulation. Network analysis shows that EpigenAU / 11 affects the body systemically and modulates more desired activities than treatment with a reference drug, following a trend consistent with a healthy physiological state. DETAILED DESCRIPTION OF THE INVENTION

[0091] Cancer cells exploit inherent properties to drive profound modifications both within and outside their environment. These transformations at the structural and metabolic levels are essential for stimulating cell proliferation, creating favorable conditions for tumor growth, and developing strategies to evade immune surveillance. Tumors evolve within a complex network of interconnected biological processes that ensure their survival and expansion, activating a series of dynamic genetic and metabolic pathways. These pathways influence tumor cells across a variety of tissues and environments, demonstrating tumors' ability to adapt and thrive in multiple biological contexts.

[0092] Carcinogenesis proceeds within a complex framework of cellular transformation shaped by internal processes and the surrounding environment. This complexity forms a web of interactions between tumor cells, the tumor microenvironment, and the host organism. The tumor microenvironment, a critical network supporting tumor growth, plays a pivotal role in cancer progression and response to treatment, influencing key aspects of tumor biology from growth kinetics to treatment outcome.

[0093] Within this complex context, the balance of pH between the intracellular and extracellular spaces emerges as a hallmark of cancer cell physiology, supporting the activation of metabolic and physiological pathways that promote tumor cell proliferation and environmental adaptation. Unlike healthy cells, cancer cells exhibit a unique pH profile characterized by intracellular alkalinity and extracellular acidity. This pH imbalance is not only a byproduct of altered metabolism, but also a functional adaptation that allows cancer cells to secure a growth advantage, create an immune-evasion niche, and establish adaptive pathways essential for survival and progression (Figure 1).

[0094] Key factors behind this pH regulation include the Warburg effect and oxidative phosphorylation, which contribute to extracellular acidification while supporting an alkaline intracellular environment. The Warburg effect, defined by the favoring of glycolysis even in the presence of oxygen, forms part of a broader metabolic network that maintains an alkaline intracellular pH, enabling key enzymes in biosynthetic pathways and supporting rapid cell division. Meanwhile, extracellular acidification aids in the degradation of the extracellular matrix, promoting tumor invasion and metastasis.

[0095] In addition to structural and metabolic advantages, cancer cells are also characterized by high levels of reactive oxygen species (ROS). While ROS are often associated with cell damage, they also function as signaling molecules within cancer cells, promoting their growth and survival. Elevated ROS levels, coupled with extracellular acidification due to increased glycolysis, create a unique environment conducive to cancer cell proliferation. However, cancer cells operate at a metabolic threshold that poses a vulnerability: any disruption to the balance of pH and ROS can induce metabolic stress and potentially lead to cell death. This metabolic vulnerability unique to cancer cells is a potential target for therapeutic intervention.

[0096] This broader understanding of tumor biology, coupled with a comprehensive picture of the interactions involved, forms the basis for innovative cancer treatments. Tumors are not simply the result of isolated molecular abnormalities but arise from a complex network of biological interactions, including physiological, environmental, and immunological factors. Beyond reductionist approaches focused on single pathways or molecules, therapeutic strategies that address the full range of physiological differences between tumor and healthy cells offer promising avenues. In this context, the unique pH balance and metabolic vulnerabilities of cancer cells offer a new entry point for treatments aimed not only at tumor destruction but also at restoring physiological equilibrium.

[0097] An integrative approach to oncology therapy does not simply mean the simultaneous use of different drugs. Rather, it involves a network of synergistic interventions that address the complexity of the tumor microenvironment. Recognizing the critical connections between tumor cells, surrounding healthy cells, and the immune system, this approach attempts to restore the body's natural homeostasis and ability to respond to tumor challenges, resulting in more effective treatments with fewer side effects. By minimizing the adverse effects of conventional treatments, this strategy aims to improve patients' quality of life.

[0098] As oncology research and development increasingly gravitates toward personalized precision medicine, therapeutic strategies that target the fundamental characteristics that drive tumor initiation and progression can become powerful tools in the fight against cancer. By harnessing the complexities of tumor biology and its surrounding microenvironment, comprehensive treatment protocols can be developed that not only inhibit tumor growth but also restore the body's natural ability to more effectively control and combat cancer. Such approaches have the potential to transform cancer treatment, offering more precise and less invasive treatment options with improved patient outcomes.

[0099] The present invention relates to novel compositions, or products, made from 100% natural materials, that exert a therapeutic effect in the treatment of cancer, or that exert a therapeutic or adjunctive effect when combined with an anti-cancer drug in the treatment of cancer. As disclosed in the specification, figures, and examples, the products of the present invention exert their therapeutic or adjunctive effect through a physiological (non-pharmacological) mechanism of action.

[0100] To act via a physiological mechanism of action, a product must be 100% natural, exhibit batch-to-batch therapeutic or adjuvant functional consistency (i.e., maintain a therapeutic or adjuvant effect despite different chemical compositions between batches), and modify the entire pathological condition rather than one or a few functions. Natural materials, such as products comprising or consisting of natural matrices as products of the present invention, are entities that at least partially maintain the self-generated properties of their starting materials belonging to a biological domain and exhibit unique properties represented by a network of material and non-material relationships that interact with the network of relationships of the treated subject (inter-network interactions), thereby recapitulating physiologically similar characteristics and interactions with similar complexity.

[0101] Therefore, according to this specification, a product comprising or consisting of one or more natural matrices is a product that is 100% natural, which means that the product does not contain any additional artificial substances, i.e. chemically synthesized substances made by man through laboratory processes.

[0102] Furthermore, according to the present specification, a product comprising one or more natural matrices also does not contain any added isolated molecules, such as excipients or active ingredients, even if of natural origin.

[0103] It is worth noting that natural matrices encompass identified substances of natural origin and are fundamentally different from "substances." To describe natural materials or matrices, it is necessary to extend the reductionist approach and use innovations from the last century. Conceptually, this refers to systems theory. From an experimental perspective, preclinical evidence includes systems biology approaches such as omics science (e.g., transcriptomics) and bioinformatics evaluation.

[0104] These allow a proper assessment of the matrix (the action network) and the human body (the receptor network), and allow the interaction between the two to be considered as a "network on a network" interaction. Mechanisms with the coordinated redundancy and coherence that characterize physiological functions in each specific context correspond to "physiological mechanisms of action" and can be characterized by network paradigms that are distinct from targeted and non-targeted models that describe PhIMs and mechanical / chemical / physical mechanisms, respectively.

[0105] In particular, according to the present invention, the natural matrix is ​​a 100% natural and biodegradable material consisting of natural components that are not modified by the process for producing the matrix from the starting raw materials, without the intentional addition of synthetic products along the entire process.

[0106] As already mentioned, to be defined as natural according to the present invention, it is essential that the matrix is ​​obtained by a non-denaturing process, so that the components of the matrix are not artificially modified. If necessary, the presence of additional indicators of the maintenance of characteristics present in the original raw material can be verified. Furthermore, a 100% natural product is one that is expected to be completely biodegradable. In this specification, a product that is "readily biodegradable" according to the OECD biodegradation test is considered to be 100% biodegradable. These characteristics ensure the maintenance of the matrix effect imparted to the matrix by the structural interactions (material interactions) of its components and the presence of functional interactions (non-material interactions) that become apparent upon exposure of a biological system to the natural matrix.

[0107] The present invention provides 20-50% by weight of component a., 49-80% by weight of component b., and 0.6 to 1.2 wt.% of component c., Total 100% It consists of Component a. is an aqueous (lyophilized) co-extract of Filipendula leaves and flowers, Laurus leaves, Brassica seeds, and Withania roots, and the weight percentages of the raw materials for its preparation are 17.5 to 32.5% by weight of Filipendula leaves and flowers, 17.5 to 32.5% by weight of Laurus leaves, 17.5 to 32.5% by weight of Brassica seeds, and 17.5 to 32.5% by weight of Withania roots, totaling 100%; and Component b. is an aqueous (lyophilized) co-extract of Cynara leaves, Curcuma roots, and Tanacetum flowers, and the weight percentages of the raw materials for its preparation are 10-19% by weight of Cynara leaves, 29-55% by weight of Curcuma roots, and 29-55% by weight of Tanacetum flowers, totaling 100%; and Ingredient c. is an aqueous (lyophilized) extract of Agave leaves; Regarding the product.

[0108] According to the present invention, 0.66 mg / ml of the product as defined above and in the remainder of the specification and claims, when administered separately to HuDe, FaDu and A431 cells in a cell-based assay in cell culture plates, resulted in the following cell mortality rates 24 hours after administration: HuDe healthy cell mortality ≤61%; FaDu tumor cell mortality ≥ 71%; A431 tumor cell mortality rate ≥ 55%, or In a preferred embodiment, HuDe healthy cell mortality ≤61%; FaDu tumor cell mortality ≥ 71%, and A431 tumor cell mortality rate ≥ 65% can be induced, HuDe cells are seeded at approximately 7,000 cells / well in 200 μl of appropriate medium, FaDu cells are seeded at approximately 12,500 cells / well in 200 μl of appropriate medium, and A431 cells are seeded at approximately 8,500 cells / well in 200 μl of appropriate culture medium, and the cells are treated with the products and then cultured for 24 hours, and cell mortality is measured by assessing cell viability by nuclear staining.

[0109] Preferably, the cell culture plate for each cell type is a 96-well plate.

[0110] Thus, according to the present invention, a product has the formulation defined above and exhibits measurable cytotoxicity against HuDe, FaDu and A431 cells, which are well known and available to those skilled in the art.

[0111] To demonstrate the cytotoxic selectivity of the products of the invention for tumor cells, tests can be carried out mutatis mutandis on healthy cells versus tumor cells.

[0112] The above cell-based assays are classical in vitro assays for evaluating the efficacy and specificity of antitumor drugs. As is evident from the examples and the results obtained, the products of the present invention, tested in various preparations according to the present specification and claims, exhibit strong cytotoxic selectivity against tumor cells, while the mortality rate of non-tumor cells is lower than that of different tumor cells, a highly desirable property in antitumor therapy. Those skilled in the art can perform the assays according to general standard procedures. In each case in the examples section, a detailed description is provided of the cell-based assays for evaluating cytotoxicity and thus verifying this desirable feature of the products of the present invention.

[0113] Thus, the products of the present invention induce minimal / low cytotoxic effects on non-tumor cells (low mortality, e.g., 45% or less) and strong cytotoxic effects on tumor cells (high mortality, e.g., greater than 45% mortality).

[0114] Cell mortality, i.e., the opposite of viability, can be measured according to any common technique known to those skilled in the art.Non-limiting examples of possible techniques commonly used in the art can be ATP level determination, methylthiazolyltetrazolium (MTT) assay, trypan blue exclusion test, Annexin V / PI staining (flow cytometry), lactate dehydrogenase (LDH) release assay, caspase activity assay, neutral red uptake assay, real-time cell analysis (RTCA), colony formation assay, etc.

[0115] According to the present invention, the mortality of HuDe, FaDu and A431 cells induced by 0.66 mg / ml of the product described and claimed herein can be calculated by applying, mutatis mutandis, the protocol detailed below for the evaluation of activity units.

[0116] According to one embodiment of the present invention, the product has the following formula: 30-40% by weight of system a., 60-70% by weight of system b., and 0.6-1.2 wt.% of the system c., Total 100%.

[0117] The products of the present invention can be prepared as disclosed in the examples. However, components a, b and c can also be prepared as a mixture of extracts of each plant material in the same proportions as each single component.

[0118] The preferred mode of extraction is by water extraction, but aqueous extracts (eg, water and alcohol, where the ratio of water to alcohol is 1:0 to 1:1) are also encompassed by the present invention.

[0119] In one embodiment, component a. is a freeze-dried co-extract in water of Filipendula leaves and flowers, Laurus leaves, Brassica seeds, and Withania roots, the weight percentages of raw materials for its preparation being 17.5-32.5% by weight of Filipendula leaves and flowers, 17.5-32.5% by weight of Laurus leaves, 17.5-32.5% by weight of Brassica seeds, and 17.5-32.5% by weight of Withania roots, totaling 100%; Component b. is a freeze-dried co-extract of Cynara leaves, Curcuma roots, and Tanacetum flowers in water, the weight percentage of raw materials for its preparation being 10-19% by weight of Cynara leaves, 29-55% by weight of Curcuma roots, and 29-55% by weight of Tanacetum flowers, totaling 100%; and Ingredient c. is a freeze-dried extract of Agave leaves in water.

[0120] In certain embodiments (e.g., DoEs 1, 2, 3, and 4 described in the Examples), component a. is a lyophilized co-extract in water of Filipendula leaves and flowers, Laurus leaves, Brassica seeds, and Withania roots, the weight percentages of raw materials for its preparation consisting of 25 weight percent Filipendula leaves and flowers, 25 weight percent Laurus leaves, 25 weight percent Brassica seeds, and 25 weight percent Withania roots; and Component b. is an aqueous (lyophilized) co-extract of Cynara leaves, Curcuma roots, and Tanacetum flowers, the weight percentages of the raw materials for its preparation being 14.30% by weight of Cynara leaves, 42.85% by weight of Curcuma roots, and 42.85% by weight of Tanacetum flowers; Ingredient c. is a freeze-dried extract of Agave leaves in water.

[0121] In non-limiting examples, each of the starting plant materials used in the preparation of the products of the present invention can be individually selected from among the species set forth below: Filipendula is selected from among Filipendula ulmaria and Filipendula vulgaris or mixtures thereof; Laurus is selected from among Laurus azorica and Laurus nobilis or mixtures thereof; Brassica is selected from among Brassica rapa, Brassica nigra, broccoli (Brassica oleracea botrytis cymosa) or mixtures thereof; Withania is selected from among Withania sinensis and Ashwagandha (Withania somnifera or a mixture thereof, the genus Cynara is selected from Cynara cardunculus scolymus and Cynara flavescens or a mixture thereof, the genus Curcuma is selected from Curcuma zedoaria and Curcuma longa or a mixture thereof, the genus Tanacetum is selected from Tanacetum cinerariifolium, Tanacetum parthenium and Tansy or a mixture thereof, and the genus Agave is selected from Agave americana and sisal or a mixture thereof.

[0122] Preferably, all plant species used are selected from among the plant species mentioned above.

[0123] In preferred embodiments, the genus Filipendula is Filipendula vulgaris, the genus Laurus is Laurus nobilis, the genus Brassica is Broccoli (Brassica oleracea botrytis cymosa), the genus Withania is Ashwagandha (Withania somnifera), the genus Cynara is Cynara cardunculus scolymus, the genus Curcuma is Curcuma longa or a mixture thereof, the genus Tanacetum is Tanacetum, and the genus Agave is Sisal (Agave sisalana).

[0124] The following table summarizes possible embodiments of the present invention. [Table 1]

[0125] The product of the invention as defined above and in the claims, as disclosed in the examples, has been fully characterized by the applicant.

[0126] The present invention also encompasses the definition of the potency of a product in terms of arbitrary units (AU or au or arb. units), i.e., the determination of the unit of activity (UoA) of a product of the invention as the amount of product necessary and sufficient to obtain a defined biological effect.

[0127] In the biomedical field, the term "arbitrary units" is often used to measure and express data where precise physical units are difficult to define or are not essential to the particular context of the experiment.

[0128] The use of arbitrary units allows researchers to focus on the measurement of a biological outcome rather than the physical properties (e.g., weight) of the therapeutic agent used to induce such a biological outcome, allowing measurements to be normalized across different experiments or conditions, making it easier to understand equivalence in the induction of biological outcomes and allowing measurements of physical properties to be ignored when they are irrelevant given the nature of the treatment.

[0129] Herein, the determination of the UoA was based on the performance of the selected standard (DoE2).

[0130] 1UoA is herein described as having the following activity in cell culture plates: 24 hours after separate administration to HuDe, FaDu and A431 cells: HuDe healthy cell mortality rate: 40-50% FaDu tumor cell mortality ≥ 90%, and A431 tumor cell mortality rate ≥ 65% is defined as a necessary and sufficient amount of EpigenAU / 11 that can induce HuDe cells are seeded at approximately 7,000 cells / well in 200 μl of appropriate medium, FaDu cells are seeded at approximately 12,500 cells / well in 200 μl of appropriate medium, and A431 cells are seeded at approximately 8,500 cells / well in 200 μl of appropriate culture medium, and the cells are treated with the products and then cultured for 24 hours, and cell mortality is measured by assessing cell viability by nuclear staining.

[0131] According to the present invention, approximately 7,000 HuDe cells / well are seeded in an appropriate culture medium, approximately 12,500 FaDu cells / well are seeded in an appropriate culture medium, and approximately 8,500 A431 cells / well are seeded in an appropriate culture medium. The cells are cultured at 37°C and 5% CO2.

[0132] To assess activity units, reference DoE2 (20-fold diluted) was seeded at a final concentration of 0.66 mg / ml and cells were treated for 24 hours before measuring cell mortality. Cell viability was assessed by nuclear staining with NuclearMask. Fluorescence intensity, indicative of cell viability, was measured using a Varioskan™ LUX multimode microplate reader; emission / excitation: 622 nm / 645 nm. To ensure the reproducibility of the above criteria, the following experimental conditions should be followed.

[0133] 1. Cell culture conditions: HuDe, FaDu and A431 cell lines should be cultured according to their conventional designated protocols, where: *HuDe cells are cultured in MEM medium containing 10% FBS, 1% penicillin / streptomycin, and 1% sodium pyruvate and seeded at approximately 7,000 cells / well. *FaDu cells are cultured in EMEM medium containing 10% FBS, 1% penicillin / streptomycin and seeded at approximately 12,500 cells / well. *A431 cells are cultured in DMEM medium containing 10% FBS and 1% penicillin / streptomycin and seeded at approximately 8,500 cells / well.

[0134] 2. Experimental Setup: o Cells are cultured in a humidified incubator at 37°C with 5% CO2. In a preferred embodiment, the seeding and treatment steps are performed using an Assist Plus robot to ensure precision.

[0135] 3. Treatment with EpigenAU / 11 (DOE2): o EpigenAU / 11 should be solubilized as described in the experimental section and added to the cells to reach a final concentration of 0.66 mg / mL in a total volume of 200 μL / well. In a preferred embodiment, the product is solubilized at 20x concentration, so that the amount of product calculated for a given number of AU can be provided for a fixed volume of final standard solubilization. o Therefore, cells are exposed to treatment with 0.66 mg / mL of EpigenAU / 11 for 24 hours.

[0136] 4. Assessment of Cell Viability: Preferably, assessment of cell viability is performed by nuclear staining with Nuclear Mask-Red according to the manufacturer's instructions. o Fluorescence intensity, which indicates cell viability, is preferably measured using a Varioskan™ LUX multimode microplate reader; emission / excitation: 622 nm / 645 nm. Thus, an activity unit is the potency achieved under these specific experimental conditions that ensures reproducibility and reliability in determining the anti-cancer potential of EpigenAU / 11. Measurement of mortality (also intended as "vital decline") can be performed as described above.

[0137] The results provided in the experimental sections of Figures 15, 24, 37, 38, 39, Examples 4, 7, and 13, in which the products of the present invention were combined with different anticancer drugs (antitumor active ingredients), demonstrate that the combination with different anticancer drugs results in an enhanced or even synergistic anticancer drug therapeutic effect. One of the results obtained in the experiments was a reduction in drug resistance, which is a highly advantageous effect (see, for example, Figure 7, Example 2.4.1). Therefore, the products of the present invention can be advantageously combined with one or more anticancer drugs. Non-limiting examples of suitable anticancer drugs to be used in combination with the products of the present invention include chemotherapeutic agents, antibodies or therapeutically active fragments thereof, small molecules, etc. Non-limiting examples of suitable chemotherapeutic agents are represented by cisplatin, paclitaxel, gemcitabine, epirubicin, cyclophosphamide, carboplatin, oxaliplatin, mitomycin C, bleomycin, doxorubicin, busulfan, dacarbazine, temozolomide, ifosfamide, melphalan, clophosfamide, lomustine, bendamustine. Non-limiting examples of suitable antibodies are provided by monoclonal antibodies such as rituximab, trastuzumab, bevacizumab, pembrolizumab, ipilimumab, nivolumab, atezolizumab, cetuximab, etc.

[0138] The products or compositions of the present invention can also be advantageously combined with radiation therapy, as will be apparent from the examples, and indeed experimental data demonstrate the adjuvant effect of the products of the present invention in combination with radiation therapy in the treatment of cancer.

[0139] Advantageously, the products of the present invention, suitably diluted in an appropriate pharmaceutically acceptable carrier (e.g., water or brine, etc.), can be used in anti-cancer therapy as an adjuvant or vehicle for known anti-cancer agents, non-limiting examples of which are provided above.

[0140] Thus, the present invention also relates to a composition comprising a product according to any of the embodiments disclosed herein and at least one of an anti-cancer active ingredient and a pharmaceutically acceptable carrier.

[0141] When two or more anti-cancer agents are included in the compositions of the present invention, these will generally be co-administered anti-cancer agents.

[0142] Possible examples of combinations are provided in the Examples section.

[0143] The at least one anti-cancer active ingredient according to the present invention may be, by way of example, any known anti-cancer agent as defined above or a combination thereof.

[0144] Compositions or therapeutic adjuvants according to the present invention can be readily formulated by one of skill in the art for oral, nasopharyngeal, oropharyngeal, aerosol, systemic injection, microneedle injection, intratissutal injection, intravenous, topical, rectal, vaginal, ocular, or intratissutal administration.

[0145] Non-limiting examples of formulations can be suspensions, solutions, lyophilized materials, creams, ointments, sprays, tablets, soft gelatin capsules, hard gelatin, gels, emulsions, eye drops, enemas, suppositories, vaginal suppositories, powders, granules, filled vesicles, filled liposomes.

[0146] The present invention also relates to a kit-of-parts for combined, simultaneous or sequential administration, comprising separate vials of a therapeutic adjuvant or vehicle according to the invention and at least one anti-cancer active ingredient (e.g. as defined above).

[0147] Concomitant administration generally refers to the use of two or more treatments within a narrow time window (e.g., within 5, 10, 15, 20 minutes, etc.), but not necessarily at the same dose or at the exact same time point together. According to the present invention, two different anti-cancer agents can each be resuspended or diluted in an adjuvant or vehicle of the present invention and then administered separately, or the adjuvant and one or more anti-cancer agents can be administered separately (the adjuvant is administered separately from the one or more drugs).

[0148] Simultaneous administration refers to giving treatments or agents at exactly the same time, and in the case of kits of the invention, this can also mean resuspending or diluting one or more anti-cancer agents directly in a vehicle or adjuvant of the invention.

[0149] Sequential administration means that a patient in need thereof is given one or more anti-cancer drugs diluted or resuspended in an adjuvant or vehicle of the present invention, or an adjuvant and one or more anti-cancer drugs, one after the other, with a time interval between them.

[0150] When two or more anti-cancer agents are administered, they may be anti-cancer agents that are typically administered in combination, simultaneously, or sequentially, according to combinations known in the art.

[0151] Possible examples of combinations are provided in the Examples section.

[0152] The present invention also relates to a product or composition, or an adjuvant, or a kit-of-parts of the invention for use in medical treatment, in particular in the treatment of cancer.

[0153] According to one embodiment of the present invention, the cancer may be osteosarcoma, breast cancer, bladder cancer, endometrial cancer, gastric cancer, ovarian cancer, squamous cell carcinoma, head cancer and neck cancer.

[0154] As disclosed in the Examples section and discussed above, the product of the present invention has demonstrated anti-cancer efficacy when used alone and in combination with one or more anti-cancer drugs.In particular, the product surprisingly exhibits advantageous ability to reduce drug resistance in suitable models of resistant patients, and additive or even synergistic anti-cancer effects in combination with various anti-cancer drugs, thereby allowing for reduction in either the amount of anti-cancer drug used or the duration of treatment, or both.

[0155] Therefore, the present invention also relates to a method for treating cancer, wherein the product, composition, adjuvant or kit-of-parts of the present invention is administered in a therapeutically effective amount to a patient in need thereof.

