Purpose Study on curcumin dissolved in natural deep eutectic solvents (NADES) was aimed at exploiting their beneficial properties as drug carriers. Methods The concentration of dissolved curcumin in NADES was measured. Simulated gastrointestinal fluids were used to determine the concentration of curcumin and quantum chemistry computations were performed for clarifying the origin of curcumin solubility enhancement in NADES. Results NADES comprising choline chloride and glycerol had the highest potential for curcumin dissolution. This system was also successfully applied as an extraction medium for obtaining curcuminoids from natural sources, as well as an effective stabilizer preventing curcumin degradation from sunlight. The solubility of curcumin in simulated gastrointestinal fluids revealed that the significant increase of bioavailability takes place in the small intestinal fluid. Conclusions Suspension of curcumin in NADES offers beneficial properties of this new liquid drug formulation starting from excreting from natural sources, through safe storage and ending on the final administration route. Therefore, there is a possibility of using a one-step process with this medium. The performed quantum chemistry computations clearly indicated the origin of the enhanced solubility of curcumin in NADES in the presence of intestinal fluids. Direct intermolecular contacts leading to hetero-molecular pairs with choline chloride and glycerol are responsible for elevating the bulk concentration of curcumin. Choline chloride plays a dominant role in the system and the complexes formed with curcumin are the most stable among all possible homo- and hetero-molecular pairs that can be found in NADES-curcumin systems.

The screening of natural deep eutectic solvents (NADES) to identify those with the ability to strongly solvate rutin was conducted using the COSMO-RS methodology. A NADES model was constructed that took into account the possible ionic and neutral forms of its constituents. The distributions of all forms were computed based on the equilibrium constants of neutralization reactions between amino and carboxylic acids. The proposed model was validated against the experimental solubilities of 15 NADES. A linear relationship between these data and the estimated activity coefficient values was found. The screening encompassed 126 different NADES. It was found that ten of them outperformed the best reference system. The most effective two-component solvent comprised proline combined with 2,3-diaminosuccinic acid, and the solubility of rutin in this solvent was found to be 130% greater than its solubility in the best reference system. The amino acids associated with the highest rutin solubilities were all cyclic, and the use of carboxylic acids with two carboxyl groups and a main chain consisting of two methylene groups with two amino substituents was observed to yield the best rutin solubilities. Because of the acidic properties of rutin, the presence of basic sites on the components of the NADES generally leads to enhanced solubility.

Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental solubility data were collected for all DES systems. A machine learning model was developed using COSMO-RS molecular descriptors to predict solubility. All studied DESs exhibited a cosolvency effect, increasing drug solubility at modest concentrations of water. The model accurately predicted solubility for ibuprofen, ketoprofen, and related analogs (flurbiprofen, felbinac, phenylacetic acid, diphenylacetic acid). A machine learning approach utilizing COSMO-RS descriptors enables the rational design and solubility prediction of DES formulations for improved pharmaceutical applications.

Theophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally studied binary systems, the one containing DMSO with water in unimolar proportions was found to be the most effective in theophylline dissolution. Likewise, for NADES, the addition of water (0.2 molar fraction) resulted in increased solubility compared to pure eutectics, with the highest solubilisation potential offered by the composition of choline chloride with glycerol. The ensemble of Statistica Automated Neural Networks (SANNs) developed using intermolecular interactions in pure systems has been found to be a very accurate model for solubility computations. This machine learning protocol was also applied as an extensive screening for potential solvents with higher solubility of theophylline. Such solvents were identified in all three subgroups, including neat solvents, binary mixtures and ternary NADES systems. Some methodological considerations of SANNs applications for future modelling were also provided. Although the developed protocol is focused exclusively on theophylline solubility, it also has general importance and can be used for the development of predictive models adequate for solvent screening of other compounds in a variety of systems. Formulation of such a model offers rational guidance for the selection of proper candidates as solubilisers in the designed solvents screening.

Objective: The aim of this study was to explore the possibility of using natural deep eutectic solvents (NADES) as solvation media for enhancement of solubility of sulfonamides, as well as gaining some thermodynamic characteristics of the analyzed systems. Significance: Low solubility of many active pharmaceutical ingredients is a well-recognized difficulty in pharmaceutical industry, hence the need for different strategies addressing this problem. Among such strategies, those that are environmentally and economically beneficial are of particular interest. Methods: The solubility of sulfanilamide and sulfacetamide in 21 different NADES compositions comprising choline chloride with sugars or sugar alcohols was measured spectrophotometrically. Thermodynamic parameters describing the studied systems were determined using the COSMO-RS computational protocol. Results: All of the considered NADES compositions gave an increase in solubility of the studied sulfonamides, with the highest solubilities obtained for the system comprising choline chloride and glycerol in unimolar proportions, which gave a solubility advantage of 83.7 and 73.8 for sulfanilamide and sulfacetamide, respectively. Theoretical studies indicated that the dissolution of both considered sulfonamides has a low endothermic character, with the lowest enthalpy values obtained for the most optimal, i.e. unimolar, proportions. The non-monotonous trend of enthalpy of dissolution was also discussed in terms of intermolecular interactions. Conclusions: The obtained results show the feasibility of using NADES as solubility enhancers for sulfonamides and encourage for further exploration in this field.