Deep eutectic solvents (DESs) have emerged as sustainable and tunable alternatives to conventional solvents for the extraction of polysaccharides. This review presents a structure-informed framework linking DES composition to polysaccharide solubility, emphasizing the differential responsiveness of amorphous, interfacial, and crystalline domains. Amorphous polysaccharides are efficiently extracted under mild DES conditions, while crystalline polymers often require stronger hydrogen bond acceptors or thermal/mechanical activation. Beyond dissolution, DESs modulate key properties of the extracted polysaccharides, including molecular weight, monomer composition, and bioactivity. Comparative analysis highlights how acidic, basic, or metal-coordinating DESs selectively target distinct polymer classes. Emerging innovations, such as in situ DES formation, mechanochemical systems, and switchable solvents, enhance efficiency and reduce downstream processing demands. Furthermore, the integration of machine learning and COSMO-RS modeling enables predictive solvent design, reducing reliance on empirical screening. By combining mechanistic insight, compositional tailoring, and computational tools, this review provides a scientifically grounded perspective for advancing DES-mediated extraction processes and enabling structure-preserving, application-oriented recovery of polysaccharides in food, pharmaceutical, and biorefinery domains.

Deep eutectic solvents (DESs) have emerged as sustainable and tunable alternatives to conventional solvents for the extraction polysaccharides. This review presents a struc-ture-informed framework linking DES composition to polysaccharide solubility, em-phasizing the differential responsiveness of amorphous, interfacial, and crystalline domains. Amorphous polysaccharides are efficiently extracted under mild DES condi-tions, while crystalline polymers often require stronger hydrogen bond acceptors or thermal/mechanical activation. Beyond dissolution, DESs modulate key properties of the extracted polysaccharides, including molecular weight, monomer composition, and bioactivity. Comparative analysis highlights how acidic, basic, or metal-coordinating DESs selectively target distinct polymer classes. Emerging innovations, such as in situ DES formation, mechanochemical systems, and switchable solvents, enhance efficiency and reduce downstream processing demands. Furthermore, the integration of machine learning and COSMO-RS modeling enables predictive solvent design, reducing reliance on empirical screening. By combining mechanistic insight, compositional tailoring, and computational tools, this review provides a scientifically grounded perspective for ad-vancing DES-mediated extraction processes and enabling structure-preserving, appli-cation-oriented recovery of polysaccharides in food, pharmaceutical, and biorefinery domains.

Background/Objectives: Capric acid (CA)–therapeutic deep eutectic systems (THEDES) are emerging as a distinct class of biofunctional matrices capable of reshaping drug solubilization, permeability, and bioactivity. Methods: Relevant studies on CA–THEDES were identified through targeted database searches and screened for evidence on their design, mechanisms, and pharmaceutical performance. Results: This review synthesizes current evidence on their structural design, mechanistic behavior, and pharmaceutical performance, revealing several unifying principles. Across multiple drug classes, CA consistently drives strong, directional hydrogen bonding and drug amorphization, resulting in marked solubility enhancement and stabilization of non-crystalline or supersaturated states relative to crystalline drugs or conventional solvent systems. Its amphiphilic C10 chain further contributes to membrane fluidization, which explains the improved transdermal and transmucosal permeation repeatedly observed in CA-THEDES. Additionally, synergistic antimicrobial and anticancer effects reported in several systems confirm that CA acts not only as a solvent component but as a bioactive co-therapeutic. Collectively, the reviewed data show that CA serves as a structurally determinant element whose dual hydrogen-bonding and membrane-interacting roles underpin the high pharmaceutical performance of these systems. However, gaps remain in long-term stability, toxicological profiling, and regulatory classification. Emerging Artificial Intelligence (AI) and Machine Learning (ML)-guided predictive approaches offer promising solutions by enabling rational selection of eutectic partners, optimal ratios, and property optimization through computational screening. Conclusions: Overall, CA-THEDES represent a rationally designable platform for next-generation drug delivery, where solvent functionality and therapeutic activity converge within a single, green formulation system.

Trilostane is a drug able to block the synthesis of progesterone from pregnenolone, dependent on the enzyme 3β-hydroxysteroid dehydrogenase/Δ⁵⁻⁴ isomerase. As a consequence of this effect, it is used to treat endocrinological diseases such as Cushing’s syndrome, especially in dogs. Because of the modulatory effects of trilostane on the hypothalamic–pituitary–adrenal axis, trilostane administration causes an increase in brain levels of neurosteroids with anticonvulsant properties, as in the case of allopregnanolone. Allopregnanolone is also of interest in curing depression, suggesting that trilostane might represent a tool to address neurological and psychiatric disorders. In this review, we investigated the historical development of this drug and its current use, mechanisms, and possible developments. By searching the literature from 1978 to 2025, we identified 101 papers describing studies with trilostane. Precisely, 55 were about dogs and trilostane, 3 were on cats, and 23 were with other animals. Some studies (15) were also designed with human patients. The main disease treatment with trilostane was hyperadrenocorticism. However, we also found two preclinical papers on trilostane’s potential use in psychiatric diseases and three on trilostane’s potential use in neurological disorders. Moreover, few clinical and preclinical studies suggested the involvement of neurosteroids modulated by trilostane in different neurological disorders, thus opening a possible new perspective for the use of this drug.

Trilostane is a drug able to block the synthesis of progesterone from pregnenolone, dependent on the enzyme 3β-hydroxysteroid dehydrogenase/Δ5-4 isomerase. As a consequence of this effect, it is used to treat endocrinological diseases such as Cushing’s syndrome, especially in dogs. Because of the modulatory effects of trilostane on the hypothalamic-pituitary-adrenal axis, trilostane administration causes an increase in brain levels of neurosteroids with anticonvulsant properties, as in the case of allopregnanolone. Allopregnanolone is of interest also in curing depression, suggesting that trilostane might represent a tool to address neurological and psychiatric disorders. In this review, we investigated the historical development of this drug, its current use, mechanisms, and possible developments. By searching the literature from 1978 to 2025, we identified 101 papers describing studies with trilostane. Precisely, 55 were about dogs and trilostane, 3 on cats, and 23 with other animals. Some studies (15) were also designed with human patients. The main disease treatment with trilostane was hyperadrenocorticism. However, we also found two preclinical papers on trilostane's potential use in psychiatric diseases and three on trilostane in neurological disorders. Moreover, few clinical and preclinical studies suggested the involvement of neurosteroids modulated by trilostane in different neurological disorders, thus opening a possible new perspective for the use of this drug.