[0156] Notably, as is evident from the examples, the applicant also provided a novel method for calculating the benefit / risk ratio of the product of the present invention, demonstrating the product's naturalness and its physiological mechanism of action. In the examples, a novel method for quantifying the differential benefit / risk ratio profiles between EpigenAU / 11 and cisplatin is provided through a thorough evaluation of the benefit / risk scores associated with treatment with EpigenAU / 11 and cisplatin, focusing specifically on the transcriptional and functional effects observed in ex vivo conditions (see Figures 29-34). The analysis was based on an integrated computer-implemented approach utilizing transcriptome data and advanced biological pathway analysis tools, such as Ingenuity Pathway Analysis (IPA), to identify gene expression changes and associated alterations in biological function, addressing both therapeutic efficacy and potential adverse effects.

[0157] The benefit / risk ratio is a key parameter that is extremely useful in understanding the differences between such important characteristics of therapeutic options. Nevertheless, such a parameter is currently difficult to re-estimate into a single, objectively calculated numerical parameter that can facilitate a first-order approach to comparison between therapeutic solutions. Here, we provide a method that can accurately predict and objectively compare the benefit / risk ratios of two therapeutic solutions based solely on ex vivo transcriptomics data. Furthermore, we provide an additional method for streamlining and summarizing the benefit / risk ratios from data obtained in vivo in animal models for the same therapeutic product into a single numerical parameter (see Figures 35 and 36).

[0158] State-of-the-art benefit / risk assessment of a drug involves comparing its observed positive effects (benefits) with its observed negative effects (risks) in patients. This process usually begins with clinical trials to evaluate efficacy and safety. Benefits are assessed based on the drug's ability to effectively treat or prevent a condition. Risks are considered by identifying side effects, toxicity, and long-term effects. Data from preclinical trials, clinical trials, and post-marketing surveillance aid in this assessment. The drug's safety profile, the severity of side effects, and the severity of the condition being treated are all considered. Regulatory agencies such as the FDA evaluate the evidence before approval, considering whether the benefits outweigh the risks. Ongoing monitoring ensures continued safety after approval. If the risks outweigh the benefits, the drug may be withdrawn or its use may be restricted.

[0159] The present invention provides a new method for determining the benefit / risk score of a new potential drug using a known reference drug with known side effects as a control.

[0160] The method can be advantageously used for the prospective assessment of the benefit / risk ratio of a new product under evaluation, particularly when compared with the benefit / risk ratio obtained by the same method for a reference drug for the treatment of the same condition treated by the product under evaluation.

[0161] According to the present invention, there is provided a computer-implemented method (Method A) for providing a benefit / risk score for a therapeutic product of interest based on transcriptional data (obtained through the use of ex vivo or in vitro generated data), comprising the steps of: 1. Performing Transcriptomic Analysis by: 1.1 Providing a sample of a biological substrate representative of the condition treated by said product; and a. treating one or more of said samples with said product; b. treating one or more of said samples with a reference drug to treat said condition; and c. using one or more samples of said biological substrate as relevant controls; 1.2 Extracting RNA from each of the a., b. and c. samples; 1.3 Performing transcriptome raw data analysis from the RNA extracted in 1.2 to obtain a list of differentially expressed genes (DEGs) in each of samples a. and b. identified based on their expression fold change relative to c., thereby obtaining a fold change value for each DEG; 1.4 IPA core analysis is performed on the list obtained in 1.3, thereby obtaining a numerical value that represents the variation in the magnitude and direction (i.e., up-regulation or down-regulation) of the biological activity associated with the differential expression of said DEGs in each of samples a. and b. normalized to sample c. 2. Determining the benefit score by: 2.1 Selecting a biological activity identified in 1.4 that is relevant to the therapeutic indication of said product (e.g., for a product of the invention, antitumor activity); 2.2 converting said numerical values ​​into absolute values; 2.3 summing said absolute values ​​of each of said biological activities, thereby obtaining a benefit score for the product under consideration; 3. Determining a risk score by: 3.1 providing (e.g., by database query) side effects associated with reference drugs for treating said condition; 3.2 Determining IPA biological activity associated with said side effects; 3.3 Building an in silico model of risk using IPA by establishing the relationship between the gene expression patterns obtained in point 1.3 and the biological activity determined in point 3.2 for samples a. and b.; 3.4 Enter the relevant fold change values ​​of each DEG of samples a. and b. obtained in 1.3 into the in silico model of risk obtained in point 3.3., and use IPA to obtain data representing the direction and magnitude of modulation of each biological activity obtained in point 3.2, and convert said data into corresponding numerical values; 3.5 summing up each positive value obtained in 3.4, thereby obtaining a final value representing the risk score of the product under consideration, said final value being automatically corrected to a predetermined minimum positive value if it is less than said minimum positive value; 4. Providing a benefit / risk score value for the product of interest as the ratio between the benefit score value obtained in point 2.3 and the risk score value obtained in point 3.5; A computer-implemented method is provided, comprising:

[0162] In this specification, the absolute value of 2.2 means that the modulus of each value is taken into account and the negative and positive signs are not taken into account.

[0163] Total means to add up each value, and the side effects considered in 3.1 are those that are commonly / frequently indicated in the reference drug package insert.

[0164] The determination in 3.2 can be made by examining the appropriate IA.

[0165] It should be noted herein that in mathematics and herein the value 0 is not considered a positive or negative number, and therefore a correction to a minimum positive value is necessarily applied when a value of 0 is obtained in the risk score values ​​provided by the methods disclosed herein.

[0166] Preferably, benefit / risk score values ​​are calculated for both the product of interest and the reference drug to allow comparison of the product of interest with the reference drug.

[0167] The present invention further discloses a method for providing a benefit / risk score for a therapeutic product of interest for treating a given condition based on data obtained from an in vivo animal model. 1. Provide values ​​obtained from the following group of animal models that represent the pathology: a. A group treated with said product; b. A group treated with a reference drug for the treatment of said condition, and c. relevant control group; The values ​​represent the following parameters: therapeutic efficacy, behavioral changes indicative of animal morbidity, and weight loss indicative of animal morbidity observed in each of groups a and b normalized to the control group c. 2. Determining a benefit score by summing said therapeutic effectiveness values, thereby obtaining a benefit score value for the product under consideration. 3. Determining a risk score. 3.1 Identify as risk parameters the changes and weight loss that indicate that the animal is ill, for which values ​​are provided in 1. 3.2 Summing up the numerical values ​​of 3.1 (see group a.) to obtain a final value representing the risk score of the product under consideration, which final value is automatically corrected to a predetermined positive minimum value if it is less than the predetermined positive minimum value. 4. Providing the benefit / risk score value of the product of interest as the ratio between the benefit score value obtained in point 2 and the risk score value obtained in point 3.2.

[0168] The therapeutic efficacy parameter depends on the condition of interest, for example, in the case of an anti-cancer drug, the parameter is primarily represented by a reduction in tumor burden, and optionally by the presence or absence of metastases, and in the case of an antidepressant, the parameter may include behavioral changes indicative of an improvement in the severity of depression, etc. Thus, the parameter is one that generally correlates with an assessment of therapeutic efficacy in treating a given condition.

[0169] Parameters indicative of behavioral changes indicative of disease in animals are those coded by standard tests commonly used in the art, such as the Irwin test, used in formal protocols for assessing disease in animals in preclinical trials or stabulation.

[0170] Again, a benefit / risk score can be provided for the reference drug.

[0171] Preferably, where applicable, both methods are performed to verify the results obtained with either one of them. The examples provided also demonstrate that the products of the present invention exhibit therapeutic or supportive consistency (i.e., still maintain the desired therapeutic effect even with slightly different batches and slightly different permutations of the relative ratios of components a, b, and c between batches), exhibit emergent properties that behave as a natural matrix itself and achieve its network-mediated effect through network interactions, thereby retaining native natural intelligence (natural capabilities).

[0172] The "native intelligence" of a natural matrix, e.g., a therapeutic plant-based natural matrix, e.g., a product of the present invention, refers to the inherent synergistic wisdom embedded in the complex relationships between plants, their biochemical properties, and their interactions with human biology and well-being. It encompasses the self-organizing adaptive processes inherent to plants that support healing, balance, and regeneration, both within ecosystems and when applied to human health. The native intelligence of a plant-based matrix is ​​observed in how diverse compounds within a single plant work together synergistically. Unlike isolated pharmaceuticals, the whole plant provides a balanced interaction between active and supporting ingredients, reducing side effects and increasing efficacy.

[0173] This synergy extends to how the different plants in the matrix complement each other, creating an overall therapeutic effect.

[0174] In summary, the native natural intelligence of therapeutic plant-based natural matrices represents the harmonious innate wisdom of plants and ecosystems in supporting health and healing. It is expressed through plants' biophysical synergy, ecological balance, partnership with human biology, and ability to guide holistic healing. This intelligence emphasizes collaboration and connection, providing a therapeutic pathway based on nature's own evolutionary wisdom.

[0175] The product of the present invention, being a novel natural matrix in itself, has the native natural intelligence (natural capabilities) typical of natural matrices.

[0176] As demonstrated in the examples, a product or therapeutic adjuvant according to any embodiment defined herein, when used in the disclosed treatments, exerts its therapeutic or supportive effect on cancer via a physiological mechanism of action on the altered physiological state underlying said cancer condition through modulation of a network of biological activities, and exhibits therapeutic or supportive functional consistency between different batches of said product or adjuvant, wherein said functional consistency is intended to maintain therapeutic or supportive properties between different batches of said product or adjuvant despite differences in qualitative and quantitative composition between batches.

[0177] This is true even when different permutations of the formulation within the claimed range are used, as demonstrated in the examples.

[0178] Indeed, the inventors have also demonstrated in the examples below that different batches of the product of the present invention (see examples EpigenAU / 11 DoE1, 2, 3, 4, and permutations thereof, for the relative amounts of components a., b., and c. within the claimed scope) showed therapeutic / beneficial functional consistency by modulating the above biological activities in the same pattern and with similar modulation values, despite their qualitatively and quantitatively different chemical compositions.

[0179] Indeed, different batches of a product containing one or more natural matrices are, by definition, batches whose qualitative and quantitative composition is necessarily variable, as discussed at length above. However, according to one embodiment, qualitative and / or quantitative analysis of each batch was performed to demonstrate the existing qualitative and / or quantitative differences in the molecular composition of each batch (Figure 27). This can be achieved by conventional techniques. Non-limiting examples include chromatography, spectrophotometry, atomic absorption spectroscopy (AAS), atomic emission spectroscopy (AES), inductively coupled plasma (ICP) techniques, chromatography coupled to a detector, etc., or combinations thereof. The analysis can focus on a limited number of selected classes of substances (e.g., Figure 27) or on all components of the product.

[0180] Although each batch was prepared according to standardized procedures to obtain a priori a high degree of uniformity between different batches, as would be expected for a product containing or consisting of a natural matrix, detailed qualitative and quantitative analysis of all tested batches clearly showed qualitative and quantitative differences between relevant batches that led to the discarding of batches that were in fact therapeutically active and the inability to assume the presence of the API using traditional validation methods used for synthetic or isolated drugs.

[0181] In Example 15, a quality control procedure for the manufacture of the product of the present invention is provided. Due to the quality control requirements, the performance of DoE2, which has been fully characterized and tested by the inventors, is set as a quality manufacturing target. Therefore, the inventors herein provide a standardized procedure, safety, and reproducibility for commercially manufacturing the product.

[0182] It is noted herein that natural matrices, by their very nature, are variable in composition even when obtained from the same type of raw material; by way of example, those skilled in the art are very well aware that a natural matrix obtained from an individual of a plant species will never be identical to another natural matrix obtained from a different individual of the same plant species, even within the same field of plants, due to the genetic and epigenetic variability of each organism.

[0183] Following the experiments reported in Figure 27, despite the different qualitative and quantitative chemical compositions of all analyzed batches, the authors surprisingly found that in all tested batches, the different molecular entities within each matrix appear to interact with each other in a functionally and possibly structurally redundant manner, providing the same therapeutic or beneficial (homeostatic adjuvant) effect despite the differences in their qualitative and quantitative molecular composition.

[0184] Indeed, the batches exhibited functional (therapeutic or beneficial) consistency despite variability in their qualitative and quantitative molecular composition.

[0185] In other words, the authors surprisingly found that different batches of the same product showed consistent modulation (in terms of trend and magnitude) of all examined biological activities associated with the desired therapeutic or beneficial effect, also defined herein as a "functional recovery effect," despite differences in the qualitative and quantitative composition between the batches. The observed maintenance of biological activity may be attributed to the fact that, as noted above, the emergent properties of natural matrices are due to the matrix network acting as a whole entity with unique properties and cannot be attributed to each single molecule as if it were isolated; the therapeutic action is due to a non-pharmacological mechanism of action that differs from that of classical therapeutic products, which are based on a structure-activity pharmacological relationship (SAR) (the most relevant relationship in classical pharmacological activity considered at the level of a single molecule, between an active pharmaceutical ingredient (API) and the receptor targeted by said API).

[0186] This is consistent with the possibility that the products analyzed by the inventors may exert their therapeutic or beneficial effects by acting on an overall pathophysiological or altered physiological state.

[0187] In accordance with the present invention, the defined and / or claimed product or composition exerts its therapeutic or beneficial effect through a physiological mechanism of action by aiding in the reversal of cancer through a network of biological activities on the altered physiological state underlying said cancer condition, and by exhibiting therapeutic or beneficial functional consistency between different batches of said product or composition, said functional consistency contemplated being the maintenance of therapeutic or beneficial properties between different batches of said product or composition despite differences in qualitative and quantitative composition between batches.

[0188] In particular, due to all the inferences regarding natural matrices provided above, together with all the experimental data collected by the applicant, it can be said that the product or composition according to the invention is a natural matrix that represents in itself a native natural intelligence, said natural intelligence being the only one capable of enabling physiological endogenous interconnection with other entities that have self-assembled in nature, such as the human species.

[0189] It should be noted that, in this specification, native natural intelligence (natural capability) refers to the inherent ability of natural matrices to store and transmit the biological and physiochemical information necessary to interact with and integrate other biological networks using logic specific to the receiving organism, since these networks are already known to the organism and therefore endogenous with respect to the organism. This intelligence is a manifestation of natural autopoiesis, i.e., the ability to self-organize and adapt to environmental stimuli without artificial intervention, transmitting messages according to a punctate logic and via mediators unknown to the receiving organism and therefore exogenous with respect to the organism.

[0190] Thus, as stated above, the product or therapeutic adjuvant of the present invention is itself a natural matrix, representing a (native) natural intelligence (natural capacity) that allows for physiological internal interconnection with other entities that self-organize in nature, such as the human species (thus, as stated above, the product or therapeutic adjuvant of the present invention is itself a natural matrix, (native) It represents natural intelligence (natural ability), and the natural intelligence (natural ability) is the ability of the human species to function independently in the natural world. organization with other entities 、 physiological And internal mutual The interconnection of enable).

[0191] Method ISO-16620-2;2019 (AMS) is a method for measuring the residual activity of 14C (an unstable isotope), and the measurement indicates the naturalness of a product. In fact, a decrease in 14C activity indicates the distance of a given compound from "living organisms." Therefore, a product with approximately 100% 14C activity can be defined as a natural product. According to the present invention, the 14C activity measured using the ISO-16620-2;2019 (AMS) method is greater than 99.0%.

[0192] According to the present invention, the presence of said native innate intelligence (innate ability) in the product or adjuvant composition of the present invention can be determined by verifying the product's or composition's manifestation characteristics in anti-cancer activity if the following conditions are met: their C activity measured using the ISO-16620-2;2019 (AMS) method is ≧99.00%, miRNA and exosomes are detected therein, the product or composition shows batch-to-batch consistency of therapeutic or beneficial function (functional consistency) between different batches of the product or composition, and the product or composition modulates an altered pathological condition overall.

[0193] According to the present invention, the presence of native natural intelligence (natural intelligence) within a therapeutic or therapeutic adjuvant product or composition (wherein the product or composition comprises or consists of a natural matrix) can be determined by verifying that the product or composition is a natural matrix that itself has the therapeutic or beneficial properties manifested in anti-cancer activity if its 14C activity measured using the ISO-16620-2;2019 (AMS) method is ≧99.00%, miRNA and exosomes are detected in the product or composition, the product or composition exhibits batch-to-batch therapeutic or beneficial functional consistency between different batches of the product or composition, and the product or composition modulates an altered physiological or pathological condition overall.

[0194] This involves using the product or composition of the present invention to subject a sample of said product or composition to the following steps: a. Evaluating the naturalness of a product or composition by: 1. Measuring the 14C activity in the product or composition using the ISO-16620-2;2019 (AMS) method; 2. Assessing the presence of miRNA in said product or composition; 3. Assessing the presence of exosomes in said product or composition; b. assessing the presence of therapeutic or beneficial functional consistency between different batches of the product by comparing, in a cell-based assay where the readout represents modulation of one or more biological activities, between batches the modulation of one or more biological activities that underlie the desired therapeutic or beneficial effect of the product on the relevant altered physiological state and / or pathological condition treated by the product or composition; c. assessing from the readout of the cell-based assay whether modulation of the biological activity underlying the desired therapeutic or beneficial effect results in modulation of an overall altered physiological or pathological state; and The measured 14C activity is ≥ 99.00%, miRNA, exosomes and therapeutic or functional coherence are detected, c., wherein said modulation results in modulation of an overall altered physiological or pathological condition. determining that the product or composition is a natural matrix that represents its own native natural intelligence (natural ability); This can be done by performing the following.

[0195] A product is determined to be natural if its measured C activity is ≥ 99.00%, miRNA, exosomes are detected, it exerts its activity through a physiological mechanism of action when it modifies a condition, and it exhibits therapeutic or beneficial functional integrity, i.e., it exhibits emergent properties. The sum of these characteristics allows the product to be determined as a natural matrix itself, thereby exhibiting native natural intelligence (natural capabilities).

[0196] Assessment of alterations in condition and functional integrity can be performed as follows.

[0197] The ability of a therapeutic or therapeutic adjuvant product to modify a pathophysiological or altered physiological state (e.g., by supporting the homeostatic response of an organism) is a key feature for establishing its physiological mechanism of action. Indeed, products that act in network interactions are products that are expected to modify a state rather than a single function when administered to an organism.

[0198] In other words, this characteristic is likely to be met by a therapeutic or therapeutic adjuvant product that includes or consists of one or more natural matrices, taking into account the network-network (product-receiver) interactions exerted by the natural matrices. Applicant's patent application PCT / IB2024 / 055892 discloses a method for defining the mechanism of action of a therapeutic or beneficial natural matrix-based product.

[0199] Products that exert a physiological mechanism of action are also expected to be 100% natural (see above) and to exhibit the flexibility and self-administration mechanisms observable within organisms, where different intracellular and intercellular messages, as well as different modulation of gene pathways, can provide the same result despite different messages being triggered within the cell. In the case of therapeutic or beneficial products, this corresponds to the functional consistency of different batches of the product (with qualitative and quantitative variability in the chemical composition of the batches).

[0200] The inventors have determined whether the products of the present invention exert their therapeutic or beneficial effects by modifying a pathological condition, and whether the products exhibit functional consistency (i.e., maintenance of the therapeutic or beneficial properties of different batches of a given product comprising one or more natural matrices, despite differences in qualitative and quantitative composition between batches).

[0201] According to the present invention, this can be verified by performing cell-based assays in which the readout represents modulation of a selected biological activity as defined above, and by analyzing and interpreting the data obtained therefrom, for example as disclosed in the examples and figures herein.

[0202] Assessment of functional integrity (therapeutic or beneficial).

[0203] As indicated in the glossary and above specification, for purposes of this specification and claims, functional consistency is the maintenance of measurable therapeutic or beneficial efficacy in different batches of a product despite variability in qualitative and quantitative molecular composition.

[0204] It is clear that the batches (e.g., the tested DoEs 1, 2, 3, and 4 of EpigenAU / 11) are intended to be identical in terms of the manufacturing process and the type and amount of each ingredient (since the main ingredients of the selected products are natural matrices, this means that each matrix in the product is manufactured from the same type of starting material using the same procedure, e.g., a given type of extract from the same plant part of the same plant species). Therefore, variability in their qualitative and quantitative molecular composition cannot be attributed to different manufacturing procedures or different ingredients, but can only result from inherent differences between natural matrices obtained using the same procedure from different organisms of the same species. Functional consistency of a product can be verified if different batches of the same product containing one or more natural matrices, regardless of their qualitative and quantitative composition, measurably and verifiably maintain their ultimate regulatory activity underlying their therapeutic or beneficial properties.

[0205] The present invention therefore also provides a method for determining the presence of native natural intelligence (natural ability) in a therapeutic or therapeutic adjuvant product or composition, said product or composition comprising or consisting of a natural matrix, through the verification of its therapeutic or beneficial emergent properties, the method comprising the following steps on a sample of said product or composition: a. verifying the naturalness of said product by: 1. Measure 14C activity using the ISO-16620-2;2019 (AMS) method; 2. Assessing the presence of miRNA in said product or composition; 3. Assessing the presence of exosomes in said product or composition; b. assessing the presence of therapeutic or beneficial functional consistency between different batches of the product by comparing, in a cell-based assay where the readout represents modulation of one or more biological activities, between batches the modulation of one or more biological activities that underlie the desired therapeutic or beneficial effect of the product on the relevant altered physiological state and / or pathological condition treated by the product or composition; c. assessing from the readout of the cell-based assay whether modulation of the biological activity underlying the desired therapeutic or beneficial effect results in modulation of an overall altered physiological or pathological state; and determining that the product or composition is a natural matrix that represents its own native natural intelligence (natural ability) if the measured 14C activity is ≧99.00%, miRNA, exosomes and therapeutic or functional integrity are detected, and said modulation in c. results in modulation of an overall altered physiological or pathological condition; The present invention relates to a method, including:

[0206] According to one embodiment of the present invention, the method further includes, prior to performing one or more cell-based assays, (1) providing a list of hallmarks representing altered metabolism and / or pathological conditions; (2) identifying, for each of the hallmarks, modifications of one or more biological activities underlying the pathological condition, thereby identifying a network of biological activities whose modulation is consistent with the pathological condition; and (3) identifying one or more parameters whose modulation is consistent with modulation of the one or more biological activities underlying the therapeutic effect of the tested product, and determining, in the network, a modulation trend for up-regulation or down-regulation of the one or more biological activities consistent with the pathological condition or healthy state.

[0207] According to a preferred embodiment, the altered physiological condition is cancer and the hallmarks are selected from angiogenesis, immune system and inflammatory processes, tumor viability and growth, metastasis, pre-metastatic niche formation, and preferably, the biological activities of (2) for the hallmarks of angiogenesis, immune system and inflammatory processes, tumor viability and growth, metastasis, pre-metastatic niche formation are selected from the biological activities shown in Figure 17 and Figure 32.

[0208] The following methods are computer-implemented methods.

[0209] In more detail, (1) Providing a list of hallmarks representing pathological conditions associated with the disease state, i.e., providing a list of hallmarks representing the disease or pathophysiological condition to be treated by the intended product; (2) identifying for each of said hallmarks an alteration in one or more biological activities underlying said pathological condition, determining its modulation indicative of a pathophysiological state associated with said pathological condition, and evaluating the opposite modulation as a modulation pattern for each of said activities indicative of a healthy physiological state; and (3) Identifying one or more markers and their regulatory patterns underlying the detectable alterations in the pathological state for each of the one or more biological activities, and for each of the parameters, identifying the regulatory pattern opposite to the identified one as the regulatory pattern consistent with the healthy physiological state.

[0210] When a therapeutic product is considered, according to one embodiment, the method of the present invention may comprise the following steps: (a) performing said at least one in vitro cell-based assay on a cell population comprising: (a1) at least one control group and at least two test groups of cells having a disease phenotype relevant to the intended use of the therapeutic product; or (a2) at least one population of cells having a healthy physiological phenotype, and at least one control group and at least two test groups of said cells having a healthy physiological phenotype, wherein a disease phenotype associated with the intended use of the therapeutic product is induced; and treating each of said test groups of cells with one of said different batches of therapeutic product; (b) determining the modulation or pattern of modulation of each of said parameters for each of said populations of cells of step (a) and calculating a respective modulation value for each of said one or more biological activities; (c) comparing said adjustment values, said therapeutic product comprising: At least 50% of the one or more biological activities for each hallmark are modulated with each product batch such that the modulation trend of the network is consistent with a healthy state, and the modulation value determined in (b) for each of the at least 50% one or more biological activities for the test group of cells of (a1) each differs from that of the control group of cells of (a1) by at least 0.15; or At least 50% of the one or more biological activities for each hallmark are modulated with each product batch such that the modulation trend of the network is consistent with a healthy state, and the modulation value determined in (b) for each of the at least 50% one or more biological activities for the test group of cells of (a2) is at least 15% different from that of the control group of cells of (a2), respectively. It has been shown that the therapeutic effect is exerted through physiological mechanisms in The functional consistency of the product is demonstrated by a modulation value for each of one or more biological activities of each of said test groups of cells that differs from the average of said values ​​by less than 20%. Process.

[0211] In the case of EpigenAU / 11, the cell-based assay identified is (a1).

[0212] This means that the modulation value of a given biological activity in the test group corresponds to the modulation value of the same biological activity in the control group, respectively, and therefore a difference of at least 0.15 or at least 15% is the difference between the modulation value of a given activity in a treated group of cells and the modulation value of the same activity in a group of cells representing the control baseline.

[0213] The phrase "at least 50% of the one or more biological activities for each hallmark are modulated by each product batch such that the network's modulation trend is consistent with a health state" means that for a single biological activity for a given hallmark, 100%, i.e., the single activity, must be modulated by the tested product such that the modulation trend is consistent with a health state in order to meet the above requirement, and the phrase "the modulation value determined in (b) for each of the at least 50% one or more biological activities" refers to the modulation value determined in (b) for at least 50% of the biological activities that meet the requirement of being modulated according to a modulation trend consistent with a health state. This applies mutatis mutandis to all embodiments disclosed herein.

[0214] As previously mentioned, the method of the present invention comprises: (1) providing a list of hallmarks representing a pathological condition of interest (i.e., a pathological condition treated by the analyzed product or a pathological condition that can result from an altered physiological state in which the analyzed beneficial product exerts its homeostasis-supporting activity); (2) identifying, for each of the hallmarks, modifications of one or more biological activities underlying the pathological condition, thereby identifying a network of biological activities whose modulation is consistent with the pathological condition; and (3) identifying one or more parameters whose modulation is consistent with modulation of the one or more biological activities underlying the therapeutic effect of the tested product, and determining, in the network, a modulation trend for up- or down-regulation of the one or more biological activities that is consistent with the pathological condition or healthy state.

[0215] All of the above embodiments make it possible to determine whether a therapeutic or beneficial product exerts its therapeutic or beneficial effect by modifying the underlying condition of a pathology or simply a limited number of activities or a single function, the abnormal physiological condition treated by said product, and whether the therapeutic or beneficial product as selected maintains functional integrity as defined herein.

[0216] The altered state is a feature not achieved with single-API drugs and therefore excludes the mechanism of action of classical drugs. However, altered state can, in principle, be achieved with drugs containing a cocktail of APIs.

[0217] A physiological mechanism of action requires that the therapeutic or beneficial product modulates a condition in a manner that involves a holistic cellular response with the network through network interactions, rather than a point of network interaction based on the API mechanism of action (whether a single API or a cocktail thereof).

[0218] In addition to modulating conditions, this also refers to the ability of a product to act with functional consistency (either therapeutic or beneficial), i.e., the ability to provide the same batch-to-batch therapeutic / beneficial effect despite differences in qualitative and quantitative composition between batches, in other words, the ability to modulate various selected parameters in a variable manner and yet provide a preserved functional result.

[0219] Thus, the present invention also provides an aspect for demonstrating the functional integrity of a therapeutic or beneficial product.

[0220] As already explained in the glossary and in the specification above, functional consistency (therapeutic or beneficial) is the ability of a given product to modulate one or more biological activities underlying a pathological or altered physiological state, despite variability in the qualitative and quantitative composition of different batches of the same product, and therefore, potentially reaching the same end result and eliciting different signals in cells, i.e., demonstrating bioequivalence as intended for the same end result. As already mentioned above, it is known that pharmaceutical (API-based) products with different qualitative and quantitative compositions are not considered bioequivalent.

[0221] The physiological mechanism of action refers to the overall interaction with the cells of the treated subject, not the interaction with a specific cellular molecular target, but is a mechanism exerted by an organism as a result of network-network interactions. Physiological systems within the body often exhibit functional redundancy to maintain homeostasis and adapt to changes or disruptions, and redundancy is a well-known physiological mechanism in organisms to ensure that a given goal is reached (e.g., the organism's response in producing various proteins, activating various pathways, etc.). When a therapeutic product interacts with these systems, it may engage multiple pathways or mechanisms, including redundant pathways or mechanisms, to achieve its desired effect. This redundancy, which results in functional consistency, contributes to the product's physiological mechanism of action.

[0222] Therefore, functional consistency in a therapeutic / beneficial product (defined as the ability of a therapeutic or beneficial product to maintain its intended functionality and effectiveness despite variability in its qualitative and quantitative composition from batch to batch) is an essential feature of a physiological mechanism of action.

[0223] The present invention also relates mutatis mutandis to a method for treating or assisting in the treatment of a cancerous condition, wherein the product or composition or therapeutic adjuvant or kit-of-parts according to the present invention is administered alone or in combination with an anti-tumour active ingredient or in combination with suitable radiotherapy in a therapeutically effective amount to a patient in need thereof, preferably wherein said cancer is osteosarcoma, breast cancer, bladder cancer, endometrial cancer, gastric cancer, ovarian cancer, squamous cell carcinoma, head and neck cancer.

[0224] Anywhere in this specification and claims, the word comprising may be replaced with the word consisting of.

[0225] Wherever in this specification and claims reference is made to cytotoxic effects (i.e., mortality / vitality of the tested cells), it is understood that the vitality value is the inverse of the mortality value, and vice versa. Thus, by way of example, -x% for vitality corresponds to x% mortality of the cells.

[0226] In any part of this specification or claims, where calculations are performed, this may be done in a computer-implemented mode.

[0227] Examples are reported below that have the purpose of better illustrating the embodiments disclosed herein, and such examples should in no way be construed as limiting the scope of the foregoing specification and subsequent claims. Furthermore, the following examples report all work performed on the products of the present invention and support all claimed subject matter. [Example]

[0228] 1. The strain of the present invention: EpigenAU / 11 1.1 EpigenAU / 11 composition: The claimed compositions, also referred to herein as EpigenAU / 11, are expressed as a weight percent of each plant system and a weight percent of each plant part used in the preparation of each system.

[0229] The following table reports the composition of different batches of EpigenAU / 11 (each labeled DoE followed by a number). The starting material (plant material) used to prepare each plant line in each batch was a different plant of the same species as indicated in the table. The different batches were prepared to analyze their chemical qualitative and quantitative composition (which was expected to be different in each batch due to the fact that plants are living organisms, and each individual plant belongs to the same species but will inevitably differ from each other in terms of qualitative and quantitative composition), and their activity was tested in various assays to fully characterize the EpigenAU / 11 line and to demonstrate the therapeutic and functional consistency of the product, i.e., maintaining therapeutic activity despite different qualitative and quantitative compositions between batches. [Table 2]

[0230] 1.2 Preparation process of EpigenAU / 11 Preparation of EpigenAU / 11: Generally, the EpigenAU / 11 system consists of three components: Plant System 1, Plant System 2, and Agave, in relative weight percentages as defined herein and in the claims. Specific embodiments of the EpigenAU / 11 composition have been prepared, each designated as a "DoE" followed by a number for practical reasons. The table above shows the exact percentages of each component of the different EpigenAU / 11 DoEs used in the following examples. In cases where additional DoEs are tested, the exact formulations of each are provided. Process (1.3) described below, mutatis mutandis for the relative percentages of each component or starting plant material according to the table above and the claims and various described embodiments, applies to all possible formulations of EpigenAU / 11 within the scope of the claims.

[0231] 1.3. Preparation of Components A, B and C Solvent: Purified water was produced from drinking water by an industrial water treatment plant.

[0232] Component A: Plant system 1: Dried bay leaves (Laurel nobilis), ashwagandha (Withania somnifera) roots, meadowsweet (Filipendula ulmaria) leaves and flowers, and broccoli (Brassica oleracea) seeds were co-extracted with 100% water (v / v) [drug-solvent ratio: 1 / 20] at 50°C for 2 hours and filtered to remove solid exudates. The co-extract was centrifuged. The supernatant was ultrafiltered (filtered at 20,000 Da) to obtain two fractions: permeate and retained. The retained fraction was pasteurized and then freeze-dried for 72 hours. The resulting co-extract was stored at room temperature, protected from light and moisture, until use. The weight-to-weight percentages of each plant material used are reported in the table above.

[0233] Component B Plant system 2: Dried Cynara cardunculus leaves, turmeric (Curcuma longa) roots, and feverfew (Tanacetum parthenium) flowers were co-extracted with 100% water (v / v) [drug-solvent ratio: 1 / 20] at 50°C for 2 hours and filtered to remove solid exudates. The co-extract was centrifuged. The supernatant was ultrafiltered (filtered at 20,000 Da) to obtain two fractions: permeate and retained. The retained fraction was pasteurized and then freeze-dried for 72 hours. The resulting co-extract was stored at room temperature, protected from light and moisture, until use. The weight-to-weight percentages of each plant material used are reported in the table above.

[0234] Component C Agave: Dried sisal (Agave sisalana) leaves were extracted with 100% water (v / v) [drug-solvent ratio: 1 / 15] at 50°C for 2 hours and filtered to remove solid exudates. The extract was centrifuged. The supernatant was ultrafiltered (filtered at 20,000 Da) to obtain two fractions: permeate and retained. The retained fraction was pasteurized and then freeze-dried for 72 hours. The resulting extract was stored at room temperature, away from light and moisture, until use.

[0235] 1.3.2. Assembly of the EpigenAU / 11 system The three components are combined according to the ratios set forth herein to reach 100% by weight. EpigenAU / 11 DoEs 1, 2, 3, and 4 were prepared by combining weight-to-weight percentages of Component A (36.05%), Component B (63.06%), and Component C (0.89%). Meanwhile, EpigenAU / 11 DoE 4.2 was prepared by combining weight-to-weight percentages of Component A (30%), Component B (69.11%), and Component C (0.89%).

[0236] 1.3.3 Solubilization of EpigenAU / 11 All solubilized EpigenAU / 11 DoEs used in the following examples were prepared by the following method: weigh the desired volume into a tube and add the desired solvent (physiological solution or medium). Then, vortex using a Multileax for 2 minutes at room temperature and sonicate at maximum power (Branson Ultrasonics) for 5 minutes at 35°C. The extract was then placed on a wheel mixer at 27 RPM for 30 minutes and centrifuged at 5000 RPM for 10 minutes. Finally, the supernatant was collected and filtered through a 0.22 μm filter.

[0237] 1.4 Overview of protocols used [Table 3]

[0238] 2. Preclinical data The preclinical data reported below demonstrate the cancer cell-selective cytotoxicity of EpigenAU / 11; the DoE used in the reported experiments is DoE2; similar data were obtained in the other DoEs listed above.

[0239] The EpigenAU / 11 system was developed through a research process that leveraged insights gained from previous formulations. This innovative candidate aims to play a discriminatory role, specifically targeting tumor cells while sparing healthy cells. Based on a comprehensive understanding of the active processes in carcinogenesis, this approach highlights the need to address the complex interactions within the tumor microenvironment to improve treatment outcomes, all while maintaining a favorable risk-benefit ratio.

[0240] 2.1 In vitro performance of EpigenAU / 11 This novel formulation was tested across a selection of cell lines from both non-cancerous and various cancer types to assess any differential responses.

[0241] Cell lines used: One non-cancerous human dermal fibroblast cell line (HuDe) Three head and neck squamous cell carcinoma lines (FaDu, Detroit562, and CAL-27) One cutaneous squamous cell carcinoma line (A431) Two osteosarcoma cell lines (U-2 OS, SaOS-2) One osteosarcoma cancer stem cell line (OCSC) Two triple-negative breast cancer cell lines (MDA-MB-231, SUM159PT) One breast cancer stem cell line (BCSC) One melanoma cell line (M14) One human bladder transitional cell carcinoma line (UMUC3) 143B: A highly proliferative and invasive derivative of the osteoblastic osteosarcoma line. MSCs (BM-derived mesenchymal stromal cells): Multipotent stromal cells derived from bone marrow.

[0242] In addition to significant histological differences between these strains, the selection encompassed over 350 known mutations in genes and proteins involved in key cellular processes including cell division, proliferation, differentiation, mitogenesis, and transcriptional regulation. The list included well-established markers such as BRAF, CREB3L2, CREBBP, ERBB4, ESR1, KRAS, TP53, TP63, TPH1, VEGFC, as well as groups of genes and proteins such as CDK, EIF, MAPK, PIK, and TRIM.

[0243] The screen aimed to determine whether EpigenAU / 11 could induce cell death across a broad range of cancer cell lines while demonstrating specificity for non-cancer cell lines.

[0244] 2.2. In Vitro Cytotoxicity Cell-Based Assay Cells seeded in the appropriate amount of medium indicated on their data sheets were treated with EpigenAU / 11 at two different concentrations, 0.66 mg / ml and 0.22 mg / ml, for 72 hours 24 hours after seeding. Notably, this treatment revealed differential sensitivity to EpigenAU / 11 between cancerous and non-cancerous cells. Quantification of viable cell nuclei demonstrated that within the 72-hour time frame, EpigenAU / 11 consistently induced cell death in all selected cancer cell types while retaining some selectivity for non-cancerous HuDe cells (Figure 2).

[0245] 2.3 In vitro 3D spheroid toxicity In addition to the above findings, several partners have contributed to the development of more complex in vitro models, including 3D spheroids that better mimic the three-dimensional structure of tumors and their microenvironment. In particular, a group from the IRCCS Istituto Ortopedico Rizzoli in Bologna investigated the effect of EpigenAU / 11 on osteosarcoma survival in our study using three tumor spheroid lines derived from different osteosarcoma cell lines: 143B: A highly proliferative and invasive derivative of the osteoblastic osteosarcoma line. SaOS-2: derived from primary osteoblastic osteosarcoma, exhibits osteoblast-like behavior in vitro with low tumorigenicity and invasiveness, and low frequency of metastasis. U-2 OS: Derived from a primary osteoblastic osteosarcoma, this moderately differentiated line is poorly tumorigenic, invasive, and non-metastatic. Additionally, two 3D spheroids derived from the following non-cancerous cell lines were included in the study: MSCs (BM-derived mesenchymal stromal cells): Multipotent stromal cells derived from bone marrow. HuDe (human dermal fibroblasts): Non-cancerous skin fibroblasts.

[0246] The viability of both control and treated cells was assessed 72 hours after the start of treatment by quantifying ATP levels using the CellTiter-Glo® 3D Viability Assay according to the manufacturer's instructions. Results demonstrated clear differential mortality between cancerous and non-cancerous cells. While cancer cells showed significant mortality, healthy cells appeared unaffected and even showed increased ATP levels, indicating their continued vitality.

[0247] Cisplatin (CDDP), used as a control, indiscriminately killed both cancerous and healthy cells (Figure 3).

[0248] This striking contrast suggests that EpigenAU / 11 may offer a more selective treatment option, targeting tumor cells while sparing healthy tissue. The differential effects observed with EpigenAU / 11 highlight its potential as a candidate with a more favorable benefit / risk ratio, especially in complex 3D tumor models.

[0249] Similarly, the Department of Pharmaceutical Sciences at the University of Pavia conducted a viability assay of breast cancer and non-cancerous spheroids, as described by the inventors. Two triple-negative breast cancer lines, MDA-MB-231 and SUM159PT, were tested alongside a non-cancerous mammary epithelial cell line, MCF 10A, derived from fibrocystic breast tissue.

[0250] The effects of EpigenAU / 11 across a range of concentrations were examined using the CellTiter-Glo® 3D Viability Assay according to the manufacturer's instructions. At the 0.22 mg / ml dose, a significant reduction of approximately 50% in cancer cell viability was observed, while non-cancerous cells remained largely unaffected. Higher doses showed a gradual effect on non-cancerous cells, but the effect was much smaller than that seen in tumor cells (Figure 4). This further strengthens the potential of EpigenAU / 11 to selectively impair tumor cells while sparing healthy cells, maintaining a more favorable risk-benefit profile.

[0251] 2.4 Utilizing In Vitro Patient-Derived Organoids to Define the Therapeutic Potential of EpigenAU / 11 in Complex Cancer Models Finally, a team at the Regina Elena National Cancer Institute in Rome conducted a survival experiment, as described by the inventors, to evaluate the effects of EpigenAU / 11 across a variety of patient-derived tumor organoids. These models represent an advanced approach in preclinical testing, providing a highly accurate in vitro platform that closely mimics the in vivo condition of actual patient tumors. By preserving both the genetic and phenotypic diversity of the original tumor, organoids capture essential features such as tumor heterogeneity, the cellular microenvironment, and the complex interactions within tissue architecture. This high fidelity makes organoids particularly valuable for evaluating the therapeutic response of experimental candidates such as EpigenAU / 11.

[0252] This study included organoids from primary bladder, breast, endometrial, epithelial, and head and neck cancer tissues, and measured ATP content as a surrogate for cell viability using the CellTiter-Glo® 3D Viability Assay according to the manufacturer's instructions. EpigenAU / 11 treatment resulted in a substantial reduction in viability across these diverse cancer types, with mortality rates consistently ranging from 40% to 100% depending on tumor type (Figure 5). These findings highlight the broad efficacy and selective cytotoxic potential of EpigenAU / 11, making it a potent antitumor agent capable of inducing significant cell death even in complex cancer models.

[0253] 2.4.1 Use of in vitro patient-derived organoids from patients with complex treatment histories For even more detailed analysis in more complex cases, the team employed the Opera Phenix Plus High-Content Screening System. With its high-resolution confocal imaging, this advanced system enabled precise and quantitative assessment of cellular responses within each organoid. This configuration enhanced the ability to observe real-time morphological changes, specific pathway activation, and detailed cell viability results, making it a powerful tool for capturing the effects of EpigenAU / 11 within complex tumor models.

[0254] Highlighted within the study were two unique clinical cases demonstrating the robust efficacy of EpigenAU / 11 in organoids (generated with patient informed consent) derived from tumors with a high mutational burden. The first involved a gastric cancer organoid model derived from a patient with an extensive treatment history, having received seven different lines of therapy, including multiple chemotherapy agents, monoclonal antibodies, and targeted therapies. This model presented a particularly challenging profile due to its high level of treatment resistance. However, within this model, EpigenAU / 11 demonstrated a remarkably robust response. After the second dose, EpigenAU / 11 induced a significant increase in cell mortality, demonstrating efficacy comparable to only two or three other broad-spectrum drugs tested (Figure 6).

[0255] The second case featured an ovarian-origin peritoneal carcinomatosis organoid model derived from a patient who had previously received two lines of therapy, including an ongoing carboplatin plus gemcitabine regimen. In this model, high-content screening revealed that only the ongoing therapy and EpigenAU / 11 demonstrated significant cytotoxic activity against cancer cells. The remarkable cytotoxicity of EpigenAU / 11 in this resistant model was particularly noteworthy because the therapy induced tumor cell death, while other treatments showed limited impact. This result further highlights the promise of EpigenAU / 11 as a therapeutic option in complex cases where conventional therapy fails to induce a sufficient response (Figure 7).

[0256] EpigenAU / 11 demonstrated robust efficacy across a wide range of cancer types and preclinical models, demonstrating potent cytotoxic effects against tumor cells while sparing non-cancerous cells. The compound demonstrated consistent efficacy in a variety of test environments, from traditional 2D cell cultures to advanced 3D spheroid systems and patient-derived organoids, including those derived from osteosarcoma, breast cancer, bladder cancer, and head and neck cancer. These models are useful for accurately assessing therapeutic potential, as they reflect the complex interactions within the tumor microenvironment in which cancer cells utilize structural and metabolic adaptations to support growth.

[0257] EpigenAU / 11's ability to selectively induce cell death across diverse tumor types highlights its broad spectrum of activity. Each experiment reinforced the discriminatory nature of EpigenAU / 11's mechanism and highlighted its potential in addressing the complex network of factors that maintain tumor cell viability. By specifically targeting cancerous cells while sparing healthy tissue, EpigenAU / 11 exhibits a favorable risk-benefit profile.

[0258] Furthermore, the dose-response study highlights the specificity of EpigenAU / 11 and is consistent with a therapeutic approach that minimizes collateral damage to normal tissues, a key aspect of cancer treatment. This approach supports a model of restoring physiological balance rather than focusing solely on tumor eradication, and emphasizes the need to consider the unique metabolic behavior and complex interactions within the tumor microenvironment. This finding reflects the fact that cancer arises not solely from isolated molecular abnormalities but from a multifaceted interplay influenced by physiological, environmental, and immunological factors.

[0259] 3. Understanding EpigenAU / 11: Early intracellular pH changes, ATP burst, and metabolic adaptation We investigated the cellular effects of EpigenAU / 11 using the DoE2 formulation and identified two key interconnected metabolic events: early acidification of intracellular pH (pHi), corresponding to increased ATP levels. This link between pH and ATP production is consistent with previous findings showing that acidification affects key metabolic pathways, including glycolysis, and cancer cells rely on rapid ATP generation even under hypoxic conditions (Madshus, 1988). Cancer cells are known to naturally exhibit higher levels of intracellular acidification compared to healthy cells, a characteristic that supports their rapid proliferation. This increased acidification is part of metabolic reprogramming that allows cancer cells to prefer glycolysis over oxidative phosphorylation for energy production, regardless of oxygen availability. This preference for glycolysis contributes to an acidic microenvironment, further supporting cancer cell growth and enhancing their resistance to stress.

[0260] This inherent difference in pH between healthy and cancerous cells sets the stage for how they respond differently to external agents, such as EpigenAU / 11, that alter metabolic pathways. By examining the effects of EpigenAU / 11 on intracellular acidification and ATP dynamics, we gain insight into how to exploit these pre-existing vulnerabilities to selectively disrupt cancer cell metabolism.

[0261] 3.1 Intracellular pH acidification as a primary response to EpigenAU / 11 We found that treatment with EpigenAU / 11 induced a significant acidification of intracellular pH across a variety of tumor cell lines. This acidification was measured over 5- and 60-minute intervals at two EpigenAU / 11 concentrations (0.22 mg / ml and 0.66 mg / ml). Both cancerous and healthy cells showed an immediate acidification effect, particularly pronounced at the higher concentration (0.66 mg / ml) as early as 5 minutes after treatment. At lower concentrations or longer exposure (60 minutes), the acidification response varied according to tumor type, reflecting a dose-dependent effect of EpigenAU / 11 on cellular pH.

[0262] For cancer cells, which are already metabolically constrained by their reliance on glycolysis, this additional acidification enhances their metabolic stress. The forced pH shift caused by EpigenAU / 11 treatment further strains the cells' ability to maintain homeostasis, pushing them toward an unsustainable metabolic state. In healthy cells, acidification is also observed after EpigenAU / 11 treatment, but their metabolic systems are inherently more flexible and resilient. Because they possess balanced oxidative and glycolytic capacities, this adaptability allows them to manage fluctuations in pH and energy demand without significant stress. Unlike cancer cells, which are heavily dependent on glycolysis and already operate under metabolic load, healthy cells can effectively compensate for such shifts and maintain stability without adverse consequences, a well-established property of non-transformed cells.

[0263] 3.2 ATP burst as a result of intracellular acidification After the initial acidification caused by EpigenAU / 11, a rapid increase in ATP levels was observed. This ATP burst appears to be a plausible consequence of the shift in intracellular pH and represents an adaptive response to the metabolic stress introduced by EpigenAU / 11. (M Madshus IH. Regulation of intracellular pH in eukaryotic cells. Biochem J. 1988 Feb 15;250(1):1-8. doi:10.1042 / bj2500001. PMID:2965576; PMCID:PMC1148806.)

[0264] In cancer cells, this ATP surge reflects an urgent need for energy as they attempt to stabilize their intracellular environment under acidic conditions. However, due to their heavy reliance on glycolysis, cancer cells struggle to maintain this elevated energy demand, potentially leading to the accumulation of metabolic by-products and increased cellular stress. These metabolic disruptions, such as the accumulation of reactive oxygen species (ROS) and other by-products that may accumulate under acidic conditions, can overwhelm cancer cells, which already have limited metabolic flexibility. This state of heightened metabolic stress may contribute to the observed increase in cell mortality, as cancer cells are unable to adapt to the dual pressures of acidification and increased ATP demand.

[0265] In contrast, healthy cells exhibit a greater ability to adapt to these metabolic changes. With a more balanced oxidative and glycolytic metabolism, healthy cells are better prepared to absorb transient ATP fluctuations and deal with acidification without incurring severe stress. This metabolic flexibility allows healthy cells to manage fluctuations in pH and energy demand without significant stress, supported by balanced oxidative and glycolytic capacities.

[0266] 3.3 Evaluation of the Differential Effects of EpigenAU / 11 and Different Acids on Cell Viability By measuring intracellular pH changes, we sought to elucidate the dynamic responses induced by EpigenAU / 11 treatment and potentially distinguish its effects from those of general acidic treatments. We treated two squamous cell carcinoma lines, FaDu and A431, along with healthy HuDe cells, with the aforementioned concentrations of EpigenAU / 11 for 1 hour. As a control, hydrochloric acid (HCl) was added to the culture medium to ensure that the pH remained stable and did not exceed the buffering capacity of the system.

[0267] Interestingly, the results revealed that only treatment with EpigenAU / 11 resulted in a significant decrease in intracellular pH, while HCl had no observable effect (Figures 8A and 8B). This observation is consistent with the known ability of cells to efficiently pump HCl and prevent it from affecting the intracellular environment. In contrast, EpigenAU / 11 appears to be able to enter and remain intracellularly, resulting in a stable and significant intracellular acidification.

[0268] This finding reinforces the versatility of EpigenAU / 11's actions and highlights its potential to induce selective cytotoxic effects in cancer cells via unique intracellular kinetics not achieved by HCl.

[0269] To further substantiate these findings, ex vivo studies were performed using explanted biopsies from the FaDu and A431 cell lines. These biopsies were generated by injecting cells into immunocompromised mice, thereby creating a more complex, three-dimensional structure that closely mimics the tumor microenvironment. After explantation, the biopsies were treated ex vivo for 72 hours with either EpigenAU / 11 at the maximum tolerated dose (50 mg / ml) established in animal studies (measured pH 5.6) or with hydrochloric acid (HCl) (added to the culture medium to achieve the same pH of 5.6). After the 72-hour treatment period, cell viability was analyzed using flow cytometry.

[0270] Results revealed that EpigenAU / 11 induced approximately 50% cell death in FaDu explants and approximately 25% cell death in A431 explants, while HCl treatment showed no significant signs of cell death (Figure 9). These experiments highlight the unique efficacy of EpigenAU / 11, demonstrating its ability to selectively induce cell death in cancer cells. Importantly, this effect highlights that the mechanism behind EpigenAU / 11's action extends beyond simple acidification, demonstrating its potential to interact with cellular systems in ways that conventional acids cannot achieve.

[0271] Further investigation prompted us to perform HPLC-UV analysis on EpigenAU / 11 samples, which identified two biologically relevant and abundant organic acids: citric acid (5.64%) and lactic acid (4.66%). Other measured acids, including fumaric acid, tartaric acid, propionic acid, shikimic acid, acetic acid, succinic acid, and malic acid, were found to be below the limit of quantification. This finding raised the question of whether citric acid and lactic acid in EpigenAU / 11 could be responsible for the differential cytotoxic effects observed in cancerous cells versus healthy cells. Both acids are known to play important roles in cellular metabolism. Citric acid is essential for the Krebs cycle, and lactic acid is a product of glycolysis. Literature has shown that high concentrations of these acids (beyond those vehicled by EpigenAU / 11 treatment) can result in cytotoxic effects, which prompted us to investigate their potential impact in the context of this invention.

[0272] Therefore, we were particularly interested in determining whether the amounts of citric acid and lactic acid present in the extracts that make up EpigenAU / 11 could be responsible for the selective cytotoxic effect observed in cancerous versus healthy cells and whether they were the main factors contributing to selective cell death. This study aimed to clarify whether the observed effect could be attributed solely to these two organic acids in the formulation, i.e., whether potential APIs could be identified in the formulation.

[0273] To investigate this, in vitro experiments were performed on three cell lines, FaDu, A431, and HuDe, by treating them for 24 hours with either EpigenAU / 11 at a concentration of 0.66 mg / ml or a combination of citric and lactic acid. The amounts of the two acids used in the combination matched the concentrations found in EpigenAU / 11, allowing for a direct comparison between the effects of the complete extract and the isolated acids.

[0274] The results showed that EpigenAU / 11 induced significant cytotoxicity, particularly in cancerous cell lines, while the combination of citric acid and lactic acid at the same concentrations resulted in nearly negligible mortality (Figure 10). For example, in FaDu tumor cells, EpigenAU / 11 caused 87.2% cell death, while the combination of citric acid and lactic acid induced only 11.5% cell death. This clear difference suggests that the selective cytotoxic effect of EpigenAU / 11 was not reproduced by treatment with these two organic acids, and that the effect of EpigenAU / 11 is an emergent characteristic of the natural matrix system. Similar results were obtained with other EpigenAU / 11 DoEs disclosed herein.

[0275] 4. Gene Expression Ex Vivo Studies Gene expression ex vivo studies of EpigenAU / 11 compared to cisplatin demonstrate that the EpigenAU / 11 system regulates global pathological conditions, as opposed to the regulatory effects of typical APIs on one or a few functions. The following data were obtained using EpigenAU / 11 formulation DoE2.

[0276] 4.1 Cytotoxicity of EpigenAU / 11 compared to cisplatin in biopsies Applying methods consistent with those used in the previous section, additional ex vivo studies were conducted to evaluate and compare the efficacy of EpigenAU / 11 and cisplatin against head and neck tumor tissue. To ensure relevance to previous findings, both EpigenAU / 11 and cisplatin were administered at doses reflecting those used in animal models, recreating in vivo conditions as closely as possible within an ex vivo environment. This approach allowed us to evaluate the effects of each compound within realistic tissue structures, providing continuity with previous in vivo findings.

[0277] As shown in Figure 11, the results demonstrate a substantial difference in cell mortality after 72 hours of treatment for explanted biopsies from FaDu explants. Specifically, EpigenAU / 11 induced approximately 50% cell death, a significantly higher mortality rate than that observed with cisplatin, which induced approximately 25% mortality under the same conditions. This suggests that EpigenAU / 11 elicits a faster and more pronounced cellular response, with an earlier onset of cell death compared to cisplatin, potentially involving distinct or additional pathways.

[0278] 4.2 Genome-wide gene expression profiling (computer implementation) To further elucidate the mechanistic differences between EpigenAU / 11 and cisplatin, genome-wide gene expression profiling was performed to capture the relevant cellular responses to each treatment. This analysis aimed to reveal the unique characteristics of each approach and identify potential regions of complementarity (see also Example 11).

[0279] As shown in Figure 12, functional interpretation of the gene expression profiles after 24 hours of treatment reveals considerable overlap between EpigenAU / 11 and cisplatin. Both treatments induce gene expression landscapes consistent with cell cycle arrest and subsequent cell death. This common response suggests that both EpigenAU / 11 and cisplatin effectively disrupt cell division and trigger the apoptotic pathway at 24 hours.

[0280] However, profiling at an early stage, 6 hours after treatment, provides a more detailed and informative view of the differences between the two compounds. As expected, cisplatin treatment primarily induces cell cycle arrest, particularly with enhanced prometaphase pathway activity, and initiates pathways associated with cell damage. This response is typical of cisplatin's mechanism, which involves direct DNA damage leading to cell cycle interruption and cell death (Figures 13A and 13B).

[0281] In contrast, EpigenAU / 11 (Figure 13) elicits a more complex and comprehensive response that targets multiple hallmarks of carcinogenesis. Specifically, EpigenAU / 11 reduces the activity of pathways associated with a pro-proliferative tumor microenvironment, including pathways related to stemness, epithelial-mesenchymal transition, energy metabolism and insulin sensitivity, growth factors, cell damage, mitotic regulation, and inflammation. This broad interaction suggests that EpigenAU / 11 engages cancer cells in a multifaceted way, disrupting a range of pathways essential for maintaining tumor growth and survival.

[0282] The ability of EpigenAU / 11 to modulate these diverse pathways represents a potentially desirable therapeutic approach, as it can interact with cancer cells on multiple fronts. By impairing pathways that cancer cells rely on to support their physiological functions, promote proliferation, and implement compensatory mechanisms for therapeutic evasion, EpigenAU / 11 may offer a more versatile and comprehensive strategy for targeting cancer cells compared to cisplatin.

[0283] 4.3 Study of the Effect of EpigenAU / 11 and Cisplatin Combination in Cytometry-Based Mortality Analysis In addition to the initial cytometry experiments on FaDu, further ex vivo studies were conducted to evaluate the combined effects of EpigenAU / 11 (formulation DoE2) and cisplatin. This experiment aimed to evaluate the impact of administering EpigenAU / 11 and cisplatin in combination, using doses identical to those previously tested in vivo to ensure consistency across experimental models. Specifically, EpigenAU / 11 was applied at the same concentration as in previous studies, and cisplatin was administered at 150 μg / m, consistent with previous in vivo administration.

[0284] As shown in Figure 14, the results were consistent with previous findings: EpigenAU / 11 alone resulted in an approximately 50% decrease in cell viability, while cisplatin alone achieved an approximately 30% decrease. Notably, the combination treatment produced a significantly enhanced effect, resulting in an approximately 74% decrease in cell viability. This substantial increase in efficacy with the combination suggests a synergistic interaction between EpigenAU / 11 and cisplatin, potentially amplifying therapeutic outcomes beyond those achieved by either agent independently. These findings demonstrate the superior efficacy of the combination treatment and suggest a favorable interaction between EpigenAU / 11 and cisplatin that may improve therapeutic outcomes.

[0285] 4.4 Study on the combined effect of EpigenAU / 11 and cisplatin on genome-wide gene expression profiling (Computer implementation) Genome-wide gene expression profiling was performed on biopsies from FaDu after 6 hours of treatment using the same doses as in the flow cytometry-based mortality analysis: 50 mg / ml EpigenAU / 11 (DoE2 formulation) and 150 μg / ml cisplatin (both alone and in combination with EpigenAU / 11), and the same profiling conditions as in 4.2. This analysis aimed to elucidate the differential combined effects of EpigenAU / 11 and cisplatin on various pathways related to cancer progression and cellular responses (Figure 15).

[0286] Expression data revealed that EpigenAU / 11 alone induced substantial downregulation across a wide range of cancer-related pathways. Specifically, pathways such as tumor cell invasion, cell migration, angiogenesis, and cell viability showed significant decreases in activity, demonstrating the ability of EpigenAU / 11 to target processes essential for tumor growth and metastasis. This effect on angiogenesis and cell migration suggests that EpigenAU / 11 may limit both the formation of new blood vessels, which are important for tumor nutrition, and the migratory ability of cancer cells, which is essential for metastasis.

[0287] Similarly, cisplatin showed comparable down-regulatory effects across many of the same pathways, indicating that at this concentration, cisplatin can inhibit important tumor-supportive functions.

[0288] In contrast, combined treatment with EpigenAU / 11 and cisplatin demonstrated significantly enhanced regulation of gene expression regulating various pathways not modulated by EpigenAU / 11 or cisplatin alone. Both combinations resulted in potent downregulation across multiple cancer-related pathways, with effects seen in cell proliferation, cell survival, and immune-related responses. This enhanced regulation demonstrates the synergistic or potentiating effect of EpigenAU / 11 when combined with cisplatin, allowing even local doses of cisplatin to achieve downregulation levels equal to or exceeding those of systemic doses used alone.

[0289] Furthermore, combined treatment with cisplatin and EpigenAU / 11 not only down-regulated pathways involved in cell growth and migration, but also appeared to affect immune system-related pathways, suggesting that this combination may have the potential to create an immunostimulatory environment within the tumor microenvironment, which may promote immune cell recruitment, increase tumor visibility to immune surveillance, and further amplify anti-tumor responses.

[0290] The data also highlighted the broad impact of the combination treatment on cellular stress responses. For example, pathways related to apoptosis, cell cycle arrest, and cellular senescence were highly modulated in the combination group, supporting the hypothesis that EpigenAU / 11 may sensitize tumor cells to cisplatin-induced cytotoxicity, thereby enhancing cell death mechanisms beyond those achieved by either agent alone. This synergistic effect may be due to EpigenAU / 11's ability to prime cancer cells by modulating the tumor microenvironment and weakening cellular defenses, making them more susceptible to the DNA-damaging effects of cisplatin.

[0291] In summary, genome-wide profiling of gene expression sheds light on the potential of EpigenAU / 11 as both a standalone and combination therapy. Its ability to enhance the effects of cisplatin highlights its promise in enhancing therapeutic efficacy. These findings provide compelling support for further investigation of EpigenAU / 11 as a multifaceted therapeutic agent that can affect several hallmark cancer processes and ultimately contribute to more comprehensive and effective cancer treatment strategies.

[0292] 4.5 Cytotoxicity of EpigenAU / 11 compared to cisplatin against A431 cells Following the aforementioned ex vivo studies using FaDu cells, we performed similar experiments using A431 cells to further verify the effects of EpigenAU / 11. Flow cytometry analysis revealed that EpigenAU / 11 (DoE2 formulation) induced approximately 25% cell death, while cisplatin induced approximately 30%. These results suggest that even in this model, EpigenAU / 11 exhibits promising cytotoxic effects comparable to those of cisplatin (Figure 16).

[0293] 4.6 Study on the combined effects of EpigenAU / 11 and cisplatin on genome-wide gene expression profiling of A431 cells (Computer implementation) Genome-wide gene expression profiling was performed as described in the previous paragraph to assess the early effects of EpigenAU / 11 treatment at 2 hours in A431 cells. The EpigenAU / 11 DoE2 formulation was used. Analysis revealed significant modulation in three hallmark cancer pathways:

[0294] Angiogenesis: Results showed a significant downregulation of genes involved in angiogenesis, with expression levels decreasing by up to -3.95, suggesting that EpigenAU / 11 may interfere with the tumor's ability to establish new blood vessels, thereby limiting the supply of nutrients and oxygen essential for tumor growth and survival.

[0295] Inflammatory response: Genes associated with inflammation showed significant upregulation, with some expression levels reaching +3.54. While inflammation can support tumor progression in some contexts, this response can also stimulate an immune-mediated response against tumor cells, potentially aiding in the recognition and destruction of cancer cells.

[0296] Inhibition of cell proliferation and viability: Several genes related to cell proliferation and viability were significantly down-regulated (values ​​as low as -3.78), indicating that EpigenAU / 11 exerted an inhibitory effect on the growth and survival mechanisms of A431 cells. This early suppression of proliferative capacity suggests that EpigenAU / 11 may effectively reduce tumor expansion by directly targeting cellular mechanisms essential for tumor cell vitality.

[0297] These initial findings suggest that EpigenAU / 11 exerts pleiotropic effects on tumor cells, affecting key pathways related to angiogenesis, inflammation, and cell proliferation. By simultaneously regulating these important cancer-related processes, EpigenAU / 11 appears to impair the tumor's ability to sustain its growth and may promote conditions unfavorable for tumor survival (Figure 17).

[0298] All data obtained in Experiment 4 above was confirmed with other EpigenAU / 11 DoE formulations within the claimed range.

[0299] 5. Biochemical and Physical Characterization of EpigenAU / 11 As a reference standard, DoE2 of EpigenAU / 11 was used for the qualitative and quantitative characterization of as many primary and secondary metabolites as possible, which was carried out using an "omic" approach, i.e., targeted metabolomic analysis, based on the use of multiple analytical methods.

[0300] The analytical methods used for characterization are listed in the relevant tables below. The same analytical methods were used for other batches (DoE) of EpigenAU / 11 in subsequent examples. The most appropriate analytical technique was adopted based on the chemical nature of the class of compounds present. Analysis by chromatographic methods combined with different detection techniques (e.g., LC, each coupled with a suitable detector) allowed for the identification and quantification of organic compounds, if necessary. Inductively coupled plasma analysis using a single quadrupole mass spectrometer (ICP-MS) or an optical emission spectrometer (ICP-PAD) allowed for the establishment of the levels of elements present, while anions were determined by ion chromatography and a conductivity detector.

[0301] The following table summarizes all the methods used in Examples 5 and 6. [Table 4]

[0302] 5.1 Targeted metabolomic analysis of DoE2 The analysis was carried out using the methods reported in the table above and the results are summarized in the table below. [Table 5-1] [Table 5-2]

[0303] 5.2 Spectroscopic FTIR characterization (computer implementation) Fourier transform infrared spectroscopy (FTIR) is an analytical technique used to obtain the absorption or emission spectrum of a sample. It is based on the analysis of the interaction between infrared light and a substance. FTIR spectroscopy can be affected by weak interactions between plant matrix components, such as hydrogen bonding, van der Waals forces, dipole-dipole interactions, and hydrophobic interactions. These interactions can alter the position, intensity, and shape of peaks in the spectrum and the absorption characteristics of various functional groups. Therefore, weak interactions within the plant matrix significantly affect the data obtained by FTIR spectroscopy. Therefore, FTIR spectra are characteristic of each material (in this case, the plant biological matrix). FTIR spectroscopy can therefore be considered a descriptive tool for system properties, providing a detailed view of the physicochemical properties of the plant matrix.

[0304] FTIR equipment and setup.

[0305] Alpha spectrometer from BRUKER Optics. The instrument is equipped with a GLOBAR source emitting in the far- and mid-infrared regions, a ROCKSOLID interferometer (Michelson type), a KBr beam splitter, and a RT-DLATGS detector. ·Resolution: 2cm-1 Spectral range: 5000~300cm-1 Background scan: 50 Scans for sample acquisition: 50

[0306] 5.2.1 Sample preparation The EpigenAU / 11 DoE2 sample was transferred to a suitable sample holder for ATR-FTIR analysis of solids and liquids. Approximately 10 mg of sample was deposited and pressed onto the diamond crystal of the ATR support. Before recording measurements, it was ensured that the entire sample holder was properly covered.

[0307] Sample acquisition The samples were measured at least three times to verify the reproducibility of the data, and the replicates were then averaged to obtain a representative spectrum of the sample for characterization.

[0308] The results are reported in FIG.

[0309] 5.3 Isotopic abundance Isotopic abundance analysis is a way of describing matter in terms of atoms.

[0310] This explanation in terms of atoms is important because phenomena such as the geometric isotope effect (GIE) and the kinetic isotope effect (KIE) are related to isotope abundance.

[0311] The geometric isotope effect (GIE) refers to the effect of isotopic substitution on the geometric structure of a molecule, especially in the context of hydrogen bonding.

[0312] This subtle change can result in a change in the overall molecular geometry, affecting both intra- and intermolecular interactions. These structural modifications can affect the physical, chemical, and even biological properties of materials, making GIE a key phenomenon for understanding isotope effects at the molecular level.

[0313] Kinetic isotope effect (KIE) describes the change in the rate of a chemical reaction due to the substitution of one isotope for another in a molecule. This effect occurs because the isotopes have different masses, resulting in variations in bond vibrational energy and reaction activation energy. KIE can be classified as follows: 1. First-order KIE: observed when isotopic substitution occurs directly at the bond broken or formed during the rate-determining step of a reaction. For example, replacing hydrogen with deuterium can significantly slow down the reaction due to the stronger and heavier deuterium bond. 2. Secondary KIE: observed when isotopic substitution occurs at a site adjacent to the reaction center and indirectly affects the reaction rate through changes in molecular geometry or electronic effects.

[0314] Isotope abundance analysis was first performed on DoE2, the reference standard for product EpigenAU / 11.

[0315] Samples were sent to the Istituto San Michele all'Adige (Fondazione Edmund Mach) and tested for stable isotopes as follows. -δ18O: Method PDP 7011:2010 REV.0 (TC-IRMS), units ‰ vs V-SMOW. -δ13C: Method PDP 7009:2017 REV.2 (EA-IRMS), units ‰ vs. V-PDB. -δ15N: Method PDP 7009:2017 REV.2 (EA-IRMS), units ‰ vs V-AIR. -δ34S: Method PDP 7013:2010 REV.0 (EA-IRMS), units ‰ vs V-CDT.

[0316] 14C activity was also tested by Chelab (Tentamus Company). -14C activity: Method ISO-16620-2;2019 (AMS), units % modern carbon (pMC).

[0317] The results were as follows: [Table 6]

[0318] Therefore, isotopic characterization was performed on the reference standard DoE2. Furthermore, the measured values ​​for the C activity of the pMC reference standard correspond to those for material from pure bio-based carbon. There is no evidence of synthetic sources in the analyzed material.

[0319] As described herein, according to method ISO-16620-2;2019 (AMS), a 14C value of approximately 100% indicates the naturalness of the product.

[0320] Therefore, this data alone is sufficient to confirm the naturalness of the product.

[0321] To confirm that the manufacturing process from the starting materials did not alter the properties of the material itself, a study of the isotopic abundance during different steps of the manufacturing process was carried out, and the results are reported below.

[0322] The results are reported in the table below showing the δ ratios of the major isotopes. [Table 7] [Table 8] [Table 9] [Table 10]

[0323] Evaluation of the isotopic abundance of the material along the manufacturing process shows that the manufacturing process does not change the abundance ratios, thus demonstrating the fact that the process preserves the native biophysical properties of the starting material.

[0324] Furthermore, the process of mixing the individual systems to obtain the correct percentages of the final product is efficient and does not alter the isotopic abundances, bringing the final product back in line with expectations.

[0325] 6. Identification of extracellular vesicles and miRNA content in EpigenAU / 11 6.1 miRNA Characterization The analytical methods used for characterization of DoE2 are described above in the relevant tables in Example 5. The same analytical methods were used for other batches (DoEs) of EpigenAU / 11 in subsequent examples.

[0326] NanoSight analysis identified high concentrations of particles within the EpigenAU / 11 sample, specified in the example below, that fit the size range of extracellular vesicles. These particles were primarily 30-120 nm, suggesting the presence of extracellular vesicles within EpigenAU / 11. Leveraging this insight, small RNA sequencing was performed using the sRNAtoolbox framework to examine the RNA content within these vesicle-sized particles.

[0327] Among the identified RNA sequences, reads aligned to mature microRNAs (miRNAs) or their isoforms were found and annotated from the Arabidopsis ( Arabidopsis thaliana ) genome, the best-annotated plant genome to date.

[0328] Qualitative miRNA characterization was also performed on ultracentrifuged samples from each batch (Method E). The results show a high metabolomic complexity, with the presence of miRNAs typical of the organism. [Table 11]

[0329] 6.2 Detection of supramolecular structures in EpigenAU / 11-based natural matrices 6.2.1. Dynamic Light Scattering The method of dynamic light scattering (DLS) is the most common measurement technique for particle size analysis in the nanometer range. DLS measures the hydrodynamic size of particles by the mechanism of light scattering from a laser passing through a solution and analyzes the modulation of the intensity of the scattered light as a function of time. The Brownian motion of particles correlates with their hydrodynamic diameter. Smaller particles diffuse faster than larger ones, and DLS instruments generate a correlation function mathematically related to particle size and its time-dependent light scattering ability.

[0330] DLS has been used to measure the particle size of dispersed colloidal samples, study the stability of formulations, and detect the presence of aggregation or flocculation. This method is also ideal for analyzing the size distribution of already isolated exosomes and microvesicles.

[0331] The analysis was performed by AlfatestLab.

[0332] Sample preparation: Reference standard DoE2 was dispersed in 0.22 μm filtered demineralized water at an arbitrary concentration of 10 mg / ml.

[0333] After dispersion, the sample was vortexed for 2 minutes to ensure complete dispersion.

[0334] Analysis parameters: Measuring cell: Plastic, (DTS0012) Detector: Backscatter 173° (NIBS) Laser wavelength: 633nm Number of measurements: 3 Correlation time: adaptation Measurement position: Automatic Attenuator: Automatic Temperature: 25℃ Temperature equilibration time: 120 seconds Dispersant: Water Dispersant refractive index: 1.33 Dispersant viscosity: 0.8872 cP (water) at 25°C

[0335] The samples were analyzed under three different conditions: -No filtration -After filtering through a 0.45 μm nylon syringe filter -After filtering through a 0.1 μm nylon syringe filter

[0336] The 0.45 μm filtered sample was subjected to 0.1 μm filtration.

[0337] Before each filtration step, the sample dispersion was vortexed for 30 seconds. The filtered dispersion was allowed to stand at room temperature for approximately 15 minutes and then gently stirred manually before analysis.

[0338] result: The average Z-average and PdI results obtained from three replicate measurements are reported in the table below, where Z-average is the intensity-weighted mean diameter and PdI is the polydispersity index. [Table 12]

[0339] Correlogram evaluation (FIGS. 19A and 19B) provides data quality information about DLS results. The graph shows the progression of the correlation function (y-axis) over time (x-axis), which should have a sigmoidal shape. The intercept value on the y-axis relates to the signal-to-noise ratio, i.e., how much of the scattering signal from the sample reaches the detector and is successfully separated from the background noise. The closer the intercept is to 1, the better the signal-to-noise ratio.

[0340] The location of the inflection point in the correlogram (on the x-axis, time) is related to particle size; the longer the decay time of the correlation, the larger the particle size. The slope of this portion of the curve is related to the polydispersity index (PdI), and therefore the variance of the sample size population; the steeper the decay, the less variance in particle size and the lower the PdI value. Finally, the portion of the curve following the inflection point is related to the presence of large particles. In general, the absence of large particles and aggregates is evidenced by the curve tending to zero in this region.

[0341] The results show that aqueous dispersion resulted in the formation of large particles exceeding 1 μm in size. The noisy right side of the correlogram of the unfiltered aqueous dispersion suggests the presence of larger, uncharacterized particles. Filtration resulted in a clear shift in the correlogram and size distribution. In particular, filtration at 0.10 μm shows a monomodal distribution with particles larger than the filtration size. In fact, the constituent substructures of the particles appear to separate during filtration and then reassemble to form the original complex. Thus, the data suggest the presence of supramolecular aggregates consisting of noncovalent intermolecular interactions. The data quality of the filtered sample is good.

[0342] 6.2.2. Detection of exosomes in EpigenAU / 11 DoE2 Ultracentrifugation sample preparation The starting sample (reference standard DoE2) used to prepare the ultracentrifugation product was weighed and resuspended in a constant volume of VIB or vesicle isolation buffer (20 mM MES; 2 mM CaCl2; 100 mM NaCl, pH 6.0), maintaining a ratio of 5 mL of buffer per 500 mg of sample. The sample was incubated at room temperature for 20-24 hours under agitation to facilitate solubilization. After incubation, several centrifugations were performed at 4°C and increasing speeds to isolate particles ranging in size from 30 to 500 nm. Ultracentrifugation was performed using a T-1250 rotor (Thermo Fisher Scientific, 11718-5) and a Thermo Scientific™ Sorvall™ WX+ ultracentrifuge (Thermo Fisher Scientific™ 75000080, No.: 15342177). The sample was centrifuged at 700 x g for 20 minutes. The supernatant was filtered through a 0.45 μm filter, discarding the pellet, and centrifuged at 10,000 × g for 30 minutes. The supernatant was then transferred to an ultracentrifuge tube and centrifuged at 40,000 × g for 70 minutes. The supernatant was transferred to a new ultracentrifuge tube and stored on ice, while the pellet (also referred to as the 40K pellet) was resuspended in VIB and centrifuged again at 40,000 × g for 70 minutes. The pellet was finally resuspended in 600 μL of 25 mM trehalose (Merck, T0167) in PBS and stored at 4°C for use within 24 hours or at 30°C for long-term storage. For some samples, ultracentrifugation was also performed at a higher speed of 100,000 × g. The resulting pellet (also referred to as the 100K pellet) was isolated from the supernatant of the first centrifugation at 40,000 × g and centrifuged again at 100,000 × g for 70 minutes. The supernatant was discarded, and the 100K pellet was resuspended in VIB buffer and centrifuged under the same conditions. The 40K pellet was freshly resuspended in 600 μL of 25 mM trehalose in PBS and stored at 4°C for use within 24 hours, or stored long term at 30°C.

[0343] Extracellular vesicle analysis using DLS: The analysis was performed by AlfatestLab.

[0344] Analysis parameters: Measuring cell: Plastic (ZEN0040) Detector: Backscatter 173° (NIBS) Laser wavelength: 633nm Number of measurements: 3 Correlation time: adaptation Measurement position: Automatic Attenuator: Automatic Temperature: 25℃ Temperature equilibration time: 120 seconds Dispersant: Water Dispersant refractive index: 1.33 Dispersant viscosity: 0.8872 cP (water) at 25°C

[0345] The average results of Z-average and PdI obtained from three replicate measurements are reported in the following table, where Z-average is the intensity-weighted mean diameter and PdI is the polydispersity index (Figures 19C and 19D).

[0346] result: [Table 13]

[0347] Analysis of microvesicle size and concentration by NanoSight The Malvern NanoSight NS300 uses the technique of Nanoparticle Tracking Analysis (NTA). This proprietary technique exploits the properties of both light scattering and Brownian motion to obtain size distribution and concentration measurements of particles in liquid suspension. A laser beam passes through the sample chamber, and suspended particles in the path of this beam scatter light in a way that can be easily visualized with a camera-equipped microscope at 20x magnification.

[0348] The analysis was performed by AlfatestLab.

[0349] Analysis parameters: Dispersant: PBS 1X Equipped with laser: Blu 488nm Camera Level: 16 Syringe pump speed: 50 Number of videos: 5 Video duration: 60 seconds Detection Threshold: 7

[0350] The samples were diluted with 1x PBS (1:50,000), filtered at 200 nm, and then mixed for 20 seconds using a vortex mixer. The samples were then analyzed.

[0351] Analytical results for samples (average of 5 replicates): [Table 14] where: - Concentration (particles / ml) is the sum of the concentrations of all particles detected. - The mean diameter is the average of all diameters found relative to their density. The mode is the value of the main peak where the number of particles is the greatest.

[0352] Thus, the data suggest that there are numerous particles in the 30-120 nm range, which matches the size of extracellular vesicles. The results of the negative control were inadequate for NTA analysis.

[0353] 7. In vivo activity of EpigenAU / 11 formulations The test was carried out using the DoE2 formulation.

[0354] 7.1 In vivo antitumor efficacy of EpigenAU / 11 in the context of squamous cell carcinoma To further evaluate the antitumor efficacy of EpigenAU / 11, studies were transitioned from in vitro models to more complex and biologically relevant systems.

[0355] Animal models offer several advantages, including the ability to assess tumor growth in the organism and evaluate the systemic effects of a compound, which is important for understanding its full therapeutic potential. The athymic (nude) mice used in this study lack an adaptive immune response but provide a suitable platform for examining tumor behavior and treatment efficacy in vivo.

[0356] 7.1.1. Epidermoid carcinoma (A431 cells) In this study, in vivo studies were performed using A431 cells derived from epidermoid carcinoma, a type of squamous cell carcinoma. This carcinoma, which commonly affects the skin, serves as a suitable model for studying squamous cell tumors. While cisplatin is not typically the first-line treatment for A431 epidermoid carcinoma, it is a cornerstone chemotherapeutic agent in the management of other squamous cell carcinomas, such as those seen in head and neck cancer. Cisplatin demonstrated significant cytotoxic effects in previously reported in vitro studies against squamous cell carcinoma lines, including A431 and FaDu cells, which led us to investigate its efficacy in this in vivo model. Understanding the effects of cisplatin and EpigenAU / 11 in animal models should help clarify their broader therapeutic applications, even in tumors not traditionally treated with cisplatin.

[0357] In this study, 1 × 10 6 A431 cells were injected subcutaneously to generate xenograft tumors. 3 Once a measurable volume of 1000 mg / kg was reached, mice were assigned to one of three treatment groups, each designed to evaluate a different therapeutic strategy (Figure 20). - EpigenAU / 11 group: Mice were intratumorally injected with EpigenAU / 11 at a concentration of 50 mg / ml every day. Cisplatin group: Cisplatin was administered intraperitoneally at a dose of 2 mg / kg every two days, following the standard treatment schedule used in squamous cell carcinoma treatment regimens. Although cisplatin is not typically used in epidermoid carcinoma, its potent in vitro efficacy justified examination of its effects in this in vivo model. - Vehicle control group: Mice in this group received injections of physiological solution (vehicle) according to the same schedule used for EpigenAU / 11 and cisplatin to serve as a control group for assessing baseline tumor growth without active treatment.

[0358] The tumor is 0.1 cm 3 All treatments were initiated when tumors reached a volume of 0.01 mm Hg, allowing for consistent tumor size between groups at the start of treatment.

[0359] Responses in mice were assessed using criteria similar to RECIST 1.1 guidelines, including progressive disease (PD), defined as a ≥ 35% increase from baseline tumor size; partial response (PR), showing a ≥ 50% reduction from baseline; and stable disease (SD), reflecting intermediate change from baseline.

[0360] The results, shown in Figure 21, highlight clear differences between treatment groups over the 15-day period. Mice treated with vehicle (saline) consistently showed tumor growth, reaching six times their initial volume by the end of the study, indicating progressive disease (PD). In contrast, mice treated with cisplatin experienced a slowdown in tumor growth, particularly during the second half of the study, leading to a stabilization of tumor burden and classified as stable disease (SD). However, EpigenAU / 11 demonstrated a remarkable partial response (PR) as early as day 3 of treatment, demonstrating a significant reduction in tumor size. By day 15, tumors in EpigenAU / 11-treated mice had slightly regrown but returned to baseline size, indicating a durable partial response.

[0361] These results highlight the anti-tumor efficacy of EpigenAU / 11 in this in vivo model, confirming its ability to significantly reduce tumor size within a short period of time. The visual representation of treated tumors in Figure 22 further reinforces this, clearly showing the differences in tumor growth between treatment groups.

[0362] At the end of the 15-day period, tumors were excised and weighed to confirm the observed effects. The mean tumor burden in the vehicle-treated group was approximately 626 mg across six mice. In the cisplatin-treated group, the mean tumor burden was significantly lower at 368 mg. Notably, the EpigenAU / 11-treated group had the smallest mean tumor burden at only 169 mg, confirming the tumor volume reduction observed during the study. The following table shows the mean weight (mg) of tumor masses extracted from athymic mice at the end of the 15-day treatment period. The table includes mean tumor weights for the vehicle control, cisplatin, and EpigenAU / 11-treated groups, demonstrating the difference in tumor burden across the various treatment groups. [Table 15]

[0363] Additionally, the weight of the mice was monitored throughout the treatment period. Vehicle-treated mice showed a slight increase in body weight of 2.5%, while EpigenAU / 11-treated mice showed a similar increase in body weight of 2.2%, indicating that EpigenAU / 11 did not adversely affect the overall health of the animals. In stark contrast, cisplatin-treated mice experienced a substantial 10.3% loss in body weight over the 15-day period, reflecting the known systemic toxicity and side effects of cisplatin treatment.

[0364] The table below shows the average weight (in grams) of athymic mice at the end of the 15-day treatment period for each experimental group: vehicle control, cisplatin, and EpigenAU / 11. [Table 16]

[0365] 7.1.2 Head and neck cancer (FaDu cells) Following studies with A431 cells, the focus shifted to FaDu cells derived from head and neck squamous cell carcinoma (HNSCC). HNSCC represents a diverse group of malignant tumors arising on mucosal surfaces of the head and neck region, including the oral cavity, pharynx, and larynx. These tumors are notably aggressive and are often associated with poor prognosis, making effective treatment strategies essential.

[0366] Cisplatin is considered the gold standard chemotherapy agent for treating HNSCC and is frequently utilized in both neoadjuvant and adjuvant settings. Its mechanism of action primarily involves the formation of DNA crosslinks, which inhibit DNA replication and ultimately trigger apoptosis in rapidly dividing tumor cells. Despite its efficacy, the effectiveness of cisplatin can be limited by various factors, including the development of resistance and significant side effects, necessitating the exploration of combination therapies that may improve its therapeutic outcomes.

[0367] In light of the encouraging results observed in vitro, in which no interference was detected between EpigenAU / 11 and conventional chemotherapy agents, this study aimed to investigate whether EpigenAU / 11 could enhance the efficacy of cisplatin in an in vivo setting. Given the critical need for improved treatment strategies in HNSCC, understanding the potential interactions between EpigenAU / 11 and cisplatin may provide new avenues for enhancing therapeutic efficacy while minimizing adverse effects.

[0368] In this study, an in vivo study utilizing FaDu cells was performed to investigate this interaction. Different dosing schedules were used for each treatment, resulting in four specific treatment groups (Figure 23). - EpigenAU / 11 group: Mice received daily treatment with EpigenAU / 11 at a concentration of 50 mg / ml, incorporating intratumoral administration. - Cisplatin group: Cisplatin was administered intraperitoneally at a dose of 2 mg / kg every 2 days according to standard treatment protocols. - Combination group: Mice in this group underwent a combined treatment approach in which they received both daily EpigenAU / 11 (intratumoral) and cisplatin (intraperitoneal) every 2 days. - Vehicle control group: This group of animals served as vehicle control and received physiological solution according to the same schedule used for cisplatin and EpigenAU / 11.

[0369] The tumor is 0.1 cm 3 All treatments were initiated when a volume of 100 mg / kg was reached.

[0370] Responses in mice were assessed using criteria similar to RECIST 1.1 guidelines. The study was extended to 27 days to evaluate the long-term effects of EpigenAU / 11, cisplatin, and their combination over a longer treatment period (FIG. 24). In the vehicle control group, tumors showed rapid growth, reaching approximately 1 cm within just a few days. 3 and mice had to be sacrificed on day 19. In contrast, consistent with established reports, cisplatin treatment significantly delayed tumor progression and ultimately led to disease stabilization.

[0371] Both the EpigenAU / 11 monotherapy group and the combination therapy group showed partial tumor regression (PR). A significant difference between these two groups emerged around day 23, with tumor regrowth observed in the EpigenAU / 11 group but not in the combination group.

[0372] The visual representation of the treated tumors in Figure 25 reinforces this, clearly showing the differences in tumor growth between the treatment groups.

[0373] Animals were sacrificed on day 27 and tumor masses were excised and weighed to further confirm the observed effects.

[0374] In the vehicle-treated group, the average tumor burden was approximately 1307 mg across five mice. The cisplatin-treated group showed significantly smaller tumor burdens, averaging 454 mg. The EpigenAU / 11-treated group had an average tumor burden of only 210 mg, with only four of the five mice having detectable tumor burdens, confirming the tumor volume reduction observed during the study. Interestingly, in the combination therapy group, only two of the five mice had residual tumors at the end of the study, with an average tumor burden of only 62 mg, highlighting the significant efficacy of the combination treatment in nearly eliminating tumor presence.

[0375] The following table reports data on explanted tumor masses after 27 days of treatment (19 days vehicle). Mean tumor weight (mg) for each treatment group is shown. [Table 17]

[0376] Additionally, throughout the treatment period, mouse weight was closely monitored as an indicator of overall health and treatment-related toxicity. Mice treated with the vehicle control showed a modest weight gain of 7.7%, while mice treated with EpigenAU / 11 showed a comparable weight gain of 7.1%, indicating that EpigenAU / 11 did not induce significant systemic toxicity. However, cisplatin-treated mice and mice receiving combination therapy experienced significant weight loss, showing decreases of -22.8% and 20.8%, respectively, over 27 days, reflecting the well-known systemic toxicity of cisplatin. The following table summarizes the percentage change in mouse weight in each treatment group from the beginning to the end of the study. [Table 18]

[0377] Additionally, to better understand the potential systemic toxicity of treatment, an Irwin test was performed to assess a range of physiological and behavioral parameters, including general behavior, CNS excitation, motor coordination, muscle tone, reflex responses, and autonomic signs. Results revealed that mice treated with cisplatin or the combination of cisplatin and EpigenAU / 11 exhibited a significant 30-40% reduction in overall biological function, including decreased activity, impaired reflexes, and altered muscle tone. These reductions are consistent with known side effects of cisplatin, including neurotoxicity and general systemic stress.

[0378] In contrast, mice treated with EpigenAU / 11 alone did not show any significant changes in these parameters and maintained normal behavioral and physiological function throughout the study. This difference highlights the favorable safety profile of EpigenAU / 11 and its potential to provide therapeutic efficacy without the severe side effects typically associated with conventional chemotherapy agents such as cisplatin. The table below shows the results of the Irwin study and highlights differences in key physiological and behavioral parameters between treatment groups at the end of the study. Parameters evaluated included general behavior, central nervous system (CNS) arousal, motor coordination, muscle tone, reflex responses, and autonomic signs. [Table 19]

[0379] Preliminary analysis of resected tumors is currently underway. However, initial hematoxylin and eosin (H&E) staining data revealed significant differences in mitotic activity across treatment groups. Specifically, the number of mitoses (2.37 mm at 10x magnification) was significantly higher than the control group (2.47 mm at 10x magnification). 2The number of tumors (measured per 1000 cells / ml) was significantly reduced in the cisplatin group (14) and the combination group (20) compared to the vehicle control group (28). Interestingly, the EpigenAU / 11-treated group showed an increased number of mitoses (34), suggesting that although EpigenAU / 11 was effective in reducing tumor burden, its mechanism of action may not be directly related to a reduction in mitotic activity as seen with cisplatin. The ability of the combination treatment to reduce mitotic activity while maintaining a strong tumor control point for the complex interaction between EpigenAU / 11 and cisplatin likely involves complementary mechanisms that require further investigation. The table below shows the results of hematoxylin and eosin (H&E) staining analysis showing the number of mitoses in tumor sections from the vehicle, cisplatin, EpigenAU / 11, and combination-treated groups. Mitotic figures were measured at 10x magnification and 2.37 mm 2 The area was counted. [Table 20]

[0380] 8. Biodegradability test according to OECD 301F:1992 Biodegradation is the process by which organic materials are broken down by microorganisms into their simplest naturally occurring components (e.g., CO2, H2O, and NH3) that can be integrated into natural biogeochemical cycles.

[0381] Evaluating the biodegradability of chemicals is one of the major challenges in environmental risk assessment. Biodegradation tests are designed to evaluate chemicals as the sole carbon source for the survival of microfauna under batch conditions. Ready biodegradation tests (RBTs) are the basis of an integrated testing strategy for the biodegradation of pure substances. These are a series of tests (Nos. 301A-301F and 310) proposed by the Organization for Economic Cooperation and Development (OECD). Microorganisms and test substances are typically incubated in a buffered pH 7 medium (called "mineral medium") containing N, P, and trace elements. Biodegradation kinetics are monitored for at least 28 days by assessing metabolic parameters such as oxygen consumption, carbon dioxide production, or dissolved organic carbon consumption. RBTs measure ultimate or complete biodegradation; a chemical can be classified as readily biodegradable if it passes one of the RBTs.

[0382] The term primary biodegradation refers to the structural modification of a substance caused by biological events, resulting in the loss of certain properties of that substance, which can be calculated from complementary chemical analyses of the parent compound performed at the beginning and end of the test (OECD 301, 310). Test item EpigenAU / 11 was analyzed for evaluation in aqueous media of aerobic biodegradability according to the screening method described in OECD 301 F:1992.

[0383] The method is based on the determination of oxygen consumption by a stirred solution or suspension of the test chemical in a mineral medium inoculated with non-adapted microorganisms; measurements are carried out automatically over 28 days in a respirometer placed in a closed environment, in the dark, and at a controlled temperature of 22 ± 2 °C, allowing the evolved carbon dioxide to be adsorbed onto potassium hydroxide. Biodegradability is expressed as the percentage of oxygen consumed (corrected by blank consumption) relative to the theoretical uptake (ThOD) or COD (if the former determination is not possible). The percentage of primary biodegradability is also calculated by additional specific chemical analyses performed at the beginning and end of the test.

[0384] Reagents and Materials The method involves working with the following reagents and materials: A) Test substance reference standard EpigenAU / 11 DoE2, diluted 50 mg / l in mineral medium; B) Mineral medium for solubilization of the test substances, consisting of the following four solutions (A, B, C and D) made up to 1 liter with ultrapure water: 10 ml of solution A: 8.50 g KH2PO4 + 21.75 g K2HPO4 + 33.40 g Na2HPO4 dihydrate + 0.50 g NH4Cl, made up to 1 liter with ultrapure water, final pH 7.4; - 1 ml of solution B: 27.50 g of anhydrous CaCl2 made up to 1 liter with ultrapure water, - 1 ml of solution C: 22.50 g of MgSO4 heptahydrate made up to 1 liter with ultrapure water, - 1 ml of solution D: 0.25 g of FeCl3 hexahydrate made up to 1 liter with ultrapure water. C) Bacterial inoculum: obtained by adding the test substance to an appropriate inoculum and taking equal aliquots of activated sludge. D) Chemical standards for BOD determinations from 5 to 28 days consisting of solutions of various analytical purities of anhydrous sodium acetate.

[0385] Assay run Sample preparation Samples were processed according to the procedure reported in Respirometric Method No. 301F (OECD). The BOD sensor and sufficient material to perform the planned instrumental analysis were used to ensure proper alignment. Sodium acetate was used as the reference material. The test was performed at a constant temperature of 22°C.

[0386] Inoculum preparation The inoculum was prepared by mixing equal amounts of nine activated sludge samples from different locations. The inoculum was oxygenated, stirred, and fed with glucose, peptone, and dipotassium phosphate. The redox potential, oxygen consumption, and total dry matter values ​​were monitored daily. Dry matter was determined at 100°C, and an equal amount (30 mg / mL) of the test substance was measured in a container.

[0387] Inoculum composition The inoculum was obtained by mixing equal parts activated sludge from eight different sectors with river water collected from two different rivers. The aggregated inoculum was oxygenated, agitated, and fed with glucose, peptone, and monopotassium orthophosphate. Oxygen, redox, and total suspended solids were monitored daily. Before using the inoculum, the total dry matter was determined.

[0388] The composition of the microfauna was determined by light microscopic analysis.

[0389] reference material Manometric respirometry also requires the performance of separate tests using ultrapure water enriched with a standard (sodium acetate) to assess proper performance and reliability of the equipment.

[0390] blank A blank analysis was performed on the inoculated mineral medium to assess the contribution of the liquid and inoculum to the BOD value of the final product.

[0391] Assay conditions: The containers are placed in a thermostatic refrigerator set at 22±2°C and kept under constant agitation by the mechanical movement of the anchors. All this is done for 28 days by automatically and wirelessly measuring the oxygen drop value every 6 hours, which becomes the absolute biodegradability value of the sample under study at 28 days.

[0392] Test results EpigenAU / 11: [Table 21]

[0393] Values ​​in bold are considered anomalous and were therefore excluded from the calculations used to assess the ready biodegradability of the products.

[0394] blank: [Table 22]

[0395] This test showed that the BOD contribution between the inoculum and the mineral medium was 10.1 mg / l, which is the value that should be used for the BOD correction of the 50 mg / l mixture of EpigenAU / 11 product.

[0396] The mean values ​​are within the positive range of the test, which is between 10 and 50 mg / l.

[0397] Reference substance: [Table 23]

[0398] The positive test was based on the following evidence: A) The chemical control was positive because the value obtained for the chemical standard (32.5 ppm biochemical oxygen demand, BOD) was within the positive range of the test, which is the theoretical demand for oxygen (ThOD) of 31 ± 5 ppm. B) After just 7 days, the BOD value is 78.77% of the total. C) After 14 gg, the BOD value will be 88.31% of the total.

[0399] Biodegradation calculations are performed for each sampling time of the reference material, test sample and blank.

[0400] The total biodegradability of the samples was calculated using the following formula: BOD: (average mg / L of O2 consumed of test material) - (average mg / L of O2 consumed of blank) / mg / L of test material in container.

[0401] There is no evidence of nitrite and nitrate production based on the fact that no correction for nitrification / denitrification was performed. -mg / l of O2 consumed by the test substance: 59.5mg / L. -mg / l of O2 consumed by blank: 10.1mg / L. -mg / l of O2 consumed by nitrification in the product: / - mg / L of test chemical in container: 50mg / L Calculated average BOD = 0.988 mg O2 per mg of test material.

[0402] To calculate the percentage of degradation and therefore the ready biodegradability, the chemical oxygen demand (COD) was evaluated by thermal oxidation with dichromate in ultrapure deionized water. Tests were performed with a 50 mg / L EpigenAU / 11 solution, resulting in a COD of 67.1 mg / L. COD = (mg / L of O consumed by test material) / (mg / L of test material in the container) COD = 1.342 mg O2 per mg of test material.

[0403] Average percentage degradation on day 28: Blank estimated / COD net corrected BOD average = (0.988 / 1.342) * 100 = 73.6%

[0404] Interpretation of results Validity Criteria A test is considered valid if: - the average biodegradation rate of the reference substance is greater than 60% after 14 days of incubation, - The difference between extreme replicate values ​​at the end of the study plateau is less than 20%. - Blank oxygen demand is 60 mg O2 / L or less.

[0405] interpretation A substance is considered to be readily biodegradable if the level of biodegradation reached within 10 days after the onset of degradation (which is considered the period in which 10% of the substance has degraded (10-day timeframe)) is greater than 60% and if the level of biodegradation reached at 28 days is >60%.

[0406] result - Study validity criteria were met. The assessment of the biodegradability of the substance EpigenAU / 11 blend at a concentration of 50 mg / l showed that during the experiments carried out, the product showed ready biodegradability under the conditions applied in the manometric respiration test developed in accordance with EC Regulation 440 / 2008 - Part c: Methods for determining ecotoxicity - Method c.4. Part v - (Method c.4-d) + OECD 301F:1992, as updated in reg. 640 / 2012. In fact, the product exceeded 60% biodegradability within 10 days after reaching 10%, thus fulfilling the criterion for the validity of the method. The product EpigenAU / 11 at a concentration of -50 mg / L showed no toxic effect on the activity of microorganisms at the tested concentrations, reaching 73.6% of the relevant theoretical COD value, thus indicating a well-present biological activity. At the end of the test, approximately 3.30 mg / L of total suspended solids were found, which demonstrated a reduction in active substances (bacteria) compared to the 30 mg / L inoculated. This biomass was completely depleted and lacked the viable forms found at the start of the test, a condition typical of end-of-life muds due to nutrient deficiency.

[0407] Based on the results obtained, interpreted according to OECD 301F:1992, the test article product EpigenAU / 11 was readily biodegradable under aerobic conditions.

[0408] 9. Functional Reproducibility and Comparison of Different Batches of EpigenAU / 11 (DoE) In PCT / IB2024 / 054526, the applicant discloses a method for the quality control and validation of therapeutic or beneficial products comprising natural matrices. Since such products have a therapeutic effect not attributable to a specific API and their qualitative and quantitative composition varies due to the variability of the plant raw materials from which they are derived, the applicant has a novel quality control and validation process based on the biological activity of the tested product (biological activity analyzed in a cell-based assay related to the therapeutic or beneficial effect of the product under consideration and modifications induced by the validated product batch compared to the activity of a reference batch of the product), as well as the spectroscopic spectra of the reference product and other matched batches for the determination of acceptable spectroscopic values ​​to be used in subsequent validation.

[0409] This method has been proven to be reliable and is used in this application to compare different batches of EpigenAU / 11 (DoE) for quality control and comparative analysis of the DoE.

[0410] The following example demonstrates that despite the botanical origin and qualitative and quantitative variability between batches of different DoEs of EpigenAU / 11, the product undergoes reliable quality control and can support the claimed formulation range. The data provided also demonstrates that the product needs to be treated as "active units" rather than as a precisely defined sum of API.

[0411] Figure 26 shows a graph reporting cell counts of tumor cell lines treated with 0.66 mg / ml EpigenAU / 11 for 24 hours (see Example 1 for protocol), testing different batches of EpigenAU / 11 (DoE 1, 2, 3, and 4.2). The graph clearly shows that the results of the cell-based assay testing cytotoxicity are fully superimposable for the four quality-validated batches.

[0412] 9.1 Description of EpigenAU / 11 DoE Biological activity and chemical characterization studies are being extended to three additional formulations of EpigenAU / 11.

[0413] To define the four formulations with the correct plant-to-system ratio, each was identified using the term DoE (Design of Experiment). Furthermore, to achieve one of the objectives of the present invention, formulation permutations of each DoE were also generated. In all these formulations, the Agave content (0.89%) and its production batch remained unchanged.

[0414] A summary table is provided below. [Table 24] [Table 25]

[0415] The plant line codes are provided solely to indicate that different lots of plant lines 1 and 2 were used (obtained from different batches of starting material using the same preparation protocol shown in Example 1), and that the different lots were used in different combinations to prepare DoEs 1-4 and their associated permutations.

[0416] 9.2 Targeted metabolomics and miRNA-seq for DoE1, 2, 3, 4, and 4.2 In order to understand whether the final matrix constituting Product A is characterized by matrix effects, a series of analyses were carried out on the batch reported above to characterize the product in different aspects. A targeted metabolomic analysis, which allows the identification of most of such molecular components, was carried out on different batches of the product, together with the other analyses reported herein.

[0417] As described above, the product consists of two separate arrays of plant co-extracts and one extract that are assembled at a given percentage to give a new final plant matrix. Several analytical techniques were used to identify and quantify compounds belonging to the major classes present in the plant.

[0418] Metabolomic analysis does not allow one to understand the dynamic changes within the components of a matrix, but allows a "portrayal" of the composition at the moment the analysis is carried out.

[0419] In the following analysis, individual components (plant metabolites) are specifically studied, hence the term "targeted metabolomics." This analysis allows capturing a frame on qualitative data by determining the chemical compounds present in the material, and quantitative data by defining the concentration of each compound in the material.

[0420] For DoEs 1, 2, 3, 4 and 4.2, a qualitative and quantitative characterization of as many primary and secondary metabolites as possible was performed using an "omic" approach, i.e., targeted metabolomic analysis, based on the use of multiple analytical methods.

[0421] Figure 27 shows the results of targeted metabolomics with reference to the main chemical classes (phenols, tannins, organic acids, sugars and their derivatives, inorganic compounds) of five batches of EpigenAU / 11, DoE1, 2, 3, 4 and 4.2. The figure clearly shows that each tested batch differs from each other and from the reference standard EpigenAU / 11_DoE2 in their qualitative and quantitative composition.

[0422] The analytical methods used for the chemical characterization of each batch were the same as those reported in Example 6. Based on the chemical nature of the class of compounds present, the most appropriate analytical technique was adopted. Analysis by chromatographic methods combined with different detection techniques (e.g., LC, each coupled with a suitable detector) allowed the identification and quantification of organic compounds, if necessary. Inductively coupled plasma analysis using a single quadrupole mass spectrometer (ICP-MS) or an optical emission spectrometer (ICP-PAD) allowed the levels of elements present to be established, while anions were determined by ion chromatography and a conductivity detector.

[0423] The results summarized in the table below show considerable compositional variability for each batch and highlight the impossibility of reproducing the properties of a matrix as the sum of its single components. The studies performed and reported herein (see cell-based assay results), together with the following data, demonstrate that the biological effects induced by a product cannot be reproduced by the sum of the effects induced by single molecular components, but are the result of interconnections and interactions between components: matrix effects. This leads to the impossibility of formally defining a structure-activity relationship (SAR) according to the principles standardly applied to APIs. [Table 26-1] [Table 26-2] [Table 26-3] [Table 26-4]

[0424] In addition, qualitative miRNA characterization was also performed on ultracentrifuged samples from each batch (Method E), and the results indicate a high metabolomic complexity, with the presence of miRNAs typical of the organism. [Table 27]

[0425] The results indicate that there are more or less significant quantitative variations in individual chemicals and qualitative variations in miRNA classes across the five batches of EpigenAU / 11. If these variations were considered as reference parameters, they would lead to a priori predictions that these batches would have different therapeutic effects. The analysis reported here demonstrates that, although biological activity was maintained across all the different batches evaluated, none of the identified molecular components adhered to the criteria set for a single API, thus demonstrating that the matrix cannot be considered a collection of APIs.

[0426] The product is capable of eliciting the same response in a biological system that is associated with its intended use, through a physiological mechanism of action.

[0427] This also highlights the fact that there are both structurally and functionally redundant mechanisms of functional consistency typical of living organisms (reaching the same result despite individual differences between individuals of the same species) that are maintained in products containing or consisting of natural matrices.

[0428] 9.3 Isotopic Abundances of DoE1, 2, 3, 4, and 4.2 To assess the isotope ratio between different batches of EpigenAU / 11 product, analyses were performed on batches prepared from different starting materials.

[0429] Samples were sent to the Istituto San Michele all'Adige (Fondazione Edmund Mach) and tested for stable isotopes as follows. -δ18O: Method PDP 7011:2010 REV.0 (TC-IRMS), units ‰ vs V-SMOW. -δ13C: Method PDP 7009:2017 REV.2 (EA-IRMS), units ‰ vs. V-PDB. -δ15N: Method PDP 7009:2017 REV.2 (EA-IRMS), units ‰ vs V-AIR. -δ34S: Method PDP 7013:2010 REV.0 (EA-IRMS), units ‰ vs V-CDT.

[0430] The results were as follows:

[0431] δ ratio of major isotopes in EpigenAU / 11 batch: [Table 28]

[0432] For these formulations, the gold standard 14C activity also provided no evidence of synthetic sources in the analyzed materials. The values ​​δ18O, δ15N, δ34S, and δ13C overlapped between batches, indicating that they were not affected by processing but only by the biological variability of the starting material, thus confirming the high reproducibility of the manufacturing process due to the preservation of this parameter. Analysis of the batches under study showed substantial similarity of values ​​and maintenance of ratios during the manufacturing process (see also Example 6 for reference).

[0433] 10. Definition of "activity units" for different batches of EpigenAU / 11 All assays performed on various EpigenAU / 11 formulations and DoEs demonstrated that the product's inherent qualitative and quantitative variable composition still resulted in essentially maintained biological activity.

[0434] Results obtained in cell viability assays on HuDe, FaDu and A431 cells (as in Example 2) show that all DoEs and permutations within the claimed scope described in Example 9.1, when treated at 0.66 mg / ml for 24 hours, maintain the relevant cytotoxicity against tumor cells and selectivity in protecting healthy cells.

[0435] In detail, the following protocol was used:

[0436] Cell culture and treatments Human healthy dermal fibroblasts (HuDe, IZSLER Brescia) and two cancer cell lines: human pharyngeal squamous cell carcinoma (FaDu, catalog no. HTB-43, ATCC) and epidermoid carcinoma (A431, catalog no. CRL-1555, ATCC) were maintained in a humidified incubator at 37°C under an atmosphere enriched with 5% CO. HuDe cells were expanded in minimal essential medium (MEM, catalog no. 11095080, Gibco) containing 10% inactivated fetal bovine serum (FBS, catalog no. 10270106, Gibco), streptomycin (100 μg / mL), and penicillin (100 U / mL) (catalog no. 15140122, Life Technologies), and sodium pyruvate (1 mM, catalog no. 11360039, Gibco). FaDu was amplified in Eagle's minimum essential medium (EMEM, catalog number: 30-2003 ATCC) containing 10% inactivated FBS, streptomycin (100 μg / mL), and penicillin (100 U / mL). A431 was amplified in Dulbecco's modified Eagle's medium (DMEM, catalog number: 31966-021, Gibco) containing 10% inactivated FBS, streptomycin (100 μg / mL), and penicillin (100 U / mL). Cells were cultured according to the supplier's specifications, enzymatically detached from the growth support, and counted using an electronic cell counter (Invitrogen).

[0437] In vitro assays were performed in 96-well plates with a final volume of 200 μL per well. The table below summarizes each cell line, the respective culture medium, and the number of cells seeded per well in the plate (table below). The seeding and treatment steps were performed using the robot Assist Plus, Integra. [Table 29]

[0438] Nuclear staining, cell viability assay To determine the number of adherent cells, we used NuclearMask-Red (H10326, Life Technologies) staining. This fluorescent dye specifically binds to nucleic acids, allowing for accurate cell counting. The day before the experiment, the three cell lines were seeded into black 96-multiwell plates with clear bottoms (catalog number: 732-3737, VWR) in a final volume of 190 μL per well. Twenty-four hours after seeding, EpigenAU / 11 was solubilized as described in the previous section in complete EMEM medium at a 20-fold concentration compared to the final concentration of 0.66 mg / mL. 10 μL of treatment was dispensed onto the cells using the Assist Plus robot in a final volume of 200 μL. After 24 hours of exposure, the treatment was removed, and the cells were stained with NuclearMask according to the manufacturer's instructions. Fluorescence intensity, corresponding to cell number, was measured using a Varioskan™ LUX multimode microplate reader. 1. Cell culture conditions: Human healthy dermal fibroblasts (HuDe) and two cancer cell lines (FaDu and A431) were cultured according to the specified protocol, which includes the following: * HuDe cells: MEM medium containing 10% FBS, 1% penicillin / streptomycin, and 1% sodium pyruvate, seeded at 7,000 cells / well. * FaDu cells: EMEM medium containing 10% FBS and 1% penicillin / streptomycin, seeded at 12,500 cells / well. * A431 cells: DMEM medium containing 10% FBS and 1% penicillin / streptomycin, seeded at 8,500 cells / well. 2. Experimental Setup: o Cells were cultured in a humidified incubator at 37°C with 5% CO2. o The seeding and treatment steps were performed using an Assist Plus robot (Integra Bioscience) to ensure precision. 3. Treatment with EpigenAU / 11 (DoE2): o EpigenAU / 11 should be solubilized as described and added to cells at a 20x concentration to reach a final concentration of 0.66 mg / mL in a total volume of 200 μL / well. o Cells were exposed to treatment for 24 hours. 4. Assessment of Cell Viability: o Nuclear staining with NuclearMask-Red was performed according to the manufacturer's instructions. o Fluorescence intensity, which indicates cell viability, should be measured using a Varioskan™ LUX multimode microplate reader MET.

[0439] Emission / excitation: 622nm / 645nm Overall, the cell-based assay results show that when administered separately at 0.66 mg / ml to HuDe, FaDu and A431 cells in culture, all DoEs induce the following 24 hours after administration: HuDe healthy cell mortality ≤61%; FaDu tumor cell mortality ≥ 71%; A431 tumor cell mortality ≥ 55%; In cell cultures in 96-well plates in a 200 μl format.

[0440] Figure 28 (Panels A-D) specifically shows that when administered separately at 0.66 mg / ml to HuDe, FaDu, and A431 cells in culture, the same treatment with DoE1, 1.1, 1.2, 1.3, 2, 2.1, 2.2, 2.3, 3, 3.1, 3.2, 3.3, 4, 4.1, 4.2, and 4.3 induces the following 24 hours after administration: HuDe healthy cell mortality ≤61%; FaDu tumor cell mortality ≥ 71%; A431 tumor cell mortality ≥ 65%; In cell cultures in 96-well plates in a 200 μl format.

[0441] According to the data provided in the above experiments, EpigenAU / 11 can be confirmed to act via a physiological mechanism of action, as it alters a state rather than one or a few functions in cell-based assays, demonstrating strong therapeutic functional consistency, as shown in Figure 28.

[0442] Furthermore, the analyses reported above also demonstrate that the product is not only composed of a natural matrix, but is itself a matrix, 100% natural, readily biodegradable, and contains miRNA and exosomes.

[0443] For therapeutic products, it is essential to define an activity unit, which, as explained in the glossary, is a standardized measure of the potency or effectiveness of a therapeutic product that defines the amount of therapeutic product required to produce a specific desired therapeutic effect or to achieve a specific biological response in a given system.

[0444] To define the activity unit of EpigenAU / 11, since a desirable feature in anti-cancer treatment is the preservation of healthy cell viability together with strong cytotoxicity against tumor cells, a preferred cut-off of desired activity in terms of the balance of healthy and tumor cell cytotoxicity exerted by the product was defined based on all studies performed on the DoE2 reference product, and one activity unit was defined as the following: 24 hours after separate administration to HuDe, FaDu and A431 cells in cell culture plates: HuDe healthy cell mortality rate: 40-50% FaDu tumor cell mortality ≥ 90%; A431 tumor cell mortality rate ≥ 65% is defined as the necessary and sufficient amount of EpigenAU / 11 that can induce HuDe cells are seeded at approximately 7,000 cells / well in 200 μl of appropriate medium, FaDu cells are seeded at approximately 12,500 cells / well in 200 μl of appropriate medium, and A431 cells are seeded at approximately 8,500 cells / well in 200 μl of appropriate culture medium, and the cells are treated with the products and then cultured for 24 hours, and cell mortality is measured by assessing cell viability by nuclear staining.

[0445] More specifically, the plates are 96-well culture plates and the conditions are as detailed above.

[0446] For EpigenAU / 11 DoE2, 1UoA is 0.132 mg.

[0447] Thus, for various lots of EpigenAU / 11, the UoA defined above can be achieved either by varying the amount of product until the desired mortality rate is achieved, or alternatively, as shown herein, by modifying the formulation within the claimed range until the desired UoA is achieved with an amount of product similar to the amount in DoE2 above, or both.

[0448] Therefore, the defined UoA is the amount of product that is necessary and sufficient to obtain a significant reduction in tumor cell vitality while maintaining the vitality of healthy cells within a physiologically acceptable range, and is being developed.

[0449] The UoA (units of activity) defined herein can be readily used by those skilled in the art to make batch-to-batch determinations for different EpigenAU / 11 batches to ensure that each EpigenAU / 11 UoA represents reproducible biological activity independent of variations in product formulation within the claimed range.

[0450] The concept of the EpigenAU / 11 UoA was developed to quantify the potency or biological effect of the products of the present invention, thereby ensuring consistency, safety, and effectiveness in their manufacture, formulation, and clinical application. The products of the present invention may vary qualitatively and quantitatively, yet maintain consistency in the observed biological effect. The UoA definition ensures that each EpigenAU / 11 UoA exhibits reproducible biological activity regardless of variations in product formulation within the claimed range. Thus, a product can be prepared within the claimed range and is considered to provide the desired technical effect if the UoA defined above can be determined for the tested formulation.

[0451] In other words, 1 EpigenAU / 11 UoA is defined as the amount of product required to obtain a significant reduction in tumor cell vitality while maintaining the vitality of healthy cells within a physiologically acceptable range. 11. Novel Benefit / Risk Assessment (Computer-Implemented / Assisted)

[0452] 11.1 Data Assembly 11.1.1 Ex vivo sample treatment (see Method A steps 1.1-1.2) To conduct the experiment, ex vivo tumor masses were generated from the FaDu head and neck squamous cell carcinoma cell line and implanted into immunocompromised mice. Once tumors reached the appropriate size, they were excised, divided into 40 mg portions, and treated with EpigenAU / 11 and cisplatin in triplicate for 6 hours. The masses were then lysed, and RNA was extracted for transcriptional analysis.

[0453] 11.1.2 Transcriptome raw data analysis (see Method A, step 1.3) Whole-transcriptome expression profiles were assessed using the Human Clariom™ S Pico Assay HT (Applied Biosystems, ThermoFisher Scientific) on a GeneTitan MC Instrument (Applied Biosystems, ThermoFisher Scientific) according to the manufacturer's instructions. CEL intensity files were generated using the Affymetrix GeneChip Command Console Software (AGCC, ThermoFisher Scientific). Data analysis was performed using the 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, providing a list of differentially expressed genes (Limma Bioconductor package). This step allows for the generation of a list of differentially expressed genes (DEGs) identified based on their fold change in expression relative to the relevant control experimental condition (i.e., untreated tumor mass).

[0454] 11.1.3 IPA analysis of transcriptional profiles (computer-implemented) (see Method A, step 1.4) The use of IPA makes it possible to infer how and to what extent modulation of gene expression in a biological system affects biological functions relevant to a pathology of interest.

[0455] The transcriptional modification profiles thus obtained were subjected to functional pathway enrichment analysis. One commercially available tool that can be used is Ingenuity Pathway Analysis (IPA version 94302991, Qiagen) [Kramer A, et al. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics. 2014]. The list of differentially expressed genes and the corresponding data measurements (fold change relative to the "untreated tumor mass") identified in the different experimental conditions were uploaded to the application.

[0456] The differentially expressed genes and corresponding fold changes are subjected to a filtering process to select only genes that are significantly perturbed, as indicated by their fold change compared to the "untreated tumor mass."

[0457] The fold change threshold was set to encompass values ​​of ≦−2 and ≧+2, with statistical significance indicated by a p-value of ≦0.05.

[0458] Available identifiers were mapped to their corresponding entities in the QIAGEN Knowledge Base.

[0459] By initiating the "core analysis," significantly perturbed DEGs, called network-eligible molecules, were overlaid onto a global molecular network developed from information contained in the QIAGEN Knowledge Base. A network of network-eligible molecules was then algorithmically generated based on their connectivity.

[0460] The core analysis provides a comprehensive list of approximately the top 500 biological functions derived from the generated network. Associations between biological functions and genes are always supported by corresponding annotations in scientific peer-reviewed publications that demonstrate the calculated directionality and magnitude of regulation of the biological function through automated z-score association [Kramer et al. (2014)]. 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 existing literature for a given annotation.

[0461] It is the responsibility of the skilled operator to carefully select biological functions relevant to the particular pathology under consideration. The selection of biological functions is structured based on the identified hallmarks of the pathology of interest, applying a Z-score threshold set to encompass values ​​of ≦−2 and ≧+2, with statistical significance indicated by a p-value of ≦0.05.

[0462] The associated Z-score values ​​are then used to indicate the direction and magnitude of regulation of each biological function.

[0463] 11.2 Risk Score Calculation 11.2.1 Definition of Cisplatin Side Effects (See Method A, Step 3.1) Officially recorded side effects of cisplatin were identified by examining the following specific sources: -https: / / www.torrinomedica.it / schede-farmaci / cisplatino-3 / (Document made available by AIFA on July 13, 2021) -https: / / www.drugs.com / sfx / cisplatin-side-effects.html, last updated March 17, 2024

[0464] 11.2.2 Identification of IPA biological functions browsing from terms used to annotate side effects (see Method A step 3.2) Information found in the aforementioned resources is used to identify biological activity associated with the identified adverse reaction (the IPA source used is the Ingenuity Knowledge Base, which includes curation from journal articles, OMIM, JAX, and ClinicalTrials.gov) and to interrogate the IPA by the following procedure.

[0465] Side effect terms are written one by one into the "Disease and Function" query box, and then the search is initiated.

[0466] The resulting resumption table allows filtering diseases / functions arising from a large body of evidence (it is possible to understand the correspondence between IPA biological activities and annotated side effects, as shown in Figure 31). The creation of an in silico model intends to associate each biological function with a defined number of genes whose regulation can influence the regulation of the biological function itself (which in this particular case can represent side effects).

[0467] 11.2.3 Overlay Analysis (See Method A, Step 3.3) The overlay analysis focuses on biological functions identified by the "in silico side effect model." The selection of biological functions is structured based on the identified side effects of cisplatin.

[0468] An "overlay analysis" is structured by establishing the relationship between patterns of differentially expressed genes and selected biological functions (always supported by corresponding annotations in scientific peer-reviewed publications demonstrating the directionality and magnitude of regulation of the biological function) using the following procedure:

[0469] Import the set of biological functions selected from the in silico model of the SIDE EFFECT PROFILE of cisplatin into a new sheet called "My Pathway".

[0470] The "Build tool" and "Grow tool" are utilized to identify differentially expressed genes (DEGs) belonging to the transcriptome profile under consideration (cisplatin and EpigenAU / 11) and associate them with the regulation of the biological functions selected in the previous step.

[0471] 11.2.4 Image analysis of the obtained color intensity of biological functions (see Method A, step 3.4) The regulation of the identified DEGs is represented using green (indicating downregulation) and red (indicating upregulation) colors.

[0472] To determine the predicted calculated impact of such experimentally observed modulation of gene expression on biological function activity, the "Overlay" and "Molecule Activity Predictor" tools (MAP) are used. The "Predict" function is run within the MAP tool to calculate the resulting predicted modulation of biological function. Color coding is established accordingly. -Orange: Increased activity - Blue: decreased activity -White: unattainable / unpredictable

[0473] "Overlay analysis" does not directly calculate the Z-score of each biological function. Therefore, it is necessary to convert the color intensity of the modulation signal into a numerical value. This is achieved by using the dedicated app: "IPAmap_Parser" (version 2.1-1).

[0474] This app is a web port of Pipeline Pilot, designed to assign scores, called z-scores, to genes and biological functions based on their coloration within biological pathways generated by QIAGEN's Ingenuity Pathway Analysis software. A key step in the algorithm is the conversion from the RGB color model to the LAB [https: / / www.xrite.com / it-it / blog / lab-color-space] model, a colorimetric encoding that allows recording of color intensity rather than just RGB composition. This conversion is performed within a Pipeline Pilot "component" that utilizes procedures written in R software, relying on specific functionality from the colorspace package [https: / / cran.r-project.org / web / packages / colorspace / index.html].

[0475] Figures 33A-B show the final list of biological activities and corresponding values ​​obtained for each treatment under study.

[0476] 11.2.5 Calculation of Global Risk Score (see Method A, Step 3.5) Thus, the risk score is calculated by the sum of each positive value obtained from the overlay analysis (to indicate that a given side effect is induced by the treatment).

[0477] Calculation of the benefit score for EpigenAU / 11 and cisplatin treatment after 6 hours of treatment (Figure 33C shows the risk score obtained by summing each annotated biological activity value for each of the treatments under study).

[0478] 11.3 Benefit Score Calculation 11.3.1 Core Analysis Biofunction Selection and Export The core analysis obtained in 11.1.3 was used to select biological activities whose trends were consistent with the therapeutic index of the product under consideration (i.e., antitumor activity) (Figure 32A). (See Method A, step 2.1)

[0479] Therefore, the biological activity Z-score values ​​are converted into absolute values, and the list thus obtained is exported to a table reporting the biological function specifications and their relative modulation values ​​(upper panel of Figure 32B). (See Method A, step 2.2)

[0480] The sum of each value for each treatment is considered the benefit score (lower panel of Figure 32B). (See Method A, step 2.3)

[0481] Optionally, biological activities can be grouped into activity hallmarks, with each hallmark given a weighting factor based on its importance in the pathogenesis of interest (Figure 32C). In this case, the biological activity value is multiplied by the corresponding factor to obtain the final list value used in the final calculation of the benefit score (Figure 32D).

[0482] 11.4 Benefit / Risk Score Calculation (See Method A, Step 4) Once the risk and benefit scores are calculated, they are applied to the following formula:

number

[0483] The value of the ratio must therefore be interpreted as follows: the higher the value obtained, the greater the safety of the administered treatment, since the benefits outweigh the risks.

[0484] Figure 34 shows the results of the benefit / risk scores obtained with EpigenAU / 11 and cisplatin treatment after 6 hours (A). Calculation of the fold change in the score obtained with EpigenAU / 11 compared to the score obtained with cisplatin: the EpigenAU / 11 score is twice the score of cisplatin (B).

[0485] Calculating the benefit / risk score while taking into account the above optional steps yields the results shown in Figure 34C, which gives a calculation of the fold change in the score obtained with EpigenAU / 11 compared to the score obtained with cisplatin: the EpigenAU / 11 score is still twice the score of cisplatin (Figure 34D).

[0486] Therefore, the benefit / risk scores calculated with and without any step are consistent with each other.

[0487] 12. Validation of the proposed transcriptomics-based "Method A" in comparison with "Method B," intended as a standard evaluation of the benefit / risk profile associated with in vivo administration of EpigenAU / 11 and cisplatin. 12.1. In Vivo Assay (See Method B, Step 1) EpigenAU / 11 (DoE2) and cisplatin were administered in vivo in a mouse model. Risks (intended as side effects) were estimated through the observation of behavioral parameters (affecting behavior itself, the locomotor system, muscle strength, and neuroreflexes) and potential weight loss in the animals.

[0488] The table below shows experimental values ​​representing in vivo side effects that have not yet been reprocessed for the purposes of risk score calculation. [Table 30]

[0489] Instead, benefit (intended as therapeutic activity) was assessed by considering the reduction in size of the tumor mass compared to untreated tumors.

[0490] For this purpose, tumors 100 mm 3 Once tumor volume reached 100 μg / mL, immunocompromised mice bearing xenografted FaDu head and neck squamous cell carcinoma cells were enrolled in the study. Mice received daily intratumoral injections of EpigenAU / 11 and intraperitoneal cisplatin every other day.

[0491] The following table shows experimental values ​​representing in vivo benefit effects that have not yet been reprocessed for the purposes of calculating benefit scores. [Table 31]

[0492] The obtained values ​​indicate that the standard-assessed benefit / risk ratio profile associated with EpigenAU / 11 is more favorable than that associated with cisplatin. Thus, the data generated using standard in vivo observations confirm the predictive potential and demonstrate the validation of the novel method reported herein based on ex vivo transcriptomics.

[0493] The results obtained for the monitored risk and benefit parameters are reported below: 12.2 Comparison of the benefit / risk ratio of cisplatin based on data from EpigenAU / 11 and in vivo studies

[0494] The interpretation of in vivo generated data has revealed the need for additional methods that allow for the reduction of the dimensionality of such datasets and allow for accurate quantitative expression of the observed benefit / risk ratios, which are usually only discussed qualitatively for therapeutic solutions. Again, such tools would objectify the comparison between profiles associated with two therapeutic solutions.

[0495] 12.2.1 Calculating the Risk Score (see Method B, step 3.1) Data obtained from animal studies that are considered in the context of risk are behavioral parameters and weight loss at the end of the experiment.

[0496] The behavioral parameters monitored are listed below. 1. Loss of spontaneous activity 2. Loss of cleaning 3. Loss of curiosity 4. Loss of responsiveness 5. Loss of corrective reflex 6. Loss of physical strength 7. Eyelid opening disorder 8. Lid reflex 9. Tremors 10. Pallor 11. Stereotypic behavior 12. Passivity

[0497] The values ​​of parameters 1 to 8 are normalized as "untreated animal value" (always equal to 0) + "treated animal value".

[0498] The values ​​of parameters 9-12 are normalized as "untreated animal value" - "treated animal value".

[0499] Potential weight loss in treated animals was also assessed. Data were processed using the following formula: 1-[[Weight of treated animals (observation day: 27) / Weight of untreated animals (observation day: 19)]]

[0500] The table below summarizes the calculation of risk scores for EpigenAU / 11 and cisplatin treatment using the sum of data obtained from the in vivo experiments. (See Method B, step 3.2) [Table 32]

[0501] 12.2.2 Benefit Score Calculation (See Method B, Step 2) The data obtained from animal studies that are considered in the context of benefit are the tumor mass sizes reached at the end of the in vivo testing of each treatment.

[0502] The data was calculated as "reduction in tumor mass size" according to the following formula: 1-[Tumor mass size recovered from treated animals (observation day: 27) / Tumor mass size recovered from untreated animals (observation day: 19)]

[0503] The calculation of the benefit scores for EpigenAU / 11 and cisplatin treatment using data obtained from in vivo experiments is reported below. [Table 33]

[0504] 12.3 Calculating the Benefit / Risk Score (see Method B, Step 4) Once the risk and benefit scores are calculated, they are applied to the following formula:

number

[0505] Therefore, the ratio values ​​should be interpreted as follows: The higher the value obtained, the greater the safety of the administered treatment, since the benefits outweigh the risks. .

[0506] Figure 35 shows the benefit / risk scores obtained with EpigenAU / 11 and cisplatin treatment in vivo (A). Calculation of the fold change in the score obtained with EpigenAU / 11 compared to the score obtained with cisplatin: the EpigenAU / 11 score is 3 times the score of cisplatin (B).

[0507] The two methods disclosed in Examples 11 and 12 (with or without optional steps) have proven useful for objectively comparing the benefit / risk profiles of two anticancer treatments. The first method, based on ex vivo transcriptomics data, has proven capable of accurately predicting the favorability of the EpigenAU / 11 profile relative to that of cisplatin and has undergone validation based on comparison with results generated using standard qualitative approaches based on in vivo data. The second method allows for the summarization of such in vivo data with a single parameter, making the comparison between the benefit / risk profiles of treatment options easier and more accessible. Both methods yield similar results demonstrating the superiority of the EpigenAU / 11 benefit / risk score relative to cisplatin (Figure 36), thus demonstrating the consistency of the ex vivo method with those generated using standard in vivo approaches, thereby returning results that represent a favorable profile of EpigenAU / 11 relative to that of cisplatin and are consistent with those generated using standard in vivo approaches.

[0508] 13.Evaluation of the relationship between EpigenAU / 11 and conventional cancer treatment 13.1 Association with various chemotherapeutic agents We evaluated the efficacy of EpigenAU / 11 in various contexts, particularly in conjunction with established chemotherapeutic agents. Previous experimental cell viability assays were performed on the FaDu and A431 cell lines, both of squamous origin and commonly associated with cisplatin treatment. This combination is relevant because cisplatin is a standard treatment in the management of squamous cell carcinoma.

[0509] The results of the experiment demonstrated that both EpigenAU / 11 and cisplatin showed significant efficacy against these cancer cell lines. Notably, when administered in combination, there was enhanced therapeutic efficacy, suggesting a synergistic interaction between EpigenAU / 11 and cisplatin. Importantly, no adverse effects were observed when these agents were used together, indicating that EpigenAU / 11 does not negatively interfere with the established activity of cisplatin (considered the reference drug in this treatment context) (Figure 37).

[0510] On behalf of the present applicant and the present inventors, the Department of Pharmaceutical Sciences at the University of Pavia conducted additional viability assays for breast cancer, focusing on two triple-negative breast cancer lines, MDA-MB-231 and SUM159PT. These assays included standard chemotherapy agents for this tumor type: carboplatin, paclitaxel, and gemcitabine. Using the CellTiter-Glo® 3D Viability Assay, we investigated the effects of combinations such as EpigenAU / 11 + carboplatin + paclitaxel or EpigenAU / 11 + carboplatin + gemcitabine. In the combination experiments, the amount of EpigenAU / 11 used was 0.22 mg / ml, and the drugs used in the combination experiments were at the same doses as those used alone. Results showed that these combinations did not exhibit adverse effects compared to the corresponding combinations without EpigenAU / 11. Rather, additive effects were observed in both tumor lines (Figure 38). This further suggested that the chemotherapeutic agent and EpigenAU / 11 act through different mechanisms without interfering with each other.

[0511] To further explore potential interactions between conventional chemotherapy drugs and EpigenAU / 11, a team at the Regina Elena National Cancer Institute in Rome performed viability assays on patient-derived tumor organoids (PDOs) using EpigenAU / 11 in combination with chemotherapy drugs. Specifically, various organoids were treated with standard of care regimens, either alone or in combination with EpigenAU / 11, for 72 hours (Figures 39A-39D).

[0512] Cisplatin, gemcitabine, and their combination were tested in bladder tumor organoids (Bladder 41 - Figure 39A, and Bladder 38 - Figure 39B). EpigenAU / 11 was then evaluated as a standalone treatment and in combination with these drugs. The results demonstrated that EpigenAU / 11 significantly reduced tumor viability and had a significant additive effect when combined with cisplatin and gemcitabine, achieving near-complete elimination of tumor viability in some cases. These findings highlight not only the absence of interference, but also a highly beneficial effect.

[0513] In an experiment using breast cancer organoids (Breast 203 - Figure 39C), a sequential regimen was applied: paclitaxel and carboplatin were administered for 72 hours, followed by epirubicin and cyclophosphamide for another 72 hours. The addition of EpigenAU / 11 to these regimens did not result in a loss of efficacy. Instead, the data suggested that EpigenAU / 11 maintained or enhanced overall efficacy, even when combined with multiple chemotherapy agents.

[0514] In endometrial tumor organoids (Endometrium 12 - Figure 39D), EpigenAU / 11 alone dramatically outperformed standard treatment. Carboplatin alone reduced survival to 85.1%, and the combination of carboplatin and paclitaxel reduced survival to 96.2%, while paclitaxel alone had no significant effect. In contrast, EpigenAU / 11 reduced survival to only 0.3%, demonstrating remarkable efficacy. Furthermore, including EpigenAU / 11 together with carboplatin, paclitaxel, or their combination further enhanced its therapeutic effect, highlighting its potential superiority over standard treatment.

[0515] These results, collected across four different organoid models, demonstrate the strong potential of EpigenAU / 11 to not only complement but, in some cases, exceed the efficacy of existing chemotherapy regimens. These findings highlight the promise of EpigenAU / 11 as a novel therapeutic agent with the potential to enhance and transform current cancer treatments.

[0516] In conclusion, consistent findings observed across various cancer models highlight the significant potential of EpigenAU / 11 to improve (adjuvant) treatment outcomes when used in combination with standard chemotherapeutic agents. The data demonstrate that EpigenAU / 11 can act synergistically with established therapies, promoting additive effects without compromising their efficacy. This aspect is particularly important, as it suggests that EpigenAU / 11 may offer a complementary approach to existing treatment protocols.

[0517] Below is a summary table of the combination of EpigenAU / 11 with various chemotherapeutic agents for patient-derived tumor organoids.The table highlights that EpigenAU / 11 does not interfere with standard treatment, and in most cases shows additive or synergistic effects. [Table 34]

[0518] The pharmacological classes and mechanisms of action of the drugs tested are summarized below. [Table 35]

[0519] Determining the maximum tolerated dose of EpigenAU / 11. Local and systemic administration After extensive in vitro studies across a variety of models, including two-dimensional, three-dimensional, and organoid systems, EpigenAU / 11 demonstrated a remarkable ability to selectively reduce cell viability. This effect was more pronounced in cancerous cells compared to healthy cells, reinforcing EpigenAU / 11 as a promising candidate for further exploration. These in vitro results highlight the need to assess its tolerability and determine its maximum tolerated dose (MTD) in more complex in vivo systems.

[0520] Determining the MTD is important when moving to in vivo studies because animal models can reveal different kinetics compared to in vitro conditions. The tolerability and behavior of a compound in an organism, especially wild-type mice, differs from the controlled environment of a cellular assay. Therefore, comprehensive evaluation of local and systemic toxicity was performed prior to efficacy testing.

[0521] Local toxicity was assessed by subcutaneous injection of various concentrations of EpigenAU / 11. Studies revealed that the 50 mg / ml concentration showed no local toxicity, as evidenced by the absence of adverse effects at the injection site.

[0522] Concurrently, systemic toxicity studies were performed by intravenously injecting 100 μl of EpigenAU / 11 at 100 mg / ml daily for one week. Notably, no general signs of distress were observed in the animals throughout the treatment period. Notably, evaluation of key biochemical markers, including GOT, GPT, gamma GT, and creatinine, showed no significant changes, indicating the absence of treatment-induced systemic toxicity.

[0523] In contrast, similar toxicity evaluations of the previous formulation at higher doses showed high mortality rates, highlighting its adverse effects.

[0524] 13.2 Evaluating the association between EpigenAU / 11 and radiation therapy in head and neck squamous cell carcinoma To evaluate the potential synergistic effects of EpigenAU / 11 in combination with radiation therapy, two head and neck squamous cell carcinoma (HNSCC) organoid models, HNSCC10847 (radiotherapy-sensitive) and HNSCC10632 (radiotherapy-resistant), were utilized. Using the CellTiter-Glo® 3D Viability Assay, the results (Figure 40) showed that in the radiation-sensitive HNSCC10847 organoid model, treatment with 0.66 mg / mL of EpigenAU / 11 in combination with radiation therapy resulted in a significant decrease in cell viability compared to radiation therapy alone. The presence of 0.66 mg / mL of EpigenAU / 11 enhanced the cytotoxic effect, resulting in an additive effect on cell mortality. This suggests that EpigenAU / 11 can enhance the efficacy of radiation therapy in this model, resulting in greater tumor cell death. Conversely, the HNSCC10632 organoid model, which was resistant to radiation therapy even at high doses (8 Gy), demonstrated sensitivity to EpigenAU / 11 treatment. When administered alone, 0.66 mg / mL of EpigenAU / 11 significantly reduced cell viability. Furthermore, in the presence of both EpigenAU / 11 and radiation therapy, cell viability was further reduced at the highest radiation dose (8 Gy), indicating that EpigenAU / 11 enhances the response to radiation therapy in this otherwise resistant model.

[0525] Findings from these studies demonstrate the significant potential of EpigenAU / 11 as an adjuvant in cancer therapy, effectively enhancing the efficacy of conventional treatment approaches such as chemotherapy and radiation therapy. EpigenAU / 11 exhibits synergistic effects when combined with standard chemotherapeutic agents, improving treatment outcomes without interfering with their established mechanisms of action. In particular, its combination with radiation therapy has shown promise in sensitized-resistant tumor models, resulting in greater declines in tumor viability at higher radiation doses. These results suggest that EpigenAU / 11 can act as a potent complementary agent in multimodal cancer treatment strategies, providing a novel approach to improving therapeutic efficacy across a variety of tumor types.

[0526] 14. Pharmacokinetics and ADME (absorption, distribution, metabolism, and excretion) evaluation of EpigenAU / 11 Changes in gene expression after EpigenAU / 11 (DoE2) administration: effects on various organs provide insight into metabolic dynamics Understanding the pharmacokinetics of EpigenAU / 11 is essential for assessing its local persistence and overall behavior within an organism. Conventional techniques for assessing drug distribution often face limitations, especially when working with complex systems such as EpigenAU / 11, which are derived from various plant sources and are inherently variable at the molecular level. The diverse components of such extracts may also interact in unpredictable ways, making it difficult to isolate and quantify individual components and their respective pharmacokinetic profiles.

[0527] Due to the heterogeneous nature of EpigenAU / 11, traditional pharmacokinetic studies, which typically rely on measuring specific compounds over time, may not provide an accurate depiction of how the extract behaves in biological systems. This complexity arises because interactions within the EpigenAU / 11 matrix can affect absorption, distribution, metabolism, and excretion (ADME) in ways that cannot be observed when evaluating isolated compounds. For example, some components may enhance the absorption of others, while others may inhibit metabolic processes, potentially resulting in differences in how long EpigenAU / 11 persists in tissues and in what form. Furthermore, molecular-level reproducibility between different batches is virtually impossible to achieve and, most importantly, is not related to the intimate nature of the product, as discussed appropriately.

[0528] Consequently, a more refined approach is needed to comprehensively evaluate the pharmacokinetic behavior of EpigenAU / 11 consistently according to the presence / absence of its biological effects rather than its molecular components.

[0529] To address this, we conducted experiments involving treatment of healthy mice with EpigenAU / 11 to characterize the transcriptome profiles of various organs at several time points (0, 2, 6, 12, 18, 24, and 48 hours) after injection, as shown in Figure 41. The primary objective was to examine global gene expression profiles across different organs and uncover potential patterns associated with EpigenAU / 11 metabolism. Control samples consisted of liver, blood, brain, and kidney from mice treated with physiological solution and were collected at the same time points as the EpigenAU / 11-treated mice. Additionally, untreated samples from all four organs were collected at time point 0 to serve as baseline controls.

[0530] For blood and brain samples, data distribution using principal component analysis (PCA) did not show a clear clustering of samples from mice receiving EpigenAU / 11, as was the case for liver and kidney samples.

[0531] In liver samples, principal component analysis (PCA) and coexpression analysis revealed a specific pattern: transcriptome perturbations increased after EpigenAU / 11 administration, peaked at 6 hours, and gradually decreased over time. To further explore this aspect, we used the Molecular Degree of Perturbation (MDP) tool to understand the grade of transcriptome perturbation in each sample compared to untreated samples. This approach was also applied to a subset of the dataset, selecting only genes related to ADME (absorption, distribution, metabolism, and excretion) processes, according to the gene set used in a previous study by Dong Gui Hu et al. (Dong Gui Hu et al. The Expression Profiles of ADME Genes in Human Cancers and Their Associations with Clinical Outcomes Cancers 2020, 12(11), 3369). Figure 42 shows the main results reflecting the time-dependent perturbation of ADME genes in the liver.

[0532] After 48 hours of EpigenAU / 11 administration, perturbations in genes involved in hepatic ADME processes (represented by red boxes) were comparable to those in mice treated with physiological solution (green boxes). Among the perturbed genes were SOD2 and NR1I3, which encode proteins that function as modulators; TAP1 and NOS1AP, which encode phase I (functionalization) enzymes; SUL1B and GSTT2, which encode phase II (conjugation) enzymes; and TAP2 and SLC16A1, which encode transporters.

[0533] Although PCA for kidney samples explained less variance in PC1 and PC2 than in liver, PCA also showed clustering of EpigenAU / 11-treated samples. Again, MDP was used to evaluate both global transcriptome perturbations and specific perturbations related to ADME processes. The gene set selected for kidney was described by genome-wide association studies (GWAS) of metabolite concentrations (Schlosser, P., Li, Y., Sekula, P. et al. Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans. Nat Genet 52, 167-176 (2020). https: / / doi.org / 10.1038 / s41588-019-0567-8). 63 genes were selected (genes found by GWAS and generally known to be involved in metabolism-related pathways). The results of this analysis are shown in Figure 43.

[0534] Peak ADME gene perturbations in the livers of mice treated with EpigenAU / 11 occurred 6 hours after treatment, whereas kidney samples showed a clear peak of ADME-related gene perturbations at 18 hours. This timing difference is consistent with the established roles of these organs within the pharmacokinetic ADME framework, where the liver primarily deals with the metabolism and modification of substances and the kidneys primarily responsible for excretion and clearance from the body.

[0535] In the liver, early metabolic processing of EpigenAU / 11 likely triggers early transcriptional activity as the organ responds to the influx of phytochemicals, resulting in the observed peak of gene expression perturbations at 6 hours. This response likely reflects the upregulation of detoxification enzymes and transporters that help metabolize and modify EpigenAU / 11 before it circulates to other tissues.

[0536] In contrast, the kidneys showed a delayed but significant response, with gene expression perturbations peaking approximately 18 hours after treatment. This timeline may represent a phase during which EpigenAU / 11 is processed for excretion. The kidney's role in filtration and elimination, likely accompanied by an accumulation phase, removes EpigenAU / 11 from the bloodstream, explaining the delayed peak to the liver.

[0537] By 48 hours after treatment, both global and ADME-specific gene expression perturbations in both organs normalized and were comparable to those in mice treated with physiological solution. This return to baseline suggests that EpigenAU / 11 is largely processed and cleared within this time frame. Normalization of gene expression highlights transient effects on metabolic and excretory systems, which may be beneficial for assessing the safety and tolerability profile of EpigenAU / 11 in a biological context.

[0538] 15.Quality control The methods used for batch-to-batch quality control of EpigenAU / 11 make it possible to assess the complexity of the formulation and its qualitative and quantitative variability.

[0539] 15.1 Batch Shipping Strategies Considering the impossibility of assigning the biological activity of a product based on the qualitative-quantitative profile of one or more chemical markers and thus relating the biological activity of a product to the expression system properties for a specific chemical marker, an approach based on FTIR spectroscopy was developed.

[0540] Therefore, the FTIR spectrum, which is characteristic of each material (in this case, the plant biological matrix), can be used to check the suitability of new batches, ensuring that each new production meets manufacturing standards.

[0541] The goal is to use machine learning to build a predictive model based on the correlation between FTIR spectra and cell-based assays, in order to obtain a model that can be used to distinguish between good quality and poor quality samples.

[0542] The batches used to construct the training set were selected according to the claims and represent a predetermined range of quantitative formulation variation from a reference standard (EpigenAU / 11 DoE2), useful for characterizing trends in biological performance with respect to quantitative formulation variation. All batches in the training set were tested by cellular assay (see Example 2).

[0543] Once the bioacceptability parameters of activity were defined and the predictive model was validated (internal validation), the same procedure was used to analyze two good quality formulations. Based on the results obtained after the analysis, the quality of the test samples was determined to be good or bad depending on whether they passed the tests performed using biological analysis to confirm the constructed model.

[0544] Next, the predictive model was used to test the increasing formulation rate for good quality of formulations rejected by the predictive model and cellular assay.

[0545] Each individual formulation permutation was tested by the model, and once a good biological correlation was predicted, all permutations were tested in cellular assays to confirm the results and good response of the predictive model.

[0546] Therefore, the aim of this study was to propose a procedure to build a model of FTIR spectra that can predict the in vitro biological activity of different batches of product formulations with the correct ratios and, in case of negative results, evaluate the adjustment of the formulation ratios to obtain the desired activity.

[0547] Therefore, prediction of biological activity was performed using partial least squares (PLS) regression models based on FTIR spectra.

[0548] The DoE used in these examples is that disclosed in Example 9.1 and the associated tables.

[0549] Below is a list of the 12 batches (DoE) used to create the FTIR library and the samples analyzed as tests. Training Set : Two batches of EpigenAU / 11 with the correct percentage of formulation (DoE2 and 3). Ten batches of EpigenAU / 11 (two of poor quality and eight from permutations of the correct formulation from DoE2 and 3). CQ1_Lot2, DoE2.1, 2.2, 2.3; CQ1_Lot3, DoE3.1, 3.2, 3.3. Test Set: Two batches of EpigenAU / 11 with the correct percentage of formulation (DoE1 and 4) Four batches of EpigenAU / 11 (two of poor quality and two from permutations of the correct formulation of two batches from DoE4, DoE4.1 and 4.2).

[0550] 15.2 FTIR equipment and setup. Alpha spectrometer from BRUKER Optics. The instrument is equipped with a GLOBAR source emitting in the far- and mid-infrared regions, a ROCKSOLID interferometer (Michelson type), a KBr beam splitter, and a RT-DLATGS detector. ·Resolution: 2cm-1 Spectral range: 5000~300cm-1 Background scan: 50 Scans for sample acquisition: 50

[0551] Sample preparation Each sample was transferred to an appropriate sample holder for ATR-FTIR analysis of solids and liquids. Approximately 10 mg of sample was deposited and pressed onto the diamond crystal of the ATR support. Before recording measurements, it was ensured that the entire sample holder was properly covered.

[0552] Sample acquisition For each sample, measurements were repeated at least three times to verify data reproducibility, and the replicates were then averaged to obtain a representative spectrum of the sample for characterization.

[0553] Spectral data preprocessing The signals are observed in two distinct regions of the measured spectral range: the OH and CH stretching bands in the high frequency range, and the bands between 1800 and 500 cm -1 appears in the group frequency along with the collection band of fingerprint regions in the interval 1800-500 cm. In the high frequency range, most of the intensity is related to the presence of humidity rather than the sample itself. Therefore, we focused on the more relevant 1800-500 cm -1 We focused on the range of

[0554] For the ATR spectrum obtained as described above, the 1800–500 cm -1 The second derivative was calculated using a 25-point Savitzky-Golay smoothing filter in the selected spectral range between 1076.4 cm and 1077.4 cm. The second derivative profile was then analyzed for comparison. -1 Normalized to the intensity of the (negative) peak at 1076.4 cm -1 The peak was chosen as an internal standard because it has minimal variability in intensity and position across different sample compositions. These operations were performed using Opus 8.1 software from Bruker Optics.

[0555] 15.3 Cell-Based Assay Results To build a predictive model, batches of the training set were tested by cell-based assays.

[0556] As discussed in Example 10 above and shown in Figure 28, cell-based assay results demonstrate that all DoEs (1-4) at 0.66 mg / ml produced: HuDe healthy cell mortality ≤61%; FaDu tumor cell mortality ≥ 71%; A431 tumor cell mortality ≥ 55%; or even HuDe healthy cell mortality ≤61%; FaDu tumor cell mortality ≥ 71%; A431 tumor cell mortality rate ≥ 65% This shows that it induces

[0557] Cell culture conditions: HuDe, FaDu and A431 cell lines were cultured according to their conventional designated protocols. HuDe cells were cultured in MEM medium containing 10% FBS, 1% penicillin / streptomycin, and 1% sodium pyruvate and seeded at approximately 7,000 cells / well. FaDu cells were cultured in EMEM medium containing 10% FBS and 1% penicillin / streptomycin and seeded at approximately 12,500 cells / well. A431 cells were cultured in DMEM medium containing 10% FBS and 1% penicillin / streptomycin and seeded at approximately 8,500 cells / well.

[0558] The volume of medium per well was 200 μl.

[0559] The seeded cells were cultured in a humidified incubator at 37°C containing 5% CO2 and treated with 0.66 mg / ml of each DoE for 24 hours.

[0560] The above ranges can still be considered compliant, however, as this batch was also tested ex vivo and in vivo, the limits of the cell-based assay for defining a batch as compliant for biological activity were set to the results of the reference standard DoE2. [Table 36]

[0561] Based on these results, limits of study vitality (as opposed to mortality) were set as reported below. -50%≦HuDe≦-40% -FaDu≦-90% -A431≦-65%

[0562] Negative numbers represent a decrease in cell vitality, so for example, -68% vitality corresponds to 68% cell mortality.

[0563] In the table below, non-conformance indicates a value where .

[0564] Given the extensive characterization of DoE2 with respect to therapeutic efficacy, cytotoxicity values ​​in cell-based assays against HuDe, FaDu, and A431 cells (see Example 2) were used as desired targets for EpigenAU / 11 performance, envisioning manufacturing quality control of the product.

[0565] Therefore, the following criteria That is, HuDe healthy cell mortality rate: 40-50% FaDu tumor cell mortality ≥ 90%; A431 tumor cell mortality rate ≥ 55% Performance that did not meet this requirement was considered "undesirable" even though it indicated a reasonable therapeutic effect.

[0566] HuDe healthy cell mortality ≤61%; FaDu tumor cell mortality ≥ 71%; A431 tumor cell mortality rate ≥ 65% Performance that does not meet the requirements was considered non-conforming.

[0567] Please note that the definition of "qualified" is based solely on DoE2 performance below, as this lot has been extensively tested and characterized and is therefore considered desirable for large scale manufacturing setups.

[0568] All samples in the training set were tested by the cell-based assay according to Example 2, and the results are reported below. [Table 37]

[0569] When referring to cell-based assays, the table indicates "fit" if the batch with the most stringent cutoff, selected based on tumor cell vitality and DoE2 performance against healthy cells, is deemed acceptable for quality.

[0570] Once this tolerance limit was established for the cell-based assay, a PLS predictive model was constructed.

[0571] 15.4 Spectral Acquisition All spectra of a batch of training sets in 15.2 were first acquired.

[0572] These spectral and cell-based assay results were used to generate a PLS regression model.

[0573] FTIR Spectroscopy Data Analysis Workflow Prediction of cell viability was performed using partial least squares (PLS) regression models. The following sections outline the data generation, model training, and evaluation process.

[0574] Data Preprocessing Formation of training and test sets: The dataset was split into a training set and a test set for model development and evaluation.

[0575] Training set: Samples from groups DoE2 and DoE3 were selected to train the PLS regression model. These samples were considered suitable for training based on their composition and experimental consistency.

[0576] Test Set: Samples from DoE1 and DoE4 groups were used as the test set, which was reserved for model evaluation to understand the predictive performance of the model evaluated on unseen data.

[0577] Feature selection on wavelength To further reduce the dimensionality of the data and focus on relevant features, a first PLS model wavelength selection was performed. This step involved identifying wavelengths highly correlated with cell viability. Wavelengths were selected based on their correlation with cell viability of at least one of the cell types. Only wavelengths with a correlation coefficient greater than or less than 0.7 were included in the final model. This ensured that only the most predictive wavelengths were used in the analysis. This process left 247 features in the dataset.

[0578] 15.5 PLS Regression Model Development After feature selection, a final partial least squares (PLS) regression model was constructed using a training set previously filtered to present the same 247 features selected in the previous step. Partial least squares (PLS) regression is a multivariate statistical method used to predict a set of dependent variables (responses) from a set of independent variables (predictors). It is highly effective for predicting response variables from noisy, collinear, or complex data and is widely used in spectroscopy data analysis.

[0579] Training process: A model was trained on selected wavelengths from DoE2 and DoE3 samples to identify relationships between intensity measurements and cell viability for the three cell types.

[0580] Model Test: The trained PLS model was then applied to the test set (DoE1 and DoE4) to predict cell viability.

[0581] Predicted rating: The model was evaluated by comparing the predicted cell viability values ​​with the true values.

[0582] Data comparison and PLS regression model validation.

[0583] After generating the PLS model, internal validation of the predictive model was performed. [Table 38]

[0584] Once the model was validated, four samples (DoE1 and DoE4) were tested and the predictive value was confirmed by cell-based assays (see Figure 28). [Table 39]

[0585] The data above and in Figure 28 reveal that different permutations of the claimed formulations can better meet the cytotoxicity criteria identified as cutoffs for defining the UoA for EpigenAU / 11 (e.g., DoE4 and DoE4.2, where the 4.2 formulation exhibits a favorable cytotoxicity profile).

[0586] Having obtained the base formula as "undesirable" with the high quality cutoff determined above, a study on possible permutations of the DoE4 formula was carried out.

[0587] As a result of this study, it is clear that two permutations of the correct formulation from DoE4 (DoE4.1 and DoE4.2) were tested against the predictive model to explore possible modifications of the formulation that could achieve the desired biological activity (i.e., similar to DoE2). [Table 40]

[0588] Finally, DoE4.2 in the predictive model showed the desired activity and was then tested in a cellular assay to confirm the results.

[0589] The results of the cell-based assay confirmed that a change of 6% or more in the absolute value of the SP2 co-extract could achieve the desired activity. Thus, internal and external validation of the control chart was performed. Therefore, according to the FTIR prediction test using the tolerance limits evaluated by the method of the present invention, all batches in the training set were found to be compatible with the internal model validation process. To confirm the validity of the process for research purposes, samples from the test set were tested with the FTIR prediction model, and the results were confirmed by cell assay for biological activity.

[0590] We then defined the acceptability criteria for products containing or consisting of one or more natural matrices and identified processes and methods for a priori evaluating their biological activity, with the aim of making any quantitative changes in the ratios between components that may ultimately allow the biological activity to be restored to the desired level. Thus, according to the method of the present invention, quantitative changes in the formulation can result in the maintenance of the desired biological activity, regardless of the concept of composition at the molecular level.

[0591] 16. Network Analysis A network analysis of the pathologies treated by EpigenAU / 11 was performed, and the data obtained demonstrates how the tested natural matrix-based product can affect the body on a systemic scale.

[0592] Specifically, it relates to the following: -Pathological context (Figure 44 Panel A): Systemic inflammation is closely related to the clinical manifestations of tumors and indicates their presence and progression. Cytokines, inflammatory proteins, and immune cells are readily detectable in the systemic circulation [Dolan RD, Lim J, McSorley ST, Horgan PG, McMillan DC. The role of the systemic inflammatory response in predicting outcomes in patients with operable cancer: Systematic review and meta-analysis. Sci Rep. 2017; Dolan RD, McMillan DC. The prevalence of cancer-associated systemic inflammation: Implications of prognostic studies using the Glasgow Prognostic Score. Crit Rev Oncol Hematol. 2020; Roxburgh CS, McMillan DC. Cancer and systemic inflammation: treat the tumor and treat the host. Br J Cancer. 2014]. - The situation when treated with the reference drug (Figure 44 Panel B): The reference drug is unable to counteract the systemic inflammation. - Conditions when treated with EpigenAU / 11 (Figure 44 Panel C): EpigenAU / 11 can modulate certain biological activities that can beneficially influence systemic inflammation.

[0593] The graphs were designed using the open-source network visualization platform Gephi (Bastian M., Heymann S., Jacomy M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media). The layout Yifan Hu selected for the "pathology" network preserved the three-dimensional structure of the graph and was applied to construct the "natural products" and "reference drugs" graphs.

[0594] The direction of regulation is represented by the blackening of nodes for upregulation and empty nodes for downregulation. Gray nodes do not present a specific direction of regulation. The size of the nodes represents a previously scaled Z-score based on all values ​​used in a particular panel. In Gephi, the size of the nodes was controlled by using the "ranking" parameter, which has a size range of 15 to 60.

[0595] The "HUBs" of the network represent central biological processes of interest for a particular pathology. They are depicted in gray and labeled with capital letters, and their predicted regulation is indicated by up or down arrows according to the literature (for pathology networks) or based on the regulation of disease and biofunction / biological parameters (for the "Natural Product" and "Reference Drug" networks).

Claims

1. Products for use in cancer treatment, consisting of the following: Component a. 20-50% by weight. Component b. (49-80% by weight) and Component c. 0.6 to 1.2% by weight. 100% in total, However, component a. is a co-extract of leaves and flowers of the genus Filipendula, leaves of the genus Laurus, seeds of the genus Brassica, and roots of the genus Withania, and the weight percentage of the raw materials for its preparation is 100% of the total of 17.5-32.5% by weight of leaves and flowers of the genus Filipendula, 17.5-32.5% by weight of leaves of the genus Laurus, 17.5-32.5% by weight of seeds of the genus Brassica, and 17.5-32.5% by weight of roots of the genus Withania. and The aforementioned component b is a co-extract of leaves of the genus Cynara, roots of the genus Curcuma, and flowers of the genus Tanacetum, and the weight percentage of the raw materials for its preparation is 10-19% by weight of leaves of the genus Cynara, 29-55% by weight of roots of the genus Curcuma, and 29-55% by weight of flowers of the genus Tanacetum, totaling 100%. and The aforementioned component c is an extract of the leaves of the Agave genus; however, The aforementioned genus *Filipendula* is *Filipendula vulgaris*; The aforementioned genus Laurus is Laurus nobilis; The aforementioned genus Brassica is broccoli (Brassica oleracea bottletis cymosa); The aforementioned genus Withania is Ashwagandha (Withania somnifera); The genus Cynara is Cynara cardunculus scolymus; The aforementioned genus Curcuma refers to turmeric (Curcuma longa); The aforementioned genus Tanacetum is Tanacetum parthenium; The aforementioned genus Agave is Agave sisalana.

2. Component a. 30-40% by weight. Component b. (60-70% by weight) and Component c. 0.6 to 1.2% by weight. 100% The product according to claim 1, comprising the above.

3. The product according to claim 1, having the following formulation Component a. 36.05% by weight. Component b. 63.06% by weight. and Component c. 0.89% by weight. 100% or Component a. 30.00% by weight. Component b. 69.11% by weight. and Component c. 0.89% by weight. A total of 100%.

4. Component a is a freeze-dried extract obtained by co-extracting with water the leaves and flowers of the genus Filipendula, the leaves of the genus Laurus, the seeds of the genus Brassica, and the roots of the genus Withania, and the weight percentage of the raw materials for its preparation consists of 17.5–32.5% by weight of the leaves and flowers of the genus Filipendula, 17.5–32.5% by weight of the leaves of the genus Laurus, 17.5–32.5% by weight of the seeds of the genus Brassica, and 17.5–32.5% by weight of the roots of the genus Withania, totaling 100%. Component b is a freeze-dried extract obtained by co-extracting with water the leaves of Cynara, the roots of Curcuma, and the flowers of Tanacetum, and the weight percentage of the raw materials for its preparation consists of 10-19% by weight of Cynara leaves, 29-55% by weight of Curcuma roots, 29-55% by weight of Tanacetum flowers, totaling 100%, and Component c is a freeze-dried extract obtained by further extracting the water-based extract of Agave leaves. The product according to claim 1.

5. Component a is a freeze-dried extract obtained by co-extracting water from the leaves and flowers of the genus Filipendula, the leaves of the genus Laurus, the seeds of the genus Brassica, and the roots of the genus Withania, wherein the weight percentage of the raw materials for its preparation consists of 25% by weight of the leaves and flowers of the genus Filipendula, 25% by weight of the leaves of the genus Laurus, 25% by weight of the seeds of the genus Brassica, and 25% by weight of the roots of the genus Withania. and Component b is a freeze-dried extract obtained by co-extracting with water the leaves of Cynara, the roots of Curcuma, and the flowers of Tanacetum, and the weight percentages of the raw materials for its preparation consist of 14.30% by weight of Cynara leaves, 42.85% by weight of Curcuma roots, and 42.85% by weight of Tanacetum flowers. Component c is a freeze-dried extract obtained by further extracting the water-based extract of Agave leaves. The product according to claim 1.

6. The genus *Filipendula* is *Filipendula vulgaris*, the genus *Laurus* is *Laurus nobilis*, the genus *Brassica* is broccoli (Brassica oleracea bottletis cymosa), the genus *Withania* is ashwagandha (Withania somnifera), and the genus *Cynara* is *Cynara cardunculus*. The product according to claim 1, wherein the genus is scolymus, the genus Curcuma is Curcuma longa, the genus Tanacetum is Tanacetum parthenium, and the genus Agave is Agave sisalana.

7. The product according to claim 1, however, The 0.66 mg / ml product, when administered separately to cultured HuDe cells, FaDu cells, and A431 cells, induced the following cell mortality 24 hours after administration: Mortality rate of HuDe healthy cells ≤ 61%; FaDu tumor cell mortality rate ≥ 71%; and Mortality rate of A431 tumor cells ≥ 55% This is in a cell culture plate, and here, The HuDe cells were seeded at approximately 7,000 cells / well in 200 μl of suitable medium; the FaDu cells were seeded at approximately 12,500 cells / well in 200 μl of suitable medium; and the A431 cells were seeded at approximately 8,500 cells / well in 200 μl of suitable culture medium; after treating the cells with the product, they were cultured for 24 hours, and cell mortality was measured by evaluating cell viability by nuclear staining.

8. The product according to claim 1, having the basic unit of activity: The basic unit of activity is defined as a necessary and sufficient amount of the product that, when administered separately to cultured HuDe cells, FaDu cells, and A431 cells, induces the following cell mortality 24 hours after administration: HuDe mortality rate for healthy cells: 40-50%; FaDu tumor cell mortality rate ≥ 90%; and Mortality rate of A431 tumor cells ≥ 65%; This is in a cell culture plate, and here, The HuDe cells were seeded at approximately 7,000 cells / well in 200 μl of suitable medium; the FaDu cells were seeded at approximately 12,500 cells / well in 200 μl of suitable medium; and the A431 cells were seeded at approximately 8,500 cells / well in 200 μl of suitable culture medium; after treating the cells with the product, they were cultured for 24 hours, and cell mortality was measured by evaluating cell viability by nuclear staining.

9. A product according to claim 1, and a composition comprising at least one of an anticancer active ingredient and a pharmaceutically acceptable carrier.

10. The composition according to claim 9, wherein the anticancer active component is a chemotherapeutic agent, an antibody, or a therapeutically active fragment thereof.

11. The composition according to claim 10, wherein the chemotherapeutic agent is selected from cisplatin, paclitaxel, gemcitabine, epirubicin, cyclophosphamide, carboplatin, oxaliplatin, mitomycin C, bleomycin, doxorubicin, busulfan, dacarbazine, temozolomide, ifosfamide, melphalan, clophosphamide, lomustine, and bendamustine.

12. The composition according to claim 10, wherein the antibody is a monoclonal antibody selected from monoclonal antibodies such as rituximab, trastuzumab, bevacizumab, pembrolizumab, ipilimumab, nivolumab, atezolizumab, and cetuximab.

13. A therapeutic adjuvant or vehicle for anti-cancer treatment comprising the product described in claim 1 and a pharmaceutically acceptable carrier.

14. A therapeutic adjuvant or vehicle according to claim 13, formulated for oral, nasopharyngeal, oropharyngeal, aerosol, systemic injection, microneedle injection, intratissue injection, intravenous, topical, rectal, vaginal, ocular, or intratissue administration.

15. The therapeutic adjuvant or vehicle according to claim 14, which is in the form of a suspension, solution, lyophilized material, cream, ointment, spray, tablet, soft gelatin capsule, hard gelatin, gel, emulsion, eye drops, enema, suppository, vaginal suppository, powder, granule, filled vesicle, or filled liposome.

16. A kit for concomitant, simultaneous, or sequential administration, comprising a therapeutic adjuvant or vehicle according to claim 13 and separate vials of at least one anticancer active ingredient.

17. The kit according to claim 16, wherein the anticancer active component is a chemotherapeutic agent, an antibody, or a therapeutically active fragment thereof.

18. The kit according to claim 17, wherein the chemotherapeutic agent is selected from cisplatin, paclitaxel, gemcitabine, epirubicin, cyclophosphamide, carboplatin, oxaliplatin, mitomycin C, bleomycin, doxorubicin, busulfan, dacarbazine, temozolomide, ifosfamide, melphalan, clophosphamide, lomustine, and bendamustine.

19. The kit according to claim 17, wherein the antibody is a monoclonal antibody selected from monoclonal antibodies such as rituximab, trastuzumab, bevacizumab, pembrolizumab, ipilimumab, nivolumab, atezolizumab, and cetuximab.

20. The product according to claim 1, for use in the treatment of cancer.

21. The product for use according to claim 20, wherein the cancer is osteosarcoma, breast cancer, bladder cancer, endometrial cancer, gastric cancer, ovarian cancer, squamous cell carcinoma, head cancer, and cervical cancer.

22. The product exerts its therapeutic effect on cancer through a physiological mechanism by modulating the network of biological activity, thereby addressing the altered physiological state underlying the cancerous condition, and exhibits therapeutic functional resilience between different batches of the product. The aforementioned functional resilience is the ability to maintain therapeutic properties between different batches of the product, even if the qualitative and quantitative composition differs between batches. The product according to claim 1 for use in the treatment of cancer.

23. The aforementioned product is itself a natural matrix and exhibits therapeutic activity based on natural intelligence. The therapeutic activity based on the aforementioned natural intelligence is identified as the inherent ability of the natural matrix to store and transmit the biological and physicochemical information necessary to interact with and integrate with other biological networks, and is a therapeutic activity that enables physiological and internal interconnection with other self-organizing entities in nature, such as the human species. The product according to claim 1.

24. The product according to claim 23, wherein the presence of natural intelligence is determined by verification of the product's appearance characteristics in anticancer activity, provided the following conditions are met: The 14C activity of the product measured using the ISO-16620-2;2019 (AMS) method is ≥99.00%, miRNA and exosomes are detected in the product, the product exhibits batch-to-batch restorative capacity for therapeutic or beneficial function (functional restorative capacity) between different batches of the product, and the product modulates the overall altered pathological condition.

25. A therapeutic adjuvant according to claim 13, The adjuvant exerts its therapeutic effect on cancer through a physiological mechanism by modulating the network of biological activity, thereby addressing the altered physiological state underlying the cancerous condition, and exhibits therapeutic functional resilience between different batches of the adjuvant. The aforementioned functional resilience is intended to ensure that the auxiliary properties of the adjuvant are maintained between different batches, even if the qualitative and quantitative composition differs between batches. The therapeutic adjuvant for use in the treatment of cancer.

26. A therapeutic adjuvant according to claim 13, The aforementioned adjuvant is itself a natural matrix and exhibits therapeutic activity based on natural intelligence. The therapeutic activity based on the aforementioned natural intelligence is identified as the inherent ability of the natural matrix to store and transmit the biological and physicochemical information necessary to interact with and integrate with other biological networks, and is a therapeutic activity that enables physiological and internal interconnection with other self-organizing entities in nature, such as the human species. The aforementioned therapeutic adjuvant.

27. The therapeutic adjuvant according to claim 26, wherein the presence of natural intelligence is determined by verification of the adjuvant's appearance characteristics in anticancer activity, provided that the following conditions are met: The 14C activity of the adjuvant, as measured using the ISO-16620-2;2019 (AMS) method, is ≥99.00%, miRNA and exosomes are detected in the adjuvant, the adjuvant exhibits batch-to-batch restorative capacity for therapeutic or beneficial function (functional restorative capacity) between different batches of the adjuvant, and the adjuvant modulates the overall altered pathological condition.

Images